<%BANNER%>

Conservation Initiatives, Community Perceptions, and Forest Cover Change

Permanent Link: http://ufdc.ufl.edu/UFE0022006/00001

Material Information

Title: Conservation Initiatives, Community Perceptions, and Forest Cover Change A Study of the Community Baboon Sanctuary, Belize
Physical Description: 1 online resource (153 p.)
Language: english
Creator: Wyman, Miriam
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: aluatta, attachment, belize, conservation, fragmentation, lulcc, place
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre: Forest Resources and Conservation thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Community Baboon Sanctuary (CBS), Belize, an IUCN Category IV protected area, was established in 1985 to protect forest habitat (especially riparian forest cover) for one of the few healthy black howler monkey (Alouatta pigra) populations remaining in Meso-America. Nature-based tourism and a voluntary, written pledge were created to promote conservation and deter deforestation within the CBS. However, after 20 years little is known about conservation within the CBS. This study aimed to assess conservation from three different angles: 1) the perspective of the landowner (e.g., place-based meanings of riparian forests and perceptions of community and individual benefits attributed to these landscapes), 2) the landscape (e.g., integrating social and land-use/land-cover change analyses to assess the influence of the pledge and tourism, as well as locational and socio-economic variables, on deforestation probability), and 3) howler monkey habitat (e.g., changes in forest cover and forest fragmentation). Methods consisted of household interviews with landowners and remote sensing of satellite imagery to conduct a change detection analysis, landscape metric analyses and modeling from the development of a time series of land cover maps based on Landsat imagery from 1989, 1994, 2000, and 2004. Addressing the three angles, overall results show 1) a significant relationship between initiative involvement (pledging or tourism) and higher perceived benefits (importance) and place attachment (meanings) towards riparian forests and conservation; 2) involvement in both tourism and pledging together were influential in decreasing the probability of deforestation, with other influential variables influencing deforestation probability linked to distance to roads, distance to the Belize River, tenure, cattle, agriculture, and education level of the household head; and 3) a 23% forest cover loss within the CBS and 500 meter river buffer between 1989 and 2004 that has resulted in increased forest fragmentation. However, high connectivity exists between habitat patches and indicates dispersal and colonizing potential between most forest patches has not been jeopardized. In addition, howler monkey populations have increased dramatically in the last 20 years and fragmented forest environments have increased the availability of figs (Ficus spp.), the preferred food source of howlers. Conservation within the CBS may be a little more complex than simply saving forests and, therefore saving howlers, as increased fragmentation actually provides better habitat for ficus spp. (e.g., figs), the preferred food source for howlers. Under the IUCN Category IV protected area designation, one could say the CBS has been successful in protecting and maintaining howler populations, as documented by increases in their population. However, if the conservation objective is forest preservation, the 23% decrease in forest cover and increased forest fragmentation would point to conservation failure and may signal that the CBS should not be managed for a single outcome (e.g., howlers) as IUCN Category IV protected area designation provides. As deforestation is tied to livelihoods of private landowners, closer examination was given to the two conservation initiatives established to deter deforestation. On one level these initiatives have been effective conservation tools, as shown by the perceived benefits and place-based meanings from residents involved in these initiatives and the role these initiatives together have had in recent years in decreasing deforestation probability. This is a strong basis for conservation. However, benefit and participation inequity in tourism and the pledge exit. In addition, various socio-demographic and locational factors are more influential driving forces of deforestation probability within the CBS. Therefore, without addressing these discrepancies that exist, this foundation is simply not enough to compete with the important economic opportunities and livelihood activities the use of river property and forests provide and reiterates the lesson that the success of any conservation initiative must be linked to local communities benefiting from their conservation of biodiversity.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Miriam Wyman.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Stein, Taylor V.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022006:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022006/00001

Material Information

Title: Conservation Initiatives, Community Perceptions, and Forest Cover Change A Study of the Community Baboon Sanctuary, Belize
Physical Description: 1 online resource (153 p.)
Language: english
Creator: Wyman, Miriam
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: aluatta, attachment, belize, conservation, fragmentation, lulcc, place
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre: Forest Resources and Conservation thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The Community Baboon Sanctuary (CBS), Belize, an IUCN Category IV protected area, was established in 1985 to protect forest habitat (especially riparian forest cover) for one of the few healthy black howler monkey (Alouatta pigra) populations remaining in Meso-America. Nature-based tourism and a voluntary, written pledge were created to promote conservation and deter deforestation within the CBS. However, after 20 years little is known about conservation within the CBS. This study aimed to assess conservation from three different angles: 1) the perspective of the landowner (e.g., place-based meanings of riparian forests and perceptions of community and individual benefits attributed to these landscapes), 2) the landscape (e.g., integrating social and land-use/land-cover change analyses to assess the influence of the pledge and tourism, as well as locational and socio-economic variables, on deforestation probability), and 3) howler monkey habitat (e.g., changes in forest cover and forest fragmentation). Methods consisted of household interviews with landowners and remote sensing of satellite imagery to conduct a change detection analysis, landscape metric analyses and modeling from the development of a time series of land cover maps based on Landsat imagery from 1989, 1994, 2000, and 2004. Addressing the three angles, overall results show 1) a significant relationship between initiative involvement (pledging or tourism) and higher perceived benefits (importance) and place attachment (meanings) towards riparian forests and conservation; 2) involvement in both tourism and pledging together were influential in decreasing the probability of deforestation, with other influential variables influencing deforestation probability linked to distance to roads, distance to the Belize River, tenure, cattle, agriculture, and education level of the household head; and 3) a 23% forest cover loss within the CBS and 500 meter river buffer between 1989 and 2004 that has resulted in increased forest fragmentation. However, high connectivity exists between habitat patches and indicates dispersal and colonizing potential between most forest patches has not been jeopardized. In addition, howler monkey populations have increased dramatically in the last 20 years and fragmented forest environments have increased the availability of figs (Ficus spp.), the preferred food source of howlers. Conservation within the CBS may be a little more complex than simply saving forests and, therefore saving howlers, as increased fragmentation actually provides better habitat for ficus spp. (e.g., figs), the preferred food source for howlers. Under the IUCN Category IV protected area designation, one could say the CBS has been successful in protecting and maintaining howler populations, as documented by increases in their population. However, if the conservation objective is forest preservation, the 23% decrease in forest cover and increased forest fragmentation would point to conservation failure and may signal that the CBS should not be managed for a single outcome (e.g., howlers) as IUCN Category IV protected area designation provides. As deforestation is tied to livelihoods of private landowners, closer examination was given to the two conservation initiatives established to deter deforestation. On one level these initiatives have been effective conservation tools, as shown by the perceived benefits and place-based meanings from residents involved in these initiatives and the role these initiatives together have had in recent years in decreasing deforestation probability. This is a strong basis for conservation. However, benefit and participation inequity in tourism and the pledge exit. In addition, various socio-demographic and locational factors are more influential driving forces of deforestation probability within the CBS. Therefore, without addressing these discrepancies that exist, this foundation is simply not enough to compete with the important economic opportunities and livelihood activities the use of river property and forests provide and reiterates the lesson that the success of any conservation initiative must be linked to local communities benefiting from their conservation of biodiversity.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Miriam Wyman.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Stein, Taylor V.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022006:00001


This item has the following downloads:


Full Text
xml version 1.0 encoding UTF-8
REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd
INGEST IEID E20101111_AAAACS INGEST_TIME 2010-11-12T00:06:45Z PACKAGE UFE0022006_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES
FILE SIZE 8423998 DFID F20101111_AABYNP ORIGIN DEPOSITOR PATH wyman_m_Page_084.tif GLOBAL false PRESERVATION BIT MESSAGE_DIGEST ALGORITHM MD5
f0fee17f2372b2eaccbcb26dd0260aa4
SHA-1
e092f59d0a8ff28f5dd7ab5a4de55adc7b7bc434
37092 F20101111_AABYOD wyman_m_Page_017.QC.jpg
afaf1611b1a3f3785b66ead963201dbd
7b066e6247f8f75dad4e3fcb063fdf5478061ab5
2863 F20101111_AABYNQ wyman_m_Page_140.txt
813a4fefd69151edee8b323ceb251049
5757c329f793fd135eccce353aeacc5cea59ae85
55835 F20101111_AABYOE wyman_m_Page_077.pro
c6540d7dd18e2ae3c521b24b3701a252
2387abecb406219cb972c6dbda06de67312f9c27
107323 F20101111_AABYNR wyman_m_Page_078.jpg
9d26b3e46f65181b0e6bfc79d2543aa6
4bc4263632955c6ea500b83f162f5fe80499cb41
141211 F20101111_AABYOF wyman_m_Page_141.jpg
a89986b0ded0a812ff29110aa6e242b2
efeba41af833be8180f61b969792098cbd348375
1721 F20101111_AABYNS wyman_m_Page_049.txt
f2994b4fd61e85501fced5e9e231323b
2a4a2bf3ecb9864a7c90d28d8438021252f82430
570331 F20101111_AABYOG wyman_m_Page_118.jp2
30ff315a07f5a2a2145734eef2b4980c
29fd63b7a822b021595190421a1d173136f773f8
110750 F20101111_AABYNT wyman_m_Page_016.jpg
f50f23d35abf8224bb11cbd064784b2d
090099cc883dd72f58d5f427c9935d0878ea0b19
115964 F20101111_AABYOH wyman_m_Page_115.jp2
04c8b1d05e0fc09efdb2a681de5eb19d
facce66f57fc51af204986cb6c2d8aa2da538bc3
36140 F20101111_AABYNU wyman_m_Page_128.QC.jpg
b51677059f806c360f8a92807a0fd64c
ff4dd11192fc68e667a9a7de31e62cdd201b6639
118470 F20101111_AABYOI wyman_m_Page_073.jp2
438e7e4d2ccb42214245335615561b0f
c66c463fdbb4cf18dc03ecbd5c7ba9fdd810b924
53381 F20101111_AABYNV wyman_m_Page_114.pro
7f46a20f11e346f65662850728e9cf78
a6559ee395cda1c3df89212e253c2dee4ed00d9f
132813 F20101111_AABYOJ wyman_m_Page_134.jpg
02910c36540ce8aa299a9d4806c2c92a
4862ce06c036135afb9b589353ae3da4cf2bdfcf
109904 F20101111_AABYNW wyman_m_Page_014.jpg
baab0389683004b3e99ca2935ff429ff
cac9c2de982fb79aec38668f86ee622f92b2d10a
100694 F20101111_AABYOK wyman_m_Page_103.jpg
42aae06fc689a57e6743c279b9c7bd4b
ce56ff4cac49c0d40b8ae084c1f33c0939d6710a
102596 F20101111_AABYNX wyman_m_Page_105.jpg
482d7ba4cbe48dee5363f36329919ef5
22afcb847c3b8e1a0962e8155f7ef67bbcda48b3
4363 F20101111_AABYOL wyman_m_Page_119thm.jpg
8e2bdf7736f106edb1a0a50b186255f1
9b313fb5222a680d7f40524b366a798334a31d85
2025 F20101111_AABYNY wyman_m_Page_022.txt
5ee42270ee5632e9a6bf889c4e2f24a5
906bea82b78512927e81294d355e0238d39a4e1b
20804 F20101111_AABYPA wyman_m_Page_121.QC.jpg
0fe07b3dbdfc113ac2dbcc7d8cd037cc
c20ee5bbe2ae84693b279c46a40ac3dc5590e050
1053954 F20101111_AABYOM wyman_m_Page_153.tif
0df127fb7bdbc281eae826813b79cdaa
e1829eaaf18e739347d6d26b3378079133dc5a7b
2081 F20101111_AABYNZ wyman_m_Page_104.txt
9ea050566f6e18a3963d856a41337192
9bc43b1446bdfb3beefc30cdc60bcbb4cc0314e7
32230 F20101111_AABYPB wyman_m_Page_079.jpg
76c995d160039e6635ad9465650111d1
4005189fd6df8894e0e61571466ed57839d78776
50086 F20101111_AABYON wyman_m_Page_105.pro
4279f6bef04202161f74480d2391f2aa
23215443090512872898f77a87d6330e84bc920b
2101 F20101111_AABYPC wyman_m_Page_028.txt
4d18246b679d976dd79ef0eea0ca0e18
0040910fc25968a4cf7a4560bbb73040f4eeb8ef
25271604 F20101111_AABYOO wyman_m_Page_046.tif
00d64f32560ba92815d8e58f928530ce
5a2b16d6d82ecb42dd9b2e495644cdbaba278cb0
5724 F20101111_AABYPD wyman_m_Page_087.pro
51ecd6627b26fc280eab4c16aa919e0a
7fb9498688ee24e498cf2ea540dea21e8463494e
32358 F20101111_AABYOP wyman_m_Page_127.pro
bc3d286e1a65eccfd7aff28197ca5e27
f666a606de8ab78301538b8a307f59a028e1bf09
115573 F20101111_AABYPE wyman_m_Page_066.jp2
61ad95a6a988465919dfef12df3d646d
4ab5914fb314be4a2ca8eaef5f720a59022a6ef0
9171 F20101111_AABYOQ wyman_m_Page_139thm.jpg
49f9856937523637e44c92c673559c4d
e22b485681c4775be9637a16e430ab56b7ebe203
2701 F20101111_AABYPF wyman_m_Page_134.txt
4b42558e4e27fdc7ede7576bb8043c35
6eadb1ebf036581fc91f2242367db6e03fac76e5
118676 F20101111_AABYOR wyman_m_Page_053.jp2
d8e7c6aecea31fe5b542431d8a6520ef
0594c896d03f1268e7471c9fa0274a6d63611e79
120162 F20101111_AABYPG wyman_m_Page_040.jp2
f2815cadfb304eca02820fde90f0df42
5b6004fd5f81edb62622e8788cff24122cc6eeae
37096 F20101111_AABYOS wyman_m_Page_096.QC.jpg
4c350c025fb5b3b1994c5583e8c12279
7a71f43b7edaafcbaece132e8db636848737d9d1
36281 F20101111_AABYPH wyman_m_Page_143.QC.jpg
fefab7ba3376c900c3c451fea1144c88
875c2470d2b15d22401738e3e7a3f882646488eb
57069 F20101111_AABYOT wyman_m_Page_098.pro
ba939656cdbe9896a3a7307eaf5275c7
1f37b9bacd831d3d57dfd5443fbb6714156ffe7f
34458 F20101111_AABYPI wyman_m_Page_069.QC.jpg
122d9056535e7ad0c067a67ec88fbc58
c6f2f319204ba540cc2db5db922b07cd8db656a1
2713 F20101111_AABYOU wyman_m_Page_133.txt
c85f24d81b8df4f37ea3e06d1ef7992e
d1316dfdd477667fea8769f4f3ad9d9670d63c61
14727 F20101111_AABYPJ wyman_m_Page_081.QC.jpg
8a53b14992fa9627c9fb7089442ff60e
7ea1095cc3743e312dce2e060f9b4a08ac9dc079
2631 F20101111_AABYOV wyman_m_Page_079thm.jpg
54c2e208628a7154ab3946ab5ab3349d
18397986de6f6a565d8298e6d0c6e39dc2422f5f
2636 F20101111_AABYPK wyman_m_Page_146.txt
0810dc0d32569b689dade19537dfabdb
ae9c9a762fab4ec21f6b73fa99a9e5e23a3b787e
2109 F20101111_AABYOW wyman_m_Page_100.txt
7d008a80219f4f50117f8be99757b838
4832b48b1e6805521a30720f3b9a8d2c458418b2
129583 F20101111_AABYPL wyman_m_Page_139.jpg
e60833f6ba100a35753d92a0d434cf44
3e645968a94621770e375c5f99519546980dd42f
128466 F20101111_AABYOX wyman_m_Page_148.jp2
2ff884b67e8932e1fce044777e187fe7
87dd3e4f2c8878fbd07857a2faad5e69a456314b
71648 F20101111_AABYQA wyman_m_Page_127.jp2
7e4de90307b001e5d42b8f67e5a5622c
604c6011ed57a5272a7d46b5ba8e472b7166f4c9
46084 F20101111_AABYPM wyman_m_Page_064.pro
51cbb4667dfd14c249afd0649896a8a4
cabc322154949e73d07cf2856683aed6d712ebe2
49092 F20101111_AABYOY wyman_m_Page_004.pro
0f2e4fb176ad7163ad5babeb94354cb2
22245f22998f66d3b7b5eca505f87404520600e0
35958 F20101111_AABYQB wyman_m_Page_100.QC.jpg
5f82c05486be417cb353004fd40f4e08
397bb0e7b5bc92250eab946dab96106a38f3207f
50821 F20101111_AABYPN wyman_m_Page_036.pro
f22ac1c9fd7c12e2c9a81ad6b122042d
4ea49f4b827ae7c3abf46ac5720864aaeb96c112
119524 F20101111_AABYOZ wyman_m_Page_129.jpg
de1fceb7965f5e604fca7a93b774ea75
81662dd370c4bfd52ea510afd0a4bafafdd70088
53801 F20101111_AABYQC wyman_m_Page_084.jpg
73d6fab900736d3a398c053004ba218f
f2a819a34924bfd7206a8911380e81d5674738e0
2000 F20101111_AABYPO wyman_m_Page_039.txt
888250395d1cb81f4c7678aa3136ad97
2871b20adc3e2327e3b7a45a3727c311f7b11bfe
F20101111_AABYQD wyman_m_Page_068.tif
806a9b920896f9a372fce49d0bdea191
8968048c06b735a14ae1272f7cbb90778b42a1d9
54280 F20101111_AABYPP wyman_m_Page_076.pro
70ab8c06816c0f3cdcefe2efa6071dec
9618da5d359383ea5bda13be0c2e25191431fdd6
1413 F20101111_AABYPQ wyman_m_Page_092.txt
e08a4b8dbc078a4cc1f87cc1030ba0ca
051bff47b5a333baa6e1c173fa0a60cecbbe543f
7416 F20101111_AABYQE wyman_m_Page_003.jp2
261da7b47920db49e7bc0f273d243af7
1e45aba525fa64f0b27005404ee2e3479246c56f
1201 F20101111_AABYPR wyman_m_Page_011.txt
7961d6545516e7f1743f9ab71a9d1cd1
b40eccf82189fc02cac388da5917322295e66222
41135 F20101111_AABYQF wyman_m_Page_005.jpg
70d5ea1aa08d2d0a18c2cb7679d5e1aa
b2a7bc77a56ab7e615945f422f2acd3c64d71d08
2637 F20101111_AABYPS wyman_m_Page_144.txt
605cb46ce9f776d362dd38b6e13314c3
668fd64b9b2e8de9273888cb63a7c62333aac487
F20101111_AABYQG wyman_m_Page_117.tif
c6e4f17bbbd0ea59e25293408003251f
7ca6fcf520ef7a01362e807fe27621a8ed2a750c
F20101111_AABYPT wyman_m_Page_082.tif
221db9fef9dac4f4cb05e750588b2114
2dc7f425895b181beae1a69e11705ff6d30cf43f
2053 F20101111_AABYQH wyman_m_Page_106.txt
43f6a1437f7aaedb39e9ff361a6a47ee
54f297f8cf555b1ff7a6859e663e82d111b544ff
53936 F20101111_AABYPU wyman_m_Page_042.pro
a6c56b3207979a6030040fdff37e8e1d
788b9fe963826bf197c3c6520284840e4257a76a
55447 F20101111_AABYQI wyman_m_Page_038.pro
85bb5bbdf3dc59b9d67390924521f671
e53c4e539e93e98bdace8173b679ec4a88df41d2
110932 F20101111_AABYPV wyman_m_Page_077.jpg
9abc7a1e8ac074f878d9ce5a8d2822f8
6bfe901cfe29b31387f46bf8117a24de4b4af527
99645 F20101111_AABYQJ wyman_m_Page_111.jpg
b57ba275e1dad911d5adc359b03db377
ac1d3ca8d87c0a068c7918699d734a85fad8f96c
9502 F20101111_AABYPW wyman_m_Page_130thm.jpg
87d9def1b24b50befacada48781d19c3
529be6cb9c0ef7c982b184ec58276cd49d851cf1
1982 F20101111_AABYQK wyman_m_Page_105.txt
9ff3c070df86b41128975f84838e083c
8a267d402789cfb0bd1caa9a445278c1d3f203e8
69262 F20101111_AABYPX wyman_m_Page_142.pro
ae7db1daf66b67026b20412b42fa5925
747aa22db565db58a84f0bc0d6174d4e84fc6779
1051979 F20101111_AABYQL wyman_m_Page_128.jp2
30678117ce49fe7edb060b88dca33a75
7e5ead920222e75984fa6faaccd06238b6b85560
62867 F20101111_AABYPY wyman_m_Page_138.pro
f8c5d78d926e4ed86837963c2876a294
65f6d0f2b8d86cbd12de0bfa8bb336ecc3024461
2033 F20101111_AABYRA wyman_m_Page_029.txt
b645811fae4e1c0e98f0813e3b0fd53b
002bb6e754443d8cecf9cbe0a989c964180ef30b
2187 F20101111_AABYQM wyman_m_Page_043.txt
acce96ddc8f8677877d2cc6a08ded196
dd4fc5570cd89a264c191d0945e7b10af64abc66
5599 F20101111_AABYPZ wyman_m_Page_085thm.jpg
fdbebf09c253d1bb9fbb6654f9309f1d
d9df351ee3d1760edd9b3155415bce6fc9bb23d2
6697 F20101111_AABYRB wyman_m_Page_091thm.jpg
ccbe835e574d80ecd8853f9b25ace86f
9f08cff8c959f8c4b30bb459330b56c8b1a5d9a0
121171 F20101111_AABYQN wyman_m_Page_013.jp2
026764aa18fec6bb2bd3a66580a6e9f6
547bf52c992666d39dcf393ee8acfdacf7c7a573
2069 F20101111_AABYRC wyman_m_Page_033.txt
65b904fd9ceb27598176960ced5a03ef
1bf7ddb63cc79cb25a1227c8a84fa4173a3ee5e4
20140 F20101111_AABYQO wyman_m_Page_050.QC.jpg
64508f89839f001bff4efa1e9978f388
113394a421cfb1c25cd475640ada0b83ca0259d5
1794 F20101111_AABYRD wyman_m_Page_003.pro
298068a49aa739a2a7bf15aff67a005d
85d92af6f1b3bff71893d5945ccc04a4385121d4
67750 F20101111_AABYQP wyman_m_Page_127.jpg
1aa9495a8c429fc91268e0636cb7270e
7482f8aa0df6e39a5acfcc5feb0803893f3d7841
53451 F20101111_AABYRE wyman_m_Page_021.pro
56ea8494a980aa2ed1a54ee399d5d694
8c7edf3d660f79c0ffbf065d3deab954ab3732a9
46158 F20101111_AABYQQ wyman_m_Page_151.pro
97f66c35a76bc9625396edd55bf5f732
00004c8a20f466d1a989e08673b01ee3b491e331
52118 F20101111_AABYRF wyman_m_Page_060.pro
9cbac43f95afe5e648ed97c7df72866c
5522c0916465db7e0037965751d008ef9e4a0aab
F20101111_AABYQR wyman_m_Page_066.tif
37d70562f833b2f4407f36fa34b12d1c
d11710a0ed0ba2aeca7615ed227d2ce8612db259
4729 F20101111_AABYRG wyman_m_Page_118thm.jpg
4fb7d659a0e851734e7892a80f5c0465
2e8738c2ab11168975c543e816fbf00fac815e6b
F20101111_AABYQS wyman_m_Page_135.tif
c6b954338c9568aa2e83d39ab8074baa
dde3b878ce0553bc461e07f2d046eefda58b3d08
142049 F20101111_AABYRH wyman_m_Page_150.jpg
933287fee5e098ef486008ca361de86e
c3b3e7c8dc06413174d79dc53bfc3041205c4317
2235 F20101111_AABYQT wyman_m_Page_073.txt
73c76022ae196b5da76d892e7b4d7703
79db58434e9bd0157fe6d0ca1fdbe747d0008dbf
8580 F20101111_AABYRI wyman_m_Page_104thm.jpg
c48cd61854e2ea11d2cc25b064134487
4da6c2d6f8f6018efc47a55b5cbb9ea289f4fceb
8690 F20101111_AABYQU wyman_m_Page_016thm.jpg
39187197ca9ec7069cf90b2270374725
b8d785c9ee3963a001e49b2c19ed0af1520efad6
60421 F20101111_AABYRJ wyman_m_Page_129.pro
d47cd730c02354de1962fe59677fb32b
b699958e9ddfadf30f0fe4a23e8bb00a788cdcb0
F20101111_AABYQV wyman_m_Page_012.tif
98e11355fbf1dd9aa3634344cceb17eb
cf438d545b63fedb50542fb997e31a4d163c6f40
F20101111_AABYRK wyman_m_Page_029.tif
134ef43332cb13497ee189e37f39dbf1
6c7d21eb64217f0e175a783e6b0a72786d1d2d37
40275 F20101111_AABYQW wyman_m_Page_049.pro
954bd837cd985748d7d6f62ae52ad442
58f47d05314aa18b27181604a6cea4c3587b098b
F20101111_AABYRL wyman_m_Page_129.tif
5b6c743721ba5bd9f7c7b3401c7200a8
cf38d860365664dba7ce211c2836fcd0c1522389
110566 F20101111_AABYQX wyman_m_Page_075.jpg
77cd3e0caf8bca026b0052d90d98eadb
1a7b4e45addbf648ae94dd5f1a7082c95932d19c
F20101111_AABYSA wyman_m_Page_020.tif
fa143c78cd3f722945500b99062711bc
3c1b804219c6f69cbaf20906d34463a2bc578558
67265 F20101111_AABYRM wyman_m_Page_136.pro
41c437776c88317a6589552146f6a128
94dae29f0b0a4d2173263508a9fa99857a76bbb4
36178 F20101111_AABYQY wyman_m_Page_113.QC.jpg
fc5b7d1a73f94ec3d9c0a7325ea0b002
049c3a6a4aed3ebf027ce4b047ccd806f0d42d28
2130 F20101111_AABYSB wyman_m_Page_023.txt
e5547e17a21d379aff3ac21ad22dfd96
b508f89b2133a9cf21a5cd88e7e7abf50816f039
740 F20101111_AABYRN wyman_m_Page_122.txt
222f8e249757ee7fef9fc7e82a3106dc
5525b8d478ad07c8cf68262113e646c40b56a363
59704 F20101111_AABYQZ wyman_m_Page_148.pro
1c4b9b07ae71714aa85cf38aa27ddab1
c5238493fb41c38a62c25f102068b42d7a22402a
F20101111_AABYSC wyman_m_Page_147.tif
925892e88bbc2924006bd9d63d3aaeed
692c473e6585a1f128b4eb823e3c232807bbf64a
27950 F20101111_AABYRO wyman_m_Page_082.QC.jpg
1b355dac55cdd053def9ad5476fd750c
fa9ac820c49f06d1edf2ee84852a297bd75fb238
7776 F20101111_AABYSD wyman_m_Page_082thm.jpg
e25425e49fff2928a4cb9196b6ab87f3
c076fa3f8ce865134e8d4a2c1af070a44d83aff7
F20101111_AABYRP wyman_m_Page_023.tif
ee5b13a00868c478915335d4ab078a2b
269817bb80a2481f239cd5cf363bc89611d88f9f
F20101111_AABYSE wyman_m_Page_021.tif
1ffd9f1d01e0a0880fdd501d10dea5f7
52aa0a2d71c1dd1f9a2127a10bbe6207ed43f0e1
120554 F20101111_AABYRQ wyman_m_Page_020.jp2
fba78e71d8bf149f87b62d19b0b8ddb7
3def56da143e56f5c9bc7d249ef3ad782a872e7e
F20101111_AABYSF wyman_m_Page_060.tif
5bad4dfb0efdd813e5e769c5f9bb726f
64e266f35b9b8ec4378f43e483f9a743d29e7265
2162 F20101111_AABYRR wyman_m_Page_101.txt
b22242869457060811476615caf97d1e
bd6bee98a69e6d4a8d6639925c5292b5e9ca9316
35840 F20101111_AABYSG wyman_m_Page_080.jpg
d5444cf4fdc7fd7f6b6d8b3dbb3dbac9
615d413c80636cd03280329542e1908715602962
112709 F20101111_AABYRS wyman_m_Page_053.jpg
0b7b2ea3813059b0b6c6d1fd14ea96fe
8421151f3ef46cbccfe3828d68d2477d6b95d587
F20101111_AABYSH wyman_m_Page_040.tif
59399f4d679670dba4d3435ae6f60d59
9d887ea011695bc98f238e59583470a3b24e415e
113006 F20101111_AABYRT wyman_m_Page_038.jpg
0ba84b4b0f5b3e414b4d1e308b9d65f6
af46a5e5451190ad9ebd602180366855835afe8e
8678 F20101111_AABYSI wyman_m_Page_023thm.jpg
a252b74d6d0c8eda6b0bb8a12f4a6d47
1e5357354f00bf59d6048160a26bedcebfbeac4e
53456 F20101111_AABYRU wyman_m_Page_018.pro
8b3aaef72ccef04e2b84f52fe09347fe
34c2381da0a2790abe128f8fa47ca507be8eccbf
1905 F20101111_AABYSJ wyman_m_Page_151.txt
88949e44cc909a95b381ddfc7ba925b0
2314b7ebae02a051c48df6f5cb649f1933becd02
36474 F20101111_AABYRV wyman_m_Page_133.QC.jpg
6c514eefccfd438995950bd1017762cb
5e4e91bb7961ea504ed0dd003baec4039c7da3e6
2051 F20101111_AABYSK wyman_m_Page_060.txt
99d7ecad04ef6216243219f90e286ed7
5e283668c9f69fc50e83f1d8cc9581d477c49c79
96860 F20101111_AABYRW wyman_m_Page_026.jpg
c93c204b15685046cde16d235bc1bf9a
4e749724f5d64c1340c076615b29f5b27948cef7
8979 F20101111_AABYSL wyman_m_Page_028thm.jpg
40d4f854fb159a5cbe2c2575a4d003cb
8304e62f96a508aa5a0f522cca18e8753627b0a4
116437 F20101111_AABYRX wyman_m_Page_106.jp2
78b7bedfcaddedb62c57a7042a46497e
bde2de111fd8372afe6c4b72f0b60017bb8d432e
81703 F20101111_AABYSM wyman_m_Page_019.jp2
48c8aff82bb3ea67c4c3a7e27345147d
86214b552932c43b622a594b9c94819bf3627061
8894 F20101111_AABYRY wyman_m_Page_135thm.jpg
9d3a0aa527ff5939f5daac1922bb6d7c
d9216e3a336ce3c2c7a184dd6828d5d563cdbcc4
F20101111_AABYTA wyman_m_Page_120.tif
279ba768107ed16a17df8e6ad2d38851
5e43f970c7a7be43ec4c2aec961884dba86ea6ed
19056 F20101111_AABYSN wyman_m_Page_083.pro
2e7882d48b7b9b1a4ce924ad389c9b62
13071ee02efa0488be3d0ec664be5e57a9c8043a
64528 F20101111_AABYRZ wyman_m_Page_146.pro
6840fed093ffb6efef184c5dcad84eaa
806522a7ce739190ef57f49fc651c7a4fbce3881
105094 F20101111_AABYTB wyman_m_Page_123.jp2
0deb3cef490cef550251ad5a2d78703b
769fed52cc7f6408ca4cb803a6481f0558420893
18234 F20101111_AABYSO wyman_m_Page_094.QC.jpg
728593c5cc83a6a3cd6018c303c3b68a
7a9a8c0ac5762faccaae85d62b7ffe9baf150b3d
F20101111_AABYTC wyman_m_Page_121.tif
09d8c37f239e1850396260e950dbe4da
925d9e2d8d4e39506dc737965bcd12738f3aabe6
53564 F20101111_AABYSP wyman_m_Page_124.pro
dae87775b5d9eb8909d3b12fbc19e721
9ff57bd88ada9f4503403b0654fed4230c06b05d
55904 F20101111_AABYTD wyman_m_Page_073.pro
5c3b7b6e407cdebc28616482af84424c
9d4572d420cbeadf40caa1d9c67d796bbf559890
1025 F20101111_AABYSQ wyman_m_Page_095.txt
4a433049bb0e20b5aee742cc8f442273
3defc225259573ce575a989efc2573d4e433c765
2205 F20101111_AABYTE wyman_m_Page_053.txt
c2add1cbed38c684e5439da8d7be8de9
4c4c9e723ee4139f0e9f5ccfa89f50b73565bc2e
F20101111_AABYSR wyman_m_Page_035.tif
c7cbc1610940a329f00f2dfe0d183350
3ff6e48502e345b4242f9de8f6f70daffa3eb6ee
51851 F20101111_AABYTF wyman_m_Page_099.pro
1304847a5cd3054de9db37bf9994d83a
1d4e6071fe911773a1bf9bae01bd591737de9e75
136071 F20101111_AABYSS wyman_m_Page_147.jpg
1beee57a46b766c8ec4a2f06627ff967
b73625e7638892232c42a5ddb01b49ad4cbf368d
50750 F20101111_AABYTG wyman_m_Page_039.pro
b678129ff6a0b60aa5e6d9e531395330
fd58c31504af543f53db9c97b9730cf2386a2d1d
F20101111_AABYST wyman_m_Page_078.tif
acbe618d68b86e835c8ed1ba7cf25b41
fe9714f272c06c4d8410b280748f869966c11675
118620 F20101111_AABYTH wyman_m_Page_035.jp2
535b9d01b75d03d6c45aa792479c54aa
ccf9d842665febda30d64c6debfe1b6f8d3205fd
F20101111_AABYSU wyman_m_Page_087.tif
0f51e082dc5178879a7750987325d2d8
5ee10a16cc4c7e1c717a456c17dc2ca9c540a77c
114478 F20101111_AABYTI wyman_m_Page_033.jp2
ab13e5c77711303dcde0ac875a164235
bab1f1ca11399309419b9584dd424040d69108e8
48494 F20101111_AABYSV wyman_m_Page_054.pro
60c09b34f22887a8d916c3a22e47c4dd
2071e4bc7a3bb46a2b6cb7ddd9850030907f37c1
108060 F20101111_AABYTJ wyman_m_Page_071.jpg
b6c22e853ffc4f3dba2f1cc5628ecb8a
9712ddd1bde2e1c568df0b76096d2cd658cd6c47
107214 F20101111_AABYSW wyman_m_Page_054.jp2
da35d27e99791cf6e999da753f981688
38134300cfb264a262071f293f0fa4e16324b68b
35171 F20101111_AABYTK wyman_m_Page_102.QC.jpg
e33319e02532c7f936cb7b5960652401
98b95c123eba2c69d3e36c5fd97980e31ad7e9f9
2119 F20101111_AABYSX wyman_m_Page_059.txt
9892edfcabc21bce90823c3c6486b5e3
1e5ad0c4377c4cb823ddc5fda655580a3f7e8cd6
14215 F20101111_AABYUA wyman_m_Page_047.pro
a42a8ee0337e8678ce381c1445a9e9ce
6886d2b05ebbc7c403e9ed9bd8f9d81c20729b2c
35857 F20101111_AABYTL wyman_m_Page_015.QC.jpg
55781e2b653bb04fbc8cd0a6fbfe5639
b4a0f063eba5f0b13d72770a214340735b005a0f
36449 F20101111_AABYSY wyman_m_Page_038.QC.jpg
8905eb1af5b71d7eb3ba64ba93b739f3
2636ccd5532d7bf2e1d386540ebc8b5cbe9f1883
2120 F20101111_AABYTM wyman_m_Page_115.txt
31390105f0153192cd0ceab0305be6e6
58ed11b4dddbc765eea5682ec9359b5f865b29a1
8705 F20101111_AABYSZ wyman_m_Page_056thm.jpg
3630c49be7aa17b1bf4b98c2dae7a329
bbc55d7d52c3795617a3561da5589b8a36a619b6
F20101111_AABYUB wyman_m_Page_140.tif
3a2a724a0eed59ca4828cd7801a5e660
e3c0bb920aa0948d94242c07ed5beaa61662e255
14287 F20101111_AABYTN wyman_m_Page_047.QC.jpg
90c82fead6ca8e97d457b1a155341b95
0a26f869bfb3aaf9de3e3809ef5be70f217303a6
142868 F20101111_AABYUC wyman_m_Page_136.jp2
c7f3044157a14ceff15a0d1479e25705
3c9135e9edd89a5ee54e3e41c738ecda5c8059a8
109278 F20101111_AABYTO wyman_m_Page_036.jp2
3f5b7d82cfc88d6f5ad08af17415257b
b0f67b736ebdae6ac0e878191ac5203764ab7499
F20101111_AABYUD wyman_m_Page_101.tif
b07fe726c8bd7317d811cf620ad15ed6
5998206472579f87cb35ce179bb2c9ca970085aa
F20101111_AABYTP wyman_m_Page_036.tif
1e6698078ebda3079bd3ca10bfe334fc
985a58a4cf11e912c607204009971ea786a7faa0
2052 F20101111_AABYUE wyman_m_Page_055.txt
91a1ecb09b7a36c69f755b69668af5af
93fd005d10e7ea86bf5c14d9ca884db1c9161447
28307 F20101111_AABYTQ wyman_m_Page_001.jp2
8d082d3a199cef1a0ea2fe3bfa25c8ab
db849d8e0cab10dd23b5067669a33036c95c5ca5
110013 F20101111_AABZAA wyman_m_Page_100.jpg
e1a67852603a91eeaeaa2db3a66369ea
a95375873a1752c34dea4501bfd43aea85391f64
55305 F20101111_AABYUF wyman_m_Page_035.pro
72f71ac66a11fa04cff1f7e9dfff65a6
8ed033715e4da55797a990b1f80106ace29aa9e6
8354 F20101111_AABYTR wyman_m_Page_109thm.jpg
34aef3ae8f95d2b0e4ff46315f0c0551
11f861bed29605c3e5fe1b6c9a37e37518787a8a
109766 F20101111_AABZAB wyman_m_Page_107.jpg
13831aa593769052776db1ba934a30a0
68765684e78cc550a7a82beaae7ba37ee9b63c8c
36518 F20101111_AABYUG wyman_m_Page_025.QC.jpg
78bebf695e70578b4262e6ed2c3e2992
2d34ef6fc728ec5845434552a96bc16bf976b028
10924 F20101111_AABYTS wyman_m_Page_090.pro
cd61d549d468d5d13b7ba37464462baa
b3d7024ec87ca30bee0e6c8eb700e60405f0e1ab
107003 F20101111_AABZAC wyman_m_Page_109.jpg
50ff1cda3bd46975fc2512ddb46484da
4a38e55d3cbbc07beba5a47dc3a062930ae22427
53729 F20101111_AABYUH wyman_m_Page_059.pro
170b1418c7b11071a92f1a9be23cacf5
803646def1395c722c3d2a56e893e0b93e32c77a
1923 F20101111_AABYTT wyman_m_Page_111.txt
2a5b0056ca44ca1baa63ac658c86e967
ba2867c028cdeb9edc779446630df661c02f982b
108584 F20101111_AABZAD wyman_m_Page_115.jpg
fe936003d76df5c2985b5ccd69550c5c
0524ae53d2e205285d12667e8b780d5eb758cf58
4661 F20101111_AABYUI wyman_m_Page_051thm.jpg
2b70c293c29b5f8f13378726245d77ad
834fd133574af68dba96ac9d1f8fd1a0961b30b3
F20101111_AABYTU wyman_m_Page_038.tif
9d1df04154daf2149123284e35dde7d2
7c818ebac2eb40cddbceb3f7ba4a88f0aa5fd7d1
49724 F20101111_AABZAE wyman_m_Page_118.jpg
1aa6a19943a3de059fe3ef3c9a7e32ad
35b39401f4993f30077c54e0ff62f7e44980ffe3
111752 F20101111_AABYUJ wyman_m_Page_031.jpg
a61a71fc0c47b645d6abc5c924fd229b
37560d94f658af4664707fb56b043600a92d5c3c
5053 F20101111_AABYTV wyman_m_Page_093thm.jpg
e34614a750bd5f11d3fa2026ce203142
338dba2fee3d48ac1ba23e0546138ce6ab21b4aa
57143 F20101111_AABZAF wyman_m_Page_120.jpg
25271512193313ada17207bb399a13eb
ad35f185ddaf00c566df6975fa1290b86ebbc6a2
2068 F20101111_AABYUK wyman_m_Page_069.txt
f9ec418c811ff185c3623b61cb327d1d
7c7d1531675d5fa37a94b979747f3d7b582377a9
569 F20101111_AABYTW wyman_m_Page_119.txt
e286349381d479cf0e554e8656c64242
9d45305774e26b9602d3bf8b6da192dbcb46f054
34705 F20101111_AABZAG wyman_m_Page_122.jpg
e3114205138fe4b23a9577cbfee30fdb
7e3f2a446cc0a5eaf614458dd8e2c9018bd78675
513 F20101111_AABYVA wyman_m_Page_001.txt
56d1805eefd0da7ed24782465bb265df
53badb03f5278133ca99654916b92e2f725ea0bd
F20101111_AABYUL wyman_m_Page_097.tif
c861a51652ecb2d330f8dc982ebd9a94
fa9feaf95c7044d6e889ebcf178d45cbac7f3140
F20101111_AABYTX wyman_m_Page_108.tif
adab9cda497387751ec5f0b492099ba0
b410b16daa334f4a38b57d8d1805a6430e561c46
108697 F20101111_AABZAH wyman_m_Page_124.jpg
433c748e1ef308c9dbc7c9b23ff3f163
3389302cead9292da55e7dea9f39be5b445284b7
116635 F20101111_AABYVB wyman_m_Page_014.jp2
9abc3ce532f42f27991fac7355c1c88d
1a4e2712657d3e5a2cd5cbe0c76011fcbb070e62
8196 F20101111_AABYUM wyman_m_Page_046.pro
90024a10c6c052fcce6ddd3b10e61209
a357b75209fecb8ce40d5156a719674550195051
F20101111_AABYTY wyman_m_Page_011.tif
c811e430200113d1a2830c8556006958
5930fb5b9fa6b347722dbeb2f5e96b83ff1601df
107197 F20101111_AABZAI wyman_m_Page_125.jpg
f5fa95ae676b2bce9cd47a02a3e251f8
4218bc61610a881a91f499fbb5017b1eb706c922
36367 F20101111_AABYUN wyman_m_Page_035.QC.jpg
ff21056b8f08b0c144d2cb15c0cf94ed
ca09a2891dd28d0d1d818b1547face8907657395
9121 F20101111_AABYTZ wyman_m_Page_031thm.jpg
1ff16b1f2cb2ba1571a9b4519aa8a029
0e618fe2e742afeb7b32a024a3b7a384840f4691
117957 F20101111_AABZAJ wyman_m_Page_137.jpg
8861be72d7a6eb78b35810edbebe1ce3
2358a45dec1ea2acf31a6b78f1dba42d0cb83664
104641 F20101111_AABYUO wyman_m_Page_010.jpg
b5543ea3f81b14deb7fefa5aea851d7f
9d2846719c44045e4edf5a699d927f551a0f032f
F20101111_AABYVC wyman_m_Page_045.tif
0f64117f9bd554bfc28201c41759358d
15dffaab74332ea30e35319f25de176c3215b46e
140987 F20101111_AABZAK wyman_m_Page_145.jpg
77fbbcebc3fb26ab22108a4bf1e7028a
f413c2f7eec0a9750f2302a92426ceb24d2ada84
52110 F20101111_AABYUP wyman_m_Page_025.pro
297adfdda132dc6ff5a808df82e60867
68d4592fc10aba7b0a708e8dcdc19c49b9d2014e
109552 F20101111_AABYVD wyman_m_Page_037.jpg
478310fd934dbdc0f3f46828f655fc2a
37cbb4add39d21757e35d7db5a1e9a1d332d97ac
119593 F20101111_AABZAL wyman_m_Page_148.jpg
e01d1f4d3d7901d3ba9bef1631b1cec6
e0a83b0a45496bcbc00139ae8e3c410f602d765e
54299 F20101111_AABYUQ wyman_m_Page_091.pro
1f128c61c58e2a18c6d2247aa34477c8
ad13b85f20b24087ad1a54e2e6abb8f2d77fc756
62435 F20101111_AABYVE wyman_m_Page_052.jpg
1b3f79820ac01e688d5bd707c644d3c8
27fdde37b1b103fcb7fff17e466598d957e55b65
113580 F20101111_AABZBA wyman_m_Page_061.jp2
3739d5c7589314c184a654d40162bca2
5a9955022078c4f8933b7e617093b51ed05dd048
F20101111_AABYUR wyman_m_Page_049.tif
ac851dc2aeb4cc5336416118dae47045
019b14b5e96f91820ba9fa48114cd15b13833a15
115877 F20101111_AABYVF wyman_m_Page_028.jp2
fcc54ee6da6d2de89e26facb07ba8b7d
6f06b86a60196fb11747f4d2cce39680a03f62d1
117515 F20101111_AABZBB wyman_m_Page_067.jp2
e019dba556e98cb1184fab5a3030de36
1fb2794747ebbbcf562b10c4f55bb160acb7c9d0
108284 F20101111_AABZAM wyman_m_Page_152.jpg
a65fb8f88f07bee5094df126fb429d89
e154cea89e08ba1ba88ebfb7439bb93845c2a042
F20101111_AABYUS wyman_m_Page_107.tif
de372ba1fb9cb5cef7e477abe6311ccb
e0af02b4c583add0f865c3452fe6bfd65c8a2a8a
102754 F20101111_AABYVG wyman_m_Page_064.jp2
45f6b13a806c8670524e03fe1e63df85
6d2caf4c1ff89fe9b023b64188e9d420a96d945a
119056 F20101111_AABZBC wyman_m_Page_075.jp2
ddece0c149b7587c837f36b7cc86cba5
6fb280b67e4628280c27d64cbed0f5e2ad45110b
106922 F20101111_AABZAN wyman_m_Page_004.jp2
120a8321473494bf77515565fe731d95
6d79b6b67ca69ace830ae616a7080eaae1bc9273
8813 F20101111_AABYUT wyman_m_Page_101thm.jpg
9b7e9428c99fa9ab389ff41d919ced34
d67df77cdeb6fe3f45a36a52a98327e01a646fca
514950 F20101111_AABYVH wyman_m_Page_084.jp2
68752b53c68d3b1e94e222b337c3fb6c
436b3a576322032c4b9d592927b56c44d1bb759e
328842 F20101111_AABZBD wyman_m_Page_080.jp2
e5f91c68ef1c9b931b2c6260894a5994
7cd6862e971f43e823f64c6c8259063645f9dc71
119348 F20101111_AABZAO wyman_m_Page_016.jp2
6a54d37d3e0975b724b9bc2def426fe5
ea5ec3f75e2c38fe0101fbb9b86674f23f242ef3
108107 F20101111_AABYUU wyman_m_Page_055.jpg
c6c5993768825d6747a9ee6bde5b6206
0d337fc8d3743fa261bb87943a451097d8dee5ca
F20101111_AABYVI wyman_m_Page_123.tif
ed0530861e6f32d14f75f358a83c149d
19a6fdc2e9f2febdd93373dfd7871f29b54b37b7
436359 F20101111_AABZBE wyman_m_Page_081.jp2
6b2af9437558f4a13da7099f009b5246
5fc2f1d14dfea3d81d154c89fbdc74be1d898627
118144 F20101111_AABZAP wyman_m_Page_023.jp2
68ce0a3c573d0484510ff8ebde9a986d
ba2f4c77536cda67b6743ea9bdd543639805ae39
8513 F20101111_AABYUV wyman_m_Page_037thm.jpg
b7eedd1d91daf09d8be3d23f1241b27e
19c6e1e3c22f1e99ef3ff246db19f798ed7d438d
148122 F20101111_AABYVJ wyman_m_Page_141.jp2
6dcd4c2d8ef582c730904a7a400c89f7
6d771afb7d7f22e3cc4a1d36b842bd2a34313dc1
1051959 F20101111_AABZBF wyman_m_Page_082.jp2
83a4c6440b4655e68eb6db8b4e58447d
85ddf046e551801ffa56a58301908718980721d9
104554 F20101111_AABZAQ wyman_m_Page_026.jp2
5393d56b7482650cb09de875f2d36ee1
b872907c28bacff4313f298fba5bc8e9a10747a3
2444 F20101111_AABYUW wyman_m_Page_148.txt
acbc957976eed63f68ccc3a1bd6ca348
6fba5a6dbe6ae168e8d7ed8d4fe641fae6ebca3c
8660 F20101111_AABYVK wyman_m_Page_022thm.jpg
20b2264fc2f4002273384c087297217c
3e3c75d82cd645c3b846b3a8b91d5a604e7c2c6d
68315 F20101111_AABZBG wyman_m_Page_093.jp2
135a823874400aa83e4834eee0709a46
5d521f48da8108ba2b52bd2523c931b4e5b38e7c
121243 F20101111_AABZAR wyman_m_Page_032.jp2
4c46d353dfc975e6d5d249a9fcd7fdf8
c819f083b13942fb0ebe168f87b85db283df454b
36080 F20101111_AABYUX wyman_m_Page_014.QC.jpg
ea8042a45994a1b19b0fc8eb6da9d3e5
a5c973ce009ffb3d3cbef29bba6a90b26e7c3c14
52243 F20101111_AABYWA wyman_m_Page_069.pro
27206edd7b6594c12a9bfb14cae95d07
3c35b4d9e0a35c0eb0a229764743d28e35e64571
2740 F20101111_AABYVL wyman_m_Page_136.txt
8338104a8fc492ed0894d173125c3a68
0fc4e53086bfcae43b030cd5debb3b753f9b3a75
121378 F20101111_AABZBH wyman_m_Page_096.jp2
0e8551f8e1f511dc3c3145b3d83c0ff9
e590f9b9653af5ee079b2cc5f0ab5ff59f52d590
116252 F20101111_AABZAS wyman_m_Page_037.jp2
532d00c6823cae9fb6f74cdb5c2affd4
5523133f280118d58ec1ab8601679291524e931a
F20101111_AABYUY wyman_m_Page_021.txt
1608d199a8a5e4ca13d95468df4a6f66
70607fcc230f59866ec367510504062a254a37cc
1733 F20101111_AABYWB wyman_m_Page_121.txt
ebd55960ca7c4241e9cfafc836965123
7961ffda5df67daa3bc22f869d78a9f31bdbf70f
122085 F20101111_AABYVM wyman_m_Page_017.jp2
874606177c10d2271d7642ac2233d65f
d23df575f2c58c8b2afb8091fec91a3155b4263b
124302 F20101111_AABZBI wyman_m_Page_098.jp2
0e032d43864134baa11e918b12d7c46c
55983715d4c8cdd1340c02079981670e9c308426
114825 F20101111_AABZAT wyman_m_Page_041.jp2
a41fae785e6e9f824adfe9c85a1c314d
11997db275259a9d29e86fea89d1d99aac68030a
1979 F20101111_AABYUZ wyman_m_Page_058.txt
deaa7c1c15fb1debe268660b5c4e9531
15296bdd5acbb65448fa3f6a2aad51b3ce039fe6
117481 F20101111_AABYWC wyman_m_Page_071.jp2
44adbba6e0733974f0efb68ee6bb58e8
9880cf8f731a3953aba536e97b9e9fac88037f8f
49930 F20101111_AABYVN wyman_m_Page_058.pro
b5de2bb6231d807df673ffb0039e1bc2
2b252a30732684ea7336e48572fd48d933d2caf8
117399 F20101111_AABZBJ wyman_m_Page_100.jp2
d91f2e44d9d15061a0029ce312f1fd27
48573afdcf5d3057f097416c90f71c03830a854b
69208 F20101111_AABZAU wyman_m_Page_048.jp2
7885e3361e424fdb7acbb0e6521bea36
1bab5411d7dfbbd10d9446981141b16f8effc443
111300 F20101111_AABYVO wyman_m_Page_007.pro
4a7997940e4d547069d708bd88535731
3a6f2f9b44a751928bade3fca2a347467eeded8a
121080 F20101111_AABZBK wyman_m_Page_102.jp2
d08e061a350608bf198b39ea7adc1ac0
80ddad3be838e3790f9b403d7f2db3b85ac281f8
51696 F20101111_AABZAV wyman_m_Page_051.jp2
49e75f65cc00c321ace2a973eb8b8b0c
c114d683a19c5fe287475ac4b823a2d921c7e38e
F20101111_AABYWD wyman_m_Page_056.tif
f37a70ac8b2fe150e123528d9e38f55d
bf8b2a2a36126ce1b932f77726d3072b93d3d7f0
F20101111_AABYVP wyman_m_Page_016.tif
bd7939e34ede04b8f3181f8b8e76b1b5
43af97429fbd8dcf0a7ed9cc0933c869e8dff05f
108250 F20101111_AABZBL wyman_m_Page_103.jp2
b1860f26aaa75047e95a869cec5002ba
c604b7106231defeaabd44faf2bb358a7605491d
65484 F20101111_AABZAW wyman_m_Page_052.jp2
2d7682ebf745f140584b79b348fb8894
89c7686f00d0800d823d90eb482c21c5cfbe35ee
57229 F20101111_AABYWE wyman_m_Page_153.jp2
382577238dc03d8554e666b8afadefc1
c1b57e5ca1cb0e4804ce53b08521ac25a763fab3
F20101111_AABYVQ wyman_m_Page_051.tif
c5b931d172630e8135dd6a5b4c79147a
70c20e312f446ba913090a79229792afeacc3dc8
F20101111_AABZCA wyman_m_Page_027.tif
2c2f734d9bd05e44588f8130a2e1d23c
7792aa7fd52ccb2da3064eaa8e9d670ce883caf4
111585 F20101111_AABZBM wyman_m_Page_105.jp2
ecdedb38efb4a6da0825eeec1ed67b43
afb1c30b0763de4ab26c616baf327c2ea1ed03a3
118387 F20101111_AABZAX wyman_m_Page_056.jp2
433c410fa2f22dcde157d5407eaa4839
775c6a72ad92570514401b98f83604971440b774
2102 F20101111_AABYWF wyman_m_Page_030.txt
e8a81c646983689a1d4bb48287219790
8c7e806114d7d2643bc3edf209db6aa52170e59b
110757 F20101111_AABYVR wyman_m_Page_074.jpg
da8095522b734b0b4c40367e93148667
eca8cf381d613d03d9a10f7797b75c342dfb2ed9
F20101111_AABZCB wyman_m_Page_031.tif
f84453370cd3eeb29a34c98e33418d24
d86f06c8a48164d077594fbf37879683e2bc090d
108458 F20101111_AABZAY wyman_m_Page_058.jp2
1943ea33cc4d10b1571c28fa175c7fbf
e6712ce9898998410cdc996d5f826e38ebd3a5dc
51008 F20101111_AABYWG wyman_m_Page_034.pro
f91e13aad735b12ea3cde92551ba143d
e18654bd8f4190bc608875bb1936af2b162b4870
113794 F20101111_AABYVS wyman_m_Page_112.jpg
00ad01dc829d7400cc28d0927808bded
f5df2d1a0f9af9f0c75d09cf8417f8d76598c503
F20101111_AABZCC wyman_m_Page_032.tif
5b4568f1d82f94f9d854c971bf4dd42b
9012155a003d5c9d9d5829d22ccf065ac405cdcf
117276 F20101111_AABZBN wyman_m_Page_114.jp2
6adb979d9d7d64ed2593f0b0360a95b4
f3228a004b26cd863728699fc4bec08647aa2790
116729 F20101111_AABZAZ wyman_m_Page_059.jp2
9b0be4fcc7a29a9af05d3c342b30710a
5c81a3e63e4796c5108378ec891ec955591729c5
31512 F20101111_AABYWH wyman_m_Page_054.QC.jpg
6d148f34b62f21cfd76103ec635686d5
7df30a04649d64ece1c80dfedf4654db48fe25f4
2213 F20101111_AABYVT wyman_m_Page_013.txt
ec5026bb2ee65703ee54e8f766899b6e
409619b141b6b17de6842b75b4402a3baf6af7a2
F20101111_AABZCD wyman_m_Page_047.tif
4b650dedf5f92a0c65e9635fcd95940e
5ee1f3be90b59a8014cffb60b16f1204589b191c
54015 F20101111_AABZBO wyman_m_Page_116.jp2
c9225e403bb9a6d05b4fc7bf61d18aa9
74348a277784297d9e7db066616ed21ea668dc25
2455 F20101111_AABYWI wyman_m_Page_128.txt
83148ec2132326e55e1ae77360de52c4
8cd76e95eed26f843577d1224f1b2d0d15ff10ab
F20101111_AABYVU wyman_m_Page_127.tif
72390a3e7f1ba47e024e4104289b6d2b
480d8978a061279b2e6f0ea489bf717d67cf338c
F20101111_AABZCE wyman_m_Page_052.tif
ef0b441b1f62a6ddf464976ec4b2e1dc
31a8514813cbe1a00b0458fd05982bc0155dd516
372690 F20101111_AABZBP wyman_m_Page_117.jp2
918c82df97eaf3e2f9b23f27bcc337f4
002f6b4fa534f85963dfac04d8e3f04bd38ed606
2753 F20101111_AABYWJ wyman_m_Page_147.txt
56fb29f42858ee766c36d5fdc0ccf41c
5960063aa29ee6308a944671b0d1edf1ee5b5d9f
119344 F20101111_AABYVV wyman_m_Page_065.jp2
f3029eb6c5d11b584dc4caf36d71f675
475269c6f80cfb28faf477a286ba3dd62500541d
F20101111_AABZCF wyman_m_Page_058.tif
40630bd89e68b51dc93717bcd95c21e4
e1431db439942c3da0d74a7a5df1326b9c3477d0
1051929 F20101111_AABZBQ wyman_m_Page_131.jp2
79eddd02faea159f6d236f7d9078db4b
68d1348edadfc04ff7314f2b90f14cb422d88c7b
F20101111_AABXTI wyman_m_Page_009.tif
1af964d18a7bbb8ef7eb5ab5a0175150
27d78dc16ce31e72b946c2286fd4b8ef7e8475db
106797 F20101111_AABYWK wyman_m_Page_101.jpg
b8ca8a769c861198e558b65852f4386d
3f5aa1a510827451a6b3dc16d65dc693d4d2a332
8621 F20101111_AABYVW wyman_m_Page_115thm.jpg
3e9475b8cf55650116fb5435c58b080d
4173c75c13fd415a40fa8013810841354f74fa47
F20101111_AABZCG wyman_m_Page_069.tif
545d1719dc004ba2e51f1eff13bcc818
1c527a577c797a90064fc714cd58762760b98d69
1051970 F20101111_AABZBR wyman_m_Page_143.jp2
e6e6d9932281379c79762e9f1f96f62f
d6d190461eca63efce5358d34e21f7fcea25f25d
330 F20101111_AABYXA wyman_m_Page_081.txt
f758ecf0074d6422f433dc6a9838060f
dfa855a7adf6f6f1161aa8550b83f1aba0fbb43e
2155 F20101111_AABXTJ wyman_m_Page_037.txt
743a2c7c1b2c774ab20202aff8ec01ef
3f6486a4d94cfdcb1681d632fcf9b9e3efa0edf9
52630 F20101111_AABYWL wyman_m_Page_104.pro
c4e09f5b1b34bc2b2f07cea4ef460043
e4532fa92494c5ab6fca08e73a36f16be04e6146
5457 F20101111_AABYVX wyman_m_Page_083thm.jpg
6edaff9ea0cf88ffc870fdacfc36dbf9
896f77e2a09b198dcf6e0d90b233e6acb73f372d
F20101111_AABZCH wyman_m_Page_090.tif
25f59a0a26db079a73125c8b0fdf99d0
63786398f14b9bb73a25b62b9f085c5db1a47f8c
1051975 F20101111_AABZBS wyman_m_Page_146.jp2
74d8b3c92af9aeba829679ec1706f803
69226cfe08d90db096c8ad33a8d383777fa2c3f4
96722 F20101111_AABYXB wyman_m_Page_123.jpg
c2ff8c6537d6167f14b7e4e2959533eb
94414592f2957e23b37b08fb0b130a783f3958c9
F20101111_AABXTK wyman_m_Page_059.tif
ca2ab99adc45717aff8d19cdd24b35b0
de6f417fc46eddb6c33dcfddd88ad1e9b5594197
9566 F20101111_AABYWM wyman_m_Page_140thm.jpg
93dcfb753dc7b7d2aee8c089da1e25ab
20000a9f6419ac25871c7b1b358feac335a2f07f
456 F20101111_AABYVY wyman_m_Page_046.txt
be5bd510e29ae4e98b5bb131886767c1
95e4f28edc2374d9985894d2e074f01da34889bf
F20101111_AABZCI wyman_m_Page_091.tif
de41ff2ae02bb4b3d7a4a044f8d53b6b
65279df6c30fdababcfdad157c9debfe55064760
102444 F20101111_AABZBT wyman_m_Page_151.jp2
5f2353704bd12b4efb0009e1e63e2d12
564108f2c47358b923d618d5ce5af1c682420ac5
502554 F20101111_AABXUA wyman_m_Page_085.jp2
3dc05353efb1594934329ccfe9db0810
e471b570f5ea0000de3745cc7f62a35f3653ccc9
F20101111_AABYXC wyman_m_Page_112.tif
a478fe321fe2a9285af01076760fa29e
eb2f75a687dad3977404556a14cc64e15f36a538
F20101111_AABXTL wyman_m_Page_089.tif
d5bec9d749448bb408d576e904168377
e867736b66db04537f90daadb4aa89980636df8f
4919 F20101111_AABYWN wyman_m_Page_120thm.jpg
6c9a5b848125d94808439375bcfd2932
a055cd5ff201eb752ff6476d5bc1e1fdc5a4dda5
34526 F20101111_AABYVZ wyman_m_Page_122.jp2
eaf74da7d7f1571672a82fceb0b95f9f
df35c376a6051b6602aacd92f5dee93359eed275
F20101111_AABZCJ wyman_m_Page_094.tif
528dc44e868f3a0729b17bef0a19652e
5690df799c19eb88872f94039ed372b10548ee7c
F20101111_AABZBU wyman_m_Page_001.tif
194ccb25829bfba33cb270f5095ae6ed
26b48fbfff7dd13537cd6c58b09ba5706cdd7406
488260 F20101111_AABXUB wyman_m_Page_046.jp2
d8bf9d69544ad449de4d4fa9b79b3671
a30b8f45cf4c15d3ed16902c1ecdcd6dfba7b758
1051977 F20101111_AABYXD wyman_m_Page_145.jp2
91dac8825a0cbaa1f6ebc67855ed167a
5fb0199bdbec4479875a65489f78d9daced18631
2061 F20101111_AABXTM wyman_m_Page_024.txt
96e52b80a922395e6a1de75e2d24e28a
18d93c1764a3633edc3f6852aa790bd1da9ebedb
F20101111_AABYWO wyman_m_Page_081.tif
09b0684f23bc760147f9bd6e8a469803
3a2cda73e9c9f2d6a69024d9a6fa6ec1b0d8d37c
F20101111_AABZCK wyman_m_Page_100.tif
6fdc6875c759d16a0e81591370a08212
67ea44c1576ed30b5928312cdd77f0a291f1541c
F20101111_AABZBV wyman_m_Page_002.tif
175a270f0ca0b112c11fbda63d267a72
ba95394c28617eb545c6b467e54fb246de161a8c
F20101111_AABXTN wyman_m_Page_145.tif
b459007bf7c877f439494102891e1dcd
9239eeecf38e83c71387ed7ddd6c3297b3341901
35324 F20101111_AABYWP wyman_m_Page_101.QC.jpg
2440d7333dc3a81265e41e55b85a5ec0
2ffb3d6ec0f9e834668a415ad91cf61f71419817
F20101111_AABZCL wyman_m_Page_103.tif
538a1ab99c71dbe5b5607f01326ae84b
6cf52023ca0affef15c2edad9ef72de92c5f474b
F20101111_AABZBW wyman_m_Page_003.tif
d87fa1581f487ee98b84d53c6a5b0a6e
d5018925b335cfffbea42a063896878826b0d210
55303 F20101111_AABXUC wyman_m_Page_065.pro
fcf04a310b5660f459369d346d9af5fb
c2c973d684806b3c83861c7f6a8d4b3648ad9c2c
8928 F20101111_AABYXE wyman_m_Page_062thm.jpg
ed100b46d8a867bd3ecfd17dafa0568f
72172c85ee5d998f253d8f924368216f9121c0f6
36048 F20101111_AABXTO wyman_m_Page_037.QC.jpg
898b43f3f22f2a3c1c5c2a6f1a5df7da
91af74005446ee6e10d4ed43c14c7bdb172bbcd0
117297 F20101111_AABYWQ wyman_m_Page_110.jp2
f3ff5c5b92ccbbdc09c3ed44b5bdd0e1
e4f968ce3a6589502b4e9614bbf2c9c5ffe70e3b
52199 F20101111_AABZDA wyman_m_Page_024.pro
58a7f950edb18ea601450086daac1e71
fe0a76ad3996176644f863c72e206174963de07d
F20101111_AABZCM wyman_m_Page_106.tif
d4e9d00e33d3950ee020995773d10174
a5f2897855dc1c5d440379d71523dda0497de036
F20101111_AABZBX wyman_m_Page_010.tif
e535d198d4aad193850df93f96366a0a
0ee2c1a93852ce3f0d542d65aaf0887a434c2302
43093 F20101111_AABXUD wyman_m_Page_081.jpg
51246d4d0d6fd15079da8368bcb72a3a
d975db92388669dfa17cdf28857c2a3bd218b6f4
F20101111_AABYXF wyman_m_Page_042.tif
1146737ed2865ef7a5e77153bc775686
e2f3722a30e4c58d85e384588b544d5d8217dab8
1002 F20101111_AABXTP wyman_m_Page_153.txt
ac287a6d29c071cdbd35297fdc69e13c
2505bd2aabfdb2f88e1be40bb628237f83f3fc0c
55596 F20101111_AABYWR wyman_m_Page_063.pro
4337fdefa31c01ec7f5e88ec4984dfc6
451be64ec9a92cb69d52479af9f8c53985b53023
46727 F20101111_AABZDB wyman_m_Page_026.pro
3f717dce5dc345354593df1c3b5ceee3
c6125e5e212f0f45fe2d34bf762bfbac43906e6c
F20101111_AABZCN wyman_m_Page_111.tif
efcf35d6b2a731e36f08617f4ced7a8b
b9b4041e193eb134038e1b7cc3ce70be542dff05
F20101111_AABZBY wyman_m_Page_014.tif
fbdbe7a39b7b4c77d5d490c2aa792a84
451f645db8757f6208438a463ddb3205f757ee81
115513 F20101111_AABXUE wyman_m_Page_096.jpg
74cbf1e65dd0bfb74ca3678554ea1f08
dc034aab5809c36b1420b93dc0e048ddde3d087b
36577 F20101111_AABYXG wyman_m_Page_016.QC.jpg
f8e38feb1e0ab9d95e447292dfbd589e
5d6c0008c0f3577025fbb5881e6b9c841d32e947
119292 F20101111_AABXTQ wyman_m_Page_077.jp2
0f7dd942a3757f1cef3e00c9b3966c0d
6d9cdc30a3d4510e68d1dea072c8c5366de4bdf4
115106 F20101111_AABYWS wyman_m_Page_042.jp2
d1713bb61c0f713bc185ddd5187dc2a6
8b52705401ea2cb5c4cb0613cb70b7c49f937988
53183 F20101111_AABZDC wyman_m_Page_028.pro
ff9b03d6d9b24cd8b7510d0794beb45e
d1f9ed26cf06728863519619334f0f9856767f0c
F20101111_AABZBZ wyman_m_Page_015.tif
e23b1e8251e0f46c1bfa51d9fd7b2e88
1e028b6bdde3f9bb8a5b8cd3a841c57dbb41d369
1515 F20101111_AABXUF wyman_m_Page_045thm.jpg
0ec7ebf46082021772a8b430e47124e6
c1e1a5774eb10ffb984de64617ff5aae457aeecd
9457 F20101111_AABYXH wyman_m_Page_150thm.jpg
8423102110c9d73f36bf2940b20cd3c6
a5cfc6a1766ab4bdf2d850ec0d83c3f4f319eba2
117087 F20101111_AABXTR wyman_m_Page_043.jp2
87e16258113a63857b75e1a9704acb0b
b54d5ee6aa0a4176b9deb71a727d2802e5c5d5e0
113138 F20101111_AABYWT wyman_m_Page_063.jpg
fd44b77de33c5fe20007aca3ecc76077
3c399658b0964b23a01ece76e86ba0728654eb68
574 F20101111_AABYAA wyman_m_Page_079.txt
34ea5008bae67c5e668706539a0ac2a6
74d04f2bf151142d31425e04b96fa9c90775fdd1
53336 F20101111_AABZDD wyman_m_Page_030.pro
f952df8312e4c497abe7020b893c4cce
e1d9d2eb6bb622d781d3eccc095225561361d66b
F20101111_AABZCO wyman_m_Page_118.tif
3fdb32776b0850990264d626de412214
61e215d30b8c9adf392782f60635ea9806f3040e
67482 F20101111_AABXUG wyman_m_Page_147.pro
5db7425eed8b521d80d12e2df37d52ad
d938d68a58cde18f58cf7924eb24dd7b6359d435
8823 F20101111_AABYXI wyman_m_Page_072thm.jpg
b48203304262d932a2042e31d47fe593
88cd9503ce4d9ab6ab4acd63a62d896327e224b1
9062 F20101111_AABXTS wyman_m_Page_113thm.jpg
63ee5b22cd814c4e908892616542eb31
1581c86a3c7d89afeeabedf96798976fe9f7b0a3
9020 F20101111_AABYWU wyman_m_Page_013thm.jpg
e49ac57a4b593cd89741c4041d48d938
7e1549a69fda29fd5bf402cc089953cf7d17c472
36128 F20101111_AABYAB wyman_m_Page_073.QC.jpg
4e6336055295e3453afa39a6dbd49982
2f2ba619366ea5b2ee58b862aa07f4b348c5f9e0
36941 F20101111_AABZDE wyman_m_Page_048.pro
f8bca7260f9934702f45aecd0dac816a
3aad7d54f6a4626ae37ae13a410dee468bb2a08c
F20101111_AABZCP wyman_m_Page_125.tif
c5bc05ef12d8196adbdb792446b05b98
bdbc2a3e56edc7af3f27827f1f09006dec0d4846
2203 F20101111_AABXUH wyman_m_Page_031.txt
e2eb6addb4bee74558594a4ed18f0d2f
97e66ed19ef4c006dc3bfbe90624505335f27524
2115 F20101111_AABYXJ wyman_m_Page_125.txt
050d7d0fc30103093c8d5ba67cc37555
941615beefc1886d0414a0cd84fb223052621c3f
2126 F20101111_AABXTT wyman_m_Page_124.txt
6ef6f0dc3e450a22cd3d7ee14dcce10b
aca93dc23848c842bdbcc2a460988a2db5863da7
121035 F20101111_AABYWV wyman_m_Page_112.jp2
4be5e2738387f87f707738cef7b94461
cfd2065522b30274c551716874a975b55f4f6689
127703 F20101111_AABYAC wyman_m_Page_143.jpg
f2ccc250eb7b9f1f72030fea722d341d
259cc460e8b20b9eb0441c30c97a409fee1c433c
32142 F20101111_AABZDF wyman_m_Page_050.pro
653b3911d4b3261f83a11a10009d8f11
2b0c84f4468dec82f7c0c92a1c5d53d5cb41f7a7
F20101111_AABZCQ wyman_m_Page_126.tif
8efe5de10949d3ce09642788b94fba25
5cf89264bf73011c8cc7cbf0957e57164d4eade3
34899 F20101111_AABXUI wyman_m_Page_060.QC.jpg
da01ac977a09da5ed8f82e5e9f8355ba
9ad4cb01d13dd1f2dbc41a4a98659bc510181165
8926 F20101111_AABYXK wyman_m_Page_065thm.jpg
b2e708301294cb2ee1d99801e4c6a597
9338baeb2783d406109fc3acd63eb19af6613adc
32812 F20101111_AABXTU wyman_m_Page_039.QC.jpg
a7e38110fb942c713d6db612e42a4a97
b02bded1e654e0ebe7a4ccfee3dab55f1d2bbdf6
16293 F20101111_AABYWW wyman_m_Page_084.pro
3ec4b53dbe4fda21a75cf34eadbdd6a6
df525ebd3c59b887e2e7b7acab80097564d78b45
34464 F20101111_AABYAD wyman_m_Page_109.QC.jpg
dda8d834a9b67d3ef85934b1f0129545
74bd429036d03dc048ca75ae46349867d48defa0
53274 F20101111_AABZDG wyman_m_Page_053.pro
234da29ae5de04ff086316114c1823a5
921e6f9d2e8c9fdc10125bfc50af71d3ad4c091d
F20101111_AABZCR wyman_m_Page_132.tif
26c3bae091cc13a5b5c4920cb8a406cb
56380493ecaca4788ed1add0c6ab35360711191a
37141 F20101111_AABYYA wyman_m_Page_149.QC.jpg
b272fddb359811cc9b09d94d170431ad
ca634aa6386b75bb0b75cf4b76ee32be71c88948
6252 F20101111_AABXUJ wyman_m_Page_081.pro
4bba765a690f3e05f6a907027f38b37a
4674a1012eff4954432b0860966bf6673205afac
F20101111_AABYXL wyman_m_Page_039.tif
7ba5c71d2cf634ac8f24ff0632f8d883
f6c4ab95d4877a4f718ebea62494186f84a27160
144069 F20101111_AABXTV wyman_m_Page_140.jpg
9de8030149f511aa50dd64bcb33fc0c5
dfc42cc9cc307db1013634388e55793daf77ba34
106840 F20101111_AABYWX wyman_m_Page_099.jpg
568d17b7896616f3d0d0fb1606a62683
3d40e2e987e7714292c46dea770456a429feb12e
95811 F20101111_AABYAE wyman_m_Page_082.jpg
20efd91fac241b957f839d54294ee4c4
3724fafd48ed7a9c4b07963d846f31332c0d17ca
50676 F20101111_AABZDH wyman_m_Page_061.pro
6d31726b22937292b00817ba598d866f
5fc05be4b8a297d3563fd891587aeccdeba405c6
F20101111_AABZCS wyman_m_Page_148.tif
2d65267245fc3cdf1ccbc8d8b969b14f
306b3d295929e8681ca65196693068b33f986004
15874 F20101111_AABYYB wyman_m_Page_083.QC.jpg
bd904404e8f52ca0fbdc9c04a8b19e68
1879b0bb5c4bb60709f904a08b1ec01b2aac80dd
387139 F20101111_AABXUK wyman_m_Page_047.jp2
b4ac97fa911ea8fadd8619bc0776cab0
197a055267f3752f9a75d3b49d703b27361a564d
53142 F20101111_AABYXM wyman_m_Page_113.pro
a02ea74253a08bfeb05a28bf4a42eac8
b0c5deeeb3c5b878780f4380fafb6045bbb940a0
35264 F20101111_AABXTW wyman_m_Page_027.QC.jpg
05e249807c4306448c2821aa49f98236
708d0058312a684e28dffe81b90137e938d043d8
2117 F20101111_AABYWY wyman_m_Page_107.txt
e99d22a03a949ce530f1b9056f8f592e
f3c7863755c9694f9315c0948234ccdde687058f
773407 F20101111_AABYAF wyman_m_Page_090.jp2
7950797b17b017741723d3df3c0d5d9b
59f6ad63cbf89ea4f56e863a471c81212c570dbb
52718 F20101111_AABZDI wyman_m_Page_066.pro
1c9eda4aea79e98c599f54b93f80b03b
293a28b7163641b821ee730b532d22240034dc43
F20101111_AABZCT wyman_m_Page_149.tif
79a29f53c31e73ca8beaf0ccb2525e8c
5b9abeccfada913345d3701c770dea84a864b8f3
116203 F20101111_AABYYC wyman_m_Page_101.jp2
9270acb8c88a56688cb9357f2e8c1e74
9f9857d3bba495785f168950e0956c2e2a367bbc
2570 F20101111_AABXUL wyman_m_Page_138.txt
ad1657bfe978c3631fa24a66eb05fa9a
6f0ce45ea66d072392df954423a38a39fd83f49b
2165 F20101111_AABYXN wyman_m_Page_075.txt
dd671e14973d9f2ab2b990803869ddbe
13d7d1d8ce4b015b789c4b0d13208ff62e3433be
112356 F20101111_AABXTX wyman_m_Page_035.jpg
9c4720ac0f4b431c61236a365a87bdb5
e1c4fb05b814b99ba411bc6177d1066c0c899228
151285 F20101111_AABYWZ wyman_m_Page_130.jp2
2ad066717b1dbfa7deb8e384c4b5ebe5
e04379bf899fc81c2a8d27f41f0a6d262ac14e1a
145816 F20101111_AABYAG wyman_m_Page_140.jp2
e33d39635cf9859b1397982ce09d79a5
9062f5071de9ad6bea88e1dcab76a6fae7cbc141
34832 F20101111_AABXVA wyman_m_Page_071.QC.jpg
5a8c93a6e9812d399e6146f1236d49ce
d0b1b2416181849e25795525bca4e2536eb32cda
55096 F20101111_AABZDJ wyman_m_Page_072.pro
465c86d5063e39c2cbaa0f52c0654e00
e2c9704721cb9856a2cd9e4278ae02e5c2839e1d
9416 F20101111_AABZCU wyman_m_Page_001.pro
7a1b70d9337f6a5b80951e397fb96b8d
e029310acfdfd602b6bcce57cc95f82a60c54c8f
8727 F20101111_AABYYD wyman_m_Page_112thm.jpg
193823e12a0d4540c98ac6b7321461c6
da660b7f0b719e6be4ade7fa5b39bd53388805c2
5080 F20101111_AABYXO wyman_m_Page_121thm.jpg
ffd33f3b8837804d210dc2d81ab867f4
e7f908a5cdb15feabe14d33a7ffb12f1498c6350
2146 F20101111_AABXUM wyman_m_Page_074.txt
b7abe56fcb2ef6b819e71c10e969c70f
c11d24d487f346f7f99cc4bfb8421a3a2ad34e01
56550 F20101111_AABXTY wyman_m_Page_017.pro
22ecaa06db9a857ebb0f4efde4310b77
4d2c010b0d63d9b1446af19765668e12b4927cc5
2098 F20101111_AABYAH wyman_m_Page_067.txt
de685e02ebbe1b4e14527c39ce4368b1
5970d82e82040e8796bcfdb74c35134fda32022c
6287 F20101111_AABXVB wyman_m_Page_003.jpg
844cf2de371bf645deba77d6def38633
bef0453e912b5bf628ada7dd5806b025fcf2e436
2310 F20101111_AABZDK wyman_m_Page_080.pro
6bab1ee3c84b365ef05ce5c8318349b9
157f1989d006a7db7e98630d6a6a8f367f05b647
29951 F20101111_AABZCV wyman_m_Page_011.pro
f39ac16ea8fb534375282250f4969fef
cfabebe1dd7b5c09704f362fac0c971d4fb11e7d
5593 F20101111_AABYYE wyman_m_Page_084thm.jpg
db067198563ffc71f5f32efae8999c39
f10d42b6adde783c2813379fcdb33c28d388dce7
F20101111_AABYXP wyman_m_Page_034.txt
f8bfc2310a205a597e79b62bc76c3abe
6c674c1b2925132ec09b8a16a8a0efe3e7deda4c
8631 F20101111_AABXUN wyman_m_Page_124thm.jpg
8ba20dc14eda7481adfcd920aac19cf6
e64c318588998ca45473534c30161733f2c8b004
111292 F20101111_AABXTZ wyman_m_Page_034.jp2
1c9b42d904c0395a72e7998509642a23
ab312cbc0055d42ee35b338597a31980b833d977
6588 F20101111_AABYAI wyman_m_Page_006thm.jpg
5fc65bc9099375c02274fe33bf3c00b5
d303e6fea95a7c379a6fd734971534c9718087c7
8710 F20101111_AABXVC wyman_m_Page_102thm.jpg
00143163cb0adf60e140357d01ded385
4037350ad9038d5800dc2921324e7fbaa51a34f6
8015 F20101111_AABZDL wyman_m_Page_082.pro
5be5219c6122bce83139c6321b8707e4
07b929f7fd2d17eaba7553f4051022ee6ab28b24
53012 F20101111_AABZCW wyman_m_Page_015.pro
cf1882c8125ff12220f9390c467dcd37
c503cd8f51d479755bb29746ca60e18ff121ebb5
21838 F20101111_AABYXQ wyman_m_Page_052.QC.jpg
84cf4e9a64e6299e8c03154e3559dcf5
fd887f91cfe48a5242f1ae0ba8c68eed1bc8cc41
36679 F20101111_AABXUO wyman_m_Page_068.QC.jpg
dd155889463c504cd5cdfb3590c438f1
e5cec2921dd56b7983c834c35328a185cf970121
54539 F20101111_AABYAJ wyman_m_Page_068.pro
6704535a39f5fb377461504e340a573c
2d10a111793151bc101a412c4140f76474e8a1c2
125 F20101111_AABZEA wyman_m_Page_003.txt
c4dfb18f511763dd760020cc1237d853
8ecff1fe225c519514416d99cf86928ee2842c04
52907 F20101111_AABZDM wyman_m_Page_101.pro
4d4bb3ed824e84b9f662eb41f2235b06
68257c9aceca789e05463e6bfb0a429a1510d28f
54363 F20101111_AABZCX wyman_m_Page_020.pro
dfdc3c0dba4e1e577b31ca278046da5f
dbbc61412b55f6bf7177e4c3c4f85204546a44f8
96343 F20101111_AABYYF wyman_m_Page_064.jpg
1a3d714b2595ce4192053b68b00fef84
c6c80cb01d1af1488e1846aac2a4b324aa24a2d0
8859 F20101111_AABYXR wyman_m_Page_053thm.jpg
338f78657f2c1bf8f5a2828bfdbf25d4
194d29433aa577e51289a5406ea1f27b6d000429
34589 F20101111_AABYAK wyman_m_Page_055.QC.jpg
b122cf0b1c90f1ce26c77a15aa395d26
50c0730e9fa9030641fa87454f7c589922c37b93
117403 F20101111_AABXVD wyman_m_Page_072.jp2
d14365d0160bbc43b523247c2d94f358
355b759b5f762021a2e1264322e61db001e11809
20585 F20101111_AABXUP wyman_m_Page_011.QC.jpg
1f5642afef5710de5ea038a4842dd9ef
ed02c0763e3bed62f33932f689bf962170f28a22
1975 F20101111_AABZEB wyman_m_Page_004.txt
9322f3aa89f38ebd30c795049a7bdaad
0ea79cfbbb7e0866beb93bf5460a41986c8ef9ca
55791 F20101111_AABZDN wyman_m_Page_102.pro
dec537a693b3f12ba21faf85e216ba7d
c3d13365d4ca61202bad98989b564b3ec0d17705
51501 F20101111_AABZCY wyman_m_Page_022.pro
2d79c0bc881fa5bca1594f4fcf2d8b17
94a2e875d9c207b8953b33cbd6dfa6ff9ffeaa6e
34284 F20101111_AABYYG wyman_m_Page_079.jp2
6d5d0ac049b6dd69c609b789121b52c7
e16755b0220af8c348faf975b52a516ac932baf3
2104 F20101111_AABYXS wyman_m_Page_109.txt
a8f413be3eba95ccb729766315b74dc8
d336e88e745fa0ca535b944098c43eb15b17b03e
110960 F20101111_AABYAL wyman_m_Page_065.jpg
64eb836b5df2634bdf1620f8d8b4ce90
287f12b533a6fd23a7b88106d6219df663d20ada
36249 F20101111_AABXVE wyman_m_Page_067.QC.jpg
5f42c35a3f0dc81fc819cdea13575a7b
0e1bd97b89feb9b540bbec5dc6f9d8a8dc1d622c
80365 F20101111_AABXUQ wyman_m_Page_049.jpg
949645108eac1b7ca4acd30b595a2066
50c0a2f17551500d07d1e5ac82b436dde3997049
4496 F20101111_AABZEC wyman_m_Page_007.txt
6543da74e8342a074c18e577d194bd56
d44cb5cdd9e6c5111158bb6b693cc2d1929ad0eb
48652 F20101111_AABZDO wyman_m_Page_103.pro
68d8d1d71afd85ecf719048d84dbf47f
78891814e99b44dc4cf01fc799f0f9fe07c68599
54159 F20101111_AABZCZ wyman_m_Page_023.pro
88a714a6501784db7f5f5e2ed169bbb9
4794836908819026ec3d0ba6c8a50a4012b43ddb
4736 F20101111_AABYYH wyman_m_Page_118.pro
0a08f7d3ba6b8674dfdd6c1665a683dc
4d6b090fa0d8375168f29cc51bb9643f462855b9
F20101111_AABYXT wyman_m_Page_110.tif
231f77319e95e15f9e2c938d30340f12
ce46411d9e5247e68f1b613c54d59416e614cad9
2080 F20101111_AABYBA wyman_m_Page_015.txt
cb85845b44d042fbedd01cda3ccd3061
6c38b7bf05dc33b40be3834d5e6401a9d4360247
35246 F20101111_AABYAM wyman_m_Page_066.QC.jpg
9be93a81d0c1431d5d16c175f4a4d90e
016131c6c664cd747975569ba78247013878d440
6150 F20101111_AABXVF wyman_m_Page_049thm.jpg
679d1bcd7ca3d1487013e4e56f7a1aff
9a084bf85b5f0c98f5c07698b813c386e9f60415
F20101111_AABXUR wyman_m_Page_050.tif
1d51a06ee4245a1c779cf38684007076
b5814439030d607481c527f583a14b54de9e4922
2665 F20101111_AABZED wyman_m_Page_009.txt
70a44af38f4d5c8557651663759a8ea8
9f457706a4e3faee666229ebbaad0fcef71592bb
241 F20101111_AABYYI wyman_m_Page_080.txt
c9015fbf9072ee52f425904cc79a809e
93c0220000ef7080cf11983df0c04b2f19e5dda2
6296 F20101111_AABYXU wyman_m_Page_045.pro
7ce87dbf8b48e4f200ceb7c1467de239
74b8fb53fc6175f29a105416c3b9facee66ce498
63993 F20101111_AABYBB wyman_m_Page_094.jp2
67527991695b4c98e065162171359d2e
f2dd9747139148924413f019abfe2e62e5e50b49
33981 F20101111_AABXVG wyman_m_Page_052.pro
71c0abc342bf7f8a99aeb1a8258aa075
b5e2111bdde29df23720b833fd6c518a3f706d37
98422 F20101111_AABXUS wyman_m_Page_054.jpg
a8971fa36809e48f4e27a0b3255009d7
02616dabe9ab20799f036189a1a97fd11bdf9ede
F20101111_AABZEE wyman_m_Page_012.txt
bf6423de3788b9d1960765303b1f5b6c
d9f0cec8dc1ebb4b0496acf11628137d1c450fcc
52231 F20101111_AABZDP wyman_m_Page_106.pro
758195cc64b175cce207795e55c38ea6
f2406c3fdf7a7ef1d0b9d38160bacb3e097ca66d
F20101111_AABYYJ wyman_m_Page_030.tif
c92325af3f7677d4a50b5243be2126b7
b67139462eb6e7ecde31651621be0211d6f13da9
111334 F20101111_AABYXV wyman_m_Page_069.jp2
0637aaca7442b9141864fcc4f01d758b
c24e4231d1ff986758d8a15591b017c83f70c63c
F20101111_AABYBC wyman_m_Page_115.tif
9ac58f823fcb51150cb0cbb3181dda77
2c824a1b63514895d5450817943631ce1289cdf2
8699 F20101111_AABYAN wyman_m_Page_106thm.jpg
45aa77495cde416013374e99483935e2
2707a159b4906d9ce6470c9eb58d5c7126b1aead
5019 F20101111_AABXVH wyman_m_Page_117thm.jpg
67497b67aac4afb3154e307283ede820
7a4796e24bed65f782349bf677d5bd1569e63e43
109593 F20101111_AABXUT wyman_m_Page_068.jpg
0ec0dc3313f7d980386f0a913fd88039
44bb415a6914edd829a833b8427abd586f8f0ca0
2253 F20101111_AABZEF wyman_m_Page_017.txt
f61a892993631becfa379f44efea7d97
d852fab8e75576b349214c5897567e0ee305902b
53874 F20101111_AABZDQ wyman_m_Page_107.pro
04af3d755eea6a23b96bf347d3cc9ccd
9aca65ed60401c6376d2551155fba73d2c0055c9
F20101111_AABYYK wyman_m_Page_026.tif
026f87be28fd28176be388614945aeb1
299b255c11e6ec89300211468c954ce7804377df
9455 F20101111_AABYXW wyman_m_Page_145thm.jpg
eeaa73e95f2e6065e85640691e8cac14
471cb5826dbc5679b456f6a6a80d4bca113dfec3
35150 F20101111_AABYBD wyman_m_Page_076.QC.jpg
db561c1f863e1448c10919f65dd481ae
8159349029fad4f012254344d23133790e50e618
64905 F20101111_AABYAO wyman_m_Page_149.pro
c13642c51861d484f2f69ef2ce55c570
2b6c887574ab1491f74a3494034dbad1a1f8eb41
1234 F20101111_AABXVI wyman_m_Page_002.QC.jpg
ab50a35f52e9542d2cf83c9628357b81
02c3445631a62fec15d425733f55b21e4eaf140e
7037 F20101111_AABXUU wyman_m_Page_087.QC.jpg
c488d6ad4ca5e2281777873f13590b48
129068c33a7e679937f8e015852771cd470db595
2129 F20101111_AABZEG wyman_m_Page_018.txt
5f602415237693c75ca1431dff84399d
5bc9e54119e8b17e1e362e20384ae8e52a133c24
52089 F20101111_AABZDR wyman_m_Page_109.pro
9759354810ddc82a045bfa159e5d7dcc
5395d62ee89760e73af9f558f8aac110da125fb6
4268 F20101111_AABYZA wyman_m_Page_002.jpg
961e4f2c15782e849dfd12b864093854
f7a02ca52afe6efc808f7adefb94d224807e0e75
F20101111_AABYYL wyman_m_Page_114.tif
76d35a938e40ff4457f8d9ce38a76f73
321a69bb82e11ae1b1b27dc234fffe57947c089d
32590 F20101111_AABYXX wyman_m_Page_010.QC.jpg
eaf5327c482a5656ab35de5d67e60688
602b024f5dfb900fb014c694867e2d5d30d360f0
9400 F20101111_AABYBE wyman_m_Page_138thm.jpg
2709c63baafbbcaceb3fec1cda7709a0
09611f072c77685f7b4d2b617bb2cbb43034b9d4
54044 F20101111_AABYAP wyman_m_Page_037.pro
26b816fdc1d38bc7dd0edf3dcd95cd9d
431ccbf07a3ef4784e4a238e1eea025e379a566d
136402 F20101111_AABXVJ wyman_m_Page_007.jpg
680ab1d14a8eb79a10529d692d1a0185
335a730d8f523777ae256aa6798f51c0d092e18f
F20101111_AABXUV wyman_m_Page_151.tif
0ae8a8e9164bced5843109d2bf74747a
319f959e7f2c012602d24940208ca358a314ddf3
2111 F20101111_AABZEH wyman_m_Page_027.txt
31bcd849e48fabfe96ec13c49422a2d4
a622b29894e5581e8cf801a1681860d3ae8c7f64
48511 F20101111_AABZDS wyman_m_Page_111.pro
21c8b28e37292ef7c1d72f799c9ecebe
025250374a753b568601c90e253d2016e87472da
119309 F20101111_AABYZB wyman_m_Page_008.jpg
2c53f3a8e1bb0d690bde548c7a243685
83463152aeaf768a789606e2eac4b6cd9b34fd6a
2142 F20101111_AABYYM wyman_m_Page_068.txt
c58da385027e440e5b3e4a8b5841e2a5
648c4057de1648a1d81ff8b39004d986817b8e66
F20101111_AABYXY wyman_m_Page_064.tif
3b9919bd293c69435902798ac586759d
046654426c2963666b2bb064738ac5b28dfa3dd8
1051971 F20101111_AABYBF wyman_m_Page_009.jp2
1d40e393cf393a81d71a4a789b2bffed
f8846b51ec28b6ac13194ee6a7b7c38eccc691ec
F20101111_AABYAQ wyman_m_Page_122.tif
4cb89bb06ee1165e359f4574dd0f96f6
388e279e026431b9747dd0b98c83cf6c4ba26a1d
2188 F20101111_AABXVK wyman_m_Page_077.txt
22b3b9367ffa248a0ae497e155156e3c
2e204af40817bb3a09c1668af4a95c3ea27de59a
106033 F20101111_AABXUW wyman_m_Page_012.jpg
ef7b30ded8d917bd19754d908340eb73
50173a9e78c9519cf718c854f50200f5c05acca0
F20101111_AABZEI wyman_m_Page_032.txt
26f30513963ed17937bf717f803ffb8f
2af370220d2e3aa2a7f9d82f6dddee1f9b22af9f
52833 F20101111_AABZDT wyman_m_Page_115.pro
27734c6d5e930ab15c32c1cf2d4ebdbb
c993c152d475c28c3b52c6fb36b351ed6115e3ce
113661 F20101111_AABYZC wyman_m_Page_013.jpg
3ceaa1d103b7416064f1570f84937c3f
ee6b43d5f19859419cd88dccffd00956f53d7e06
F20101111_AABYYN wyman_m_Page_076.tif
62f4a2e3b2e1d711f8f5a516b68b948f
cc2904054ecbc2bca792d5505aea612f85a1053e
F20101111_AABYXZ wyman_m_Page_028.tif
13b02f486e9473c69e38b27118993e00
b55d261458f75cc67f579a1d0092291e839e3c1d
8703 F20101111_AABYBG wyman_m_Page_110thm.jpg
bfb72477133c038c6d0bd8c8beecaa0a
2ba8c2473e7e94b04f8817248303a4984149a345
9073 F20101111_AABXWA wyman_m_Page_063thm.jpg
a385b9ea560c35f83184eae27c4bc481
f3e654bd1bf2841a7e13863211c8c9dea6ffe738
60316 F20101111_AABYAR wyman_m_Page_120.jp2
11ae41fef617d1afd498f2bd55a44fa7
bfcbc1f9ca45dcccbac7302d4f81a307ee293535
89964 F20101111_AABXVL wyman_m_Page_006.pro
c8df4a5a227f5622086db4ce248e40cf
61f9621b3a99ae15299fcb93b5e0256d910f10aa
F20101111_AABXUX wyman_m_Page_043.tif
38b4b384135927a77936af15eaa5e2d2
7666f908022203bc04e8ae3ea138a7ee9e29e542
F20101111_AABZEJ wyman_m_Page_035.txt
b53993643e9642a4aa0123cfd701e296
f6b221d425f52e2b9466b0df64f73248cffc46f3
49123 F20101111_AABZDU wyman_m_Page_126.pro
ec74033dbe7d2ddba2487461ce235015
1cbf0160c8c8cdd3841dc272595aa9c5a91e2e07
112265 F20101111_AABYZD wyman_m_Page_020.jpg
d4a9a23abce0a1170dc6f012b70d03ca
ef1383e0a371fe7ca0ee97bdd1da546c7bb2436e
F20101111_AABYYO wyman_m_Page_137.tif
ad24093c6c8999bacfa082b9ee9b6825
b208df30e2fdd9a3879e120101306b4b7ca4eb17
112983 F20101111_AABYBH wyman_m_Page_017.jpg
aad2444d9355c9847b3ce32a7b8a2d1b
c768619067e8de9eea2ceaf4c189c1094076c93a
F20101111_AABXWB wyman_m_Page_124.tif
ae99bdc0c48481a0dc224c16f480f0a5
7f9734a26649f0a53eac8f12f13bfe85b2ba2abe
F20101111_AABYAS wyman_m_Page_142.tif
5854cb719d3334420b0bb68d46c7eb61
cb298f0e4dd62fc4f7478f0f036a4798d31b7814
36700 F20101111_AABXVM wyman_m_Page_095.jp2
d8e8c043790d2a1c0991140ea17f1332
e1bda2e65a1504b318149914276531660e630707
F20101111_AABXUY wyman_m_Page_019.tif
8d0d70a0e26e64704774b602ba680d57
d9740b81e8d7e35561fa6425b4492f6efe5f8bf0
2175 F20101111_AABZEK wyman_m_Page_038.txt
60ef0305c6a306ad3dbed514bccf9821
89cfffa5be12351573eeada9cd88003ee139b826
71057 F20101111_AABZDV wyman_m_Page_130.pro
ba3828162a8a3a2059a84fb253cf5f2b
99f7b4023953a7a1fa3b665eff83b12d4ded865f
110704 F20101111_AABYZE wyman_m_Page_021.jpg
71fe71dabbd40e3f998da681b3114ac7
925a3a77dc1bcbb3d51bf1415360f1ff8fb1a85a
64994 F20101111_AABYYP wyman_m_Page_135.pro
8a4cf45d4ddaf2af51ac5b27cc3f8067
50a659a2ef414c66a8145807c207f6299a285b3a
1966 F20101111_AABYBI wyman_m_Page_123.txt
f8543f0dd8d88604252bfd0c44ceb23f
3d225d53895fd1e0491ef9c7de2408c47fcb6869
38685 F20101111_AABXWC wyman_m_Page_150.QC.jpg
4d6942c1487e86ab37bcaa65985f232b
fee372cd54aaa474eae0bf0ae76e8a3b13482f82
109629 F20101111_AABYAT wyman_m_Page_113.jpg
acc4c821b114ce7cd58d242b90d820ad
ceda0b185652b796cbed789c4171e928ea0aef6d
116226 F20101111_AABXVN wyman_m_Page_113.jp2
cf529499cc47b8023e7a3e8b9c7c2813
077d103e78de094e11bff67d99de00376be1b9a7
57432 F20101111_AABXUZ wyman_m_Page_044.pro
4a7ee17408288e31ef2dd94238dac63f
9b29a804cddec98450b2f1d61cc68ac79bb49641
2200 F20101111_AABZEL wyman_m_Page_040.txt
6e9f9a0e5b5473973d066456dc73792e
5474bf4d99840bead90b355da8b529871cca1f8a
67055 F20101111_AABZDW wyman_m_Page_131.pro
c489ffc317d626e2352e7166b6e6ffe0
5461e914a93a85ac7413238799063cf3d097a746
105554 F20101111_AABYZF wyman_m_Page_022.jpg
d3c9cfb043f79aea141effee209e8c29
a0bdb01a57365e35f0270b21dee9ec9eaedb8186
F20101111_AABYYQ wyman_m_Page_053.tif
9dc63cb0dd25041a0b57b4ceb443c1a2
df66c21de89e4f800ca96487a3b42aa2977c90e2
F20101111_AABYBJ wyman_m_Page_070.tif
29bc477b24ec9350d7f9a37f4700e178
b32289d7bb47454b0b765e7b2ddde7d0c6d7b80f
34615 F20101111_AABXWD wyman_m_Page_099.QC.jpg
4de0f488e9f2d2b72dadf1967b5c2a33
f377f02f5577eeb359c68c2767d1745fe11f2641
117530 F20101111_AABYAU wyman_m_Page_074.jp2
c5dfe417a6d61a345d8e70a19343b88c
55904fdd311a79671e258ec160dd2380bb281fcb
134613 F20101111_AABXVO wyman_m_Page_132.jp2
46501c7dbdf7af7f8d8b8c21cf5d4f83
83260e32c3206f9de0d2e0c4c59d14a3b97281fc
307 F20101111_AABZFA wyman_m_Page_087.txt
824da982d88233d5d266f5c79ce9831a
7f1349c8d55115ab8d4bfcc25fb68b2bfea4d1a3
2122 F20101111_AABZEM wyman_m_Page_041.txt
19bc567109260d9356733b2e9bdd5807
50f7d9494960e90be018b1e8bc0765f504444c44
71225 F20101111_AABZDX wyman_m_Page_141.pro
ea674373f19bf2fcfe69addae87d7215
3067a2ef2060b1ee08b7bb3576031daeab4a18b6
2123 F20101111_AABYYR wyman_m_Page_001thm.jpg
82fcfb42142c923ef2b46db701833c89
5e8195869940493002e9f3aa66072b898c629636
122074 F20101111_AABYBK wyman_m_Page_044.jp2
a584d04498a0e16075ea9e78ea3cccfb
a79fad3aad96dd3130d39b4b1ccee6e572d486de
2492792 F20101111_AABYAV wyman_m.pdf
58a369fca5d2059ebf1d299ffeb2f0fa
956e87207c76bc76f5902de08270ec958656259c
8039 F20101111_AABXVP wyman_m_Page_009thm.jpg
766e8c9994692237751e81bcfcbe7173
15ef03befe81efc279ffadfdcddd9d1ffba22bd5
517 F20101111_AABZFB wyman_m_Page_089.txt
8f34dd52c281d3fb995283fe35ea2516
6a56afee184728a456ec7a3baeb1b5e2baa68d24
2131 F20101111_AABZEN wyman_m_Page_042.txt
2aa705864c566e84ba0f797a75d21b34
98cf2ccc82a79b8fb5f783bd8cce9758adece163
52579 F20101111_AABZDY wyman_m_Page_152.pro
4e6f7fa00eee377f8f8a29c75f06f948
2317c98d2b0f25b0d0b6d537f2434842e2aec6dd
108119 F20101111_AABYZG wyman_m_Page_025.jpg
9b54ccb8d69a0d7532ac5f8f242bdb38
c2e1a1225c44a9eaf1f705940e17093af25ea582
39053 F20101111_AABYYS wyman_m_Page_141.QC.jpg
3037fd52c56b3f3213dd3658b6b7a41a
e00829a01a385fc485fef852e40f755b03d4e04c
7097 F20101111_AABYBL wyman_m_Page_090thm.jpg
45322ad09f859ec1ea66fb8b2e3d958f
bfa7fddeab3532ce8a527012077f1dcdb10015e5
19229 F20101111_AABXWE wyman_m_Page_085.QC.jpg
172b6297b3e87e414651aa35458bcfaf
9d5c12205f7248b60adb91c11893bd290ff35e98
69930 F20101111_AABYAW wyman_m_Page_140.pro
b29f2685ac885eb4163f4a07a79d2a9b
b43038dfd5d003912af1b905fae2c38a05b576b6
110782 F20101111_AABXVQ wyman_m_Page_102.jpg
5791cf7ff6ae47d85c467a65afae5383
4607da74deae569b9063cf3ae822add7c39ca004
1564 F20101111_AABZFC wyman_m_Page_093.txt
a159f63c1d7ab2c978630a62c5f4611a
f0e535dfe34475e07990a140ad25f160bf2d0a2e
2247 F20101111_AABZEO wyman_m_Page_044.txt
d6827d52e4d00368d547fde240e94dc4
f29a3cafb68db187148818527ab07d3578990223
24840 F20101111_AABZDZ wyman_m_Page_153.pro
4ed51ef9e03c7edac40423ebbbb88d7b
9df815094a47e3a79bf3a6da15c571d3ebfcc331
107359 F20101111_AABYZH wyman_m_Page_028.jpg
ce97f0651fe904d1b1bcb95a40cda8e0
edc5ee35b24d0e1a754d0b4aa80f670fa5c8eb5f
253 F20101111_AABYYT wyman_m_Page_045.txt
fa416f5582412d730e8d94c579f8abb3
00903abbb4f4565dfe2e14eb2a51800602c4ac2c
9032 F20101111_AABYBM wyman_m_Page_128thm.jpg
6d032662ca94da6535d9020ce3e4bfd5
6f549a388355d9e8302275e0ba8f88067c232c8b
F20101111_AABXWF wyman_m_Page_104.tif
96341f7605b8660105a4d76339cb705e
cb2ee84de5a0e7b737d49fe7c753574fe69a1ddb
36482 F20101111_AABYAX wyman_m_Page_040.QC.jpg
53682b1dd3ef5d4bb76e7723b7099111
ef699ff2c05be296a7ac6d2e891f73370ee49010
31576 F20101111_AABXVR wyman_m_Page_126.QC.jpg
b2430af3bd106c1d94a9c1457cff7143
27cf68bc1ac2a7a96a4fb28c3b0ac25f2385f2f5
34696 F20101111_AABYCA wyman_m_Page_152.QC.jpg
8b5f0c41e248e9648bbd757c053ad841
2a46efc0bd87b103cd9363e699ebc90395095ba2
2216 F20101111_AABZFD wyman_m_Page_102.txt
c7ab9bdbb11ec6455592f6df57fa31db
b94ed5d0ccf2c45e4303a027322ff658bb8a6766
1937 F20101111_AABZEP wyman_m_Page_048.txt
923eb30cd1bd7f73844ae03a3d461ec4
58d0e1be039182f8f80a67d76afff85dbaae7d80
107656 F20101111_AABYZI wyman_m_Page_029.jpg
896a32995e5c02908db29bf82c37e473
4d3a806467ced097714a550e461b808cbb39cd31
65835 F20101111_AABYYU wyman_m_Page_134.pro
258fed69aa846bbf581cae57626a19fa
50478055cec417fd4247392e830a1fa795c7f663
8637 F20101111_AABXWG wyman_m_Page_060thm.jpg
585b4ef7824f2ff35688016a1cb8cca2
025ff1df148645fd724d528276281ebe440285cf
F20101111_AABYAY wyman_m_Page_034.tif
c64eea6c09a41304c17b816681cb3edb
b2718982686ac2d7b493b790a1dba7ab4fa4126a
31885 F20101111_AABXVS wyman_m_Page_103.QC.jpg
db53e09b704e8ab86315fd644bcf8a35
c2e41209acc1254b3b616534280543c779ee9173
33165 F20101111_AABYCB wyman_m_Page_058.QC.jpg
d0c89f226d106d1c13016acc7f7c3221
a7a76dead8968ff3a569cc3d09842c0184482233
8931 F20101111_AABYBN wyman_m_Page_059thm.jpg
d9ff1d5f4485363ce7ddaf8dd0eeee51
52e0bb0d1cbd02ce1b544c8b97d94a552f99e0bf
F20101111_AABZFE wyman_m_Page_108.txt
3875ad753d058776133cb897d85f592a
eccc5b82a1b5de1c91505ebc7e795882b86eb307
101339 F20101111_AABYZJ wyman_m_Page_039.jpg
f92dd581132a8d86b9d41735b7f0c1e0
4640ffdb021b0430c4b102b8124420a85e98ff9d
53545 F20101111_AABYYV wyman_m_Page_067.pro
65d0552367177447277bf30967006503
ebb15b9162ae2515287834a9c69d5c71aae1389e
F20101111_AABXWH wyman_m_Page_096.tif
477d9609a241af258f9bc31110a99cec
eec4e6d06d478ba194c9407209cf82ff9ff5926b
9704 F20101111_AABYAZ wyman_m_Page_142thm.jpg
d025ded45d69b0f8c7ffef2127d1bead
8e44ccdcca909eebe832aae09ca3a280cb3f8f4a
F20101111_AABXVT wyman_m_Page_116.tif
96b6d930ed12a4df16f2dc810d16887a
e604a76c2ca49f99f77f310472c925c53054fbc0
F20101111_AABYCC wyman_m_Page_079.tif
91dbfe895458be843da31d4af19c9599
58f2a9e5a805f2028f82e69d92b8969525154109
287 F20101111_AABZFF wyman_m_Page_118.txt
bf1695a9a74b4be327a071db82fe23d4
054f3069c1e31acfa5008e93753cd7ce4ec5c96d
1707 F20101111_AABZEQ wyman_m_Page_051.txt
3f91a7e961eaa1cf3d84294582b1c64a
8b5ad293c45f7fc2381d16320c45dd74590dc0a2
108719 F20101111_AABYZK wyman_m_Page_041.jpg
609e96815d5f777c69a8bbeb3b431d50
774e5fbf24b5d03c2a926723927e4907647de4da
227756 F20101111_AABYYW UFE0022006_00001.xml FULL
994aba85053cdbe5778de32e2314381f
17249f98b70966407da33a3024c7852293bf98d5
112684 F20101111_AABXWI wyman_m_Page_040.jpg
98961674b19ca1b95043ebd3d6362d18
adff1c9102cb81adb9fff7ce5c57a642ee30cdc5
39249 F20101111_AABXVU wyman_m_Page_140.QC.jpg
81dfbc9b76f6a70739a33d4aa92f2333
104fe0b0b5af30a60eed7be6909f52fe469c6abd
4010 F20101111_AABYCD wyman_m_Page_080thm.jpg
0674ab1fe6047ada013ed2fb0ded072e
e7b0241fe719444f43649855a65eea836895d0a6
117685 F20101111_AABYBO wyman_m_Page_068.jp2
e6391485ee9b7f34853a75f99cb22715
0ed40a49e1b9a182d72bf7a4840da3ec9aba2634
1289 F20101111_AABZFG wyman_m_Page_127.txt
98d6b034248bc0ffd19cc402398d582a
37a319ba469854296af86b4aea66dec38008f031
2002 F20101111_AABZER wyman_m_Page_061.txt
8dde4122ce5ff48aacdc15d03b1a517d
39c7356c8369e12d37f0766590de2f47b06d7dac
109793 F20101111_AABYZL wyman_m_Page_043.jpg
252163fac18b51b32fa444af17076e17
f8ecd513a1e9afbc04a6b03dd6408831358fcd73
2669 F20101111_AABXWJ wyman_m_Page_135.txt
fc81a5046c98b6862d5a0e9b784e454b
e4a5d2093b8158953280e50288665a570b8b9ce8
1051962 F20101111_AABXVV wyman_m_Page_007.jp2
1bba3a0dbaf9ce4978833e9871423a8c
81a8808a6f722e392819c7abe369f69fd1fae8c0
5741 F20101111_AABYCE wyman_m_Page_046thm.jpg
53f7f5fa4d274b86653c5e7990ed55a8
7d024c596b47111aea4560a6d2f91e6f2f3dc7d7
37667 F20101111_AABYBP wyman_m_Page_077.QC.jpg
59dfbfc6c4e183412596e0e755d41383
acab9f2bdc71c691f134318e06125b3328eddbc3
2486 F20101111_AABZFH wyman_m_Page_129.txt
1545279d800d1d4287c0c12343963638
2c549fbeb9e9034a687ede9da0fce33df6d2d630
2169 F20101111_AABZES wyman_m_Page_062.txt
f1eeb5d23716882b6916cbc666603c36
7052f3c1cd0fd94737c523dbb6914b93efa67833
114085 F20101111_AABYZM wyman_m_Page_044.jpg
78b980d9337706f77a719986d265e4fd
6b6f6af694e2a29f7e2d0d746e0d59b85515e648
131207 F20101111_AABXWK wyman_m_Page_130.jpg
e5cbd949196e32242d642d456d852f6f
72253c08726b5e4967716fc95e5231f2b60773a0
8549 F20101111_AABXVW wyman_m_Page_057thm.jpg
ffbf680e6a8745d2add4bc318f103a0d
3d8105f99913127be511a92098290df23c4a0240
53892 F20101111_AABYCF wyman_m_Page_014.pro
21a86902e93d9f3f9efba32e2c37877e
efc5d5c59bf484a02107db6a068d26948518a8db
6862 F20101111_AABYBQ wyman_m_Page_089thm.jpg
09d7ed5691600f9b808e9c82a79b6698
fdf070dc45f3e23e05ca7af0b288afbcc04e092b
2543 F20101111_AABZFI wyman_m_Page_132.txt
53ec39a39b4584d20cbc0512f2c5abfc
576097b03b82b5b8455a4f6012759f3c2ab2e91c
1880 F20101111_AABZET wyman_m_Page_064.txt
4fbc1e603b873980f03a343d49619b56
128613d213934c92258f00396a3d62d9af5e5028
15881 F20101111_AABYZN wyman_m_Page_045.jpg
54a2fef4152a3d637950d6f87dcd89a3
4cd54ef3033b3947f884368b23a38b9d2bad2038
29355 F20101111_AABYYZ wyman_m_Page_001.jpg
85875bf9fc9ef801f12319ff32ba0eeb
dd8570f1e94fa2ad34d353c0ec1a41b188dd9182
57986 F20101111_AABXWL wyman_m_Page_070.pro
6caace1262f1cfa6e35f552fd2c52948
2159c0faa99b9e929d49f0bb2bdf63b14f522b65
67652 F20101111_AABXVX wyman_m_Page_011.jp2
952693724c1e777779c9965c4c355214
0c4f738eb25cdbb036a4a23baccc3d0f802c65dd
35832 F20101111_AABYCG wyman_m_Page_065.QC.jpg
2af82fc67c35f4fd435ecfd27c95f201
9b8f2699e2e7459fd24dd53ef2b875885548a0db
1931 F20101111_AABXXA wyman_m_Page_054.txt
c2c2af132372b01c400d74a6478c6cca
a2fff36185b5f03b56fb5782d00eb6c5b395ff9c
F20101111_AABYBR wyman_m_Page_055.tif
0cf4a56834cb77b42951279ecbf3af9a
30a287c745c589fb3a2b4b049ebdea2717175c84
2339 F20101111_AABZFJ wyman_m_Page_137.txt
014ffe35aa6e661cfbc14b4f9bddcd3c
80bcf9030d17d3bb3ed459ef5dd2faa8848bb88b
2261 F20101111_AABZEU wyman_m_Page_070.txt
420726f2394ba444016419924ff6d2a6
2cb7340dfb0a3d8659cccf9274a71d485339a648
42181 F20101111_AABYZO wyman_m_Page_047.jpg
1aec1989607a6b74d022538756aef8f7
6276b821649e764454534fd38fe94b10fc65e55a
109536 F20101111_AABXWM wyman_m_Page_076.jpg
c72b065d20826df99ab5203aa048fa76
487f05c524274592f7420c13d7fbd803e325bbfa
54463 F20101111_AABXVY wyman_m_Page_074.pro
8e9a28166e8d273f8769c48b1e59a1c5
90343da016f4bf9fdad619f67be783756f057f77
2044 F20101111_AABYCH wyman_m_Page_099.txt
9c7cd778b23791c89d5ca1f38204eb0b
e37a3863415833871df7a1a8fd42d427ab0d46cd
8523 F20101111_AABXXB wyman_m_Page_105thm.jpg
3fcf907b9e4ec8b5f783cca80ac49a69
e9a3cc5eebd5ca382875a5de09b9971064b05daf
115260 F20101111_AABYBS wyman_m_Page_078.jp2
4d4fc3c4c8af78943e5958afffaaf619
a4a16427199de1aa048470ec7c8cbdc7b9538256
F20101111_AABZFK wyman_m_Page_152.txt
71a7b5a5273c5e0260332b22666853b1
8583b7378ee8abfe2ee4883d306e7677eacbe535
2103 F20101111_AABZEV wyman_m_Page_071.txt
b48eb8de59eaac153376c7acd70ccd28
86f0a6209d04f8aa9765753d8cee6ba324736119
62596 F20101111_AABYZP wyman_m_Page_050.jpg
1d1095ba97c2ac10f49948a94bff9eca
1b45c1f93fa306d55394e1ed433a2a900f1db3f1
75985 F20101111_AABXWN wyman_m_Page_019.jpg
6809d05a5293548891fd5073daaaf354
dcf04cfb53e3ccfadd2f7014f1980f36bd043cd5
F20101111_AABXVZ wyman_m_Page_033.tif
ba5f02c79959f91cfa2e353551ca6c92
fd48eb2b81ea3143be4c0dd8c042da7c7792c268
33736 F20101111_AABYCI wyman_m_Page_004.QC.jpg
ebc55b9726e215350e0f571414fe740a
68f80d65bff7aeadac48ba70799bd990a10f05ee
103079 F20101111_AABXXC wyman_m_Page_036.jpg
6752bad0df852ccef3281ce0b9353f21
88ff36d1dd39e458a864a669dacb6a586d3678ff
1369 F20101111_AABYBT wyman_m_Page_094.txt
11cd811af3f796b0ec4b0274f9dc03c1
596266f75c89cda8d7a3e83d07dbdd79d8de3133
175974 F20101111_AABZFL UFE0022006_00001.mets
1e73d15ac39ae8643fc7eaf296cd7157
36ebbe3890b8df87a17984f825b8d1a954992cdf
2166 F20101111_AABZEW wyman_m_Page_072.txt
9affdf86b589394ace08e5e1a1f76350
285f10090d271cecbbb1e100be8d20e7b41d616e
109457 F20101111_AABYZQ wyman_m_Page_059.jpg
4ec9c3f21d1383349ab9ea0c1b5ba5aa
893b8352144a8b82a9d4e5582a945de03bd9eb05
35760 F20101111_AABXWO wyman_m_Page_121.pro
fed975d6e33552b34ff4ad9c3771e051
d8ca0acf582287a9957ced438e0e27eb75f85703
114515 F20101111_AABYCJ wyman_m_Page_109.jp2
b371151428cf728e9e5b2d8bc8c474e7
b1fdedd34f97e27c6dc50b7ad92514c91bc8abc0
8420 F20101111_AABXXD wyman_m_Page_043thm.jpg
df89b45cc93c433785f9e247778aad2c
8154a4711683ab303c5acca21f16223d73a10278
36620 F20101111_AABYBU wyman_m_Page_086.jpg
4fe37ae404ea5db673b0e0769d21eb12
e7f3a1f0503bb59bac259dd0434fcf5891ee988c
8584 F20101111_AABZGA wyman_m_Page_024thm.jpg
2d690e651c375f91bb4993e439f5eaed
4138b9cd09a35baf2838ca73c6dd0ec7181ca13d
734 F20101111_AABZFM wyman_m_Page_003thm.jpg
e43024073fb3623b261e3d854a758b2e
eab90db96739b6e11215f0d6dea2a21ee6d1ffd0
2132 F20101111_AABZEX wyman_m_Page_076.txt
bba32923e65e5610f1631cfa7ce860dd
346f0e9cad7e52884cced6ddb3e10850adf5af74
105859 F20101111_AABYZR wyman_m_Page_060.jpg
7d5d3cef8c62d493313c7df1347c465f
57ef1f5fa7bfd0f7781b8ea6e6c3967ade5ecc19
137946 F20101111_AABXWP wyman_m_Page_149.jp2
a1472fdf8ee22806bbff01b05b52932f
9d71e545b5d160c6d1582370fa40edab9ce9eae9
8760 F20101111_AABYCK wyman_m_Page_068thm.jpg
8f77ea454b8210da143986afd2acbba0
d86595d9c34a3fcf8ef637a89494890c62da4dd2
50207 F20101111_AABXXE wyman_m_Page_116.jpg
5ab0a2614df0cd20480be26359aee12e
fe992f0ece1cab71e01cbe726248bca6df575a16
17117 F20101111_AABYBV wyman_m_Page_045.jp2
c70c7c60d8f116f0c2af870f7c95c46b
30290a7f2fc3d81f49d762c804e73ecc3028a9ba
8096 F20101111_AABZGB wyman_m_Page_026thm.jpg
66235415df0900440a6771a46563283d
b9bf8649ed2f0517591c620877c1d8335b8d2ba9
8422 F20101111_AABZFN wyman_m_Page_004thm.jpg
f5578dbeb2c2bf01f169503271412a29
0f51333a76cb8ff4d77868b4cc2a309e501fb252
2154 F20101111_AABZEY wyman_m_Page_078.txt
8ac7ed13c29cf7498c18522ea4535650
a753efeb0960d8957e6eb0daf6314ecbca06d2db
112136 F20101111_AABYZS wyman_m_Page_062.jpg
b16c0c47c2cb73276cd7e1d8728e7a76
d522efd1d90026c74fed5d74ac5e9b12e64c5624
9664 F20101111_AABXWQ wyman_m_Page_086.pro
67b6d6f9e5822b4d84203c3e3d821882
ac99270af7ee3403389de24ae5db18ccb36a4735
55757 F20101111_AABYCL wyman_m_Page_112.pro
2d74635020154d58c8efda57fc3d86db
befb87578638810439b4d753f90adbfb455d6abe
37135 F20101111_AABYBW wyman_m_Page_020.QC.jpg
aa3051765716e1e7a70044858c3852db
c607a86dbfd45c3db3bd2b9c7f16c994bb587e35
8862 F20101111_AABZGC wyman_m_Page_029thm.jpg
3abdd3797cceb2c8c220be9791ac8f7c
fc1ff25bb57eede164961dadcb0264371767bd05
3675 F20101111_AABZFO wyman_m_Page_005thm.jpg
984b05b672338cef00f4ae4db3eaecdf
c5ab248325b16e7880390037731541339473eb31
1160 F20101111_AABZEZ wyman_m_Page_085.txt
995c91bee06c37582043b74cbf4a5b43
4dbc09eecbd93c6602189f1ec0ba729daf198817
104013 F20101111_AABYZT wyman_m_Page_069.jpg
fb82203e087aa4082170d13a9ea7ee0d
26eed526db0f1d76f89b7742097f9c94f3603477
119989 F20101111_AABXWR wyman_m_Page_006.jpg
0f9fb533c116e6be898bcd1b882550a9
6d6c0bd3c7a87138db8d631217fe37bf10edf87f
460 F20101111_AABYDA wyman_m_Page_086.txt
907455f56a8ca6fb01448101e13fd4c3
0dd747cb7c4178e7946196d797f79c748d9a0fa8
59769 F20101111_AABYCM wyman_m_Page_128.pro
ee4f15dfe3cd498172dfcc77897254c9
013a6f3e7e7c9612654d247a7f576d2dfa488603
112456 F20101111_AABXXF wyman_m_Page_056.jpg
bbf73fc2417837efe71b09a012009391
77c3327df8e817e4f017310ef93c3ee923398ec3
2227 F20101111_AABYBX wyman_m_Page_096.txt
139311e6a67fdef4c5981ae19ed083c8
42951fb1fd4f7b687bfd633357e1f69e30a43521
35595 F20101111_AABZGD wyman_m_Page_030.QC.jpg
4877084c81ee40d849e7a51074bc8c9a
0df78a159415e3bff5c4b8cc060e0bf186721e0d
26001 F20101111_AABZFP wyman_m_Page_006.QC.jpg
291eb280c0a9ff826416fb26db19dedb
7943777783c951105f3b318a32f12293681842e7
22217 F20101111_AABYZU wyman_m_Page_087.jpg
b8f91b581ef3636d38603f51e83d632c
e79bbcbe502cadb8a530715f264c0d4657cb72d7
F20101111_AABXWS wyman_m_Page_077.tif
978f208bc86c874330f82c53a22db29f
d4c1352ddf13bec828ba285539a523e8f6030c89
9275 F20101111_AABYDB wyman_m_Page_144thm.jpg
2760d6d2f1d1b4c0daff56cb6e46abc8
433e85ea86613029ea5acf3be4466bf3fba86c91
115682 F20101111_AABYCN wyman_m_Page_025.jp2
e198d2ebbed89aa828aeca706ab7d157
608f287fb03c1c53178dda41daa30da2dcf28eaf
114624 F20101111_AABXXG wyman_m_Page_099.jp2
9657d5ad792c00cd96062cabef713d43
290f6c4a59b4ac3ecd3f66e7d2edb6478c92753d
37246 F20101111_AABYBY wyman_m_Page_063.QC.jpg
f0ba67740e2fe0979824409ab4b83d9b
d5c32d76ae0d4fa06c523ecd5a976def4157626e
8627 F20101111_AABZGE wyman_m_Page_030thm.jpg
aa95c9e67318c5de5bd80f6a33eeff0b
570724e7aa757579ff642ce96f265db147323705
29469 F20101111_AABZFQ wyman_m_Page_007.QC.jpg
97de9a1cfecfc7f68443889b59907073
f68dccfbd5fdf2865a0f1589b33a7d31918c17ba
56786 F20101111_AABYZV wyman_m_Page_089.jpg
d9d1680b130a2ff2f4d31da164ba5105
e7e9f6bf9ac5dd5f5fc6699effea3356df3f5cc3
127209 F20101111_AABXWT wyman_m_Page_146.jpg
0b414a2899f8afbaaaf44ea9a8f8e90a
4141f83f400c1b0c4e56643e9ba017e81721d31e
F20101111_AABYDC wyman_m_Page_037.tif
fb71879fc4d92f98dd2768ce479c8e9d
f25e2d9aeb224d73fd4a5bf4dfc60556782501cf
8967 F20101111_AABYCO wyman_m_Page_100thm.jpg
7bf421560aed36c6744e5449dbbbcf0e
9add1e42e2ae237159c5b23b2271a6ac7bc63f17
2048 F20101111_AABXXH wyman_m_Page_057.txt
3067cdcbc919b97566a99caa0816d1aa
3b9ef5df4a7bbf918b7f783cb0b364a8eca853d8
8762 F20101111_AABYBZ wyman_m_Page_033thm.jpg
cf3aa6feb3a034feaed49d3e1c31404d
66e6e3897d2ee30f9ab8b516cb022592cbf7b8e5
36695 F20101111_AABZGF wyman_m_Page_031.QC.jpg
e96aa5604fb7499d80d04df367cdf70f
06480cb1cc9ffa93dedcd9b7298f3eb0fc12fef1
60217 F20101111_AABYZW wyman_m_Page_090.jpg
24766af7edda40f6869735cbd99739a0
fce69ca33bef31af3ac638adee6cb958241882c5
69513 F20101111_AABXWU wyman_m_Page_150.pro
64a97bd190c81e9a30a37d13113b0fe2
ed1a16a455f33dbf8f8737b7f658c90686b67c98
108625 F20101111_AABYDD wyman_m_Page_126.jp2
f7d78a747b2dd7f5c7d270bdb8409f6f
efb1d51f3664ac031908a27c363a4e0daacd380e
23692 F20101111_AABXXI wyman_m_Page_116.pro
0b691f70a6d2749650ab38e601dffa86
37f9a8dbc226571906339a112100745727e40277
8707 F20101111_AABZGG wyman_m_Page_032thm.jpg
b72c7c9e3c6f8780230f998d22e14d13
8914a7563215b4782ba5306a8b585c9e4d9beb4b
34749 F20101111_AABZFR wyman_m_Page_008.QC.jpg
c4cab0d9e38b9db8fcf928803b3daee6
d7a9810e3bc2fafc4e1944c84871a5b5611ed2e7
101721 F20101111_AABYZX wyman_m_Page_091.jpg
ab7e2aa6c3755fe243b8f3512937511e
579fd144318177b7bb0797bff0f49e46854bd079
110460 F20101111_AABXWV wyman_m_Page_067.jpg
ad1e1d711161de91c0de763075308c37
1c7e0c5736a44d87e210b4d94d7e357db5cb9e08
10324 F20101111_AABYDE wyman_m_Page_119.pro
bfa5d19cccc7ace251a8155b66eff850
591a96ed0cc4ea0ebbd3779ba7ea4456d81b18e6
107823 F20101111_AABYCP wyman_m_Page_027.jpg
70374570f4190ef85cc10bca83d51339
79396f4a8192b3ac2a076f74d469330e4df55702
F20101111_AABXXJ wyman_m_Page_144.tif
81ff931816aa624eeef4ad44acc285ba
082ce19f595e1c7537dc8c0841325341928c8d5b
34605 F20101111_AABZGH wyman_m_Page_033.QC.jpg
bd1c4b9c2e117ce9898697c9516216bb
989b50607fbbc2034180c89186a60257bf700c07
8182 F20101111_AABZFS wyman_m_Page_008thm.jpg
f96418707e5ff6c7d86674390742a9e6
e7c69b4b99047b272013e33785851d2169b4fe17
56483 F20101111_AABYZY wyman_m_Page_092.jpg
7bc5e375067f1c816630e9e97534767a
1d32b462568b659a98f0016c2ead03e6aa2ad3c8
17441 F20101111_AABXWW wyman_m_Page_051.QC.jpg
dd63a05d0ab36915c9167710d9a47f29
9dfdd793e955747b7b70f1924c38f533f7d38728
8544 F20101111_AABYDF wyman_m_Page_073thm.jpg
7b8f73efe5391f1632cb0e66bb669c0d
2c17578b5cbdc7eb50d4646d476722c83d8ad4b0
38877 F20101111_AABYCQ wyman_m_Page_131.QC.jpg
2e8e7b28af578933b8254229a07183a1
dda2e0cbe01f6157553c24ec8183cf956530be16
20858 F20101111_AABXXK wyman_m_Page_095.pro
00bf58a9704b8ddd480a3403231433c6
fd8d302bcb4bcd5fba3fe52f544c8bc7ca61a2d6
33208 F20101111_AABZGI wyman_m_Page_034.QC.jpg
f094535e51a0e2f746abc344162d8710
a4daba1dc28fc9570d079055f0d347a204d604a1
32067 F20101111_AABZFT wyman_m_Page_009.QC.jpg
50ce17bb053fe18c363643d5d242ff2d
3422a11aeccef70b049f7f71bef56a7ae5df1c5d
64713 F20101111_AABYZZ wyman_m_Page_093.jpg
4b188dc06f03ef72cff3109cbab0f60e
64c664f2933263f3fffd6835598fddf7fc37d1a7
36982 F20101111_AABXWX wyman_m_Page_044.QC.jpg
2f990d84808dae42d1fd6cd92f79a3dd
16b72cd7ebea9da6a20b09616998bf10ad2c41a0
12624 F20101111_AABYDG wyman_m_Page_080.QC.jpg
8811a50c4280fa353f4c02b442506c96
7077a129484fdd1627a2cee21d5fc5ce7dfa90a8
138857 F20101111_AABXYA wyman_m_Page_139.jp2
013ca8081aef3ef684ea1a4a7b80ecc7
b9bed89416b8771c4212af28e9c7c738f3d0a482
40364 F20101111_AABYCR wyman_m_Page_117.jpg
2eb6d46655faa06598104a2696c7e33b
7e8c31b4b576a1263edc20be9dc2ba75a328ff3a
120243 F20101111_AABXXL wyman_m_Page_038.jp2
7d1b35cb5e4a5aca71c09c0267686f86
5d91b4f782db87c4c9b912ee9cb7f9270e73e925
8923 F20101111_AABZGJ wyman_m_Page_035thm.jpg
006d647557a352e21e65d4441c19765b
f4a19d583efb2e80e4ddb586ba165df5ef3a4130
8375 F20101111_AABZFU wyman_m_Page_012thm.jpg
ba153ae76e247076b21b14f72d15d3ef
f170136c1a19f7cfb3ce473f3b06fa2de2fadd0b
132413 F20101111_AABXWY wyman_m_Page_133.jpg
5e9f22bf7075c3d32bca1bc046bf85e4
f1c2ebeca7581f65eff8c3387d6bfaf7012593f4
99526 F20101111_AABYDH wyman_m_Page_126.jpg
6f2514e29fb499297b3e8545c8ea05b9
8505a8a8f54b021782eb5dca44133b7ef161cf6c
F20101111_AABXYB wyman_m_Page_004.tif
9804a89638d55023ef5af3c55b174cc0
ebf73a826e9150ab6b207f7864312068d9efa609
11056 F20101111_AABYCS wyman_m_Page_089.pro
1673ebdd8b0544d715cd5d875ece2c35
490d7c9355285e2f9fcdb3692047644f98c1fe37
8237 F20101111_AABXXM wyman_m_Page_103thm.jpg
feace1e4086694dad6d2e6c4391da17f
b013205e838aedc2651296b99cf0c1d8f954731c
8796 F20101111_AABZGK wyman_m_Page_038thm.jpg
48e8b2fd82ab274eae3133afd823bff6
16d2786dcda0721d33f3e2b38c257e48c08eb3d5
8459 F20101111_AABZFV wyman_m_Page_015thm.jpg
467487bd7a1fdeefae5524cece07396d
e82fc4e3eeb8ba8c20b8dd3869d09d5f6aca9e4a
F20101111_AABXWZ wyman_m_Page_072.tif
e72921f6909f11990b171ce02ef697b9
fc42c68a965438c60d7e49e195e4c67e6c3be035
115297 F20101111_AABYDI wyman_m_Page_027.jp2
488d57fffe6b611912e7f91564d28aa7
513066be6061f22b9185eae714b1904aaaaf4d95
7456 F20101111_AABXYC wyman_m_Page_064thm.jpg
e6a694369669f8692d7fc14379221fa7
ded2e3cd37a887934c2037ce921c638aed063fff
36965 F20101111_AABYCT wyman_m_Page_112.QC.jpg
260de58ecf53e05ab9d7edaf41ec8c93
c0245617fec1fb524feb778cd4e2b062432787d8
9394 F20101111_AABXXN wyman_m_Page_147thm.jpg
2709f2a7ca5da5d329931de133f0800f
292e58ac5e301c50bb53a52fef6b72b85f583be7
8991 F20101111_AABZGL wyman_m_Page_040thm.jpg
f2c9575f98e5687f384be963f0ca0368
3b48d07c08b7f19680537cddb5a3d9d22a18bcea
8737 F20101111_AABZFW wyman_m_Page_017thm.jpg
2221986da1372a5c13e8f87e578bffed
6e4f40a704fe8fbaf2dc9d9b75c99c93ba5851b1
2220 F20101111_AABYDJ wyman_m_Page_056.txt
7d0dbfb578348262d17ee3918080f055
22e5e3d3292a1f1e59f780c714350145c72c56b9
939 F20101111_AABXYD wyman_m_Page_116.txt
0d53abe289d5548c748ec85a2ca6109b
546ddcd3c38242eff83f488a7ae5c6833fb46334
37223 F20101111_AABYCU wyman_m_Page_134.QC.jpg
bcb236f5489256f4ed459b56ceb64c65
ca2379bff7fb4e09f6ef42460d5069093106dc1b
51958 F20101111_AABXXO wyman_m_Page_012.pro
8a33f2d71e5cd5f49372b5ff7c330866
6e7afe980b9c3ee62282f1e3419b241b4a116fee
11063 F20101111_AABZHA wyman_m_Page_079.QC.jpg
f6207dbc08d9f1d6f7de07059e745293
cac900804c58490a19f40d2f2eafa445a3dcc701
35914 F20101111_AABZGM wyman_m_Page_043.QC.jpg
87ce68be4cdc636324958e13873a9d9b
7fe53fd55528ccce5cf259de3761ecd0079eb224
34840 F20101111_AABZFX wyman_m_Page_018.QC.jpg
8d5c70cc3dbde5fe3ca51e43964acee0
7b07cc90f542c17c9fffb33e1d49ef75eac90989
36220 F20101111_AABYDK wyman_m_Page_023.QC.jpg
635f2e2882e3ce53ef47834a0a551a70
605fc41f2e735bdc2d63c2909aa7d71ca53a69ec
34376 F20101111_AABXYE wyman_m_Page_057.QC.jpg
e588f3f7108fdfcd2424396890c68b74
3eec9b5850fdaf9bbd4cadaa2a6c544afa618645
2156 F20101111_AABYCV wyman_m_Page_110.txt
e86e53039737d8af04c1a239a8eade28
a755e026523432125c476d50308dadd78cb84017
108395 F20101111_AABXXP wyman_m_Page_104.jpg
0e26ddc9f827695d0476ac2571aa3775
f182caba773ab45002c6c1ae7158dad2f4752428
18740 F20101111_AABZHB wyman_m_Page_084.QC.jpg
a317b404b35d628c5fd5476001d42fbb
d87351d932e90d3878021d81fb506c1929ac5f52
18011 F20101111_AABZGN wyman_m_Page_046.QC.jpg
1dcaa8832ab115d595810981ea61068a
74d037e11036e4a79eca565c4ca548507a4c16e0
35912 F20101111_AABZFY wyman_m_Page_021.QC.jpg
f19658fa17f247a785fe2291df6ba9ff
55d468191e5bed496f99b0d66dc8f1548d32babd
108630 F20101111_AABYDL wyman_m_Page_030.jpg
d875136b1afa86569b39f4e64e183045
f895f12d4450c9a257323aa179fe7e913b71a907
773 F20101111_AABXYF wyman_m_Page_005.txt
a9814ccab47c543c83b7d1cc14e6b4a3
05e0126f4df6165630757b3829d962890d519b17
F20101111_AABYCW wyman_m_Page_088.tif
e916204431ec33bd608aabde31bc0f28
e26bc13e0a8aeee8bc7496fb1cb28cf968b8f3e0
57260 F20101111_AABXXQ wyman_m_Page_137.pro
faad3b65126e16def2061e89a01263c3
c70f6643398ca68ce3c8272c4d55845076abe401
11477 F20101111_AABZHC wyman_m_Page_086.QC.jpg
c918acbc9b5701e36625f44c5266a0b6
82d5ac6ec955a6955bf1f90d95e2ee5493384f82
6323 F20101111_AABZGO wyman_m_Page_050thm.jpg
b3736f1c6b237cb61657034e49a3aca6
8a1481e7db88a492268424ed5ed72e009006abdc
8839 F20101111_AABZFZ wyman_m_Page_021thm.jpg
443de5ea3f65548d4d30305f0e0dd020
664bde6edddec56d612e43cf31d085a8a9d4314e
66385 F20101111_AABYDM wyman_m_Page_008.pro
b358fc007e38d145162bd0ed30d5c957
c1be49bace7efb104b3144afc5478045dde7021b
8295 F20101111_AABYCX wyman_m_Page_058thm.jpg
3a6d5d71acf7076b78cabc9bb8a8863f
300d822cf3b6e77bbd83c6f8abd89bcde96e5968
9868 F20101111_AABXXR wyman_m_Page_131thm.jpg
27027722777f0891c9555518269ab22e
7c41255f0ed1b0af6bdc28f938f342896132d294
119677 F20101111_AABYEA wyman_m_Page_107.jp2
a1700b35eab4f7329017821edcf3c9f4
2cd850cff9ef78fc2f684c7f823b744e00785711
3701 F20101111_AABZHD wyman_m_Page_086thm.jpg
a6ac330fb9d2f369ca813abb9bca7265
38a47c9b1378317ff7dcd60c9ef86a2084890b6a
8811 F20101111_AABZGP wyman_m_Page_061thm.jpg
7731f669e4ba9f46437ca6c25dd8d6ce
729c5b963ebb51f7ed9584dc4f911bef8cd0b72b
108038 F20101111_AABYDN wyman_m_Page_097.jpg
8f72d4f9c48ae70dd111f236e1e6eab6
ea37f9e9ebc546249cab794bd7440188841d7320
38975 F20101111_AABXYG wyman_m_Page_142.QC.jpg
56903866a5caeabfba96437e44bae580
6fd4b47a89c1df684291f6cc38d5f9857b333bfe
825 F20101111_AABYCY wyman_m_Page_084.txt
f84fffd803e76c492257343ec2d65045
b1a59bedb130b0c2a7eb6020d4cf756cdda43bec
52791 F20101111_AABXXS wyman_m_Page_125.pro
460da07df5aaf421151dde24b6b40411
4579c445af23587dab5f6b57c78407120fcf7782
102601 F20101111_AABYEB wyman_m_Page_004.jpg
813a2e4107ac8def9703cadc36aeec6e
8a3290ab6aa47603c590023ab54b2407e42246ed
2243 F20101111_AABZHE wyman_m_Page_087thm.jpg
4797a537f939898f8f4350340f6cd603
44b145f1f7f51e1cfc09347fea1db4b2ee677796
36307 F20101111_AABZGQ wyman_m_Page_062.QC.jpg
51bbe6b5ec050bd0d9d716e3c2b63251
1650caf249388dbdeae21b994b7e37a54269c05a
4984 F20101111_AABYDO wyman_m_Page_092thm.jpg
9b562ede4f2d7921e34d5a22afe7b31a
842e1c88815d84a88e62116579649ba7bac7590c
48752 F20101111_AABXYH wyman_m_Page_083.jpg
a1ced616227679ff0a59ad9ab26d64ca
bd6d75566e6c45862485a781aa8ed4d2b8991047
558082 F20101111_AABYCZ wyman_m_Page_083.jp2
61de07aae6417554f7be50d42737be98
3931d70f0cb6c58ae8b1a3d72574eac9cb69b9f1
72923 F20101111_AABXXT wyman_m_Page_145.pro
29c3964407b1a3d449916157df2311df
bdca7b58b5b54c12a768cba1ade3667c6ee33fa3
F20101111_AABYEC wyman_m_Page_129thm.jpg
fb28635a8bd2738fb84321122294ecd4
945d1c2d646fc975b1326a174b3f970a78955c56
6871 F20101111_AABZHF wyman_m_Page_088thm.jpg
49c4d18fc0dd3a27d6c4307f65cd5acc
1e8bd29a3d08d23a36026e4734de593afcd9da25
30676 F20101111_AABZGR wyman_m_Page_064.QC.jpg
3cc99bc54a71a0d38e48febe04b4393c
e024c086406a2065f23c8f56e75e751a43d54654
117145 F20101111_AABYDP wyman_m_Page_098.jpg
f836804790a6d2aaca6536d3ad5d38c9
113d279fb770dd1f6d76808e11b0653886c68799
53639 F20101111_AABXYI wyman_m_Page_078.pro
f7ba1f37e507e608f0568088e129196a
d0730e17f4068fbf09124064f6f69ceaa8bd66c2
2726 F20101111_AABXXU wyman_m_Page_131.txt
87c730bac6c6a547b8c4df179a32c11a
2110baffe0c7e07e6d19b49e2fa0a757c82895e0
23372 F20101111_AABYED wyman_m_Page_049.QC.jpg
01675dcb67c2f54b72c097c4c4791b5a
e3703706735f8aef8e9b2a2b7dc9a231ec91ed15
20542 F20101111_AABZHG wyman_m_Page_089.QC.jpg
082b6fa7c88395db5bbae48b042ec9ad
7dc5bcf74eb0f65ee7c0e9d4eb29251a707bfa0a
33915 F20101111_AABXYJ wyman_m_Page_022.QC.jpg
823d4244d008e9f7575d278b7f1b2804
73d2af386b48712e6ff80b1f727b7c568dc09e08
F20101111_AABXXV wyman_m_Page_086.tif
2c5f7fac692ad9ec90cef324eced858d
377afd4aeb0cc8d3e56280ab17056c17019f4515
14771 F20101111_AABYEE wyman_m_Page_117.QC.jpg
f5212f3a14c06fdb8b984f2b9ad7f89f
b06d93811440590f9a0edee91bb35144cb9eb937
20489 F20101111_AABZHH wyman_m_Page_090.QC.jpg
d8b1357919cb66f4e70b348cda1f16d0
ae7cd5911f4c88d536a3b27629cc3f0dbdbdcc74
8351 F20101111_AABZGS wyman_m_Page_066thm.jpg
40512114b7797f248f36530385efba16
7ed86c1a2bbb72d4dbb3aa99835807695b20193e
116344 F20101111_AABYDQ wyman_m_Page_018.jp2
6c0d7386fa6e4f2f2089e7f9ae4b53f9
f3bcbd7300c2fea88ab7391f00d654f6c4ea4e14
36077 F20101111_AABXYK wyman_m_Page_042.QC.jpg
19a31a9b4ef99f045cee80e8dbc5a056
03b2b0998e19fa596ce3065dfe0648695aa093f9
37559 F20101111_AABXXW wyman_m_Page_013.QC.jpg
f7c74801b120c9840860fdd36ce2a503
9742a1f74fdf12f7abb38c10ad34894c100cacc1
107068 F20101111_AABYEF wyman_m_Page_111.jp2
c78846b26bdd2209420509019dbf679f
3e928546802d8178be41e811a6745ee9eb7c7039
17994 F20101111_AABZHI wyman_m_Page_092.QC.jpg
69b3b0b19c4658a3d27cad387457f0e9
b7942a1bccce2b0bdabb7645f35151e0385df001
37728 F20101111_AABZGT wyman_m_Page_070.QC.jpg
dee53fe85ed4826cbc5f3ca3c1845e7d
80cbf60216bb5512314108e3fa3049e88a5c87a6
F20101111_AABXZA wyman_m_Page_048.tif
e98f1baae9b1ac09fbaa56c7bafe4eac
b0d503a8990ae5331cf8b157abc8c1f84bfb80d7
8290 F20101111_AABYDR wyman_m_Page_034thm.jpg
2d5feb6e15ca96281c664cf567e56ae2
811cca3521c3b83090eb942c0881d013cc759153
13407 F20101111_AABXYL wyman_m_Page_005.QC.jpg
9999b7c5d0af1457a559144218d42654
42649412afade60fe534b7322dd8981c39718070
F20101111_AABXXX wyman_m_Page_080.tif
8aaec8c0bc6051f6395c8ec6d5fcf876
459b04b4cefb63036d4268f8f765a930c7424e12
54127 F20101111_AABYEG wyman_m_Page_085.jpg
dc161d004b14da1a5f2ee7b8dd27786a
6aeb9cb634cf154ae2f6aec3342af53b9a60b107
4708 F20101111_AABZHJ wyman_m_Page_094thm.jpg
a80902e6413611bb7d31926d2bd800d0
2033f39da24e828b5d7a452d099e894719add474
8821 F20101111_AABZGU wyman_m_Page_071thm.jpg
43e82355771a711fc98b81f1975e27b3
be3688323d15d277ce25c76318bade7afba21355
109717 F20101111_AABXZB wyman_m_Page_023.jpg
090c51e83c8a3d2afa8c3a191fd1692d
fc7d00f26ba2082849cb21c5fc5a2ee4832273c2
11239 F20101111_AABYDS wyman_m_Page_088.pro
36ed139ffe7efabc6bb83fb8c3619544
3e51da9d0ac8c1324f2dc9418c3cd003890d7fbd
8435 F20101111_AABXYM wyman_m_Page_042thm.jpg
05853f2938dd898dde254fc042d4b159
afa2f28bdd14975f99ad8bd9390e06dfc4091abe
F20101111_AABXXY wyman_m_Page_061.tif
d8bb36b9a5425d296208b331f1293c95
83cb388ec631915df77a0b0edcab53ff52f186b8
1472 F20101111_AABYEH wyman_m_Page_019.txt
8f317720ec395afc23250600b825fbf0
5e8db6f2e8458dbb44c2d805d62b331e51e4c846
9025 F20101111_AABZHK wyman_m_Page_096thm.jpg
2d1b61c3c283c7e73ac14d3c775eb371
2ffaacea2654fe331681fcd86b74b151bacd2965
35461 F20101111_AABZGV wyman_m_Page_072.QC.jpg
018b63a04590a6297ae31d8414a6e0a1
cb9b5aabd31fe2be67a942cb113addce000f9bdf
2653 F20101111_AABXZC wyman_m_Page_139.txt
4ae8b56d24ea0b75808987da6fcc15a7
888ee15ed1764912afba48c0e10dd37577d7abab
F20101111_AABYDT wyman_m_Page_007.tif
c515743f783157d7b01ae4a461774796
e067a1d83780863826a4f54f9be58cd82380ade9
84755 F20101111_AABXYN wyman_m_Page_049.jp2
7764484395af54ea7834b1c13f29abcd
968920f97d70bf00ba6a0000bba51869ed3a433d
2910 F20101111_AABXXZ wyman_m_Page_141.txt
614220c85aefcda709a7b71248c6978e
100fe50f34cf288074f6b8c360cabaff348a6896
104242 F20101111_AABYEI wyman_m_Page_061.jpg
8de23db1f6bd6f0ba6d3e2a1fe41b309
c1d9fa2b5ae8608fb9bcbf27fbb2c69a8d1f0348
34428 F20101111_AABZHL wyman_m_Page_097.QC.jpg
bea104ea146fd855e8d8fe388b53e595
62645072aa07ccb0daec3b5ca1172f48f79aa8df
8709 F20101111_AABZGW wyman_m_Page_074thm.jpg
83896f9c97adf7674dd8678eaf490e41
df793c3f526ed35bab30345f39f4c80e02e2efb3
F20101111_AABXZD wyman_m_Page_093.tif
b5409deb0f12eff8f62d8557491b3bb5
2e3d8eb8976a45f1a4022e3af423236950746be7
1051960 F20101111_AABYDU wyman_m_Page_134.jp2
17e407951e119b2028bcb4d024acc59a
3157755364bcd04abba8576738752027181917ef
109988 F20101111_AABXYO wyman_m_Page_110.jpg
7e250a07884a5ee87b19cc39daa35e66
c9a0c65cabbd109f3f58b557feb046341e5b1a16
35811 F20101111_AABYEJ wyman_m_Page_114.QC.jpg
3cf16c8ff949bfa092569a5d2fe53fd2
823b8a0c617752ca11f2d16318f836c1ac23d997
21725 F20101111_AABZIA wyman_m_Page_127.QC.jpg
160fb32f51ec60972acff342d490e0b4
1569b0926b43b93f99b5de94088220df8729f472
9201 F20101111_AABZHM wyman_m_Page_098thm.jpg
0fdd50bb7510f0b34e889239b1b28175
be993bf5c18ded0fd6f18bbe319fbd98af59bb06
35657 F20101111_AABZGX wyman_m_Page_075.QC.jpg
7784536cd5ea33a8de97ccfd17c4b015
294a578d9cf184a7db9bd901179bd367d8735731
F20101111_AABXZE wyman_m_Page_109.tif
decd925505ae48ab732266471f70fb6b
098f70c4ea08e4e8ddb757bae9d34d453b6eb2a2
108963 F20101111_AABYDV wyman_m_Page_039.jp2
b86b8c9c950446cf104d7702981c4e40
0820a6858e6584e99b02599f129c0cf8c89396d3
F20101111_AABXYP wyman_m_Page_138.jp2
3af1d401fb64b64fecfe7db425025183
940cb948fdfa8b26394f43c6da1f5c59bb9fc88a
119586 F20101111_AABYEK wyman_m_Page_021.jp2
2cdb3be958b13673f217de273d0e3828
fe0c10d8783313186dcc3cf7163a1e385e2c4759
5308 F20101111_AABZIB wyman_m_Page_127thm.jpg
4b4eaca8367c158615e758485fafd3d8
66fdc8bfabb13bbd5533b14c33053d6b6a1e0f8c
8745 F20101111_AABZHN wyman_m_Page_099thm.jpg
df30fa924495ccbde93997c9f1b5461b
366bb447812a46a6a36a98fd44e1d4b57944e304
8992 F20101111_AABZGY wyman_m_Page_075thm.jpg
eea8e323a05119cb973562960f0f2abb
659bea873a69aa475d388bf1066456d3ca4f52a1
F20101111_AABXZF wyman_m_Page_146.tif
930574ec2a203737c5b303b7735b890d
65603f2fabca0574b1c2eb636cf1ba8749202931
6582 F20101111_AABYDW wyman_m_Page_052thm.jpg
918d614e88961f6a96e0deeb43a13553
4d6b1bdc478f35c8ee8f35da4da4bee484e9652e
F20101111_AABXYQ wyman_m_Page_067.tif
f9744c0a0f51052a23d185bdc066aaf5
508765a270f71845066f5357196dfe2d42a21e9e
66058 F20101111_AABYEL wyman_m_Page_133.pro
c444c51ac98a0b917b1d95a071ed0894
8dfcea0197d2aa9e14d994f4ff117413be01c8c2
35624 F20101111_AABZIC wyman_m_Page_132.QC.jpg
30aec6516fe67f85c7a7e964c0f29f7e
a6fbe4cadcf7462858a137cbf6d0f0a13cebf083
33667 F20101111_AABZHO wyman_m_Page_105.QC.jpg
fbcf85b61c0956170833958a37702304
b081295e4108bdd75fff63a51a201b1969b5b17d
36346 F20101111_AABZGZ wyman_m_Page_078.QC.jpg
99d843ac7f96fee6c6b011d1783b6051
e36c7cee4ccf7fcd06de47628687034c9b73dcfa
2224 F20101111_AABXZG wyman_m_Page_020.txt
53639af3455ea8dfc05c32d2c242861b
6db41b52b874315dd5a3085d78f14f6fde55c0cb
104276 F20101111_AABYDX wyman_m_Page_151.jpg
af1ce1e34dc46acacd34cfc640f212c2
03f3c81cf2f24d31bf419c775735a8bdca987377
38563 F20101111_AABXYR wyman_m_Page_098.QC.jpg
767fc5d1dbbfad9a153a2cf5a11eea5c
18d59761445a24902b444c3e77e16660f309b4ec
F20101111_AABYFA wyman_m_Page_134.tif
caa8dec2ffab92ba6f7b17b566897d8d
1a4f4126b085f0fc17c2d121ebf343ac1de3861a
52537 F20101111_AABYEM wyman_m_Page_033.pro
ca67248b3d75ea241e6768585c07d8a1
52034fad444b749428dcb97bac80e0c1610d9409
8922 F20101111_AABZID wyman_m_Page_132thm.jpg
821c90aede6aadee843a6fa4c2cda952
de81a3c26d246ec07125f322c7ef8c654da0be17
35067 F20101111_AABZHP wyman_m_Page_106.QC.jpg
584f5b768ce38276dc567481b850c4c3
08eb4c50f33380bd8c25fc7b9d67537b56f50fd8
51420 F20101111_AABYDY wyman_m_Page_051.jpg
61b5b69949663db324355c50729106ca
e3a209cb8a5e7b396d197b480e3b871ddc943b09
103119 F20101111_AABXYS wyman_m_Page_034.jpg
ba71b817b6bfa3112e789c593b12a01f
d8cb3d99cc4d34877b68bb3a5a89a5d40f32135b
115561 F20101111_AABYFB wyman_m_Page_030.jp2
5f360e703d98aee3d574e7e2add2e2a3
193682f88b7a84602c46f6531521fd4ce21fc4dc
8749 F20101111_AABYEN wyman_m_Page_107thm.jpg
27be68270b6ebbd43147703aedb4cdc7
759e5b45c804f93ee1f35a2d4f39a8d7fc73aa06
9097 F20101111_AABZIE wyman_m_Page_133thm.jpg
3748936f42a96828dfab906bfcf4b550
f32fcbb56f86b842e76f9d4e47471291c0a6bddd
35579 F20101111_AABZHQ wyman_m_Page_107.QC.jpg
338802a5ca005904472977831196bef5
c0ac29da525c4c4e9b44d54611b1e892253c2605
8578 F20101111_AABXZH wyman_m_Page_097thm.jpg
a0d585fa28b5e4f85368779092f608f8
249f95d52dcbf5e9173a56e2c9ba5c4ebd0390ec
7806 F20101111_AABYDZ wyman_m_Page_117.pro
63e9111ba5bdd9badb7a53032e7d7960
00b84c7fb60629678ea8d7e4cd83633383d0bda0
10216 F20101111_AABXYT wyman_m_Page_095.QC.jpg
3cdcbc7e55331fd73cf60c1d7a8abcc1
bb0f12a75e95afafbd4ba188995ae538ff63758b
7805 F20101111_AABYFC wyman_m_Page_123thm.jpg
ad10946f923fa084c369b70f1835538e
ccfa8431914021fd8c435e5f5110b393799b5dfc
1705 F20101111_AABYEO wyman_m_Page_003.QC.jpg
af425b67d1b8a2d9b03d763010c69099
c9e13ced938ade6377890a81d3e0b429b6d8912a
9332 F20101111_AABZIF wyman_m_Page_134thm.jpg
13c3b697cf85713cf53f6943a1dbdd6d
46b5c1de2f1d3bb23c1518af6519f62990de7a61
33960 F20101111_AABZHR wyman_m_Page_108.QC.jpg
de2fc851e68213b057a14502bd5f5491
61a56e1bf75c1746319682503200a60210c0ba6a
2099 F20101111_AABXZI wyman_m_Page_114.txt
e5231c60b21a4976a59930294c94bfff
07ffea681d50c49380cca3b67576021e2083e152
8914 F20101111_AABXYU wyman_m_Page_067thm.jpg
3ce2d09cb4c077f4937b53ac6bc1a869
91ccc13087325f90489e058800c92d436afdbeb1
1051984 F20101111_AABYFD wyman_m_Page_129.jp2
5980d87d7cd227d739b3c7ba97b29c84
59158dba2d0bae2722fb2ee5f5618218ec5af6b8
F20101111_AABYEP wyman_m_Page_133.tif
3c5723a9b99fe969c864958a0b0b71e6
da0c9e11435b42f3f07071f543731535af897e9c
35994 F20101111_AABZIG wyman_m_Page_135.QC.jpg
1266b93e8e26a7e76a50e9882033b89b
0ea06a275415ff829a1e218f4e9363ca8c279dae
8323 F20101111_AABZHS wyman_m_Page_108thm.jpg
3119923a73bb25f86e7070fa91eb6075
22477adf9560e70cd84025707961500d2a6d4dd7
110654 F20101111_AABXZJ wyman_m_Page_010.jp2
732041d12ee93e09381c8d384029b654
548a8bf193c295b0af5f25c5aa6627804ada78f2
20986 F20101111_AABXYV wyman_m_Page_088.QC.jpg
1dfcbb24523d0e77277b22c590d13a56
50b92a9a8d27928ff6b6174748448bbc39af0bee
F20101111_AABYFE wyman_m_Page_017.tif
63f1a3dae76157765aa12153ca064048
7bdfc377318b69dc7c2d6c59b77d0a7172d5c199
47505 F20101111_AABYEQ wyman_m_Page_123.pro
0e76b51efb52820d19ae8081f1487bc4
16e3538704592b6d83a8410efacea3c720543b64
37927 F20101111_AABZIH wyman_m_Page_136.QC.jpg
ba35bd67c5c040e4a9cbeba05023619b
080fc15ced580eb9e5f05794d6256a31f8c59422
53514 F20101111_AABXZK wyman_m_Page_071.pro
b8ae358639a85f6393608505b649e8cd
fe0ba9b8039cb4dd9e2aeb3cf0c6e5907e44dd56
54214 F20101111_AABXYW wyman_m_Page_016.pro
db99c37296d3fed61beccea32fb5c580
639099fae1e52c6fef09a295ff84f0ecdecacdbe
144272 F20101111_AABYFF wyman_m_Page_147.jp2
af828829b5917061db7376e7adc6c210
2cdbf47576e415d8175020dc93cf71ac5225a24c
9146 F20101111_AABZII wyman_m_Page_136thm.jpg
a7c0fdfe67414fbb2b54b23270a0828d
f13de8c67bcc52467d3054dcc0ac6694711c2368
37327 F20101111_AABZHT wyman_m_Page_110.QC.jpg
21d1f7b89825c604a0b812a9a703ad53
f6a0ff7401136558637f0b394a2ad41196f2aaa7
1898 F20101111_AABXZL wyman_m_Page_026.txt
317949589a6d0288ae98dcdbdc64a416
e31e5e440534072555f81373c6d42a46637d0c59
5181 F20101111_AABXYX wyman_m_Page_048thm.jpg
ccee173c63b51ec1670af6f6a2e97ecf
1dd30ce662afd03fdeb96750e6501174f40309b5
124502 F20101111_AABYFG wyman_m_Page_070.jp2
c459a959c18f51534caa3ac7bcee961b
b4fe7e8b58377c9304c644c19a1c5278455c33e8
F20101111_AABYER wyman_m_Page_041.tif
d196c57f696d860d2ba0015969ef98c3
36fcbfab5642de1829bc1b17fdee3c9960ac0354
34569 F20101111_AABZIJ wyman_m_Page_137.QC.jpg
25aff82e4d46abe37f5c7fc19e2295f3
3023567080755d6cc4509555022e89823e68d032
8882 F20101111_AABZHU wyman_m_Page_114thm.jpg
a9cc508191a5b5e40fe7457d0ea23fb9
1eefffed569a43a5ec894ca55cf53812e2b6bed2
F20101111_AABXYY wyman_m_Page_099.tif
04484eeb52d55bffc52aa6ae256d8cf3
4ba700729fb9ceb27d1c0c5476bc41ad42537a4f
8677 F20101111_AABYFH wyman_m_Page_027thm.jpg
96d0a4986c133598edafc338f9ebb76c
70da7100ea783ead48c6468508ae23cc414ef2d1
38057 F20101111_AABYES wyman_m_Page_144.QC.jpg
ead077738d785b04095afb3c490c1b43
eff266f68acc3158066eed46d9d722a17fa917ec
F20101111_AABXZM wyman_m_Page_074.tif
34867474f5373322fd2e1f39ae47b632
3a454277d6bd67c9dbc27983a4466a717e693588
8661 F20101111_AABZIK wyman_m_Page_137thm.jpg
6623e157f5a17bf36c210b0532d8cece
e276c1d44256adc6644bb9565c65e08a6b99144f
35024 F20101111_AABZHV wyman_m_Page_115.QC.jpg
14dbc425a4bcb23579187299c6b4aa31
ec75f7352fbeee68cf1b64b1a09820478328b475
188725 F20101111_AABXYZ wyman_m_Page_087.jp2
6bd8cad7c9659ffaf2fd762d6d6d8ca6
eb5b46b5634048f6b42200781a9626ef99e57aa1
F20101111_AABYFI wyman_m_Page_075.tif
94d3812b3512271f327fa939a582a266
2a57075a9ee1fbcc6b24356085efb9e00261cccc
106284 F20101111_AABYET wyman_m_Page_057.jpg
1a092c7a82c4c29a517ecee550aa59d6
fa9d46608b11fef0e66d111f89ddb2ad061c9e27
F20101111_AABXZN wyman_m_Page_139.tif
b288bd7398a19db72e6b30721b30f2b8
410326373f9cce906a85bd025886f9f61a3fa1f3
39984 F20101111_AABZIL wyman_m_Page_145.QC.jpg
bb2f75aefa4ffc477b8ac1e8ccab6598
edaef7707b65f1524b626e1e4e61c808eedf6ccf
15898 F20101111_AABZHW wyman_m_Page_118.QC.jpg
87f4a1902476978f1c04d67a43852e96
86a5ea24869d658fcb1bbab2ac64fbfaef8e4405
27733 F20101111_AABYFJ wyman_m_Page_092.pro
9801df2a27f05bf0ef2d78676669de53
bf704c1f165bc78a5dedc748c65ed85d8dd1e7d7
2839 F20101111_AABYEU wyman_m_Page_095thm.jpg
710aa72fdd706311f6e4677b07b53b87
5e20069747a75bdae41d51356ab55c8b24589f5a
19198 F20101111_AABXZO wyman_m_Page_093.QC.jpg
5fe877d22315f8f650fc0b92cbca9b8b
5dd8b373d947a4288cb91a2232e9247b44c27e70
38114 F20101111_AABZIM wyman_m_Page_146.QC.jpg
afb3ac8837dd49bb65181b8fc4753c41
d104cb0a61cf5e6d028591b1414c37f31d35661b
12694 F20101111_AABZHX wyman_m_Page_119.QC.jpg
ad3fc79cca0b0ba499ff70726931876c
d0d74d086cf4417ef973823d13d717f86c33a004
557 F20101111_AABYFK wyman_m_Page_088.txt
2fbad4591827b5683bdfbe6361b8e079
983d97a178fabf90cba2e4f6baab7babf777a874
F20101111_AABYEV wyman_m_Page_022.tif
1f3f5a297d9367dd3d4597746754930f
d54179aa75e2e7d3ea6dd9cd865deafcc2de22a5
F20101111_AABXZP wyman_m_Page_019thm.jpg
7ebf86c254e8ae823c16e05446ccea0d
40924f2d7c0dc5256dba9009e2c2d53012ba3c2b
34611 F20101111_AABZIN wyman_m_Page_148.QC.jpg
f1010423078fd168b2186939d6621d26
566c087eea56c6b80707d1b3b983bd37d724542f
10306 F20101111_AABZHY wyman_m_Page_122.QC.jpg
7a4358cee895174c06c773eec22a9747
ad96de73ab7490088dfb871d78ff2bcf4f303104
54694 F20101111_AABYFL wyman_m_Page_096.pro
2357caed5b316c396cc0388c7c2c03e3
fbfc03594189c3a6b7b844b941d3dc10a8445592
36441 F20101111_AABYEW wyman_m_Page_029.QC.jpg
6d215c61e61cadbccd1507a4d610e46e
52c1a844bd60c15d41dc047a6ca101fd171e5661
139744 F20101111_AABXZQ wyman_m_Page_144.jp2
08c359f8b19ba1d65ba0c00cef2873e7
ea6cfc419d1dc26107b453665d2359b62b4d670b
8765 F20101111_AABZIO wyman_m_Page_148thm.jpg
7aee543d5d08ffa79da161cf86db7487
21bf967d1ee7898e149ad4948e84398c56319ed2
35069 F20101111_AABZHZ wyman_m_Page_124.QC.jpg
e4870dd698f50a0d0e8e88ccd7f6448d
481f2d69a786a9a6135b392692d15b94e0490c92
926 F20101111_AABYGA wyman_m_Page_083.txt
b421298e99aaa1740ff1470022efa667
9eed2a7be9afc54d2199055a0ae9b4376b0175a7
36132 F20101111_AABYFM wyman_m_Page_019.pro
03f4eb83e149c2729dee91834e920a93
59c7a2661252b2473c9c1eb0326b7f5f07c5d697
5763 F20101111_AABYEX wyman_m_Page_002.jp2
f04c2d214ad04677c89f9c5142d4fc13
962f41cb5dbf5e7345372b9d289a5ce50f3c63b0
8503 F20101111_AABXZR wyman_m_Page_055thm.jpg
13af1575ccd9bae4b1624b2b0f907cae
5a0c5869f43afc6a40da50c0894dcb73b11a7594
9300 F20101111_AABZIP wyman_m_Page_149thm.jpg
caabb0b8ad7d0fef0c3cd942c94ddf9b
619f73fc0fd9e06a21f0d667b963d9f13fe47587
114055 F20101111_AABYGB wyman_m_Page_012.jp2
babd9c18cc7a4807b059300cea11ac76
fc2e08c9f1aba60b9f46a6ac5ce6709e16508ce9
139977 F20101111_AABYFN wyman_m_Page_142.jpg
e8e4bb61c0a5e842d2e821e47156d9ee
adb571d29f9f59327e6f3bcf475331587340cf89
9522 F20101111_AABYEY wyman_m_Page_141thm.jpg
c2d14bc414d6897ecdf19b5aff3004d3
e15f140988d2c17d5b3e3514bf9e8205156adfaa
119053 F20101111_AABXZS wyman_m_Page_031.jp2
7dbafddd42ad29a8d4919d22a78ea8f9
1693546d23eee81ce457c440168a097617f68d10
28190 F20101111_AABZIQ wyman_m_Page_151.QC.jpg
9bfe675c1aa8168aa2387f074cf01d62
e321155fa239299ed5b37b8b0838aaae3c33bfe7
64788 F20101111_AABYGC wyman_m_Page_144.pro
1dff94c9c4a5c95242f17cd2715e07b3
354deeb98e9720d7afe1872b6c3158373ab89fd3
33636 F20101111_AABYFO wyman_m_Page_093.pro
659ea463d06c77363a9c9e73a25f3e45
6ebcec1ca9708dd56640de45bba8a8850efaef34
2127 F20101111_AABYEZ wyman_m_Page_016.txt
075df4305003f9818c98a65d2e87be5c
1c5d8e728d5e53f43ef2ea34d51bf64bf91f4a95
31285 F20101111_AABXZT wyman_m_Page_094.pro
962323002a34c08e1d38331c7064961b
987aab53cfe4bfd5b0bc37c0fc8c58361915535f
6649 F20101111_AABZIR wyman_m_Page_151thm.jpg
61a6b4b4f1198f86ecdc2e13edfee613
ef6c2244464bd31850689d90dacad228b8d14c4f
35520 F20101111_AABYGD wyman_m_Page_129.QC.jpg
0190e899d53f8f38f7f34fa656f6407e
373c397fd9dd183e85960cefc2fa5902694fd91b
F20101111_AABYFP wyman_m_Page_057.tif
59e641f912dd24172aa2450529810e42
0fb8e81ad27c50a3d375e9ca1ff63ea6d50d0555
1669 F20101111_AABXZU wyman_m_Page_050.txt
73cbd2a340160f349a24ffc760788502
edbf88593b3073374bad634bd4824cdfdc6ecc55
8370 F20101111_AABYGE wyman_m_Page_152thm.jpg
1029d3c75b91a004744111b06be2305a
b643774d5c165280e46e326bba1ea8b3125fc149
4191 F20101111_AABYFQ wyman_m_Page_047thm.jpg
5e4517feeccee7fadfcace72cf8906f5
81e44b92c1e03a02f4d78091cf346555c30c347c
F20101111_AABXZV wyman_m_Page_065.tif
467e496f7b8a0f27b790ca2b1c5ad73d
f3dffe7eb5c1fbd37703c1a48abc01b484ab393a
2847 F20101111_AABYGF wyman_m_Page_150.txt
7c9abf80483b121fab3df6770b18a6e0
2d5d37e3083df5abaa6026ac030aa0749c89fde6
F20101111_AABYFR wyman_m_Page_071.tif
bf3984478173e1dcadde4c86dc66e720
a02425c3f38f20e2bbbdc22c2febbc0a840cdeb8
109309 F20101111_AABXZW wyman_m_Page_106.jpg
512d0937d6d5bd9b975e51ad75327774
5b24741edd761e48a6a0abbbd41fed35a4629e10
8194 F20101111_AABYGG wyman_m_Page_111thm.jpg
f0a4b799f9a3694ccd2c25806aa44a55
e4acf16cc1a7b62ad168bb6e878bd196bbf155f6
106047 F20101111_AABXZX wyman_m_Page_066.jpg
e7b3320bc0c382c518f57beabb7c7213
73ba4938e20c518cbfea9f8d740e23b342208d1b
F20101111_AABYGH wyman_m_Page_063.tif
f5a75d0c567ed82d3869edf0b974d172
d2aed6069bf171160979ee871b73ab887d2a77b5
9137 F20101111_AABYFS wyman_m_Page_077thm.jpg
1a100b8d1efa546d92cada1c34fc48bb
d80309d9ef9633d21e93ccb170b357e184d6f63c
9618 F20101111_AABXZY wyman_m_Page_146thm.jpg
19c9d30a2a6c9658e4ae42b41c7f11f1
cde77911221a7515244f1af073fd47e32928f96c
73195 F20101111_AABYGI wyman_m_Page_121.jp2
8e77de34ad0f7e2a5e660109f72d2e0e
626fa5fdafa210078f56d4fb33e9daf85f6fea20
33574 F20101111_AABYFT wyman_m_Page_061.QC.jpg
864cf99fefdefd6b87d42f0aa0befbda
074eabf28b6d8416eda5892ae4bd99feff622374
116162 F20101111_AABXZZ wyman_m_Page_124.jp2
c9e9f65ff72659207e83d56c251a8ab3
d4f0ec837aacb009baf8b46989433c10031f66b2
52165 F20101111_AABYGJ wyman_m_Page_055.pro
4b92fd1f14d35eb0c00f5f152a52e788
1e2ca9064db9bdc67f95b3a76b00c2de71c48570
35419 F20101111_AABYFU wyman_m_Page_059.QC.jpg
1cdf49166421de0b852f45f122eb561b
2916d059266715dbc1ec6ca7db90940f7f8fede2
329868 F20101111_AABYFV wyman_m_Page_086.jp2
ee543c45e9e210a3a49de7271c65afba
06f29e49a90e82cddb8c7df7e4f5537ec5fb2e8f
F20101111_AABYGK wyman_m_Page_062.tif
7eb07976bee4580ea52dd4d89eb8b0e5
7aab4d5a1476ce37056c329f2aa80e1d7f72c8c6
62459 F20101111_AABYFW wyman_m_Page_050.jp2
40ff41e6a99344c2c65a8be6701a4f44
d93028b3dd0a07dae02a940e4ee4911bb01db186
8835 F20101111_AABYGL wyman_m_Page_125thm.jpg
9acaba29e0ed0737ae22c517f0ab8d52
576a5385833fabe79b63c2ae4d44e8233ddefe37
F20101111_AABYFX wyman_m_Page_136.tif
c79936494c634e9f168c200fec8e347c
49564df7e71d8027d552e66a9a62340a49b56e56
473 F20101111_AABYHA wyman_m_Page_117.txt
0caccc2d7d5458a253e0cb117f6fa70b
aaa8b805a25a5ff4ef3db98143a8039022baf9e1
107346 F20101111_AABYGM wyman_m_Page_015.jpg
af9ec9688a73fda6a9548a5550e055eb
2025128f9322ca1fa3d9ab663a24652fb7254013
390842 F20101111_AABYFY wyman_m_Page_119.jp2
960b59b797cc98a3d1abb5a166dff2f2
386296f1a987b96b04bd82348a2dc096572647ec
38032 F20101111_AABYHB wyman_m_Page_138.QC.jpg
4dbdd76ff2304722a0e63039fbe09b73
c220d456f82efbe01d6f15ab4c78ef378e5e567c
108733 F20101111_AABYGN wyman_m_Page_114.jpg
7e567146290562e0250a3031ef3d54b1
3f24441f0998dee659516a456527e1447f5faefb
122032 F20101111_AABYFZ wyman_m_Page_063.jp2
6b13a58be867ff9eea5775207974b862
ed5d0be9edd5eec0c1674e7f87914b102ebe42a0
7974 F20101111_AABYHC wyman_m_Page_054thm.jpg
8ddcb382e52425a78e25477fbcae94fb
affbdc44579c4dee6b90584e2f4c32cf6d27ab9d
107904 F20101111_AABYGO wyman_m_Page_108.jpg
fce954b4b616687767a4c9e6af3bd664
c4cc2c783862bb4cf7181cb3833c572e463ee3f2
53745 F20101111_AABYHD wyman_m_Page_100.pro
ac21b240ed4d30f66e8e9ad6141d7d8f
5616c132661a649f4758367f36103744cde23beb
F20101111_AABYGP wyman_m_Page_006.tif
472ff17971ffd8df357b27bd1108059a
ca0599c5558455a577cd1fcdd895b4806bfdc685
109608 F20101111_AABYHE wyman_m_Page_072.jpg
db0521f84947400dc79bb011e8207ed0
319b04b909d0b7affecc9c6281f019f0ed3e3db2
112538 F20101111_AABYGQ wyman_m_Page_073.jpg
318877f2fe9468388c1a77a3d233b62b
8ec626e1b977f1867312e271dd8bb069148b2554
F20101111_AABYHF wyman_m_Page_098.tif
6e37940ee7a68ba78b56ebff2f90736e
263080046648794ac3848260abfd34bac27a3874
9013 F20101111_AABYGR wyman_m_Page_143thm.jpg
e1147f122ba341bbbe08cbe8750d9b01
a7802e05b6cfb0e47cff81a28781a3925e771944
1419 F20101111_AABYHG wyman_m_Page_120.txt
bc37284716f4b9258a1bd9eea199b5be
f8506610626a24ed7749b460caae0c1644c46ffb
56309 F20101111_AABYGS wyman_m_Page_032.pro
113182004c31611e4905dbb24e663d36
a2b6c392cc2e1d11263b3ba337c0c14632f987fd
6960 F20101111_AABYHH wyman_m_Page_007thm.jpg
d284d0dbac9171a28a975c855b8ae1d0
7703d1997140aee4706cce952a62e1f21c9f7313
F20101111_AABYHI wyman_m_Page_078thm.jpg
b7fd2945c89ed14fbf008c570dd81ede
ce9f083f759ee8d88f7cb4fffaf28327c4149d3c
2270 F20101111_AABYGT wyman_m_Page_098.txt
6de340fa38fe43b6e7843d2ab691ffdb
63a9e92534151d5be77145091f8efe985505ef69
59412 F20101111_AABYHJ wyman_m_Page_092.jp2
cb49c7ea2fefb7f85964d9d715806cef
102a90e14aca92d41eccb7db3e6e0243c39afa68
114856 F20101111_AABYGU wyman_m_Page_057.jp2
c53034b7d157a2230090646e333fb0b0
8cdf42a3062a41bc415897cbae43b608c4bc0c54
27443 F20101111_AABYHK wyman_m_Page_120.pro
05e25a6f438522dc60bc98d1ae2f1537
a0910f57a31d4a584e4c86422c26ebb5e1532c74
137029 F20101111_AABYGV wyman_m_Page_144.jpg
83093099d8bd88cb350209da961c0719
bfc35d0160771c162ad17023826dc717accce1ba
F20101111_AABYHL wyman_m_Page_150.tif
063e74e8b058fef4f87d6636fbd1f87f
862a4a48e19b2dde531ddc058fd8e2a8eabb4971
16688 F20101111_AABYGW wyman_m_Page_116.QC.jpg
99776aa684f7c2f8197051d784a05eef
68eb689ef2d4db896808dc990d4cf39d6c89b4cd
1051952 F20101111_AABYIA wyman_m_Page_142.jp2
60a14dcc3333bd9659ec33c64f28f21d
0c984209470620bf785155fcc46c8c4326e66148
132497 F20101111_AABYHM wyman_m_Page_131.jpg
cdb11b4a6f3b02125e7405693157ac69
96def9244bed4d564d8d187d3fe1b7c3a3023807
52131 F20101111_AABYGX wyman_m_Page_097.pro
004bd8181a62bec7650e92a3976cbf6f
e98af019a5bde7e6734ed367a63cc7615d295272
34532 F20101111_AABYIB wyman_m_Page_056.QC.jpg
8019e77007cc8b3174db52589bd9da2a
b7837b61a30dd1fcd944f630b265ecc5ad73af22
33495 F20101111_AABYHN wyman_m_Page_051.pro
9207ce225ea837695595d0e949d1e986
f9e1b6f3be59e912824a0fa2185b792f58cf26a3
4915 F20101111_AABYGY wyman_m_Page_011thm.jpg
04d15df77ba34d6fb43453116f856b7e
4af4078600c877867c8352e959c7daf88ff84b11
19178 F20101111_AABYIC wyman_m_Page_005.pro
20ccda3261eaf97a6cbf52dcaa34ecb8
b075f8ab9ef4924e9b16a05f4d1037ccacb608a3
7989 F20101111_AABYHO wyman_m_Page_010thm.jpg
efbb5f8c77aaeef7122e95a4e4507c00
14c0a49a78f086ba3c544d56394b4b5dbd9b924b
17800 F20101111_AABYGZ wyman_m_Page_153.QC.jpg
676dff018dc47ee96bf9be03258e423d
20c7a8a868d6eb4417b495bd4929c9fc15107acb
F20101111_AABYID wyman_m_Page_113.tif
68750b1f36a452c1af967e3ceac01011
f3a6ed6774c2113c3fa3de8c1f64e24445c37c01
2089 F20101111_AABYHP wyman_m_Page_113.txt
05d1919d0325beac3ac0cc34dafe6990
ac290207a8ab824b88b134c4b9819dcea2b6b1d5
54000 F20101111_AABYIE wyman_m_Page_041.pro
dd3424db1afbeee1ce9e9fa8b5e8e4ba
b82d5e4f17acb2fe890ee8cd1ff8de203aece491
3673 F20101111_AABYHQ wyman_m_Page_006.txt
2fe644d2f0d68309bfe1449c537fa5c6
3012e203004919c21e9ed30dd5af6b370fc6e1a5
35980 F20101111_AABYIF wyman_m_Page_074.QC.jpg
83b19704b8f2ea26313efe867706dfc0
76dd44529580008c3cadbf2162d8beb1e104c970
55477 F20101111_AABYHR wyman_m_Page_013.pro
99b11b4d2b9a6dc0fb110dd0e9bca20d
643632e71320580c5f4c196cce5b77c8747911bb
130206 F20101111_AABYIG wyman_m_Page_149.jpg
24a2d575de06564e10306131ca116831
d5fce3f9fe279f632cab05c8d038f44152cfbdf5
30975 F20101111_AABYHS wyman_m_Page_123.QC.jpg
cba5f02ff57fa44338041442d07f649a
9dd2d334168c1ec2bd377636b14df39082aa5b71
112376 F20101111_AABYIH wyman_m_Page_009.jpg
43ca9e49e08e02b0f9a0e7e500f12d1f
ac27e41439defd0c9448d5891613c2a9a937c13a
54411 F20101111_AABYHT wyman_m_Page_153.jpg
ecb77b30c6030575f126f5d7b25a6f5a
b11154b1b52b5ac8a677dd563e4f4f10cbde6813
61179 F20101111_AABYII wyman_m_Page_094.jpg
0137f79040bba50388437e505c1bef45
d8d88b093a9c3f17c578a14715380e95a4c37365
113985 F20101111_AABYIJ wyman_m_Page_024.jp2
41f9283af345058c77817829178434c3
15344fd42e44bd4a72e405d34f9c8e6d4669fd0f
34504 F20101111_AABYHU wyman_m_Page_036.QC.jpg
05dd79d94a4fa415f00e7f129e266bbf
41a08085e58dece4e390ceac7a693eea961e2d4a
4763 F20101111_AABYIK wyman_m_Page_081thm.jpg
5fb4fd299da8c1129cc71bbfdd8d1def
b919b34fa4a40fbd63ca0ba919f202f2abff0191
9174 F20101111_AABYHV wyman_m_Page_070thm.jpg
8def4c29dcb3be35907bc832ff9ab7e9
c4f8c21b98befd3a9295b5da1a3e893bfd3954bd
1051981 F20101111_AABYIL wyman_m_Page_006.jp2
947b0bcc1d08565d534555387f4fb6bf
8b7f66db43e0b17e2acba6dd86b2c1c6ca3fe99a
F20101111_AABYHW wyman_m_Page_119.tif
5337ab2a9fa3160f1dc5aea814cf7e8d
8e40107afe01081b6a33c6752c41163ceabb5b4f
35441 F20101111_AABYIM wyman_m_Page_104.QC.jpg
67509d5070b2988fa2444ab33126dd34
c00eaa4178c302cabc650253c4a0cd0329ecc44d
F20101111_AABYHX wyman_m_Page_025.tif
8222fdec3f8bf87f2df4fa51300ac6d2
609d46d29d2d5c52e75bf49fe8757807cf3ad86c
372 F20101111_AABYJA wyman_m_Page_082.txt
35445baf0501c9ae824476e4017e2803
8586bedccd19d989a2e4be1f33d3c06789ccb68e
8617 F20101111_AABYIN wyman_m_Page_036thm.jpg
df07f17dde6c8f225d3a91b0bd36ae97
2df09efeb80752c22230054c47cc65337d2e56e4
117427 F20101111_AABYHY wyman_m_Page_015.jp2
9984ae7a15ff0bedfe085a12b0ceb41b
29fffc961186d3ad48ce16ab21e249d7ee2ac3a4
F20101111_AABYJB wyman_m_Page_130.tif
cc910a7ae27e55fc10d18db6074f8f74
da6f54091968b79014f36f9d19dfc621d6901bc4
25213 F20101111_AABYIO wyman_m_Page_019.QC.jpg
3de896710e15c8355d3f1bc0fc7eb105
0729b584414e120ff424284d5957310893624186
14453 F20101111_AABYHZ wyman_m_Page_079.pro
5c95810a5f4bac33100504eb73baca43
a69ffef0b24d4556991ce23d2e6c38a8caa87cd1
8658 F20101111_AABYJC wyman_m_Page_014thm.jpg
c58881f5403394e3cdb78fd4b4333fda
dc75eb58cb60a7fdf62a67cd7e343a56f9cfbf8c
2193 F20101111_AABYIP wyman_m_Page_112.txt
9dd83a19fc1fe62e1fda35b2545b9900
50ec80dc07a5e9db74d2b7ea53b31351c10cb93f
F20101111_AABYJD wyman_m_Page_102.tif
e192a6fb040bbd74352f00948dba585c
0ab93c4dc84880d97cc099ec63ae8bdce14ff5dd
51378 F20101111_AABYIQ wyman_m_Page_029.pro
4a3dce0340060f77703eae3360291db0
ec61aa2b7129b096346a3f850b55d09454c0c07d
105853 F20101111_AABYJE wyman_m_Page_024.jpg
bc92a9136a78baacf84bc3f2b20d17a9
766ff1668e3c7a9db1aa410287f95ac08a276ec3
114828 F20101111_AABYIR wyman_m_Page_055.jp2
ed218505dc4bd5416bd536c90a840d1e
d4d241cfd5fcb583a0d704e09ffab2ee8c7a6ba3
4205 F20101111_AABYJF wyman_m_Page_116thm.jpg
45a4651c7e18a5e51a5c710d1d2478d6
df2c743ad9e1f659027c6284367e5766bfbc5416
1051954 F20101111_AABYIS wyman_m_Page_008.jp2
eba83bbc6fcbbaae3d6efb62485e0b0b
51ac1466af7b34f47eeaa0f0923f759c8687024c
743772 F20101111_AABYJG wyman_m_Page_089.jp2
625289ad61744c2783647bd6f6b04c9b
a698859bb4e944cf62ad83cb2f93b5cf616b80db
123914 F20101111_AABYIT wyman_m_Page_137.jp2
bc0e9a311f0dbc3391c77895802eaf95
6e2cd943b65f1963cb4a861a4f985d8a0569d994
F20101111_AABYJH wyman_m_Page_044.tif
bdeb0e90388c0be935407ec59256756a
cae417c5374d29ceb39b843b2f0ba4677eae896e
66474 F20101111_AABYIU wyman_m_Page_009.pro
e4db8fd2a8735ea172a5a38ee92add82
1f6973314faf2af0da497fc14f2f045039393de8
F20101111_AABYJI wyman_m_Page_005.tif
ce2526c56884bdbbc9a289dc8504631d
acd32b7cccbb46b6a91c89f77e792886e5594916
8738 F20101111_AABYJJ wyman_m_Page_018thm.jpg
e24a7c34722fde2d115df7fb932c510a
ff7e0323b1cff23c867ec6baced8e74bf1aea8e8
49150 F20101111_AABYIV wyman_m_Page_010.pro
c02b9ace6cae13e6e393595b89226bf6
6ed942ed278294ee74b57e7a1ae75e96affc1439
5802 F20101111_AABYJK wyman_m_Page_045.QC.jpg
cf061837dec59da5625cbddfff85004b
5c42396d4a7d58e4b34fc3922e9e210a5313e1fa
2645 F20101111_AABYIW wyman_m_Page_122thm.jpg
14327df2b9e37290e472db6e6795bb52
11957a5394fdfb415ffffbe5b18a1e71b0cb0aae
141243 F20101111_AABYJL wyman_m_Page_133.jp2
1025ee7a70830533820da612eacf3192
093ec50f6aff4bcc282c715f5e1164e969666f2a
107735 F20101111_AABYIX wyman_m_Page_033.jpg
70b941cf75b8cffb322ad0effef50795
d35634589d3ef09819007451d52005e26943f886
55668 F20101111_AABYKA wyman_m_Page_046.jpg
cad377b5c7e7cbcb34ae08d2e2af64c7
7af7b6f901a34954ca56d066ed2803c1c3e3e30a
8573 F20101111_AABYJM wyman_m_Page_025thm.jpg
d345772fb5e7b74627a0d905fd3a00e9
c00a840fe9eff9abc25cd3c8f564cf5e8ce76ebc
94 F20101111_AABYIY wyman_m_Page_002.txt
64320278ad7b2d5f0f95b95e60fb6220
f054f234af15524fda1a7cb0e91088108d226d7b
F20101111_AABYKB wyman_m_Page_143.tif
774ce1f457285e34472bc9a673ee30b5
8d2dbbaf73b0fac060965673eefd497f5ef7dab6
34695 F20101111_AABYJN wyman_m_Page_095.jpg
c8cf624e84bfc26b9728816d15aa1c17
25608340861ee064db5f9248d20f88008463c66e
938 F20101111_AABYIZ wyman_m_Page_002.pro
56062408bf1e68ab3710d0874e125470
117e320869f7c273aea60ac8fd95693b256df08c
36844 F20101111_AABYKC wyman_m_Page_053.QC.jpg
10241c7a68304e956c46fb7b0a119067
1a01c47b6499b19b4006b5a4b20666586be786ff
36914 F20101111_AABYJO wyman_m_Page_139.QC.jpg
e745b60b36ac52bf42b7c1ec41976e85
9e1c4693adfd2916c58cbffa1296439e001aa3b8
54473 F20101111_AABYKD wyman_m_Page_056.pro
653a48f2b4156977ef056c3deedb8855
7915d6d96a615892d49eba9ad8b525cfff1f6473
33739 F20101111_AABYJP wyman_m_Page_012.QC.jpg
a2b013bcb5caccdf4ad76ffff5d7c66a
1e68f69d96a3ed7a37bdc1819c87faa564a81f77
8974 F20101111_AABYKE wyman_m_Page_044thm.jpg
5fc99d2470c3af3e152395eae85a8145
2f854140d87e85949e9996f0ebd03b662599d4fb
39194 F20101111_AABYJQ wyman_m_Page_119.jpg
170ff8d8bb882dddd70de25bf6391fcd
17ca46c7ffa8464839e021813c7485be3da3469e
1051976 F20101111_AABYKF wyman_m_Page_062.jp2
369bd36e1551aab5c1643d95a9119830
e240243d27e96b964ab5fc01e71e3e7147803912
113221 F20101111_AABYJR wyman_m_Page_022.jp2
18dc5a68d637ec3401c3db028d7fc38c
13f95c6237175b26dc91235df439abf3810958ba
F20101111_AABYKG wyman_m_Page_054.tif
7ca7b1007dc0c5c1ed5089f90cc46b61
c35936f1b1bcd676a07dd0ea173eac9b461737a3
746701 F20101111_AABYJS wyman_m_Page_088.jp2
319316e51727b90cdad20ab613526325
12d44060f6a1f40abae90006a04bd4935ba821e6
115430 F20101111_AABYKH wyman_m_Page_097.jp2
5525a09fea8e952bcc3161eb36a37ee2
51b84b3d72c7301416d9507d3f548a3174a12e94
F20101111_AABYJT wyman_m_Page_105.tif
5c7571cce45b14d880139ebae4ece07a
54dbffa49d4af7613fc81b16152828b5bf8d854b
2838 F20101111_AABYKI wyman_m_Page_142.txt
df40423196971dfeabefd18d7e624c08
b8d735ef9e14a9e67fcc63b260edcab569bc191f
8163 F20101111_AABYJU wyman_m_Page_069thm.jpg
3fbfd1c0fe67f04f04bb53e13606c845
4d16ed46f1d623bc391d7d2ba097a899e9e69e01
2114 F20101111_AABYKJ wyman_m_Page_014.txt
1efa04a6fd0d278ec2e69fa970e0de7e
e8d2f428b3735c4ae5496e14b523099f03ca2b76
8150 F20101111_AABYJV wyman_m_Page_126thm.jpg
b52cba2e0cf11e16199669601dbeda58
a924c6db6edad979b6fca02fe843af9eb136f00e
2112 F20101111_AABYKK wyman_m_Page_066.txt
0f0c8f48038d468d964d20bb68daf1bf
24dea1e180bbd0afa5b977e7eed6d20e78dc05bd
F20101111_AABYKL wyman_m_Page_008.tif
3ae3448ba595c87ac910c5b8e459d7b9
f553f6b4fe2b5956a363dd65fa147f7d5ee6f829
30847 F20101111_AABYJW wyman_m_Page_026.QC.jpg
1773b015e890ea00968d5752c0c86d3b
3316d27606d63694b2260d05ede6499f2d2987f8
129287 F20101111_AABYLA wyman_m_Page_128.jpg
1bf96e4c8b770c02362e4627ae3b8c1c
acb9641c576f2dc96a4fa6fa9712ab9e3373e75c
32185 F20101111_AABYKM wyman_m_Page_111.QC.jpg
71d48b454eb646e466a2d743f73c9116
27b92df6d0531fa06c8ebad67e6f317e12d23013
53487 F20101111_AABYJX wyman_m_Page_110.pro
62cdba92b30c31e697ca6007630c284a
b43b09c8d5052588ced8aea9d209504c2d6ca783
123962 F20101111_AABYLB wyman_m_Page_132.jpg
f3175107c05cd7e176deead1553f8033
108dab2d5bce5f5da5359ba7a8f5f8e8f325774d
129461 F20101111_AABYKN wyman_m_Page_135.jpg
027efcc8d6326e14aa96047f65786cae
e2a01f7150ee18ea0df84029330679bd86e19644
115061 F20101111_AABYJY wyman_m_Page_152.jp2
7987d982e37ac9856baf96b97ab4b407
bcc218de9b2985b6b067d862fd3a77481d27d45a
2189 F20101111_AABYLC wyman_m_Page_063.txt
a436b0787102c69546656367a1c899e6
8b4b39dafb91edd28ed53fe773f1bd9610418adc
38923 F20101111_AABYKO wyman_m_Page_147.QC.jpg
2359b2fea79a40e41015b96a7a6dabc5
6dff02e798ce2cb55b898ec30ee2adca0675cff2
1778 F20101111_AABYJZ wyman_m_Page_052.txt
c5576533147ec3829f31d0316726eab9
f9fca6492cc8ab34ec1d6fe7357c764db3bc400c
8787 F20101111_AABYLD wyman_m_Page_076thm.jpg
b6410542c1e8d7e3a317ebaf6cfa446e
ab8b6da3ff552122bd8fe5bdcbbf14810082a2e9
35530 F20101111_AABYKP wyman_m_Page_125.QC.jpg
f388dfe69bbdce916744cd1af58b5882
bbcc01e259cd2b71d85cddb05bdde64e5c770e88
57337 F20101111_AABYLE wyman_m_Page_088.jpg
2317e1ee7062919b21341fc85ddc8349
f4f808c6d73b95eb07390a86cb1c117a0f49c843
34564 F20101111_AABYKQ wyman_m_Page_024.QC.jpg
47b00adf6d19cdeda4143a60fa321ccc
81806122837eae2e26ae953112355a320ea9095e
8761 F20101111_AABYLF wyman_m_Page_041thm.jpg
02e31870d3fa722352c85fec8cd32f97
989c652f03f0d1ca77cbb5a4a4e72064d37e9152
53067 F20101111_AABYKR wyman_m_Page_108.pro
b25958f0f536932b6edc285f3bf89da3
b3274039bf7e147c1bf6975548493c659b4753cb
F20101111_AABYLG wyman_m_Page_131.tif
bc93ba57fbe9b7039ad49e6c6e818153
3b93d949a34c856338212644987669e9f37dad0e
67106 F20101111_AABYKS wyman_m_Page_048.jpg
c4c8ba4b43f941a3c9707421a71cb1ef
389e74e73ec0063b11c3cf2b5e11ed041e2b2722
F20101111_AABYKT wyman_m_Page_095.tif
529260ec5194fbb4a399b138bb46991e
da336d08a2f0f1fd252f6bde376047dace29adf7
137043 F20101111_AABYLH wyman_m_Page_135.jp2
e3f4631e8786887d42ab794e9871d5ff
bbb7d9ca154e669afe27ff3751180052d400833c
8337 F20101111_AABYKU wyman_m_Page_039thm.jpg
8a28af1dbf17def8924a97e492e30dd2
2c657bb852d6976535abbabc3b9d0ad0b4053027
F20101111_AABYLI wyman_m_Page_010.txt
ee1c0a167dcbb522e61ff441e85ab3cd
9fc9bcd21df331027e97c6040e7d704c8845bf0c
2012 F20101111_AABYKV wyman_m_Page_036.txt
ed75c3b9da2c6a50458b6d6eb2d2151c
65efe90360415295dc2bc0b629b41bf29748bcc0
54514 F20101111_AABYLJ wyman_m_Page_043.pro
39de53612cd6355cbeac1b1eb4f86019
ca38e60b563b6ecf19d1350bc30623285003440d
117525 F20101111_AABYKW wyman_m_Page_076.jp2
f8fedf0f176fbf447cc94c0e14e21983
44afb0c10f68cbd5c418d4f876c49ca62d663654
2171 F20101111_AABYLK wyman_m_Page_065.txt
664e0e27e5d0f226a95a382769617b94
d50fe0e763371e426a987292698c341d754ad7f2
56026 F20101111_AABYLL wyman_m_Page_040.pro
b34c25530edd0f8d64bf851b1a38fd58
eef99b6d89a594ba8199f6e51b37aa2f07f6309c
F20101111_AABYKX wyman_m_Page_013.tif
03f87599252a0eadfb55804fde70318a
fe4a1ef42d2843a16e7c1c642b0e45b053b34e3e
53421 F20101111_AABYMA wyman_m_Page_027.pro
94b950051a524574fa9cb904c9479f61
16d333591e8fcc141fccf486cabf91e659a1adbc
F20101111_AABYLM wyman_m_Page_097.txt
342582e3931c97f77008331995999b69
5ddfa2d6151437b09925be7fe926c2dd0d33a4ef
2428 F20101111_AABYKY wyman_m_Page_143.txt
50516014360185398e764d9bb58ec2ac
854b39878ba91b4e799032b336ba0234939b8363
115702 F20101111_AABYMB wyman_m_Page_104.jp2
625c5e44603e96c441e5571a4a0bfcfe
ea70c6bd42f0191ceef575263a50452b98a6f146
F20101111_AABYLN wyman_m_Page_138.tif
15f79a89f57ce3627584ff0ef74e4e7e
1707fe82ac8e5f833ce2af71a6f1bd03beb808d7
114929 F20101111_AABYKZ wyman_m_Page_125.jp2
03a10387cd759eb0be2617d4385cc687
fe6d46ea59fc04eb2e7f49a6d06bc65c600121dd
62194 F20101111_AABYMC wyman_m_Page_132.pro
37a3bc9b330f065f3272f713b97b7807
9de76c787891fd866730782b094ba683aa229621
114314 F20101111_AABYLO wyman_m_Page_060.jp2
e1bbf10077e7c558bd8044bb026e070d
016163b22d08ebd70eaf0922c925cccbecfb3425
F20101111_AABYMD wyman_m_Page_008.txt
64be070dfe030f58a0fe9bc197e02fd1
2fd691ea31ada63f5acd28396d9e175cae043476
8856 F20101111_AABYLP wyman_m_Page_020thm.jpg
e77af88540bf71ecfe3d6c96bd9085e3
9404391806f9570754cddeeaee61b2a1921da4bd
63244 F20101111_AABYME wyman_m_Page_011.jpg
4fa015b2f812fe0f00860b115f2995f7
9846299c768756276e4d88bcb58421d534ea2e99
101620 F20101111_AABYLQ wyman_m_Page_058.jpg
ae16fbc5afc5a4db2e30d30b2a3b18a5
39185e3ed1e5653ada222f5456b09e6a4e17ed8d
F20101111_AABYMF wyman_m_Page_025.txt
0b4b0a6fd6d147178c14b0b8cf58b1c0
581862036ede748937838c057d27adfacffae39b
116596 F20101111_AABYLR wyman_m_Page_070.jpg
a63179071f46d588da1bcfef5f9fd3c4
ce8a5be67a794a3322d33f1f001c4750580bf12b
35405 F20101111_AABYMG wyman_m_Page_041.QC.jpg
8cbb42df1d2800f3297fd91698fe3e0d
2feeb23d1b9d528d6e4e85f2d247fb1c4381b140
F20101111_AABYLS wyman_m_Page_073.tif
4e873e87ce1d658e07614806c9e4edc0
e4fcb7958936d49737fd8f58d8281b9f8f590e34
4520 F20101111_AABYMH wyman_m_Page_153thm.jpg
cd320c37d6eec208b8dd70aefd4d14c8
b3f8684868f65e5e69518a48391f6d95f33bb191
108737 F20101111_AABYLT wyman_m_Page_042.jpg
723ab5861176d884c40700fdc08d6372
284d297e1ba6b58786ee41daaf20afc3c31c86d5
1051940 F20101111_AABYMI wyman_m_Page_091.jp2
e9fdecf96770998fa0509e3fdc3fdc7d
da222a27eb04765667a2f7565a2d93ae60b296e5
F20101111_AABYLU wyman_m_Page_085.tif
0f78f1c01831f14720cae44fa85d0189
9d9bf8a1222fbb26106038260fad2a6dc415b370
2891 F20101111_AABYMJ wyman_m_Page_130.txt
fb6ec0b0a1013975872d2addff024125
8dbc5a68dd81929f5fd965896aff62c141f2eb4e
44267 F20101111_AABYLV wyman_m_Page_005.jp2
35cf6700a1d65550fba55411ff477d2d
beaa85580e6cab90b67e52e6014f10ff4c471473
F20101111_AABYMK wyman_m_Page_024.tif
eeeb450c536ebfa60601bf9cb3870ce6
f4a9807f07c5917ff75f6beb89fb9dc7b8aa94a0
1964 F20101111_AABYLW wyman_m_Page_103.txt
6c60f643e2ad31be37ca9cc3e10019db
e968421e6891d83493c93fcd99a227fe0533ec7c
55293 F20101111_AABYML wyman_m_Page_075.pro
5214e23ab133121a143a0230f3d55f13
811bde421bc832d84711210a9c76d7ddefe1ac3e
F20101111_AABYLX wyman_m_Page_018.tif
646e5d72c2bb52bf5c3d220e8d845b0e
5fbff621d75aab45597577042fe40cceed63f862
F20101111_AABYNA wyman_m_Page_149.txt
bac58afb1b840af2a2fcafd6c6577fce
feba5251e90858ac4984ebc921ac5e66e3e0dca4
114339 F20101111_AABYMM wyman_m_Page_032.jpg
3dc707662b8ceada6dff8e82cad1c4f6
0ac22a2917174a9a00ddf643abebfe580a4ab9d8
58891 F20101111_AABYNB wyman_m_Page_143.pro
00c25c8c1a3c9bf171348724f677e764
ee80012434e923fb539219bf7c9cf9555bbc83e0
139090 F20101111_AABYMN wyman_m_Page_136.jpg
aaab0bd7185cf7f20a3e85c611a559d9
46b1a34fc8668d44c93b68050b4fafb0862ed389
37829 F20101111_AABYLY wyman_m_Page_032.QC.jpg
6d455cd29c9a468f291b20dfcdf4668a
d7c8cd2de6857206f9b3fa6a0a23364761c893b2
52086 F20101111_AABYNC wyman_m_Page_057.pro
5813f385a4a94b927f212759b643ca0d
e3c60eeb3ed38c089bf632f2fbed4378921401c7
71024 F20101111_AABYMO wyman_m_Page_121.jpg
d8a46ad9daf2c463f6bda86a519b28b4
6dacdc27e9f5dace460ffd83ccd7e1651d86400f
108040 F20101111_AABYLZ wyman_m_Page_018.jpg
da75a4e71999f4bdfa392efa821befb3
fef0e1152ed2386debdc0eeee6096a29d6f4c040
F20101111_AABYND wyman_m_Page_141.tif
3a3a1e08765ca8d69ae0ae2b7533ccd4
8bbedf2fcfac43c0f9bd2027e2d18ae4a54dba68
116236 F20101111_AABYMP wyman_m_Page_108.jp2
46ad7bf0977f845d063e93adc62ecb9a
eee0eb7ce9d7ccc45b025a70ca58a25c9e3bdfdb
28164 F20101111_AABYNE wyman_m_Page_091.QC.jpg
392d9acb7ce4c11cd7ffac9b5fdf3d09
5a4de12346d47f91edca60ddfbec91cb4b36d730
38670 F20101111_AABYMQ wyman_m_Page_130.QC.jpg
a16015c42a4ace3124329edb8eefd26a
31e7cf47d802ae53b8839864140db758bfee2880
514 F20101111_AABYNF wyman_m_Page_090.txt
a1638880b20537b2a30642e7bc1e3356
4c6479257653f127296c4f346216cf7039b40062
F20101111_AABYMR wyman_m_Page_150.jp2
975a0c7c1a280299263c3fc1612aa8bb
7c80b1983dd9ffc58994e472b5d1bb2d1e5173bc
137132 F20101111_AABYNG wyman_m_Page_138.jpg
a80a1de82f36d6b51c560cbbd6eb9718
4d01c52646df81cff6bf8201ed787dd4758775b9
56094 F20101111_AABYMS wyman_m_Page_031.pro
ad29cd146e3e26262ce649eef86bbd7f
f107b93bf05f61d4df7c2c09cf43400592de9e5a
2959 F20101111_AABYNH wyman_m_Page_145.txt
f417b5becf65c8e0ee820e8bb5c79a6a
edb07833764dd8f124840fcd4687de9be50065e2
814 F20101111_AABYMT wyman_m_Page_047.txt
49e4021764fcbeffb381e0ed423bc9af
122d07aa30b0ea848eaf3ac954ea4e8b43dbe940
114644 F20101111_AABYNI wyman_m_Page_029.jp2
4426daf9249eaf181a6cf3be9d941cee
6ed5e09cdc037c6a0fb1fdc7fc5beb4bbb5ef1d4
8909 F20101111_AABYMU wyman_m_Page_001.QC.jpg
bda6c6cdbd109dba92e9af714a228a0f
7a53b262e73f0a96838d5f519640873553209aca
1998 F20101111_AABYNJ wyman_m_Page_126.txt
023929a52f68f1bfbb6ffcf9614b3a5f
2af08875f7efca55f23eb34ff7eac17905025c14
F20101111_AABYMV wyman_m_Page_128.tif
6b6f187d21f42f36427dc6e536b910cd
a8fc54eb92dcad2aa3e2480b999e3ef1c008711d
2609 F20101111_AABYNK wyman_m_Page_091.txt
9af386e4217b6f94c4061f2d6a336b79
35e8f3ac24e61939e7e2868c0e151388177c04e9
20494 F20101111_AABYMW wyman_m_Page_048.QC.jpg
87ce52407e51f6d01951d48a4b77723c
95a6434789e9b39c46a227cd9948264e52512e5f
64983 F20101111_AABYNL wyman_m_Page_139.pro
c31b7411dee5571efc91d28073d95688
049657eff37f5f3d75156293e0abba9b8ac6ee51
34424 F20101111_AABYMX wyman_m_Page_028.QC.jpg
b06b69ed2e046982833c7805b83c117a
c043d423f6a387fee9caf415fc418e8c010da15d
15282 F20101111_AABYNM wyman_m_Page_122.pro
cb97774b139093d93fc85880c54a9d31
b0f4c84d6a428c1914faf92b42ed7e764c1e99ae
F20101111_AABYMY wyman_m_Page_083.tif
b6aa754bb1263be0b3a1131943ea3732
a052908eb5f7a96289d88ca1e6a4d046390f89e5
552 F20101111_AABYOA wyman_m_Page_002thm.jpg
614b521554c7cf12ea91a7b5ff072735
4b51cf869d758a2f7af3786cbae309b7a079f745
19262 F20101111_AABYNN wyman_m_Page_120.QC.jpg
bac1aaff6f9e82595a7dc8935f51cf68
b777a5261f8862dfda391c0bdfa20f65345d2a90
55261 F20101111_AABYOB wyman_m_Page_062.pro
25c97c90f47d72d35e0fb4ffd86b4bdb
4476740a8c1b45e7e81d0eed76dc778889ad091f
F20101111_AABYNO wyman_m_Page_152.tif
89dfdb9123b4ac9a0aa7dde48473750a
2fd0dde1be4472ba5d95a0e1c51b1457fc8bf20f
F20101111_AABYMZ wyman_m_Page_092.tif
8e5431834040737424f9d73e5d891274
0ea12396865c4e4c4ffe01b0863ddc37c50b0e04
19158 F20101111_AABYOC wyman_m_Page_085.pro
e94726ae7dfa79cf8a8b4afd5a0c8fd1
1925b5fabf37874506d3c6014728c5c7dbd4ffa4







CONSERVATION INITIATIVES, COMMUNITY PERCEPTIONS, AND FOREST COVER
CHANGE: A STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE




















By

MIRIAM SARAH WYMAN


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2008


































2008 Miriam Sarah Wyman


































To the residents of the Community Baboon Sanctuary, Belize









ACKNOWLEDGMENTS

I want to thank the people in Belize who made my stay there so enjoyable: my host

families (Ms. Matilda Banner, Mr. Robert and Ms. Alma Hendy and family, Mr. Ruben and Mrs.

Dorla Rhaburn, Mr. Elston Wade, and Ms. Olive Thompson). I also want to thank Ms. Jessie

Young and the Women's Conservation Group for their support with conducting this research.

Additionally, thanks go to Aaron and Rachel Wagner (Peace Corps volunteers) for all their

logistical support and to my research assistants, Sharon Hazel and Mandy Bailey, who were

instrumental in helping me conduct interviews. Thanks also to the Belize Forest Department for

their support of this research. Lastly, I want to also thank Dr. Robert Horwich and Dr. Gail Lash

for their information and advice on my many questions.

I want to first thank my supervisory committee (David Bray, Martha Monroe, Brian Child,

and Jane Southworth and especially my chair, Taylor Stein) for their patience, time, and

mentoring.

I owe much to my friends at the Land Use and Environmental Change Institute (LUECI)

lab at the University of Florida: Lin Cassidy, Forrest Stevens, Natalia Hoyos, Hector Castafieda,

and Matt Marsik. It is also to my friends who kept me sane from ultimate frisbee, to running out

at San Falasco, to craft days: Yael Gichon, Katy Garland, Deb Wojick, Katie Painter, Gaby

Stocks, Amy Duchelle, Dave Buck, Ellie Harrison-Buck, Dave Wilsey, John Engles, Christine

Archer Engles, Cara Rockwell, Chris Barloto, Mandy Bailey, Lisa Seales, Maria DiGiano, and

many more I'm sure I am forgetting.

I also want to thank my family for all their support and for their influence that certainly

played a strong role of who I am today. To my father who fostered a love of nature and the

outdoors and to my mother who showed me a love of languages and traveling. You both have









encouraged me to follow my dreams. I thank my sister Ruth and brother Dan for always being a

phone call away whenever I needed to talk.

I thank my husband and best friend, Matthew Catalano, who has always been an incredible

source of emotional strength and support. As we finish this chapter of our lives together, I look

forward to many more wonderful and exciting adventures with you.

Last, but not least, I thank my sister-in-law and close friend Jenny Keller, who left this

world much too soon. You were always an inspiration to me. It is in large part because of you

that I pursued an advanced degree, and the memory of your passion for change and positive

attitude still encourages me during challenging times today.









TABLE OF CONTENTS

page

A CK N O W LED G M EN T S ................................................................. ........... ............. .....

L IST O F T A B L E S ........................................................................................... ........................... 8

LIST OF FIGURES .................................. .. ..... ..... ................. .9

A B S T R A C T ......... ....................... ............................................................ 10

CHAPTER

1 IN TRODU CTION ....................................... ..... ............................. 12

Stu dy O v erview .................................13.............................
C om m unity B enefits.................. ................................. ............... ...... ...... 14
Place-B asked M eanings..................................... ...................................... ...... .... 15
L and U se L and C over C change ............................................................. .....................16
Research Statement.......... ................. .. .... .... ..................17
Im portance of the Stu dy ............................................................. .......................................19

2 COMMUNITY BENEFITS, PLACE-BASED MEANINGS, AND CONSERVATION:
A STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE.........................20

Introduction .............. ....... ........... ......... ....................... .......................20
The Role of Benefits in Conservation .................... ............................................ 23
Theoretical Framework: The Place Attachment Framework .......................................24
Study O objectives ................ ....... ............................. ...........................25
M eth o d s ............................................................................................. 2 6
S tu d y S ite .............................................................................. 2 6
Data Collection .............. ...... .. ............ ........ ... ............... .......... 32
R results ............ .. ........................ ........................... 34
D iscu ssion and Im plications ......... ..... ............ ................. ............................ ....................37
Pledging ............ ........................... ........ .........................38
Tourism ............... ...... ............. ............. ...............39
L im stations ......... ....... .......... .................... ............................42
C o n clu sio n ............. ..... ............ ................. ........................................4 3

3 INTEGRATING SOCIAL AND LAND-USE/LAND-COVER CHANGE DATA TO
ASSESS DRIVERS OF DEFORESTATION: a STUDY OF THE COMMUNITY
BABOON SANCTUARY, bELIZE ........................................ ................... 53

In tro d u c tio n ....................................................................................................................... 5 3
M eth o d s ........... ..................................................................... 56
LULCC in Belize .................. .. .... ........ ....... ...........56
S tu d y S ite .......................................................5 7









H household Surveys ................................... ..................... .. ............ 58
R em ote Sensing ................. .......... ........................... ........................... 60
Spatial Regression Models of Deforestation ...................................................64
R results ............. ... ..... .. ............... ..................... ............... 66
C B S L and-C over T rends ....................................................................... ....................66
River Buffer Trends ......... .... .. .... .... .... ...... ............... .. .. ..... 67
D rivers of D deforestation ......... ................. ........................................ ..........................68
M odel 1 (1989 1994) ........ .................................... ........ ..................... 68
M odel 2 (1994 2000) ........ .................................... ........ ..................... 69
M odel 3 (2000 2004) ........ ..... ........................ ......... ..... .. ..................... 69
M odel V alidation ......... ............................................................................ .. ..... ....... 7 1
D iscu ssio n .....................................................................7 3
D rivers of D deforestation ............. .......................................................................... 73
L im stations ......... ....... .......... .................... ............................77
C o n clu sio n ............. ..... ............ ................. ........................................7 8

4 FOREST FRAGMENTATION AND HABITAT CONSERVATION FOR THE
BLACK HOWLER MONKEY: A STUDY WITHIN THE COMMUNITY BABOON
SA N C T U A R Y B E L IZ E ......... ..... .......... ........................................................................96

Primate Populations ................. ... ........ ......... ............................. 98
B elize F forests ......................... ...... ............ .................................... ............................10 1
S tu d y O bjectiv e s ...................... .. ............. .. .....................................................10 1
M eth o d s .............. ..... ..............................................................10 3
S tu d y S ite .................................... ... ...... ... ...................................1 0 3
The Community Baboon Sanctuary Howler Populations ...........................................104
Remote Sensing ............................................... .................. 105
Landscape M etrics ............................................... .................. 107
Results ...... ............ .................. ........... .......... 109
Landscape Fragmentation.................. .................109
D iscu ssio n ..................... ......................................................... 1 10
Current Suitable H ow ler H habitat ........................................................... 111
Howler Populations ..................................... ............ ............112
L im itatio n s ...................... .. ............. .. ......................................................1 14
C on clu sion ...................... .. ............................................................................ 1 15

5 C O N C L U S IO N ............................................................................................................... 12 3

Perceived Benefits and Place-Based Meanings of Riparian Forest Landscapes ............... 123
Relative Influence of Factors on Deforestation Probability ..................................... 124
Forest H habitat Fragm entation ............................................................125
C o n clu sio n ......... .... ................................................. ...........................12 6

L IST O F R E FE R E N C E S ............. ..... ............ .............................................................128

BIOGRAPHICAL SKETCH ........................................................................... ......... ..................152









LIST OF TABLES

Table page

2-1 Reported Household Income from the 45 households receiving remittances....................48

2-2 CBS tourism participation and financial income by village...........................................48

2-3 Results from nominal group meeting and first-round interviews ....................................49

2-4 Survey sample ....................................................... ............... ........... 50

2-5 Community Benefits (Importance) M eans................................... .......................... 50

2-6 Community Benefits (Attainment) M eans ........................... ........................ ............. 51

2-7 Place Attachment of Riparian Forests M eans..............................................................52

3-1 Preceding year/month precipitation information of the CBS area..............................91

3-2 Accuracy Assessment of 2004 Landsat ETM+ image..................................................91

3-3 Change Detection Analysis of the CBS landscape..................................................92

3-4 Change Detection Analysis of a 120 meter river buffer ..............................................92

3-5 Deforestation probability on household land parcels Model 1 (1989 to 1994). ...............93

3-6 Deforestation probability on household land parcels Model 2 (1994 to 2000) ..............93

3-7 Deforestation probability on household land parcels Model 3 (2000 to 2004). ...............94

3-8 Prediction results for binary logit m odels..................................... ......................... 95

4-1 CBS black howler monkey population and population density estimates.......................120

4-2 Area (ha) and percent land cover of CBS forested and non-forested landscapes in
1989 and 2004 ..................................... .................. .............. ........... 120

4-3 Area (ha) and percent land cover of forested and non-forested CBS 500 meter river
buffer landscape in 1989 and 2004 ....................................................................... .... 120

4-4 Forest Patch Level Analysis of the CBS landscape and 500 meter river buffer .............121

4-5 Class Level Analysis of the CBS landscape and 500 meter river buffer........................121

4-6 Suitable how ler habitat. ......................................................................... .................... 122









LIST OF FIGURES


Figure page

2-1 Map of the Community Baboon Sanctuary and Belize River Valley area ...................46

2-2 Tourist Figures to the Community Baboon Sanctuary, Belize. .......................................46

2-3 Households involved in tourism by village.. ........................................ ............... 47

3-1 Map of the Community Baboon Sanctuary, Belize .........................................................80

3-2 CBS parcel map of study location .................................. .....................................81

3-3 Land-cover change trends for CBS....................................................... ............... 82

3-4 Change detection analysis for 120 meter river buffer......................................................83

3-5 Probability of deforestation as a function of distance..................................................84

3-6 Probability of deforestation as a function of cattle. ................................ .................84

3-7 Probability of deforestation as a function of agriculture. .............................................85

3-8 Probability of deforestation as a function of education of household head and family
siz e .. ......................................................... .....................................8 5

3-9 Probability of deforestation as a function of tenure and remittances ..............................86

3-10 Probability of deforestation as a function of conservation initiative...............................86

3-11 Probability of deforestation as a function of outside (CBS) work and pasture. ................87

3-11 Predicted versus observed pixel deforestation / stable forest for 1989-94 (Model 1). ......88

3-12 Predicted versus observed pixel deforestation / stable forest for 1994 2000
(M odel 2) ................................................................................. 89

3-13 Predicted versus observed pixel deforestation / stable forest for 2000 2004 (Model
3) ............................................................ ......................................90

4-1 Map of the Community Baboon Sanctuary in Belize.................................................117

4-2 CBS forested and non-forested landscape. .............................................. ............... 118

4-3 CBS 500 meter river buffer landscape............ .................. ......... ............... 119









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

CONSERVATION INITIATIVES, COMMUNITY PERCEPTIONS, AND FOREST COVER
CHANGE: A STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE

By

Miriam Sarah Wyman

December 2008

Chair: Taylor Stein
Major: Forest Resources and Conservation

The Community Baboon Sanctuary (CBS), Belize, an IUCN Category IV protected area,

was established in 1985 to protect forest habitat for the black howler monkey (Alouattapigra).

Nature-based tourism and a pledge were created to promote conservation. This study assessed

conservation from three perspectives: 1) the landowner (place-based meanings and benefit

perceptions attributed to riparian forests), 2) the landscape (social and land-use/land-cover

change analyses to assess deforestation drivers), and 3) howler habitat (forest cover change and

fragmentation). Methods incorporated household interviews and remote sensing to conduct

change detection analyses, landscape metric analyses and modeling using Landsat satellite

imagery from 1989, 1994, 2000, and 2004. Results show 1) a significant relationship between

initiative involvement and higher perceived benefits (importance) and place attachment towards

riparian forests and conservation; 2) involvement in tourism and pledging together decreased

deforestation probability, with other influential variables including road and river distance,

tenure, cattle, agriculture, and education level; and 3) a 23% forest cover loss between 1989 and

2004 and increased forest fragmentation. However, high connectivity exists between most forest

patches and indicates dispersal potential has not been jeopardized. Additionally, howler

populations have increased dramatically in the last 20 years.









CBS conservation may be more complex than simply saving forests and, therefore saving

howlers, as increased fragmentation actually provides better habitat forficus spp. (e.g., figs), the

preferred food source. Under IUCN Category IV designation, one could argue conservation

success, as documented by howler population increases. However, if the conservation objective

is forest preservation, the 23% forest cover decrease would signal conservation failure. This

indicates the CBS should not be managed for a single outcome (e.g., howlers). As deforestation

is tied to livelihoods, the two initiatives should be closer examined.

On one level these initiatives are a strong basis for conservation. However, benefit and

participation inequality exit. Additionally, other variables are more influential deforestation

drivers. Therefore, without addressing these discrepancies, this foundation is not enough to

compete with the important economic opportunities forests provide and reiterates the lesson that

the success of any conservation initiative must be linked to local communities benefiting from

their conservation of biodiversity.









CHAPTER 1
INTRODUCTION

The overall focus of this dissertation examines conservation within the Community

Baboon Sanctuary (CBS), Belize from three different perspectives: 1) human perceptions and

values (e.g., focusing on perceived benefits and place-based meanings of riparian forest

landscapes); 2) land cover change (e.g., focusing on the influence of these initiatives on

deforestation probabilities, in addition to other locational and socio-economic variables); and 3)

black howler monkey habitat (e.g., focusing on forest fragmentation based on howler habitat

criteria). The research is presented as three separate papers, presented in publication style for

submission to academic journals. Therefore, each paper is a stand-alone document, addressing

different aspects of the research statement described below. The first paper, "Examining the

linkages between community benefits, place-based meanings, and conservation program

involvement: A study of the Community Baboon Sanctuary, Belize" expands on sense of place

and place attachment conceptualizations as an incentive to conserving forests, in addition to the

role these conservation initiatives play in managing community benefits. The second paper,

"Integrating social and land-use/land-cover data to assess drivers of deforestation: A study of the

Community Baboon Sanctuary, Belize" integrates remote sensing and spatial modeling to

quantify and analyze the relative influence of tourism and the pledge, along with locational and

socio-economic variables, as drivers of deforestation within the CBS over a 15 year time period

(1989-2004), using information from 33 landowners. The third paper, "Forest fragmentation and

habitat conservation for the black howler monkey: A study within the Community Baboon

Sanctuary, Belize" assesses the performance of conservation within the CBS as an IUCN

Category IV protected area by examining changes in forest cover and forest fragmentation within









the CBS over a 15 year time period (1989-2004) from the perspective of suitable habitat for the

black howler monkey, the impetus for the creation of the CBS, based on habitat criteria.

Study Overview

A response to deforestation worldwide has been the creation of protected areas for fragile

natural and cultural resources (Primack et al. 1998; Brandon et al. 1998; Bates and Rudel 2000;

Langholz 2002). Nearly 35% of Belize has been designated some type of protected area status

(Primack et al. 1998). However, designation alone is insufficient. Many protected areas are, in

reality, "paper reserves" and "paper parks" (e.g., only protected on paper), which have resulted

in land conflicts and continued extractive uses of the forest now deemed illegal. This inability to

manage and police protected areas, coupled with an environmental justice narrative, has called

attention to the needs of local people living within and around these areas with schemes for

community management of natural resources advancing as an alternative option (Alcom 1993;

Primack et al. 1998). Many researchers and conservation practitioners posit that conservation of

tropical forests is more effective and efficient at small-scale and local-level regimes and that, in

certain circumstances, and under an emerging set of institutional conditions, local communities

are the most effective managers of local natural resources because of their dependence, contact,

and subsequent knowledge of local resources (Lepp and Holland 2006; Agawal and Gibson

1999; Tisdell 1995).

In conjunction with conservation, community-based conservation initiatives are

increasingly developing revenue-generating activities, using market incentives to promote

conservation (Tisdell 1995; PfB 2000; Wunder 2000; Langholz and Brandon 2001; Murphree

2003). Many criticize, however, that economic incentives alone may not be the only factors

involved in impacting land-use decisions, and there is not necessarily a connection between

economic income and pro-environmental behavior (Funder 1995; Wunder 2000; Salafsky et al.









2001; Stem et al. 2003). Even where economic factors have a strong influence on people's

behaviors, it is often associated with social, infrastructural, and psychological factors, as seen in

the following examples: Salafsky et al. (2001) found that the projects that generated the most

community support for conservation were those that provided non-cash benefits. In addition, a

study by Funder (1995) on the impacts of the Campfire program on two communities in

Zimbabwe found that women's evaluation of income-generating projects focused more on the

provided services than on the revenues generated. Such findings suggest that other types of

benefits must be considered in communal approaches to management and conservation. It is

through the extension of conservation's benefits, argues Hulme and Murphree (1999), that

attitudes towards conservation will be improved that, ultimately, will foster pro-conservation

behavior.

Community Benefits

Research does not often examine both the economic and non-economic benefits

potentially associated with protected areas in developing countries. Research in the U.S.,

Canada, New Zealand, and Australia that has examined these potential benefits shows improved

and more efficient planning of natural areas that directly involves the community (Driver 1996;

Moore and Driver 2005). Research is needed in developing countries where community-based

conservation is often targeted as a solution for protecting natural areas.

It is by focusing on both intangible and tangible benefits from conservation that

management plans will better respond to local resident needs (Stein et al. 1999; Davenport and

Anderson 2005). For example, a Hulme and Murphree (1999) study on the Kuenene region of

Namibia show that the intrinsic values (e.g., benefits) of wildlife and the importance of passing

them on to future generations plays an important role in wildlife conservation. Also, a study by

Stein et al. (1999) identifying how two state parks in northern Minnesota benefit rural









communities showed that attracting tourism dollars to surrounding communities was just one of

a variety of benefits of conservation community stakeholders felt were important. In fact,

benefits such as pride were considered more important than economic benefits for stakeholders

of one state park.

Place-Based Meanings

Although understanding local residents' perceived benefits of natural areas and

conservation will better enable management to respond to local resident needs, research that

examines the specific benefits residents attain from nature might not address the relationship of

people's attachments to specific areas. The emerging research on place-based meanings

provides an opportunity to more thoroughly explore locals' relationships with natural areas. One

framework for addressing place-based meanings to natural areas is with the place attachment

framework.

Following the expansion of protected areas worldwide and an interest in understanding

the relationships between protected areas and local people and the social outcomes of

conservation, the application of place attachment is now expanding internationally (Kaltenborn

et al., 1999; Kappelle 2001; Leppens 2005; McCleave et al. 2006) and is accepted as a relevant

theoretical framework to understanding these relationships between local people and protected

areas (Zube and Busch 1990; Williams et al. 1992; Brandenburg and Carroll 1995). Protected

area managers are recognizing that the successful management of parks and protected areas must

consider socio-cultural issues along with nature conservation (Stankey 1989). For example,

following national park expansion in southern Norway, understanding the complex meanings and

relationships local people develop with their surroundings has become an important management

strategy when addressing contested issues and development planning (Kaltenborn et al. 1999).

Furthermore, the importance of considering people-park relationships has been emphasized in









several international environmental summits, such as the Durban Accord developed at the Fifth

World Parks Congress in 2003, where input and involvement from locals within and around

protected areas was stressed to ensure their needs and interests are considered when management

decisions are made (IUCN World Commission on Protected Areas 2003).

Land Use Land Cover Change

In addition to understanding the relationships between protected areas and local people,

land-use / land-cover change (LULCC) studies are an important component in examining

community-based initiatives for forest conservation. Change dynamics of land-cover (i.e., the

biophysical attributes of the land surface) and land-use (i.e., the anthropogenic influences on the

land) are considered one of the main driving forces of global environmental change and its

research is considered fundamental to sustainable development efforts (Meyer and Turner 1992;

NRC 1998; Lambin et al. 2000; Geist and Lambin 2002). Within the umbrella of LULCC

research, the need to understand the relationships between cleared and forested landscape

patterns and agricultural land use dynamics within tropical forests has been stressed (Lambin et

al. 2000; Mertens et al. 2000; Geoghegan et al. 2001; Klepeis 2003; Garcia-Barrios and

Gonzalez-Espinosa 2004). As trends in Belize show agricultural intensification replacing

forested landscapes and forests becoming more important in creating connectivity between

smaller, fragmented, isolated habitat patches (PfB 2000), LULCC research within the CBS has

an important role.

Remote sensing data provide information on the differences in land cover characteristics

on spatial and temporal levels and has been used on a wide range of analyses, one of which is

forest change detection (Fernside 1986; Vogelmann and Rock 1988; Skole and Tucker 1993;

Sader et al. 1994; Jha and Unni 1994; Foody et al. 1996; Di Fiore 2002; Southworth et al. 2004).

Remote sensing has also been used extensively with ethnographic methods, from household









surveys to socio-economic data, to better understand the drivers of land-use change (Guyer and

Lambin 1993; Sussman et al. 1994; Mertens et al. 2000; Sader et al. 2001; Hayes et al. 2002;

Southworth et al. 2002; Schweik and Thomas 2002; Bray et al. 2003; Dalle et al. 2006). The use

of remote sensing data to measure forest cover change after implementation of community-based

conservation initiatives has also demonstrated an objective way to evaluate the long-term

effectiveness of these initiatives (Dalle et al. 2006).

Research Statement

The Community Baboon Sanctuary (CBS), the focus of this study, is not community-

based conservation as commonly discussed in the literature. In most cases, the concept of

community-based conservation focuses on government-owned protected areas (e.g., National

Park) with people living outside its borders. In contrast, the CBS consists of private landowners

who have voluntarily pledged to set aside their land and to manage it in a particular way that

increases its conservation value by creating an inter-connected habitat within a large landscape.

Despite the fact that the CBS has existed since 1985, little monitoring has been conducted

to assess the effectiveness of the conservation initiatives in promoting conservation and deterring

deforestation. Also, research has not explained the potential influence of other factors (e.g.,

locational and socio-economic variables); the level of deforestation and forest fragmentation that

has occurred (specifically riparian forest cover, considered critical habitat for the black howler

monkey); or residents' perceived benefits and place-based meanings of riparian forest landscapes

as an incentive to conservation (the initial habitat focus of conservation within the CBS). This

dissertation hopes to address these issues through a holistic overview of conservation within the

CBS to more effectively base future management decisions and contribute to a better

understanding of community-based initiatives for forest conservation.

Objective 1: Assess perceived benefits and place-based meanings of riparian forest landscapes,









Objective 2: Assess the relative influence of tourism and pledging on deforestation probabilities,

in addition to other locational and socio-economic variables, and

Objective 3: Assess forest fragmentation for the black howler monkey based on habitat criteria

Chapter 2 addressed the first objective and expanded on sense of place and place

attachment conceptualizations by applying a framework within a less developed country (Belize)

that has only been employed in the US and a few other more developed countries (e.g.,

Australia). The objectives of this paper are to identify the importance and attainment of

community benefits from riparian forest landscapes (the focus of the conservation initiatives),

measure CBS residents' attachment to riparian forests, and understand if involvement in the two

conservation programs (nature-based tourism or pledging) is related to residents' perceptions of

community benefit importance, community benefit attainment, and attachment to riparian

forests.

Chapter 3 addressed the second objective conducted parcel-level spatial models (binary

logit models) to assess the relative influence of the two conservation initiatives (nature-based

tourism and pledging) on deforestation probability. In addition, this paper evaluates the relative

influence of other variables locationall and socio-economic) driving deforestation within the

CBS, using information from thirty-three landowners and their parcels over a 15 year time period

and 4 satellite image dates. Overall land cover change trends within the CBS, as well as along a

120 meter river buffer within and outside the CBS are also assessed.

Chapter 4 addressed the third objective examined changes in forest habitat for the black

howler monkey (the impetus for the establishment of the CBS). Using remote sensing of satellite

imagery and landscape metrics, this study reviews the performance of the CBS as an IUCN

Category IV protected area by assessing changes in forest cover and forest fragmentation within









the CBS and 500 meter river buffer over a 15 year period (1989-2004) and how this has

impacted habitat for the black howler monkey, based on specific habitat criteria.

Importance of the Study

Combined, these papers provide an overview of conservation and the effectiveness of two

conservation initiatives (nature-based tourism and pledging) in deterring deforestation and

promoting conservation within the CBS. This study takes into account human perceived benefits

and place-based meanings, potential drivers of deforestation, and fragmentation of howler

monkey habitat. It is through this triangulation of social and spatial data, from understanding the

human perspective, to forest cover change, to howler habitat fragmentation, that conservation

assessment and future management decisions can be more effectively made. It is also hoped that

the methods employed will encourage others to also examine conservation initiatives from

different perspectives to provide a more thorough and accurate assessment of the effectiveness of

conservation. It is from here that more appropriate decision-making can be made to improve the

role conservation initiatives play in not only meeting conservation goals, but also in managing

for community benefits, considering community-based conservation is often argued, in some

circles, to be the solution for protecting natural areas.









CHAPTER 2
COMMUNITY BENEFITS, PLACE-BASED MEANINGS, AND CONSERVATION: A
STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE

Introduction

A response to deforestation worldwide has been the creation of protected areas for fragile

natural and cultural resources (Brandon et al. 1998; Langholz 2002; West et al. 2006). There has

been a dramatic increase in the area falling under protected status within the past 25 years with

current figures indicating over 100,000 protected areas worldwide, covering 11.5% of the

world's land surface (17.1 million km2) (IUCN 2004; West et al. 2006). Defined as "an area of

land and/or sea especially dedicated to the protection and maintenance of biological diversity,

and of natural and associated cultural resources, and managed through legal or other effective

means" (IUCN 2003), 84.5% of the world's protected areas (under IUCN categories) are open to

human use at some level (Naughton-Treves 2005).

Designation alone is insufficient. Many protected areas are, in reality, "paper reserves"

and "paper parks" (i.e. only protected on paper) which have resulted in land conflicts and

continued extractive uses of the forest now deemed illegal. This inability to manage and police

protected areas, coupled with an environmental justice narrative, has focused attention on the

role of local communities and the decentralization of resource management and conservation,

with schemes for community management of natural resources advancing as an alternative

option (Agrawal and Gibson 1999; Gibson et al. 2002; Schmink 2003). Those in support of

community-based conservation posit that the conservation of tropical forests is more effective

and efficient at small-scale and local-level regimes and that, in certain circumstances, and under

an emerging set of institutional conditions, local communities are the most effective managers of

local natural resources because of their dependence, contact, and subsequent knowledge of local

resources (Tisdell 1995; Agrawal and Gibson 1999; Lepp and Holland 2006).









It is worth noting, however, that the conservation community is divided on its support of

protected areas as they relate to the coexistence of land use to improve livelihoods and

biodiversity conservation to protect ecosystem services (Brechin et al 2002; Adams et al. 2004,

DeFries et al. 2004). While one side favors the community-based conservation narrative and

balancing human well-being with nature conservation (Adams and Hulme 2001, Schwartzman et

al. 2000), others argue in favor of 'fortress conservation' claiming that development and

conservation are contrasting goals (Oats 1999; Redford and Sanderson 2000; Terborgh 2000).

The Millennium Ecosystem Assessment (Brown et al. 2005) and World Resources

Institute (2005) recognize livelihood needs and biodiversity conservation as complementary

goals and support the integration of livelihood needs and ecosystem management. Considering

these new protected area directions, some conservationists have changed their approach to meet

these goals through various strategies linking development and conservation, including

integrated conservation development projects (ICDPs) and community-based natural resource

management (Naughton-Treves 2005). Considering forests can provide multiple products and

services, including non-timber forest products (NTFPs) and nature-based tourism, community-

based conservation initiatives are increasingly developing revenue-generating activities, using

market incentives to promote conservation (Tisdell 1995; Wunder 2000; Langholz and Brandon

2001; Murphree 2003).

In conjunction with an increase in protected areas, the number of privately-owned

reserves worldwide is also increasing (Langholz 1996), with those owned or operated by NGOs

or communities increasingly developing nature-based tourism. Reserves with nature-based

tourism have been categorized as 1) communally-managed, by usufruct rights, leased or owned

lands, 2) NGO managed, or 3) owners of contiguous, small-size holdings jointly managing their









lands (Langholz and Brandon 2001). In both private and common property (a form of private

property where members of a recognized group share rights to a resource) examples, nature-

based tourism initiatives within communities can be considered a common pool resource where

benefits from tourists using a resource are shared by the providing community (Healy 1994).

Tourism landscapes, stresses Healy (1994), can have 'common pool problems' characterized by

the susceptibility to overuse or damage a resource and the potential for 'free-riding'. Even where

complex property rights with competing users exist over common pool resources (including

'open access', public and/or private property rights), collective action and rules must be devised

that prevent depletion or degradation of the resource (Healy 1994; Lindberg et al. 1996; Edwards

2004).

Although revenue-generating activities, such as ecotourism, can provide important

financial benefits to communities and aid in conservation goals, financial incentives alone are not

the only factors affecting land-use and resource-use decisions. There is a connection between

financial income and pro-environmental behavior but, equally, many people's behaviors are

driven by non-financial incentives (Wunder 2000; Salafsky et al. 2001; Stem et al. 2003). Even

where income factors have a strong influence on people's behaviors, they are often

complemented by social, infrastructural, and psychological factors, as seen in the following

examples: Salafsky et al. (2001) found that the projects that generated the most community

support for conservation were those that provided non-cash benefits. Furthermore, a study by

Funder (1995) on the impacts of the CAMPFIRE program on two communities in Zimbabwe

found that women's evaluation of income-generating projects focused more on the provided

services than on the revenues generated. Aside from a few case studies, however, there is a lack









of good, empirical data for understanding the social impacts of protected areas and the positive

and negative impacts conservation has on communities (Igoe 2006).

Along this same vein of social impacts, the comparison between potential financial and

non-financial benefits associated with protected areas and conservation in developing countries

is not often examined (Zube and Busch 1990, Salafsky et al. 2001). In the U.S., Canada, New

Zealand, and Australia, a wider view of these potential benefits shows improved and more

efficient planning of natural areas that directly involves the community (Stein 1999; Kappelle

2001; Davenport and Anderson 2005; McCleave et al. 2006). Based on this broad understanding

of conservation incentives, a range of complementary benefits must be considered in communal

approaches to management and conservation. It is through the extension of conservation's

benefits, argues Hulme and Murphree (1999), that attitudes toward conservation will be

improved that, ultimately, will foster pro-conservation behavior.

The Role of Benefits in Conservation

The role of identifying and managing benefits effectively in conservation is a difficult

task. With little research addressing local residents' perceived benefits of protected areas, one

approach taken in this study is to look at the Benefits Based Management (BBM) framework.

Although initially applied to recreation and leisure management, BBM is applicable to the

broader context of amenity resources such as cultural resources, wildlife, wilderness, and scenic

values, which also includes the physical, social, and psychological benefits that individuals,

families, communities, and even societies at large might gain from exposure to these resources

(Driver 1996; Moore and Driver 2005). Considering the purpose of BBM is to assist managers

to better define how their actions will benefit humans or the natural environment, the concept of

BBM is appropriate for my current study to better understand how to best provide community

benefits.









Under the BBM framework, a benefit is defined as "(a) a change in a condition or state

viewed as more desirable than a previous one; (b) maintenance of a desired condition and

thereby prevention of an unwanted condition from occurring, prevention of an undesired

condition from becoming worse, or reduction of the unwanted impacts of an existing undesired

condition; and (c) the realization of a satisfying recreation experience" (Moore and Driver 2005,

p.38). This concept has often been used in research within the human dimensions of natural

resource management (Anderson et al. 2000; Booth et al. 2002).

Of equal importance with providing benefits from conservation, but an often overlooked

part of the process, is the understanding of community benefits attributed to natural areas that

can help ensure that management plans are responsive to local resident needs (Stein 1999;

Davenport and Anderson 2005). For example, research by Jones and Murphree (1999) in the

Kuesene region of Namibia shows that the intrinsic values of wildlife and the importance of

passing them on to future generations play an important role in wildlife conservation. Also, a

study by Stein et al. (1999) on how two state parks in northern Minnesota benefit rural

communities showed that attracting tourism dollars to surrounding communities was just one of

several benefits of conservation community stakeholders felt were important. In fact, benefits

such as pride were considered more important than financial benefits for stakeholders of one

state park.

Theoretical Framework: The Place Attachment Framework

Although understanding local residents' perceived benefits of natural areas and

conservation will better enable management to respond to local resident needs, research that

examines the specific benefits residents attain from nature might not address the relationship of

people's attachments to specific areas. Emerging research on place-based meanings provides an









opportunity to more thoroughly explore locals' relationships with natural areas. One framework

for addressing place-based meanings of natural areas is through the place attachment framework.

Initially coined by Tuan, a human geographer, place attachment applies to places that

gain meaning and definition through the individual experiences that occur within those places

(Tuan 1980). The concept of place attachment has been found in various disciplines including

human geography, psychology, and anthropology with the accepted basic definition as an

emotional bond between people and places (Proshansky et al. 1983; Low 1992; Williams et al.

1992; Cuba and Hummon 1993; Vaske and Kobrin 2001; Williams and Vaske 2003; Kyle et al.

2004; Davenport and Anderson 2005). Research on place attachment has been conducted largely

in the U.S. to examine how natural areas influence how residents feel about their community

(Williams et al. 1992; Eisenhauer et al. 2000) and residents' attitudes toward tourism

development within natural areas (Sheldon and Var 1984; Um and Crompton 1987; McCool and

Martin 1994; Williams et al 1995).

The place attachment framework, when used to understand the links between natural

resource management and these emotional connections to natural landscapes, includes two

constructs: place identity and place dependence (Williams et al. 1992). The constructplace

identity concerns symbolic meanings of place and is based on the notion that places affect the

development of individual and community identity and promotes a sense of "belongingness."

Place dependence, in contrast, reflects more tangible meanings of place that represent an area's

physical characteristics (Stokols and Shumaker 1981; Williams et al. 1992; Williams and Vaske

2003).

Study Objectives

Following the expansion of protected areas worldwide, the application of place

attachment is now expanding internationally, albeit primarily in more developed countries, to









examine the relationships between protected areas and local people, and the social outcomes of

conservation (Zube and Busch 1990; Kaltenborn et al. 1999; Kappelle 2001; Leppens 2005;

McCleave et al. 2006). Considering the increase in protected areas (West et al. 2006) and the rise

in community-based conservation initiatives developing revenue-generating activities to promote

conservation (Tisdell 1995; Wunder 2000; Langholz and Brandon 2001; Murphree 2003),

examining the relationships between protected areas and local residents and the social outcomes

of conservation has an important role; the Community Baboon Sanctuary (CBS) in Belize is one

such example. Objectives of this study were to assess the social impacts of the CBS by

1. Identifying the importance and attainment of community benefits from riparian forests, the
impetus for the creation of the CBS,

2. Measuring CBS residents' attachment to riparian forests, and

3. Assessing if involvement in one or both of the two conservation programs (nature-based
tourism or pledging, described below) is related to residents' perceptions of community
benefit importance, community benefit attainment, and attachment to riparian forests.

Methods

Study Site

The Community Baboon Sanctuary (CBS), Belize (17 33'N, 88 35'W), was established

in 1985 to protect one of the largest remaining populations of black howler monkeys (Alouatta

pigra), locally called "baboons", in Meso-America (Figure 2-1). The CBS is not community-

based conservation as is normally conceived. The concept of community-based conservation

under the IUCN definition is based on communities next to public protected areas. The CBS,

however, is a unique situation with private landowners agreeing to manage their land in a









particular way that would increase its conservation value and create an inter-connected habitat in

a larger landscape.

This effort to create a community baboon sanctuary began when two American scientists

recognized the area for its howler population and the positive attitudes villagers had toward the

howler monkeys. After approval from the villagers and Village Council to investigate the

potential of creating a community-based sanctuary in the area, and with support of a local non-

governmental organization (the Belize Audubon Society), the lands for this sanctuary were set

aside by private landowners from seven Creole communities situated along 33 kilometers of the

Belize River (Horwich and Lyon 1990). For 20 years various residents within the CBS

communities have participated in two conservation strategies: 1) a written, voluntary pledge for

private landowners to leave a strip of riparian forest and forested corridors that provide habitat

connectivity for howler monkey populations and 2) nature-based tourism centered on the howler

monkey that provides financial incentives to landowners protect howler monkey habitat.

Pledge: The private landowners who make up the CBS share a common pool resource for

conservation and nature-based tourism: the howler monkey. Because this resource is mobile,

although tends to remain in close proximity to the Belize River, pledging landowners have

accepted a form of 'conservation easement' on their private property where forested corridors

and their integrity, along with the howler monkey population, depend upon the collective action

by all landowners to observe a set of rules. This collective action has been established in the

form of a voluntary, written, public pledge and landowners are encouraged to sign and agree to

do their part in protecting howler monkey habitat.

The concept of pledging is a form of commitment to a particular conservation practice by

an individual landowner. The idea behind a landowner pledge was that by signing this









voluntary, written pledge, landowners agree to not clear their land along the riverbank and to

leave a forested corridor between property boundaries. River property is highly valued for its

fertility, compared with other soils of the area, which reflects the location of farming in these

areas. Furthermore, those residents with cattle and river property often maintain cattle here so

cattle can easily access water.

Although the pledge was not initially linked with any financial compensation with money

that was collected through tourism, CBS records and research by Lash (2003) indicate that

pledged landowners were paid twice (1998 and 2000 totaling -$250 per landowner) by the CBS

management at the time, but presently no residents are given any financial compensation for

pledging. Because of this initial payment, pledged residents expect to be paid; reality now

associates the pledge with financial compensation.

Nature-based tourism: Nature-based tourism centered around the howler monkey was

initiated with the establishment of the CBS as a way to create a financial incentive for residents

to conserve important forest habitat. Residents involved in tourism obtain both permanent and

seasonal employment, ranging from tour guiding, selling crafts, housing visitors, trail

maintenance, and visitor center/ museum assistance. The CBS tourism headquarters that house

the museum and visitor center are located in Bermudian Landing village. Tourist visitation to the

CBS has dramatically increased in the last few years (Figure 2-2) due, almost exclusively, to the

introduction of cruise ship tourism to Belize. Decreased numbers from 2005, relative to 2004,

reflect that year's active hurricane season that cancelled many cruise ship docks in Belize City

which, subsequently, affected tourism numbers to the CBS.

CBS management: From its inception, management of the CBS (pledging, museum, tour

guides, and education programs) was given to a local resident manager under the guidance of the









Belize Audubon Society (BAS). In 1994, autonomy of CBS management responsibilities (e.g.,

all accounting and marketing, museum, tourism guides, etc.) was given over to a local CBS

committee (Lash 2003).

CBS management has changed at least seven times in its first thirteen years, with various

combinations of the BAS, a local committee, and resident managers in charge (Bruner 1993;

Horwich and Lyon 1998). The only consistencies within the CBS (Lash 2003) are as follows:

1. The body of the CBS comprised of pledged landowners

2. The CBS headquarters (museum) housed within Bermudian Landing village

3. The continued involvement of one specific family within the CBS to some extent (a
member of this family was selected as the first manager of the CBS)

Since 1998, the Women's Conservation Group (WCG), a committee made up of women

representatives from the different CBS villages, has managed the CBS (in 1998 the former

committee was asked to resign). This committee was responsible for one of the two payments to

pledged residents (Lash 2003). Currently the director of the CBS and Women's Conservation

Group, as well as the manager / lead tour guide position are occupied by family members from

one family that has always been involved with the CBS. Another barrier to effective

management of the CBS are the external influences of a negative context (such as drug use) have

a presence within the CBS and have not been appropriately addressed or resolved.

CBS villages: Today there are 222 households within the seven villages of the CBS,

comprising approximately 1500 people (Jones and Horwich 2005). Within the literature, the CBS

is designated as a 4800 ha area (Horwich and Lyon 1990). However, this did not include the full

village boundaries or account for households located on properties away from the river. Because

of this inclusion within my study, the total study area encompassed 8703.54 ha (87.04 km2).









Land tenure is roughly evenly divided between titled and government leased lands (20 year

leases). Despite the difference in dejure property rights, there is little variation between de facto

property rights of the two land tenure regimes; the majority of residents are long-term residents,

many having lived here for generations, and possess high perceived land security.

Ethnic composition is overwhelmingly "Creole" (descendants of British settlers and

African slaves) within the seven villages of the CBS. Although only comprising a few families

each, the other ethnic groups represented within the seven CBS villages include Asian,

Hispanic/Mayan (from Guatemala and Honduras), and Caucasian (US Mennonites). These other

ethnic groups have migrated to the area over the past ten years for various reasons. Those

leaving Guatemala and Honduras were looking for employment and land opportunities; in the

late 1980s, the Chinese population increased dramatically with immigration from Hong Kong

and Taiwan; and US Mennonites are increasing their presence and missionary work in rural parts

of Belize (Merrill 1992).

An interesting duality exists in this area that is located very close to Belize's largest city

but still maintains forest cover and some of the traditional ways of living and income generation.

Information from interviewing residents reveals that although farming and other traditional land

and forest use are less common today with more people choosing to work outside the home and

often outside the villages, residents (young and old) still prefer to live in the "country" and view

living in Belize City as expensive, dirty, and dangerous. The main livelihood activities of the

CBS villages include: employment with nature-based tourism (primarily in the village of

Bermudian Landing); small-scale agriculture; small-scale cattle raising; small-scale coconut oil

and cohune nut oil (Orbignya cohune) production; cashew; and outside wage employment

(primarily in or around Belize City).









There are several households in each village that have over 50 head of cattle but many

residents have a few head of cattle that serve as a bank account in many ways; if someone is sick

or another occasion to need cash presents itself, a cow can immediately be sold. Agriculture is

an important livelihood activity for residents of the CBS, especially for those with river property

where the soils are the more fertile of the area. Slash-and-burn agricultural plots are locally

called "plantations" or "milpas" and primarily are used for home consumption or local sale

(within villages). The villages are located roughly 35 miles from the nearest district market

where agricultural and forest products are sold, including medicinal plants and game meat

(Belize City). The closest market where a good variety of agricultural products are sold is in a

neighboring town en route to Belize City named Burrell Boom (located roughly 15 miles from

the villages). It isn't uncommon for individual residents to simply take their products around

their village and neighboring villages to sell along the roadside or even try to sell these goods

house to house. These products range from agriculture crops, fish and game meat, and cohune

and coconut oil. Collecting cashew seeds and cashew fruit for a few months every year is a

period when local residents can supplement their income. At least one middle man in a

neighboring town (Burrell Boom) purchases the cashew seeds from residents. Although small-

scale, many residents also living in villages with cashew trees collected and roasted nuts for sale

in Belize City and for visiting tourists to the CBS.

Sixty-three percent of the 135 households interviewed for this study have at least one

family member who works outside of the CBS. The 5 year-old paved road that crosses through

four of the seven villages has increased bus service with access to 6 of the 7 villages several

times daily (Monday through Friday) to Belize City in the mornings and returning to the CBS

villages in the evening (approximately a 35 mile / 56 km commute). This has made living in the









CBS villages and working in Belize City very feasible. Another important income source is

remittances. One-third of the interviewed population receive remittances from family members

who have left and live and work in the U.S. From the 135 households interviewed, 45

households reported receiving remittances; together remittances totaled $95,850 BZE (approx

US $ 47,925) over the course of one year, accounting for 28.5% of their total income (wage and

other) (Table 2-1). Additionally, out of the 45 households who received remittances, 11

households reported remittances as the only source of monetary income.

Although the pledge and nature-based tourism have existed for over 20 years within the

CBS (at different levels of activity), little monitoring has been done to assess the effectiveness of

these conservation initiatives. Additionally, little is known about the communities' perceived

benefits of riparian forests and the function of place attachment as an incentive to conserving

forests, in addition to the role that these two conservation initiatives play in managing

community benefits. Considering this, it is worth examining the non-financial benefits and ways

residents perceive riparian forest landscapes, along with the financial benefits that are presumed

to come from tourism and pledging. The significance of assessing both importance and

attainment of community benefits, as well as place-based meanings attributed to riparian forest

landscapes, addresses not only what benefits residents feel are most important, but also how

much they feel these benefits actually improve their livelihoods. This study will aid future

planning and management to determine how to improve the integration of nature-based tourism

and pledging into community development and environmental conservation strategies.

Data Collection

Semi-structured interviews and one focus group meeting were used to initially identify

perceived benefits residents attributed to riparian forests, nature-based tourism, and pledging

(Table 2-3). In total, 135 resident interviews from the 7 villages (61% of the CBS population,









approximately 20 households per village) collected quantitative and qualitative data on perceived

social, environmental, and financial community benefits and residents' place-based meanings

towards riparian forests within the CBS. Initially, a stratified sample was conducted with all

pledged and tourism households. Twenty-six households participating in tourism (out of

approximately 35 total, with 12 households participating only in tourism) and 51 households

participating in the pledge (out of approximately 75 total, with 37 household participating in only

the pledge) agreed to participate in the study. Approximately half of those households involved

in tourism are also pledged households (n = 14). The remainder of the household interviews (n =

58) were composed of randomly selected households (all non-tourism / non-pledged households)

(Table 2-4).

Questions were presented verbally with the head of the household (if the household was

not involved in either tourism or the pledge) or with the individual who was involved with the

pledge or tourism initiative. Interviewees were shown and explained the Likert-type scale with

the value system presented to help residents gauge the strength of the answer (e.g., very

important versus somewhat important), with examples demonstrated for clarity before the

interview process began. Data analyses used SPSS 11.5 to generate descriptive statistics and T-

tests, using Levene's test for equality of variance. The survey consisted of two parts: community

benefits and place attachment of riparian forest landscapes.

Community benefits. One nine-item question on community benefits asked if riparian

forests are providing benefits. Interviewees answered from an Importance category (five-item

Likert-type scale) and an Attainment category (four-item Likert-type scale) developed from

nominal group meetings conducted with residents, and from the established literature (Davenport

and Anderson 2005; Stein et al. 1999).









Place attachment. Place attachment questions consisted of a twelve-item Likert-type

scale adapted from a variety of literature (Williams et al. 1992; and Jorgensen and Stedman

2001; Davenport and Anderson 2005). Based on work by Davenport and Anderson (2005), scale

items fell under the following categories: Place dependence: economic stability, nature and

natural processes and Place Identity: family legacy, community character, and self identity.

Results

The 26 residents interviewed who are participating in tourism estimated their total

tourism earnings to be US $14,005.00 during the year of this study (July 2005 July 2006)

(Table 2-2). Out of the 35 estimated residents known to be participating in tourism over the

course of study (but not all interviewed), the largest amount of residents,13 (37%), were

residents of Bermudian Landing village (the CBS and tourism headquarters) (Figure 2-3). The

village with the second largest number of residents participating in tourism (n = 6) was Double

Head Cabbage, followed by Scotland Half Moon and St. Paul's Bank (both n = 5). The

remaining three villages had 3 or less residents participating in tourism.

Community benefits: Importance (general means). Overall, all benefits of riparian

forest landscapes identified through focus group meetings and past literature were rated

important (all above 3, out of 5) by residents (Table 2-5). "Living in a healthy environment" was

ranked highest for importance (mean = 4.6). Benefits specifically addressing quality of life (e.g.,

"providing a good quality of life") and future generations ("knowing conserved natural resources

exist for future generations") received the second highest importance means (means = 4.2).

"Attracts tourism dollars to my community" was tied for the fourth most important perceived

benefit of riparian forests with "a feeling that your community is a special place to live" (means

=4.1).









Community benefits: Attainment (general means). Respondents believe they are

attaining their most important benefit "living in a healthy environment," giving it the highest

attainment mean (mean = 3.6 out of 4). "Attracts tourism dollars to my community" received the

lowest mean (1.6). Based on this benefit's high importance, results show a disconnect between

respondents' importance and attainment of this benefit (Table 2-6).

Community benefits: Pledging and tourism. From examining the differences between

tourism only (n=12) and non-tourism residents (n=123), tourism residents had slightly higher

means on most perceived importance of riparian forest benefits. Considering statistically

significant differences, those involved in tourism thought riparian forests were more important in

providing "a greater concern for the natural environment" than those not involved in tourism

(mean = 4.1 / 3.7) (Table 2-5). Under perceived attainment of these benefits, "living in a healthy

environment" was ranked the highest, with "attracts tourism dollars to my community" ranked

the lowest for tourism residents. With respect to significant differences, no differences were

found for attainment of these benefits between tourism and non-tourism residents (Table 2-6).

From examining the differences between pledged only (n=37) and non-pledged residents

(n=98), pledged only residents had slightly higher means on conservation-related scale items

under perceived importance of riparian forest benefits. Considering statistically significant

differences, those pledged only residents thought riparian forests were more important in

"knowing conserved natural resources exist for future generations" (Table 2-5).

Under perceived attainment of these benefits, pledged only residents ranked "living in a

healthy environment" as the most perceived attained benefit from riparian forest landscapes

(mean = 3.7), with "attracts tourism dollars to my community" as the lowest (mean = 1.6).

Additionally, pledged only residents' scores were significantly higher than non-pledged residents









for attainment of specific benefits associated with community character and nature and natural

processes ("Knowing conserved natural resources exist for future generations", "Providing a

good quality of life", and "A natural setting in which your community takes great pride") (Table

2-6).

In comparing benefit importance means between those residents involved in both tourism

and pledging (PT) (n=14) and those not involved in either (Non-PT) (n= 121), "attracts tourism

dollars to my community" was ranked the second most important benefit from riparian forest

landscapes for PT residents (mean = 4.4), while ranked fourth for Non-PT residents. "A greater

concern for the natural environment among residents" and "improved care for community

aesthetics" was of statistical significance between PT and Non- PT residents (Table 2-6). In

examining benefit attainment means, "attracts tourism dollars to my community" was the lowest

ranked perceived attained benefit for PT residents, although significantly higher than Non- PT

residents (mean = 2.1 / 1.6).

Place attachment: Tourism. Tourism only residents (n=12) rated items tied to water

quality and habitat for wildlife significantly higher than non-tourism residents (n=123) (Table 2-

7). "These riparian forests are important in providing habitat for wildlife" was ranked highest by

tourism residents (mean = 7.0). The two place attachment scale items ranked the lowest by

tourism only residents were related to economic scale questions: "My community's economy

depends on riparian forests" (mean = 3.8) and "My family's income or livelihood depends on

riparian forests" (mean = 2.8).

Place attachment: Pledging. Those residents who pledged only had significantly higher

means (p < 0.05) on all place attachment scale items, with exception to the two economic items

and "these forests have helped put my community of the map" (Table 2-7). "These riparian









forests are important in providing habitat for wildlife" and "My community's history is strongly

tied to this riparian forest" were ranked highest by pledged only residents (mean = 7.0) followed

by "This riparian forest contributes to the character of my community" as the third highest

ranked item (mean = 6.4). The two economic items, "My community's economy depends on

riparian forests" (mean = 4.0) and "My family's income or livelihood depends on riparian

forests" (mean = 3.0) were ranked the lowest by pledged only residents.

PT residents also ranked these economic questions the lowest (mean = 4.0 and 2.4).

From examining statistical significance, PT residents ranked the following place attachment

scale items significantly higher than Non-PT residents: "This riparian forest contributes to the

character of my community", "These forests have helped put my community on the map",

"Many important family memories are tied to these areas", "This riparian forest is a special place

for my family", and "I feel a sense of pride in my heritage when I am there".

Discussion and Implications

While there are only slight differences between the scores for many of the scale items

under perceived benefits, attained benefits, and place-based meanings between residents

(tourism, pledged, PT, and non-), there are some important differences and results worth noting.

Although CBS residents as a whole perceive that riparian forests are providing conservation and

environmental benefits, riparian forests are not perceived to be providing substantial financial

benefits (including those residents involved in tourism), based on their lowest rankings

acknowledged through place attachment and community benefits questions. In addition, through

statistical analysis, there does appear to be a significant relationship between being involved in a

conservation initiative (pledging or tourism) and placing more importance in certain perceived

benefits and place-based meanings (attachment) towards riparian forests and conservation.









Pledging

Results show residents who pledged only and PT residents have higher perceived benefits

and place-based meanings towards riparian forest landscapes. This indicates that they are likely

more aware of the connections and benefits of riparian forests to conservation and quality of life

issues than non-pledged residents. In fact, pledged only residents had significantly higher place

attachment scores for all dimensions except economic items and one community character scale

item. The benefits pledged only residents believe they are attaining might help explain these

results. They believe they are receiving benefits associated with health, quality of life,

sustainability, and pride to a greater extent than non-pledged residents. These correspond to

place attachment items relating to water quality, history and family ties to the forest, and

personal attachment to the forests.

Another reason for this relationship might be explained through the very act of making a

commitment. Unlike CBS's tourism program, which requires much planning, management, and

coordination among residents, the pledge is a simple process of landowners making a written,

public, and voluntary pledge to manage their property under certain guidelines. Although these

data do not show direct cause and effect relationships, past research on the concept of

commitment is based on the premise that once a pledge is formally made, a bond is strengthened

between the promise and future action (McKenzie-Mohr and Smith 1999). Others propose that

commitment can make one's beliefs more salient (Pallak et al. 1980) and, therefore, less likely to

be ignored when faced with an opportunity to demonstrate that commitment. Some scholars

within the field propose that commitment functions on the feared social disapproval of others

when a public commitment is not made (Wang and Katzev 1990) and the expectation on

ourselves, as well as others who have made a commitment, to honor them completely (Katzev

and Wang 1994). It is not surprising that pledged residents ranked economic scale items low









since reality now associates the pledge with some financial payment resulting from past

payments. The fact that pledged residents are not given any financial compensation for pledging

but are aware tourism is bringing in money (and many are probably aware of its growth), may

explain the low scores on economic scale items.

Tourism

Results show residents involved in tourism only do not perceive tourism to be a major

benefit from riparian forests, nor impact their attachment to riparian forests. CBS residents

involved in tourism only were more likely to rate only three out of the lowest four benefits more

important than residents not involved in tourism ("A place to conserve various natural and

unique ecosystems," "Improved care for community aesthetics," and "A greater concern for the

natural environment among residents"), with only one scale item significantly different ("A

greater concern for the natural environment among residents"). Additionally, tourism only

residents did not significantly differ from non-tourism residents in their perception of attainment

of any benefits.

A surprising result was the lowest ranked scale item for tourism only and PT residents,

considering tourism residents are receiving financial revenue indirectly from these forests.

Under place attachment, "My family's income or livelihood depends on riparian forests" had

mean scores of 2.8 and 2.4. For perceived benefit attainment, "Attracts tourism dollars to my

community" had mean scores of 1.6 and 2.1 (Table 2-2). Nearly 13,000 tourists visited the CBS

in 2005 (Figure 2-2), correlating with the time of this study, yet benefits that would be directly

tied to these visitors (i.e., financial) were not perceived to be attained by tourism residents (nor

non-tourism residents). This may relate to perceived inequality in the distribution of tourism

jobs and money that the management may wish to explore.









Elite capture of benefits is not an uncommon occurrence within development projects

(Bardhan 2002, Platteau 2004) as development projects can set off local political struggles and

rent-seeking opportunities (gaining control of resources) that elites can often easily dominate

(Tai 2007). The concern with conservation initiatives is that the stakeholders who should be

benefiting the most, based on their activities that impact the environment (with expectations that

they will promote conservation in return), are seeing the benefits go to only certain stakeholders,

such as the local political elites (Chan et al. 2007). For example, a study on community-based

ecotourism development in Gales Point, Belize, showed that the majority of people employed

through tourism belonged to only five households (Belsky 2000).

Where tourism shows equity in benefit distribution, conservation successes have been

reported. For example, The Cofan Community Ecotourism Program in Zabalo (Cuyabeno

Reserve), Ecuador, where tourism benefits have been shown to be equitably distributed, has

resulted in the protection of the more rare and attractive wildlife species due to their recognition

as being important for ecotourism (Ceballos-Lascurain 2001). In another example, a nature-

based tourism project to protect wildlife within a Maasai community adjacent to Amboseli

National Park, Kenya also transformed conservation attitudes of the local community (Fitter

1986). Benefits from tourism, such as employment and community development projects from

concession leases, have resulted in no poaching or harassment of wildlife on the whole within the

community-owned lands, in contrast to neighboring areas where bush meat poaching is now

rampant and causing a serious decline in wildlife (Lusigi 1981). In both these cases, the

equitable distribution of tourism benefits transformed attitudes resulting in tangible conservation

outcomes. Additionally, if the financial benefits from tourism are not being equally or fairly

distributed throughout the CBS, then it is not likely that benefits indirectly associated with









nature-based tourism (e.g., "A place to conserve various natural and unique ecosystems" and "A

greater concern for the natural environment among residents") would be attained.

These results show that Bermudian Landing village had the largest number of households

participating in tourism, the same village where the CBS headquarters are located (Figure 2-3).

This demonstrates the spatial distribution of tourism income within the CBS. Distance and travel

time is likely a factor, as being involved with tourism in most situations requires coming to the

CBS visitor center in Bermudian Landing village. In an attempt to benefit communities outside

Bermudian Landing, a Creole Heritage Museum was built in St. Paul's Bank village around 1998

with the help from Program for Belize (PfB), a Belizean non-profit. For about a year PfB

arranged for tourist visits but today this museum is only visited on rare occasions by school

groups, arranged through the CBS. During my study, two residents from St. Paul's Bank earned

some tourism money from a few school visitors, although this was the smallest amount of money

earned by tourism residents during this year of field work. Other residents in St. Paul's Bank

earned tourism money from housing visiting US students. The same situation applies in Flowers

Bank, the most rural and least accessible of the CBS villages, where one family occasionally

houses visitors. Housing visitors is an attractive job, compared to other tourism related jobs, as it

happens infrequently (approximately 7 days per year) and is lucrative. This, too may be an

example of elite capture as families that are better off financially are those with more developed

homes and are, therefore better able to receive visitors. Belsky (2000) found in her study of

community-based ecotourism in Gales Point, Belize that logically, it tends to be the families in a

community that are better off that are chosen to house visitors, as these households have the

sanitation and cooking facilities and additional bedroom space.









Some residents upset over the lack of tourism benefits they are receiving have taken

matters into their own hands and are developing tourism on their own properties (and also

focusing on the howler monkey and experiencing Creole culture). In some cases they are also

siphoning off of tourists driving to the CBS. Four households are trying to promote their own

tourism efforts, at different levels and with varying success. Two are located in Scotland Half

Moon, one in Isabella Bank, and one in Flowers Bank; all households are located on the Belize

River.

Results suggest that tourism and place attachment have a slightly stronger relationship in

the CBS than tourism and perception of benefits, with scale questions showing statistical

significance related to conservation ("These riparian forests are important in providing habitat

for wildlife" and "These riparian forests are important in protecting water quality"). The

explanation for this significance with conservation-related scale items is likely related to the fact

that many of those involved in tourism, especially those employed as a tour guide or clearing

trails, will have a higher tendency than those residents not involved in tourism to spend time in

and around these forest landscapes. Past research has shown that attachment to a place increased

with more frequent visitation, which also fostered an increased perceived familiarity and the

belief that the place was special (Williams and Vaske 2003; Davenport and Anderson 2004).

Considering that the majority of residents interviewed within the CBS have at least one

household member working outside (63%), the majority of residents may not have the leisure

time or necessity to spend time in these landscapes.

Limitations

This study was not without its limitations. I took note of the non-responses in my study,

of which a variety of reasons exist. For example, some residents are American Mennonites who

are a fairly closed group and did not want to participate in my study. However, these residents









are not involved in pledging nor tourism and are not long-time residents of the area. Other

residents were not available for interviews despite repeated attempts to contact them.

Additionally, some residents were working temporarily outside of the CBS during my research.

However, considering I interviewed 26 out of the 35 residents involved in tourism, 51 out of the

75 residents involved in pledging, and a total of 135 out of 222 existing households

(approximately 20 households in each of the 7 villages) demonstrates that I incorporated a good

representative sample of the area.

In addition, applying theoretical frameworks (e.g., place attachment) that were developed

in western cultures to less developed countries may also present some issues. However, there has

been an expansion of protected areas worldwide and an interest in understanding the social

outcomes of conservation. Therefore, it was important to attempt to expand this application

within protected areas in less developed countries where community-based conservation is seen,

in some circles, to be an important component for protecting natural areas.

Conclusion

The concern with some conservation initiatives is that the benefits (and participation) are

not being distributed equally or are not going to the residents who should be the focus of these

initiatives. This appears to be occurring within the CBS where there is a perception of skewed

distribution of both tourism participation and benefits, signaling a potential elite capture of

benefits. Although tourism might impact residents' attitudes, this study shows it must be

managed more effectively and equitably to have any other significant impacts on improving

people's attitudes toward riparian forests or actively helping conserve those forests.

This inequality of benefits can have additional impacts on community-based

conservation. Where community conservation could fail is where the collective action and

involvement with protecting howler monkey habitat is jeopardized. According to Burger et al.









(2001), unless a resource provides some benefit, individuals are not apt to accept the costs

involved in protecting or managing that resource. Benefits from tourism do not appear equitably

distributed, nor are funds going to pledged residents for protecting howler monkey habitat on

their properties, while at the same time the number of tourists are increasing (nearly 13,000 in

2005). Because of these factors, there is probably not much incentive from those not benefiting

from tourism directly or indirectly (e.g., pledging) to participate. This could impact collective

action and involvement with protecting howler monkey habitat.

On another note, this research has revealed some positive points. Although the tourism

and pledging initiatives might be perceived as income-generative failures by respondents, the

people involved in the activities value, benefit from, and feel attached to the forest for a variety

of non-financial reasons. In particular, pledging residents are more highly aware of the non-

financial benefits and feel more attached to riparian forests. Since this study does not indicate

causal patterns, it is not known if the activity helped to instill these attitudes and values, or if

people with these existing attitudes and values were self-selected for pledging. Regardless, this

study shows that involvement in either conservation initiative, whether they are financially

successful or not, is related to higher conservation values and perceived community benefits and

is a strong basis for conservation. Such perceived benefits would not have been realized without

investigating place-based meanings and perceived benefits and demonstrate their important role

in conservation program analysis and planning. As conservation policy discussions today

emphasize the importance of local communities benefiting from their active role in biodiversity

conservation, the findings from this study have implications for local planning and management

by identifying how community residents believe nature-based tourism and pledging provide

incentives and barriers to improving livelihoods and conserving natural resources. It is this type









of information that will aid future planning and management to determine how to improve the

integration of initiatives such as nature-based tourism and pledging into community development

and environmental conservation strategies.
















































Figure 2-1. Map of the Community Baboon Sanctuary and Belize River Valley area (Lash 2003)


18,000-

16,000- # of Tourists

14,000-

12,000-

10,000-

8,000-

6,000-

4,000-

2,000-

0
1995 1997 1999 2001 2003 2005


Figure 2-2. Tourist Figures to the Community Baboon Sanctuary, Belize.































N


Bermudian Lan
s Bermudian Lan




Double Head Cabbage











Willo s Ban



i ** St P Is Bank
*0


Flowers Bank
















,


Scotlar


~"
i;'
ii
d
P
(i
ii
ii
If
ii
ii
ii
ii


id Half


1Kilometers
0 0.5 1 2 3 4
Legend

Belize River
== Village roads
SCBS boundary

Tourism Household


Figure 2-3. Households involved in tourism by village. There are an estimated 35 households

participating in tourism during the course of this study. Although only 26 were

interviewed, the other residents involved were identified.









Table 2-1. Reported Household Income from the 45 households receiving remittances
Type of Income Amount in Amount in Percentage of
BZE $ US $ total income

Wage Income $163,073.00 $81,536.50 48.6%
Remittances $95,850.00 $47,925.00 28.5%
Other non-wage income $76,939.00 $38,469.50 22.9%
Total $335,862.00 $167,931.00



Table 2-2. CBS tourism participation and financial income by village. As reflected in this table,
in Bermudian Landing there are seven more households benefiting from tourism that
declined to be part of this study (out of 135 residents interviewed).
Number of CBS Number of CBS Total tourism Village
Village households households involved income earned in household size
Name involved in tourism in tourism in 2005 1 year (US$) by (during year of
in 2005 (not all interviewed) households per data collection)
(interviewed) village
Willows 3 3 4,410 35
Bank
Isabella 2 2 4,275 23
Bank
Bermudian 6 13 2,325 39
Landing
St Pauls 5 5 950 26
Bank
Double 4 6 910 43
Head
Cabbage
Scotland 5 5 825 32
Half Moon
Flowers 1 1 310 24
Bank
Total 26 35 14,005 222









Table 2-3. Results from nominal group meeting and first-round interviews regarding costs and
benefits of pledging and tourism.
Pledging Tourism
Benefits Costs Benefits Costs


People still abide by
it / have respect for it




People are not
cutting down forests
where baboons live



Trees preserve the
bankside (river
erosion lessened and
more people are
becoming aware of
this)
Benefits everything:
protects animals
(animals, birds) and
river systems (water,
fish) that humans
depend on
Jobs are scarce and
the forest (protected
through pledging)
allows people to
have tourism on their
land


No economic benefits
of pledging




Conservation limits
other activities, such
as hunting



One can't clear the
land as you would
want especially
riverside for pasture



Baboons eat all (fruit
trees) and there are
none left for people




One has to clean up
leaves (under the
trees that are left
from the pledge)


Money


Jobs


Generate Ideas/
Learning and
Educational


Tourists take liberties
with their safety
(encourages behavior
from others to take
advantage of tourists)
Endangered /
threatened species (that
ecotourism is focused
on) can't be hunted and
/ or sold
We have to be on our
"best behavior" when
tourists are around


Incentive to keep
your place and your
village clean and
nice-looking



Contacts made with
those from away


Note: This was later used, along with the established literature, to develop scale items for place
attachment and benefit questions.










Table 2-4. Survey sample
Survey sample Number of CBS households

Tourism-only 12

Pledged-only 37

Pledged and Tourism (PT) 14

Non-Pledge / Non-Tourism 72

Total 135


Table 2-5. Community Benefits (Importance) Means. Likert Scale (1 = not very important, 5 =
very important) p < 0.1 ** p < 0.05
Community benefits Non Tourism Non Pledge Non
(importance) Overall P&T PT only tourism only pledge
N=135 N=14 N=121 N=12 N=123 N=37 N=98


Living in a healthy
environment


Providing a good quality
of life

Knowing conserved
natural resources exist
for future generations

A feeling that your
community is a special
place to live

Attracts tourism dollars
to my community

A natural setting in
which your community
takes great pride

A place to conserve
various natural and
unique ecosystems

Improved care for
community aesthetics

A greater concern for the
natural environment
among residents


4.6 4.6


4.2 4.3


4.3 4.2



4.2 4.1



4.4 4.1



4.1 3.9



4.1 3.8



4.1* 3.8*


4.1* 3.7*


4.1** 3.7**


4.5 4.6


4.2 4.2


4.4** 4.2**



4.1 4.1



4.1 4.1



3.9 4.0



4.0 3.8



3.9 3.8


3.8 3.7










Table 2-6. Community Benefits (Attainment) Means. Likert Scale (1


attained) p < 0.1 ** p <0.05
Community benefits Non- Tourism Non Pledge Non
(attainment) Overall PT PT only tourism only pledge
N=135 N=14 N=121 N=12 N=123 N=37 N=98
Living in a healthy environment 36 3 3 3 3 3
3.6 3.8 3.6 3.7 3.6 3.7 3.6
Providing a good quality of life 2.7 2.5 2.7 2.5 2.7 30** 26**

Knowing conserved natural
resources exist for future 3.1 3.1 3.1 3.0 3.2 34** 3.0**
generations

A feeling that your community is
a special place to live 2.8 3.0 2.8 2.7 2.8 2.8 2.8

Attracts tourism dollars to my
community 1.6 2.1** 1.6** 1.6 1.6 1.6 1.6

A natural setting in which your
community takes great pride 2.6 2.9 2.6 2.7 2.6 2.9** 2.5**

A place to conserve various
natural and unique ecosystems 2.6 2.6 2.6 2.4 2.6 2.8 2.5

Improved care for community
aesthetics 2.2 2.1 2.1 2.2 2.1 2.1 2.1

A greater concern for the natural
environment2.2 2.4 2.2 2.1 2.2 2.3 2.2
environment among residents


= not attained, 4 = fully











Table 2-7. Place Attachment of Riparian Forests Means. Likert-scale (1


strongly agree)


* <0.1


** p < 0.05


Place-Attachment Items Overall PT Non- Tourism Non Pledge Non
PT only tourism only pledge
N=14 N=121 N=12 N=123 N=37 N=98


These riparian forests are
important in providing
habitat for wildlife

My community's history is
strongly tied to this riparian
forest

This riparian forest
contributes to the character
of my community

These forests have helped
put my community on the
map

This riparian forest is a
special place for my family

Many important family
memories are tied to these
areas

I am very attached to this
riparian forest environment

I feel a sense of pride in my
heritage when I am there

These riparian forests are
important in protecting
water quality

My community's economy
depends on riparian forests

My family's income or
livelihood depends on
riparian forests


6.9 6.7



6.6 6.6



6.4 5.9



6.5 5.6



6.5 5.5



6.4 5.4



5.9 5.3


6.1 5.1



5.3 4.8



4.0 3.6


2.4 2.5


5.8 5.9



5.7 5.7



5.3 5.6



4.8 5.5



5.0 5.4


5.4 5.2


3.8 3.7


2.8 2.5


5.8 5.6



6.0** 5.4**



6.1** 5.3**


5.4** 4.7**



4.0 3.6


3.0 2.3


strongly disagree, 7


7.0** 6.7**


7.0** 6.7**









CHAPTER 3
INTEGRATING SOCIAL AND LAND-USE/LAND-COVER CHANGE DATA TO ASSESS
DRIVERS OF DEFORESTATION: A STUDY OF THE COMMUNITY BABOON
SANCTUARY, BELIZE.

Introduction

Dynamics of land-cover (e.g., the biophysical attributes of the land surface) and land-use

(e.g., the anthropogenic influences on the land) change are considered two of the main driving

forces of global environmental change (Meyer and Turner 1992; NRC 1998; Lambin et al. 2000;

Geist and Lambin 2002). Understanding these dynamics help inform, manage, and predict

impacts from land-use changes, such as carbon storage, biodiversity, and ecological services

(Skole 1995; Turner et al. 1995; Olson et al. 2004). Within Land-Use / Land-Cover Change

(LULCC) research, tropical deforestation is considered one of the most significant threats to

biodiversity (Laurance 1999). To better conserve tropical forests the proximate causes of

deforestation must be investigated, in addition to assessing forest cover and forest loss (Roy

Chowdury 2006a). Therefore, research is increasingly focusing on linking social survey

information from local land managers to land-cover changes (Lambin et al. 2000; Mertens et al.

2000; Geoghegan et al. 2001; Klepeis 2003; Garcia-Barrios and Gonzalez-Espinosa 2004). This

study assesses forest cover trends, and examines the relative influence of factors affecting

deforestation, within the Community Baboon Sanctuary (CBS), Belize by linking social survey

and locational information from local land managers to land-cover change.

At the household level, any land manager's land-use decisions are shaped by many

factors including land characteristics, land ownership, household socio-demographics, economic

and livelihood activities, and any institutions or policies that present opportunities or limitations

for a particular land-use activity (Olson et al. 2004). To better understand and identify the causes

and driving forces of deforestation at the household level, past research has focused on the









factors of location, socio-demographic, tenure, socio-economic variables and conservation

initiatives.

Areas more suitable to agriculture, such as forests in more level areas and areas of higher

soil fertility, are more likely to be deforested (Kaimowitz and Angelsen 1998; Geist and Lambin

2001; Gibson et al. 2002; Gautam et al. 2004). Locational variables, such as distance to roads

(access to transportation routes and markets) also promote deforestation (Chomitz and Gray

1996).

People are connected to their natural environment through the system of property rights

(Hanna et al. 1996). Insecure land tenure can encourage deforestation; people will deforest or

harvest what they can when unclear restrictions to resources exist (Wood and Walker 1999).

Chambers (1993) argues that unless people have secure rights to the resources they use, people

will not be motivated to manage and protect them. Overall, the literature supports that secure title

and control over land resources encourages organizational capacity and can be linked to

sustainable forest management and improved economic opportunities (Ostrom 1990; Godoy and

Bawa 1993; Nelson et al. 2001; Murphree 2003).

Among characteristics of the individual land owner, higher education levels were found

to decrease deforestation where it provided greater opportunity for non-farm wage income

(Pinchon 1997; Irwin and Geoghegan 2001; Roy Chowdury 2006b). Another household

characteristic, increasing household size, has been found to increase deforestation probability

due to subsistence demand, although lifecycle phases can also relate to land clearing activities

(Moran 2000).

The uses to which scarce land is allocated is usually determined by the relative value of

alternative uses of the land. Socio-economic drivers to deforestation, such as cattle or









agriculture, can be linked to external market demands (Lambin et al. 2001; Hubacek and

Vazquez 2002). Analyses of driving forces of land-use change studies worldwide have identified

agricultural expansion (ranching and/or cultivation) as the leading proximate driver, which is

often accompanied by timber extraction and transportation infrastructure (Lambin et al. 2001;

Geist and Lambin 2002; Lambin et al. 2003).

Additional factors that may influence deforestation and land-use intensification can be

linked to projects (government or NGO-sponsored) intended to promote development or

conservation (Gibson et al. 2000; Lambin et al. 2001). Conservation policy discussions today

emphasize the importance of local communities benefiting from their conservation of

biodiversity. Increasingly, community-based conservation initiatives are integrating revenue-

generating activities and market incentives with conservation (Tisdell 1995; PfB 2000; Wunder

2000; Langholz and Brandon 2001). Under this scenario, nature-based tourism has been

recognized as an approach for providing communities local financial incentives for conservation

(Tisdell 1995; Kangas et al. 1995; Bookbinder 1998; Kimmel 1999; Langholz 2002). The

impetus for many community nature-based tourism projects is to reduce the local threats to

biodiversity, such as unsustainable harvesting of wild plants, hunting, and expanding agriculture

by providing socio-economic alternatives to current forest depletion and unsustainable

agricultural practices (Boo 1990; Lindberg et al. 1996; Wunder 2000; Nyaupane and Thapa

2004).

Another factor tied to conservation strategies shown to influence conservation behavior is

the act of making a commitment or pledge to conservation behaviors. 'Commitment' within

social marketing is defined as "a binding or pledging of the individual to an act or a decision"

(Kiesler and Sakumura 1966: 349). The theoretical foundation of commitment is based on the









premise that once a pledge is formally made, the bond is strengthened between the promise and

future action. An important element of commitment and conservation behavior change is that

over time, if a behavior continues, a change in attitude will also occur (Werner et al. 1995).

Commitment theory suggests that a public, voluntary, and written pledge not to deforest should

decrease the probability of deforestation.

Many decisions to modify land-use are taken by the household. Therefore, this study

links remote sensing and household socio-economic data to integrate factors affecting

deforestation (McCracken et al. 1999). Decision making at finer scales (e.g., the household

level) has Oto be structured within a broader set of issues at coarser scales (including the

community) and policy, pricing and regulatory issues at regional, national, and even global

scales (e.g., public policy and institutions, global markets and prices) (Walsh et al. 2003). To

understand land-use change at more aggregated scales, research must examine individual land-

use decisions at the parcel level (Ludeke et al. 1990). The objectives of this study were:

1. Determine rates and trends of forest cover change within the Community Baboon
Sanctuary (CBS), Belize landscape over a 15-year time period (1989, 1994, 2000, 2004);

2. Determine and compare rates and trends of forest cover change of the 120 meter riparian
forest buffer landscape within and outside the CBS over a 15-year time period (1989,
1994, 2000, 2004); and

3. Evaluate the relative influence of locational, land tenure, socio-demographic, socio-
economic, and conservation initiative variables as drivers of deforestation within the CBS
from the development of spatial, statistical models.

Methods

LULCC in Belize

The deforestation rate (2.3% per year) in Belize surpassed that of Central America (1.2%

per year) during 1990-2000, increasing abruptly from an annual forest loss of only 0.2% in the

early 1980s (DiFiore 2002). In 2007, Belize had 79% forest cover (FAO 2007), down from 97%









forest cover in the early 1980s. However, as of 1992, the north-central part of the country retains

only 30% of its original forest cover (King et al. 1992). The main drivers encouraging

deforestation and fragmentation of remaining forests in Belize are large-scale agriculture, milpas

(small-scale slash and burn farming), large- and small-scale cattle ranching, large- and small-

scale logging, and urban growth (Horwich and Lyon 1990).

Study Site

Established in 1985 through the efforts of the Belize Audubon Society and two American

scientists, the Community Baboon Sanctuary (CBS) was created to protect habitat for the black

howler monkey (Alouattapigra) along the Belize River (Horwich and Lyon 1998) (Figure 3-1).

The CBS is not a conventional protected area (e.g., national park) with people living outside its

borders. In contrast, the CBS is comprised of seven Creole villages with private landowners who

have agreed to manage their land in a particular way that increases its conservation value. The

CBS totals approximately 8700 ha located in the climatic region of north-central Belize (170

33'N, 880 35'W) with forest cover classified as lowland, semi-deciduous rainforest. An annual

rainfall of 60-70 inches (150-175 cm) is typical of the region, with a pronounced dry season from

February through May (Horwich and Lyon 1998). The forests within the CBS (as throughout

Belize) have been periodically logged for the past 300 years and today are comprised of

secondary forests (10-75 years old) with cleared areas and secondary growth (Horwich and Lyon

1990). The main livelihood activities within the CBS villages include employment with nature-

based tourism (primarily in the village of Bermudian Landing); small-scale agriculture; small-

scale cattle raising; small-scale coconut oil and cohune nut oil (Orbignya cohune) production;

cashew harvesting; and outside wage employment (primarily in or around Belize City, roughly

35 miles away).









Since 1985 various residents within the CBS communities have participated in two

conservation initiatives: nature-based tourism focused around the howler monkey and a written,

voluntary conservation pledge for private landowners to leave a strip of riparian forest and

forested corridors that provide habitat connectivity for howler monkey populations. Little

monitoring, however has been conducted to assess the effectiveness of these two initiatives and

other factors that influence deforestation.

Household Surveys

This study evaluated the relative influence of landowner characteristics on deforestation

probability. Remote sensing data were linked with the following land and landowner

characteristics: locational, land tenure, socio-demographic, socio-economic, and participation in

conservation initiatives.

Locational: The locational factors chosen for this study include distance to the Belize

River and road networks from each forested pixel. Riparian areas are often chosen for

agriculture within the CBS because of their more fertile soils. Most of the riverine and cohune

palm forests of the CBS are located on alluvial soils of the Bermudian Landing Series (USDA:

Vertic Europept) (Horwich and Lyon 1990). In addition, road networks throughout the CBS

have increased access to Belize City for outside employment opportunities and markets (roughly

35 miles away).

Land tenure: The CBS includes private (titled) and government leased (20 year)

landholdings. The majority of the 33 landowners interviewed have title to their land (n = 27),

with six households possessing government leases. Within the CBS, as well as throughout

Belize, property is transferred through formal title or leased land that has been 'worked' (e.g.,

cleared for agriculture or livestock) (Lash 2003) and, as such, there is a disincentive to leave

large tracks of forest in place.









Socio-demographic: Two demographic variables considered were family size and

education level (number of years of education) of the household head. Family size of the 33

households interviewed ranged between 1 to 10 members (mean = 4.8). Education level of the

household head for these 33 households ranged between 0 to 18 years of schooling (mean = 8

years).

Socio-economic: Agriculture and cattle activity were the two variables examined under

socio-economic variables. Although not as prevalent as years past, cattle ranching (both large

and small-scale) and small-scale agriculture (mostly for home consumption) are common

livelihood activities. From the 33 households interviewed, 21 practiced agriculture in 2005,

cultivating 101.5 acres (out of an approximate 2566 acres total within the 33 parcels). The

majority of those with cattle have less than 50 head, but cattle serve as a type of savings account

for many residents; when instant cash is needed for medical emergencies or events such as

weddings and funerals, a cow can be sold immediately either within the villages or in Belize

City. Twenty of the 33 households interviewed (61%) manage some cattle, accounting for a total

of 432 head of cattle. Cattle are also often kept by the river where they can easily access water.

Conservation initiatives: Nature-based tourism and a conservation pledge were two

conservation initiatives examined within the CBS. The black howler monkey (Alloutapigra) is

the focus of tourism within the CBS, developed to provide economic incentives for residents to

protect forest landscapes (especially riparian forests). Tourism related jobs range from

employment in the visitor center and museum to tour guiding, housing visitors, and maintaining

trails, involving both seasonal and permanent positions. Ten out of the 33 households

interviewed have at least one family member currently involved in tourism. There does appear

to be some inequality of tourism benefits, with the majority of residents currently involved in









tourism residing in the village of Bermudian Landing, the location of the visitor center. Still, a

few residents from other CBS villages are also involved with and benefiting financially from

tourism, with some residents even starting to develop tourism opportunities on their own lands

(see chapter two).

The voluntary, written, public conservation pledge asks landowners to agree to do their

part in protecting forest habitat for the howler monkey. By signing this pledge, landowners

agree ('commit') not to clear their land along the riverbank (the main focus) and to leave a

forested corridor between property boundaries. Although the pledge was not initially linked with

any financial reward, CBS records and research by Lash (2003) indicate that pledged landowners

were paid twice (1998 and 2000 totaling -$250 per landowner) by the CBS management at the

time, but presently no residents are given any financial compensation for pledging. Currently, 11

out of the 33 households interviewed are involved in tourism only, 10 households are involved in

pledging only, and 8 are both pledged and tourism households.

Remote Sensing

Because of the different drivers contributing to land-use decisions, understanding LULCC

requires the integration of multiple disciplines and tools, in this case remote sensing and socio-

economic data. Remote sensing data provides information on the differences in land-cover

characteristics on spatial and temporal levels and have been used on a wide range of analyses,

one of which is forest change detection (Femside 1986; Vogelmann and Rock 1988; Skole and

Tucker 1993; Sader et al. 1994; Jha and Unni 1994; Foody et al. 1996; Di Fiore 2002;

Southworth et al. 2004). Remote sensing has also been used extensively with ethnographic

methods, from household surveys to socio-economic data, to better understand the drivers of

land-use change (Guyer and Lambin 1993; Sussman et al. 1994; Mertens et al. 2000; Sader et al.









2001; Hayes et al. 2002; Southworth et al. 2002; Schweik and Thomas 2002; Bray et al. 2003;

Dalle et al. 2006).

Image pre-processing: Three Landsat TM satellite images and one Landsat 7 ETM+

SLC-off satellite image (Path 19, Row 48) were processed from 1989, 1994, 2000, and 2004 to

analyze land-cover change within the CBS and outside landscape. To decrease errors associated

with seasonal variations on biophysical properties and subsequent change detection analyses,

these images were taken between November and March, corresponding with the study site's dry

season (Jensen 2005). Preceding year/month climate information of the area, in particular

precipitation levels, were obtained and considered for the change analysis process considering

extremely wet or dry conditions on one of the dates can cause serious change detection issues

(Table 3-1).

Each Landsat image was corrected for atmospheric, sensor, and illumination variance

sources through radiometric calibration and atmospheric correction procedures (Green 2000) to

ensure change detection accuracy at the Earth's surface (Jensen 2005). The 2004 image was

corrected geometrically using a 1:50,000 scale map of the study area obtained from the Belize

Land Information Center (UTM Zone 16, WGS 1984). Points from the 2004 rectified image

were then used to register the other images, maintaining the root mean square (RMS) error of

each registration below 0.5 pixels (<15 m).

Image classification: Training sample protocol forms from the Center for the Study of

Institutions, Population, and Environmental Change (CIPEC) were used (CIPEC 1998) for

ground truthing the 2004 image within the CBS between September and December, 2005. Areas

to include in a training sample covered a 90 X 90 m area to ensure that at least one full pixel fell

within that particular land-cover. In total, sixty-six training sample points were taken (31 for









"forest" and 35 for "non-forest") which included as many different types of forest and non-forest

cover in and around the CBS. Locations were recorded with a GPS (global positioning system)

unit and other information, such as qualitative descriptions (e.g., photographs) was recorded for

reference and comparison with classified maps and satellite imagery. A class was considered

"forest" if it had a canopy covering 25% or more, using a definition of forest that functioned both

socially and physically for the CBS. Training samples within the CBS were primarily taken

along roads and the Belize River but in areas difficult to access, vantage and edge training

sample points were also taken. To further aid with the training samples, the nature and extent of

land-use was obtained through informal landowner interviews and personal observations.

Before classifying the images, clouds were removed from each image to create a mask

that was then applied to all images. Training sample data and GPS points were then used to

conduct a hybrid supervised / unsupervised classification using the Gaussian Maximum

Likelihood technique on the 2004 image, starting with an unsupervised classification of 60

classes. Considering forest was the class interest, other non-forest areas (e.g., wetlands, built,

agriculture) were merged into a final class: non-forest (NF) after all the spectral reflectance

differences were represented. An accuracy assessment on the 2004 classified image resulted in

an overall classification accuracy of 84.85% and an overall Kappa Statistics of 69.47%, with no

individual class less than 80% (Table 3-2). An overall accuracy of 85% (with no class less than

70%) has been established as a target for accuracy assessments (Thomlinson et al. 1999). The

remaining images were classified through comparison with signature mean plots of 2004 classes,

and also contrasting vegetation using the NDVI and thermal band of each image. The result of

the classification process was the creation of "forest" (F) and "non-forest" (NF) classifications

for each image date.









Data analysis (change detection): For the landowner property change detection

analyses, a 1992 CBS property owner map (1:50,000 scale map) was georeferenced to the 2004

Landsat image in ArcMap, using roads and rivers as ground control points (GCPs) maintaining a

RMS error below 0.5 pixels (<15 m). Individual properties were then digitized as shapefiles in

ArcMap. Out of a total of 77 river property owners, 33 landowner properties were analyzed for

this study, which accounted for those landowners who were interviewed, whose properties had

not changed for the entire 15 year duration, and whose property boundaries were not impacted by

cloud coverage in the satellite images (Figure 3-2).

The Belize River was digitized to create a shapefile in ArcMap. There is no existing

precedence for establishing river buffer widths in Belize (for wildlife use or any other ecosystem

function). Specific to the Belize River within the CBS, 120 meters has been suggested by Dr.

Robert Horwich (personal comm. 2008), a primatologist familiar with the riparian forest areas of

the CBS, as the approximate river buffer area of flooding and higher soil fertility.

Two types of change detection analyses were conducted: a change detection analysis of

the CBS area over the four image dates (1989, 1994, 2000, and 2004) and a comparison of an

120 meter buffer of the Belize River within and outside the CBS over the four image dates. For

these analyses, the Spatial Modeler function in ERDAS Imagine software was used to create

change detection images using the four images as inputs to develop an image differencing

algorithm as the function and create a change detection image as the output. These change

detection analyses using the four image dates created 16 change classes. To better assess general

trends of forest cover change over this 15 year period, the 16 change classes were grouped into

five categories: stable forest, stable non-forest, tending towards deforestation (starting with F and

ending in NF), tending towards reforestation (starting in NF and ending in F), and transitional.









Spatial Regression Models of Deforestation

The model of deforestation within the CBS employs binomial logit models with the

classification derived dependent variable (stable forest versus deforestation during the two image

comparison) and landscape and socio-economic GIS layers as independent variables to produce a

predicted probability of deforestation, as well as parameter estimates. Munroe et al. (2004) found

that binomial logit models yielded better model fit, compared to multinomial logit models, in

examining land-cover change in Honduras. Roy Chowdury (2006a, 2006b) also applied

binomial logit models to understand parcel-scale deforestation decisions in Southeastern Mexico.

Decisions about deforestation on parcels within the CBS are informed by considerations

on (1) locational factors, such as distance to roads and distance to the Belize River from each

forested pixel, (2) land tenure, (3) socio-economic and socio-demographic factors (for model 3

only), and (4) participation in conservation initiatives (nature-based tourism and pledging).

Following Geoghegan et al. (2001) and Roy Chowdury (2006a, 2006b), for the classification

derived-dependent variable, the probability of deforestation at a pixel can be given as:

Pr(y, = 1I x) e= e P x ...

1+ el o+P1+ P2
W here

y = 0 if pixel j was forest in the first year of the model and remained forested in the last

year of model (stable forest) or 1 if pixelj was forest in the first year of the model and was

deforested in the last year of model (deforestation)

x, = value of independent (explanatory) variable at pixelj

P = estimated parameters (coefficients) for each independent variable that can be estimated

using a binomial logit specification (Maddala 1983).









Preliminary statistical analyses: Steps were taken to assess which variables were most

important for modeling deforestation for the 2000 2004 time period (model 3), based on a

priori information from the literature, as well as their importance within the region and the CBS.

Tests of collinearity were conducted between the binary independent variables using Chi-square

analyses, and between continuous and continuous-binary interactions using Pearson's

correlation. Consideration was given to both the p-value and the magnitude of the value. A value

of 0.50 or greater was a measure of high correlation, following Munroe et al. (2004). After

eliminating some of the independent variables due to high collinearity, a binominal logit

regression was conducted for each of the three two-year period combinations (1989 1994, 1994

- 2000, and 2000 2004). Model 1 (1989 1994) and model 2 (1994 2000) assessed the

impacts of 4 variables (tenure, pledge, distance to river, and distance to roads), due to temporally

restricted variables while model 3 (2000 2004) employed a stepwise regression and addressed

other socio-economic and socio-demographic variables collected from household interviews

conducted in 2005.

Next, spatial autocorrelation of residuals for each model was assessed through calculating

Moran's I value, using ArcGIS spatial statistics. Moran's I is one of the most common ways to

measure spatial autocorrelation, and is defined as a measure of the correlation among

neighboring observations in a pattern (Boots and Getis 1988) and refers to the fact that the value

of a variable at one point in space is related to the value of that same variable in a nearby

location. This statistic is used to evaluate the presence or absence of spatial autocorrelation and

is interpreted like a correlation coefficient, with values near +1 indicating strong positive spatial

autocorrelation, values near -1 indicating strong negative autocorrelation, and values near 0

indicating an absence of spatial pattern (Rogerson 2005). Spatial autocorrelation was expected









to exist within the models, as it is common in remote sensing studies (Munroe et al. 2004) and

because much of the data for this study is measured at the parcel level (socio-economic data) but

the unit of analysis is at the pixel level (data are at mismatched scales). Measures of spatial

pattern were included in the analysis, such as distance to the Belize River and distance to the

nearest road measured from each pixel, to decrease autocorrelation (Moran's I values) to 0.07,

0.06, and 0.05 for the three models. After these preliminary statistical analyses, a final model

was created for each two-year period combination (three models in total). All data were

standardized (subtracting the mean and dividing by the standard deviation) to enable comparison

between binary and continuous variables within each model. Measures of accuracy (pseudo R2

and overdispersion parameter) and model validation were then assessed for model goodness of

fit.

Results

To adequately address conservation success, research must first assess forest cover and

forest change before examining the causes of change. Therefore, this study's first two objectives

were to assess land-cover change trends of the CBS landscape and land-cover trends of the 120

meter river buffer within and outside the CBS. If conservation loss is occurring, the proximate

causes of deforestation must also be investigated (Roy Chowdury 2006a), and this study's third

objective, which was to determine the relative influence of chosen variables on deforestation

probability, was designed to understand these causes.

CBS Land-Cover Trends

Covering the entire 15 year time period (1989 2004), the largest proportion of the CBS

landscape follows the "stable forest" trajectory, comprising 33.4% (2908.98 ha) of the landscape.

The second largest proportion of the CBS landscape follows the "tending toward deforestation"

trajectory, comprising 29.7% of the landscape (2582.79 ha). "Tending toward reforestation" and









"stable non-forest" accounted for 18.9% (1647 ha) and 13.8% (1200.6 ha) of the landscape,

respectively, with the "transitional" trajectory accounting for 4.1% (361.17 ha) of the landscape

(Figure 3-3 and Table 3-3). Major results indicate the CBS landscape follows both stable forest

and deforestation trends.

River Buffer Trends

Although assessment of the entire CBS landscape is important as a community reserve,

the river buffer is the focus of conservation with the goal of protecting habitat for the black

howler monkey (Alouattapigra) (the impetus for the creation of the CBS) and can serve as a

proxy for conservation within the CBS. A 120 meter Belize River buffer running through the

CBS was compared to the non-protected segment of the Belize River buffer running north and

south of the CBS. The leading land-cover trend within the CBS' 120 meter river buffer followed

"tending toward deforestation." Although a difference in total river distance exists, attributed to

cloud coverage on the satellite images and the importance of focusing on similar rural areas, the

major land-cover changes that have occurred along the river buffer within the CBS from 1989,

1994, 2000, and 2004 are the same changes that have occurred along the river buffer outside the

CBS (Figures 3-4 and Tables 3-4). The largest proportion of the 120 meter river buffer both

inside and outside the CBS falls under the land-cover trajectory "tending toward deforestation,"

accounting for 30.95% (257.22 ha) of the CBS river buffer and 29.83% (99.18 ha) of the river

buffer outside the CBS. A close secondary leading land-cover trend was "stable forest,"

accounting for 26.09% (216.18 ha) of the CBS river buffer and 28.1% (93.42 ha) of the outside

river buffer. The next land-cover trajectory is that proportion "tending toward reforestation,"

accounting for 25.71% (213.66 ha) within the CBS and 23.09% (76.77 ha) outside the CBS.

"Stable non-forest" and "transitional" land-covers account for the smallest proportions of both









river buffer landscapes, covering 10.55% (87.66 ha) and 6.71% (55.8 ha) within the CBS and

9.64% (32.04 ha) and 9.34% (31.05 ha) outside the CBS.

Drivers of Deforestation

To determine the major drivers of deforestation within the CBS, variables were chosen a

priori from the literature and/or based on the observations and information obtained by the

research during field work. Because much of the household characteristic information (e.g.,

socio-economic and socio-demographic) was only relevant during the last time period modeled

(2000 2004), this information was not included in the two earlier models (1989 1994 and

1994 2000). The results of the three separate binomial logit models of deforestation for the

periods from 1989 1994 (model 1), 1994 2000 (model 2), and 2000 2004 (model 3) are

presented in Tables 3-5, 3-6, and 3-7. These tables present the values of the parameter estimates

(coefficients) with their corresponding Z value statistic and indicated significant probability.

Positive values of parameter estimates indicate that larger values of the explanatory variables

increase the likelihood of deforestation (given statistical significance), while negative values

indicate the opposite. By addressing deforestation probability, the binomial logit models also

address stable forest probability, covering the two dominant land- cover trends within the CBS

landscape and 120 meter river buffer (Table 3-3 and Table 3-4).

Model 1 (1989 1994)

Only those variables relevant during the 1989 1994 time period for the 33 landowners

and their parcels were analyzed in this model. These variables included distance to river from

each pixel, distance to roads from each pixel, land tenure, and participation in the pledge.

Distance to road was the most influential variable in the model. Areas further from the road and

the Belize River, as well as titled tenure decreased the probability of deforestation (p = 0.001).

Participation in the pledge increased the probability of deforestation (p = 0.01) (Table 3-5).









Model 2 (1994 2000)

Only those variables relevant during the 1994 2000 time period for the 33 landowners

and their parcels were analyzed in this model. These variables included distance to river from

each pixel, distance to roads from each pixel, land tenure, and participation in the pledge.

Similar to model 1, areas further from the road and the Belize River and titled tenure decreased

deforestation probability. In contrast to model 1, participation in the pledge decreased the

probability of deforestation (p = 0.001) (Table 3-6), perhaps coinciding with one of the payment

years for pledgers.

Model 3 (2000 2004)

Since surveyed data were relevant to current participants, the last model included all

variables of interest. Cattle, cattle income, agriculture, education level of the household head,

and tenure were the five most influential variables in this model. Increasing cattle income,

education level of the household head, titled tenure, distance from roads, distance from the

Belize River, family size, agricultural income, and involvement in both the pledge and tourism

were significantly linked (p = 0.001) to decreasing probabilities of deforestation. Pasture also

decreased deforestation probabilities but at a lower significance level (p =0.05). Cattle,

agriculture, remittances, and involvement in tourism were significantly linked (p = 0.001) to

increasing probabilities of deforestation. Working outside the CBS and involvement in the

pledge also increased probabilities of deforestation but at lower significance levels (p = 0.05)

(Table 3-7).

Because of the large number of variables in this model and the large number of pixels, it

is possible that many of the variables that show statistical significance in the model may not be

good predictors of deforestation within the CBS. To better assess their influence, all variables

were plotted individually and examined in more detail on their strength of effect using logistic









regression. Results show that the most influential variables in this model were distance to the

Belize River and distance to roads (figure 3-5), cattle (figure 3-6a), agriculture (figure 3-7a),

education of household head (figure 3-8a), and participation in both pledging and tourism (figure

3-10). The least influential variables in this model (with low predictive power) included cattle

income (figure 3-6b), agricultural income (figure 3-7b), family size (figure 3-8b), tenure (figure

3-9a), remittances (figure3-9b), outside work (figure 3-1 la), and pasture (figure 3-1 lb). Both

distance to river and distance to roads have an approximate 50% decrease in deforestation

probability (from 0.4 to 0.2) as distance increases to 2500 meters away. Owning cattle also

shows a 17% difference in deforestation probability difference between those residents with

cattle (39%) and those without (22%). In contrast to owning cattle, which is statistically

significant and influential, an increase in cattle income only slightly decreased deforestation

probability. Agriculture was also fairly influential showing an approximate 9% decrease in

deforestation probability between those carrying out agricultural practices (37%) and those not

(28%). However, agricultural income, although showing a decrease in deforestation in the

model, has very strength of effect when plotted. Education of household head had strong

strength of effect and decreased deforestation probability by approximately 50%. In comparison,

although greater family size was predicted to increase deforestation probability, results show this

was not influential within the CBS. Tenure, although one of the top five influential variables in

the model, did not show strong strength of effect and indicated only a slight decrease in

deforestation probability for those with titled land ownership. Remittances, although increasing

the probability of deforestation in the model, showed very low strength of effect when plotted.

Additionally, outside (CBS) work and having pasture, two of the three least influential variables

in the model, both showed very low strength of effect when plotted. Lastly, comparing the two









conservation initiatives (tourism and pledging), there was a 12% decrease in deforestation

probability between those households involved in both pledging and tourism (26%), compared to

those households not involved in either initiative (38%). Households involved in either tourism

(30%) or pledging (32%) showed a 6-8% decrease in deforestation probability compared to those

households not involved in either initiative.

Model Validation

There are several ways to assess model accuracy. One indicator of model fit is the

overdispersion parameter. This parameter is useful for indicating whether the relevant model has

been applied and if outliers exist in the data, measuring a model's residual deviance over degrees

of freedom (Burnham and Anderson 2002). With a value of "1" considered a strong fit,

parameter results were 1.13 (model 1), 1.01 (model 2), and 1.19 (model 3), indicating no issues

with outliers and overall correct model choice. The second model (1994 2000) had the highest

prediction accuracy result for deforestation (74%) and stable forest (78%). The first model

(1989 1994) had the second highest prediction accuracy for deforestation (68%) but the lowest

prediction accuracy for stable forest (72%). The third model (2000 2004) had a prediction

accuracy of 69% for deforestation and 70% for stable forest (Table 3-8).

Additionally, many LULCC modeling studies report apseudo R2, as the R2 statistic as a

traditional measure of fit is not easily calculated in a categorical regression framework. A

pseudo R2 statistic was calculated for each model (based on the ratio of restricted and

unrestricted log-likelihood function). The pseudo R2 results were 0.116 (model 1), 0.063 (model

2), and 0.129 (model 3). Although the model chose the most significant variables influencing the

probability of deforestation, these low pseudo R2 values signal that overall these variables are not

the most influential predictors of deforestation probability and that other important variables are









missing from the model (information that was either not available for this study or was not

collected) that predict deforestation probability.

Lastly, following other LULCC modeling studies, a predicted versus observed

deforestation / stable forest map was created to assess the spatial pattern of model performance,

using 50% as the threshold for the model-predicted probability of deforestation to classify a pixel

as deforested (Figures 3-11, 3-12, and 3-13). Generally speaking, all models show most

incorrect predictions of deforestation (where stable forest actually occurred) located around

correctly deforested pixels. In models 1 and 2 this over-prediction of deforestation was likely

distance-related, considering that the two largest z values belonged to the 'distance to road' and

"distance to river' variable, and could be responsible for this over-prediction. In addition, the

spatial pattern of pixels where all the models over-predict stable forest (where forest was actually

deforested) does not appear necessarily random, but does not fit any distance-based criteria and

is difficult to interpret any consistent spatial patterns. This may indicate that other variables not

captured by the models may be influencing deforestation in certain areas, or even other spatial

processes that are occurring in these areas (e.g., soil maps for the region were not at the detail

needed to show differentiation within the CBS).

In comparison to the other models, although some correct predictions for deforestation in

model 3 are located near roads and rivers, overall these predictions appear to be more unique to

each land parcel, potentially pointing to the role of household survey-derived socio-economic

and socio-demographic variables over distance-related variables in this model (e.g., cattle and

agriculture). However, there were no clear patterns or variables unique to these landowners

from the model that would explain this, which also signals that other variables not included in

the model are probably influencing deforestation within these parcels.









Discussion

Although the two leading land-cover trajectories within the CBS were stable forest and

deforestation, leading land-cover trends of the 120 meter river buffer within and outside the CBS

also needed to also be examined, considering the conservation focus of riparian forests. Within

the 120 meter river buffer the leading land-cover trend both within and outside the CBS was tending

toward deforestation. This result of similar land-cover trends inside and outside the CBS riparian

buffer indicates riparian forests are not any more conserved within the CBS as they are outside.

In addition, areas within the 120 meter river buffer are more likely to be deforested than other

areas within the CBS. Following these analyses, modeling social survey and locational

characteristics of individual landowners with land-cover change provided insight into the relative

influence of these factors on deforestation probability within the CBS.

Drivers of Deforestation

Locational: As predicted, distance to river was an influential variable in all three models

negatively linked to probabilities of deforestation (increased probabilities of deforestation the

closer a pixel is to the river). Distance to river also had high predictive power in model 3 (2000

- 2004) and supports "tending towards deforestation" as the leading land-cover trend within the

120 meter river buffer. In addition to distance to river, distance to roads in all three models was

negatively related to probabilities of deforestation (increased probabilities of deforestation the

closer a pixel is to the road) with high predictive power in model 3 (2000 2004). This follows

a wealth of past research, as well as intuitive sense that infrastructure and clearing would take

place closer to roads for access. Access and distance to markets is an important driver

explaining contrasting patterns of land-cover and land-use in other areas (Chomitz and Gray

1996 on commercial agriculture and Kaimowitz and Angelsen 1998; Wickham et al. 2000;

Nepstad et al. 2001; and Nelson et al. 2001 on access to markets and deforestation).









Land tenure: In all modeled time periods titled land ownership significantly decreased

probabilities of deforestation as households moved from leased (lower) to titled (higher)

ownership. Although statistically significant, tenure did not have strong predictive power in

model 3, indicating there were other more influential variables. Nevertheless, the findings from

these models follow the hypothesis that secure title and control over land resources can be linked

to more sustainable forest management (Godoy and Bawa 1993; Nelson et al. 2001; Murphree

2003).

Socio-demographics: Education level of the household head in model 3 was influential

in decreasing deforestation probabilities and followed the prediction that higher education levels

of the household head can lead to other employment and economic activities (flexibility), which

put less demand on clearing land. In comparison, family size did not follow my prediction that

larger families increase deforestation probabilities from increased subsistence needs. Roy

Chowdhury (2006a) attributed larger families and lower deforestation probability to larger

households farming the same area for longer periods of time. Additionally, Roy Chowdhury

(2006a) emphasizes that this result could occur if families are further along in their lifecycle.

Even though family size showed a decrease in deforestation probability, its predictive power in

the model was very small, indicating this variable it is not a strong predictor of deforestation

within the CBS, compared to other variables. Although family size among the 33 landowners

ranged between 1 and 10 (mean = 4.8), this study would speculate that CBS families today do

not grow the majority of their food. Because of this, family size would not considerably

decrease or increase the amount of agricultural activity (and deforestation) by the household.

Socio-economics: Cattle is the most influential variable in model 3 and showed high

predictive power linked to an increase in deforestation probability. Agriculture also had high









predictive power on increasing deforestation probability. This presence of cattle as the leading

driver of deforestation also follows in line with the worldwide leading proximate driver of

deforestation (agricultural expansion for ranching and/or cultivation) (Lambin et al. 2001; Geist

and Lambin 2002; Lambin et al. 2003). As mentioned earlier, having a few head of cattle is a

good financial investment as one can readily sell a cow when there is an urgent need for money.

Access to roads and distance to markets may be another factor encouraging cattle ranching as a

good road network through most of the communities make transportation to Belize City an easy

commute (roughly 35 miles). The low predictive power of cattle income in model 3 may signal

that not many people sell their cattle and when they do, with the exception of a few cattle

herders, the money does not get reinvested into land intensification but, rather, other household

needs (e.g., emergency expenses, education, house improvements, etc). The low predictive

power of agricultural income in model 3 also indicates that few people actually sell their

agricultural crops (primarily for home consumption) and when it is sold, it is not invested into

deforestation. In fact, families may farm the same areas over several years, as was observed by

Roy Chowdury (2006a).

Conservation initiatives: Out of the 33 households interviewed, 11 households are

involved in tourism-only, 10 households are involved in pledging-only, and 8 households are

involved in both tourism and pledging. Pledging, a variable that could be modeled over the three

time periods, followed the transition from increasing deforestation probability in model 1 (1989

- 1994), decreasing deforestation probability in model 2 (1994 2000), and then increasing

deforestation probability again in model 3 (2000 2004). Tourism-only and pledge-only

residents increased deforestation probability in model 3. The second chapter of this dissertation

showed why tourism and the pledge might be considered financial failures for conservation,









pointing to the inequitable distribution of tourism participation and benefits from an elite capture

of benefits by a few households since 1998. Tourism jobs and income may motivate residents to

protect howler monkey habitat and deforest less. However, if benefits are not linked to

conservation 'inputs' or the benefits are considered too small, revenue received may actually be

reinvested into activities that undermine conservation efforts (e.g., cattle ranching) (Christ et al.

2003; Aylward 2003; Kiss 2004).

Current dissatisfaction in the pledge can be linked to no current financial compensation

when earlier payments were made in 1998 and 2000. Pledging influences a decrease in

deforestation probability during model 2 (1994 2000), which may be explained through

coinciding with these two payment years. However, by this same argument this decrease in

deforestation probability should have also been observed in model 3 (2000-2004), accounting for

the impact from the received payment, rather than increasing deforestation probability. This may

signal that other influential variables in this model (e.g., cattle, agriculture) or other variables not

accounted for in the model (an indicator of the low pseudo R2 value) may have provided greater

incentive than the payment from pledging provided.

In comparison to the pledge-only and tourism-only variables, those involved in both

pledging and tourism decreased deforestation probabilities in model 3 and showed strong

predictive power. The combination of being involved in both tourism and the pledge actually

decreasing deforestation probabilities may indicate that having both the values of pledged

residents (whether the pledge influenced these residents or these residents had these conservation

values to begin with is not known) and the income from tourism participation may actually

create a stronger connection between tourism dollars received from the resource attraction (the

howler monkey) and the habitat (forest) it is dependent upon. This connection can also be









observed from chapter two of this dissertation where residents involved in both pledging and

tourism had significantly higher perceived benefit attainment values of tourism dollars to their

communities, something tourism-only and pledge-only residents did not (see chapter two).

Limitations

The accuracy of predicted deforestation and stable forest in all the models was greater than

50%, implying that each model was likely capturing more than random variation. However, the

low pseudo R2 values revealed that the variables used together do not explain the majority of

deforestation that is occurring. This indicates there are other important variables missing from

the models that would help explain deforestation probability (and stable forest probability)

within the CBS, such as other biophysical or spatial processes (e.g., soil quality) or socio-

economic variables (e.g., national policy institutions). Despite the overall low explanatory power

of the variables assessed in this study, there was a need to assess the influence of the two

conservation initiatives and this study helped to better understand their role on deforestation

probability. In addition, this study provided a better understanding of the influence of other

potential drivers chosen a priori from the established literature and from time spent in the

research site and region.

Modeling studies conducted by Roy Chowdhury (2006a, 2006b) linking social survey

data with land-cover change also revealed fairly low pseudo R2 values, indicating variables used

in this study were also not explaining the majority of deforestation occurring. This is an

important step in better understanding data, however, and the knowledge gained can be used in

subsequent studies to incorporate other factors that might be more influential. It was not possible

to obtain reliable figures for population within the CBS and various macro-level policy

institutions that may have encouraged or discouraged land intensification practices were not

known (e.g., subsidies, market changes, agricultural loans, etc.). With regard to spatial









processes, one limitation to this study was that the Belize ARC GIS soil and geologic cover maps

were not at the detail needed to show differentiation within the CBS. Further research should

incorporate other factors to better explain deforestation trends within the CBS.

Conclusion

Relationships between humans and the landscape are complex, and vary greatly according

to biophysical, cultural, socio-political and economic perspectives. It is these interrelationships

between areas such as biophysical and locational properties, land tenure, economic, and socio-

political that will allow a better understanding of drivers of LULCC (Binswanger 1991; NRC

1998; Mertens et al. 2000; Geist and Lambin 2001; Nelson et al. 2001; Hubacek and Vazquez

2002).

Across the models, trends show riparian areas are more likely to be deforested, as are areas

closer to road networks. Agriculture and cattle are the activities most influential in driving

deforestation in the last modeled time period, which is also linked to riparian areas, while higher

levels of education for the household head decreased deforestation probability. Of statistical

significance in the model but of lower influence were secure land title and pledging and tourism

working together. Titled land ownership decreased the probability of deforestation in all three

models, although did not show strong strength of effect in the last modeled time period. This

indicates that it has importance in the model, but much less influence than other variables (e.g.,

cattle and agriculture). Similarly, pledging and tourism working together during the last

modeled period indicated some level of decreased deforestation probability but not as influential

as other leading drivers.

The models created in this study, similar to other LULCC modeling studies, simplify

complex processes at various dimensions and, in reality, highlight only some of the variables

most likely influencing deforestation within the CBS. Nevertheless, this study helped to explore









and identify the relevant influence of some of the factors affecting deforestation. This

information can be used to assess the effectiveness of conservation initiatives and impact of other

land-use activities and predict future landscape change. In addition, this study will contribute to

more reliable decision making with respect to conservation planning and landscape management

and is part of an emerging focus of research coming out of the LULCC community linking social

survey information from local land managers to land-cover changes.

















































Figure 3-1. Map of the Community Baboon Sanctuary, Belize, Central America













80






























Legend
E CBS landowner parcels (not within stu
1] CBS landowner parcels (within study)
- Road
fL Belize River


N

W 4V E

s


II Kilometers
0 0.5 1 2 3


Figure 3-2. CBS parcel map of study location



















Legend

M Stable Forest
I Tending Towards Reforestation
I Transitional
W[ ] Tending Towards Deforestation
SStable Non-Forest
No Data


fg /J

e:4


d;l


I L__. JI Miomerer-"
0 05 1 2 3


Figure 3-3. Land-cover change trends for CBS.


N


NULte






















% Land Area (Ha)
.I -.ci3 9918
281 9342
] 2309 7677
S964 32.04
9.34 31.05


W E
S


% Land Area (Ha)
S30 95 257.22
S26.09 21681
S-' 1 21366
1055 87.66
6 71 55.8

N

s<^


Legend


Silometers
0 0.5 1 2 3 4


CBS boundary
Belzie River
Stable Forest
STending Towards Reforestation
| Tending Towards Deforestation
Stable Non-Forest
M Transitional


flJlJ Kilo meters
Legend 0 05 1 2 3 4
Legend
CBS boundary
Belzie River
Stable Forest
S Tending Towards Reforestation
j Tending Towards Deforestation
Stable Non-Forest
STransitional


Figure 3-4. Change detection analysis for 120 meter river buffer outside (A) and inside (B) the
CBS.












O
o ,,
m 00






o
c,

o ,,

o0 -
9

e(


6 500 1500 2500
Distance to River (m)


S C 00


Figure 3-5. Probability of deforestation as a function of distance to (A) river and (B) road
networks in Model 3 (2000 2004).


No Cattle


Cattle


5000 10000
Cattle Income ($)


A B
Figure 3-6. Probability of deforestation as a function of (A) Cattle (B) Cattle Income in Model 3
(2000 2004).


0






00


0

o 0


8
o O
O O


15000


I



o,,

,,
, 00
^0
cc
(D
Q
cce

a
* s
*i-
d=
e(


60 1000 2000
Distance to Road (m)





















404














_ t
So


No Ag Ag


A
Figure 3-7. Probability of deforestation as
in Model 3 (2000 2004).


5 10 15

Education (years)


S0 50 100 150 200 250 300 350

Agriculture Income ($)


a function of A) agriculture and B) agriculture income
a function of A) agriculture and B) agriculture income


o
0

0

o 0 o
o o
o o


0 0 0
o O
o 0




2 4 6 8 10

Family Size (people)


Figure 3-8. Probability of deforestation as a function of (A) education of household head and (B)
family size in Model 3 (2000 2004).


0
0
0
@ 00



8
0 0


0




S
0

0 0 0
o--------< 2^

0 8
o o
o o
OOO
OO













S00


cOO

0


No Title Title


No Remit Remit


Figure 3-9. Probability of deforestation as a function of A) tenure and B) remittances in Model 3
(2000 2004).





a,
0,,
*I,,




9
I'D





i
Q
e(


Pledge Neither Both Tourism


Figure 3-10. Probability of deforestation as a function of conservation initiative in Model 3
(2000 2004).














0

oo





nOO
0



(>0
rc

Cc(






90


~00

~o
01

0>



0


No Pasture


Figure 3-11. Probability of deforestation as a function of A) outside (CBS) work and B) pasture
in Model 3 (2000 2004).


No Outside Work



















Legend

EI Outside parcels or nonforest in 1989

Correctly predicted deforestation

Correctly predicts stable forest

Incorrectly predicts deforestation

M Incorrectly predicts stable forest

- Road

(\- Belize River

N



s /


I LI II- Kilometers
0 0.5 1 2 3


Figure 3-11. Predicted versus observed pixel deforestation / stable forest for 1989-94 (Model 1).




















Legend

E Outside parcels or nonforest in 1994

Correctly predicted deforestation

Correctly predicts stable forest

Incorrectly predicts deforestation

II Incorrectly predicts stable forest

-- Road

C\Y Belize River


N



S


I I I Kilometers
0 0.5 1 2 3


Figure 3-12. Predicted versus observed pixel deforestation / stable forest for 1994 2000
(Model 2).




















Legend

] Outside parcels or nonforest in 2000

Correctly predicted deforestation

Correctly predicts stable forest

Incorrectly predicts deforestation

Incorrectly predicts stable forest

-- Road

( )Belize River


N



S


rI --- JI... I I Kilometers
0 0.5 1 2 3


Figure 3-13. Predicted versus observed pixel deforestation / stable forest for 2000 2004 (Model
3).










Table 3-1. Preceding year/month precipitation information of the CBS area. To assess if rainfall
patterns might impact classification, image year rainfall was compared to the 30 year
average, looking at the 2-3 months prior to image month. Rainfall for the CBS is
recorded at the Phillip Goldson International airport (-40 km away).


Rainfall (mm)
96.4
308.7
208.5

35.1
196.1
286.6

24.9
56
185.2

32
32.2
102.8

229.2
194.2
195.9


30 Yr Ave
227.385
282.2663
272.023

176.4367
227.385
282.2663

47.28607
79.45614
137.0435

47.28607
79.45614
137.0435

227.385
282.2663
272.023


Percentages
42.39506 below
109.3648 normal
76.64793 below


19.89382
86.2414
101.5353

52.65822
70.47914
135.1395

67.67321
40.5255
75.01266

100.7982
68.80027
72.01597


below
below
normal

below
below
above

below
below
below

normal
below
below


Rainfall Percentage Category
<50% Well below normal
50 90% Below normal
90 110% Normal
110- 150% Above normal
> 150% Well above normal


Table 3-2. Accuracy Assessment of 2004 Landsat ETM+ image. The Producer's Accuracy
indicates the probability of a reference pixel being correctly classified and is a
measure of omission error. The User's Accuracy is the probability that a pixel
classified on the map actually represents the category on the ground. This divides the
total number of correct pixels in a category by the total number of pixels that were
actually classified in that category. This is an accuracy measurement between the
reference data and the remote sensing-derived classification map. The Kappa
coefficient represents the decrease in error obtained from the classification process
compared with the error that would have been obtained from random classification.
Total number Number Producers Users Kappa
trng points correct
Forest (1) 31 25 86.21% 80.65% 0.6548

Non-forest (2) 35 31 83.78% 88.57% 0.7399


Nov-84
Oct-84
Sep-84

Dec-89
Nov-89
Oct-89

Mar-94
Feb-94
Jan-94

Mar-00
Feb-00
Jan-00

Nov-04
Oct-04
Sep-04









Table 3-3. Change Detection Analysis of the CBS landscape. This covers the 4 image dates
(1989, 1994, 2000, and 2004) with the 16 change trajectories aggregated into 5 land-
cover categories.
% CBS landscape Ha
Stable Forest 33.4 2908.98

Tending Towards 29.7 2582.79
Deforestation

Tending Towards 18.9 1647
Reforestation

Stable Non-forest 13.8 1200.6

Transitional 4.1 361.17


Table 3-4. Change Detection Analysis of a 120 meter river buffer inside and outside the CBS.
This covers the 4 image dates (1989, 1994, 2000, and 2004) with the 16 change
trajectories aggregated into 5 land-cover categories.
Inside the CBS Outside the CBS
% landscape Ha % landscape Ha
Tending towards 30.95 257.22 29.83 99.18
Deforestation

Stable Forest 26.09 216.81 28.1 93.42


Tending Towards 25.71 213.66 23.09 76.77
Reforestation

Stable Non-forest 10.55 87.66 9.64 32.04

Transitional 6.71 55.8 9.34 31.05











Table 3-5. Deforestation probability on household land parcels, binomial logit regression model
for Model 1 (1989 to 1994), n = 8361 pixels on land parcels belonging to 33
landowners.
Variable Coefficient Std.Error Z value P value Significance
(Intercept) -1.0062 0.0271 -37.0760 < 2e-16 ***
Distance: road -0.5639 0.0306 -18.4350 < 2e-16 ***
Distance: river -0.3894 0.0351 -11.0880 <2e-16 ***
Tenure -0.2329 0.0263 -8.8670 < 2e-16 ***
Pledge 0.0884 0.0272 3.2440 0.00118 **
*p = 0.05, **p = 0.01, ***p = 0.001; Moran's I= 0.07,pseudo R2= 0.12 overdispersion
parameter = 1.13


Table 3-6. Deforestation probability on household land parcels, binomial logit regression model
for Model 2 (1994 to 2000), n = 6436 pixels on land parcels belonging to 33
landowners.


Variable
(Intercept)
Distance: road
Distance: river
Tenure
Pledge
*p = 0.05, **p=
parameter = 1.01


Coefficient Std. Error Z value
-1.3306 0.0319 -41.6590
-0.3196 0.0358 -8.9170
-0.1785 0.0385 -4.6390
-0.2377 0.0292 -8.1540
-0.1987 0.0312 -6.3660
0.01, ***p =0.001; Moran's I = 0.06, pseudo R2


P value Significance
< 2e-16 ***
< 2e-16 ***
3.50E-06 ***
3.51E-16 ***
1.94E-10 ***
0.06, overdispersion












Table 3-7. Deforestation probability on household land parcels, binomial logit regression model
for Model 3 (2000 to 2004), n = 6895 pixels on land parcels belonging to 33
landowners.


Variable
(Intercept)
Cattle
Cattle income
Agriculture
Education (HH Head)
Tenure
Distance: road
Family Size
Agriculture income
Remittances
Pledge*tourism
Distance: river
Tourism
Outside (CBS) work
Pasture
Pledge
*p = 0.05, **p = 0.0
parameter = 1.19


Coefficient Std. Error
-0.7209 0.0280
0.7330 0.0465
-0.5926 0.0498
0.5259 0.0491
-0.4011 0.0424
-0.3802 0.0452
-0.2925 0.0354
-0.3108 0.0403
-0.4555 0.0695
0.2907 0.0470
-0.2319 0.0401
-0.1703 0.0403
0.1343 0.0376
0.1004 0.0342
-0.1057 0.0480
0.0770 0.0355
1, ***p 0.001;Moran's I


Z value
-25.7700
15.7590
-11.8918
10.7221
-9.5400
-8.4158
-8.2620
-7.7100
-6.5511
6.1911
-5.7860
-4.2279
3.5770
2.9358
-2.2009
2.1670


P value
< 2e-16
< 2e-16
< 2e-16
< 2e-16
< 2e-16
<2e-16
< 2e-16
1.26E-14
5.71E-11
5.97E-10
7.21E-09
2.36E-05
3.48E-04
3.33E-03
2.77E-02
3.02E-02


Significance
***
***
***
***
***
***
***
***
***
***
***
***
***
**
*
*


0.05, pseudo R2 = 0.13, overdispersion










Table 3-8. Prediction results for binary logit models
Prediction type Pixel (number) Proportion
Model 1 (1989 1994)
Correct stable forest 5791 0.72
Incorrect stable forest 2226 0.28
Correct deforestation 236 0.68
Incorrect deforestation 108 0.31
Total 8361

Model 2 (1994 2000)
Correct stable forest 5005 0.78
Incorrect stable forest 1396 0.22
Correct deforestation 26 0.74
Incorrect deforestation 9 0.26
Total 6436

Model 3 (2000 2004)
Correct stable forest 4322 0.70
Incorrect stable forest 1858 0.30
Correct deforestation 494 0.69
Incorrect deforestation 221 0.31
Total 6895









CHAPTER 4
FOREST FRAGMENTATION AND HABITAT CONSERVATION FOR THE BLACK
HOWLER MONKEY: A STUDY WITHIN THE COMMUNITY BABOON SANCTUARY,
BELIZE

Anthropogenic activities have led to forest cover loss worldwide, with forest fragmentation

within developing tropical regions occurring at an alarming rate (Rudel and Roper 1997;

Laurance 1999; Sanchez-Azofeifa et al. 2001; Lamb et al. 2005; Abdullah and Nakagoshi 2007).

Fragmentation, defined as the "breaking up of a habitat or cover type into smaller, disconnected

parcels" (Turner et al. 2001, p.3) affects forest habitat when large, continuous forests are divided

into smaller blocks, either by roads, clearing for agriculture, urbanization, or other human

development (Kupfer et al. 2006). The concern with extensive deforestation is the resulting

'forest island' habitats within a fragmented landscape that can be more easily accessed for

further degradation, such as over-hunting, ground fires, and logging (Horwich and Lyon 1990;

Cayuela et al. 2006). Smaller forest fragments can also result in the "empty forest" syndrome

(and often from human activity) where trees are still standing but the species that make up the

complex ecosystem are not (Redford 1992; Robinson 1996).

Fragmentation affects a variety of population and community processes over a range of

temporal and spatial scales with significant implications for biodiversity conservation (Lovejoy

et al. 1986; Kapos 1989; Saunders et al. 1991; Debinski and Holt 2000; Laurance et al. 2000;

Fahrig 2003; Githriu and Lens 2007). Habitat area loss and patch isolation can change predator-

prey dynamics, competitive interactions, and species composition, which may affect community

structure (Fahrig and Merriam 1985; Hobbs 1993; Palomares et al. 1996; Debinski and Holt

2000) or lead to extinction of vulnerable species (Burkey 1995; Weaver et al. 1996).

Characteristics that determine the principle effects of a fragment are isolation (connectivity,

surrounding landscape change, distance from other remnants, and time since isolation) and









microclimate change (wind and edge effects, radiation, water fluxes). In addition, remnant size

and shape, and position within the landscape can also influence the effect of fragments (Marsh

1999). In a fragmented forest, edge effect is one of the distinguishing features, defined in

conservation biology as "the distinct edge between previously undisturbed forest and deforested

clearing" (Lovejoy et al. 1986).

Landscape ecology seeks to understand spatial arrangements and their ecological effects,

examining interactions between the spatial landscape structure, function, and temporal change.

It is through the identification and quantification of landscape patterns that our understanding of

these interactions between landscape structure and ecological processes develops (Turner et al.

2001). Measuring fragmentation (e.g., habitat fragmentation and forest fragmentation) is one

way to quantify landscape pattern. The effects of forest loss and fragmentation can be

interpreted with landscape metrics, algorithms that quantify specific spatial characteristics of

patches, classes of patches, or entire landscape mosaics (McGarigal and Marks 1995).

Studies on forest fragmentation have used island biogeography theory (within the

landscape ecology discipline) to estimate species survival within fragments (Saunders et al.

1991; Redford 1992; Bierregaard and Dale 1996), the optimum size of fragments for species

conservation (e.g., SLOSS; Single Large Or Several Small: Gilpin and Diamond 1980; Shafer

1995), and predicting species numbers (MacArthur and Wilson 1967; Wilcox 1980; Shafer

1995). Another theoretical framework for studying forest fragmentation out of landscape

ecology, metapopulation theory, assesses the impact of habitat fragmentation on population

viability. This theory differs from island biogeography in that it assumes no persistent mainland

habitat, but rather a network of small patches, and also focuses on a single species. The









importance is on dispersal among habitat fragments, where inadequate dispersal and habitat loss

past a certain critical threshold will lead to extinction (Harrison and Bruna 1999).

Primate Populations

Forest fragmentation has become a principle focus of conservation and ecological research

on organisms in tropical regions, including primate populations (Lovejoy et al. 1984; Offerman

et al. 1995; Laurance and Bierregaard 1997; Schelhas and Greenberg 1996; Harrison and Bruna

1999; Clarke et al. 2002; and Laurance et al. 2002). Research on the effects of deforestation on

primates has largely focused on habitat degradation, reduction, and isolation (Andren 1994;

Marsh 2003). When primate populations are isolated from each other due to habitat

fragmentation, continued habitat decline (including human encroachment and hunting) further

endangers these populations (Rylands et al. 1995; Estrada and Coates-Estrada 1996; Crockett

1998; Estrada et al. 1999). How severe a disturbance is to a primate species depends on the

composition and spatial layout of remaining habitat patches, such as shape, size, isolation from

other habitat patches, and amount of edge habitat (Saunders et al. 1991; Collinge 1996).

Concern for the black howler (Alouattapigra) stems from substantial habitat loss (56%)

within the howler's range with a predicted 70% population decline over the next 30 years if

trends continue (IUCN 2003). A. pigra occurs in Belize, northern Guatemala, and parts of

Mexico (Campeche and Quintana Roo, northern Chiapas, and parts of Tobasco states) (Horwich

and Johnson 1986). Black howler monkeys are found primarily in low altitude areas under 1,000

ft. (300m) asl, and in riparian and seasonally flooded forests (Freese et al. 1982; Horwich and

Johnson 1984; Horwich and Lyon 1990; Horwich 1998; Silver et al. 1998). Although A. pigra is

classified at a low risk of extinction according to the Mace-Lande system (Rylands et al. 1995),

their restricted geographic distribution in habitats that are being rapidly fragmented and

converted to agriculture and pasture places this primate species at risk (Estrada et al. 2006).









Some scientists believe A. pigra's preference for riverine and seasonally flooded forests explains

its narrow distribution, compared to other howler species (Horwich and Johnson 1986; Estrada et

al. 2002).

Their association with riverine areas has been explained by the high numbers of figs

(Ficus spp.), an important food source with fruits available throughout the year (Milton 1991)

that affects population and troop size (Horwich and Johnson 1986). A study by Estrada and

Coates-Estrada (1984) in Los Tuxtlas, Mexico found A. palliata spent an average 49% of their

feeding time monthly eating Ficus spp. fruits. Within the Community Baboon Sanctuary, Belize,

Ficus spp., especially fruits and leaves of strangler figs, are an important year-round food source

(Estrada and Coates-Estrada 1984), which also may point to howlers as important fig dispersers

in areas with high howler populations (Marsh 1999). Ficus spp. has been considered to play an

important role in howler conservation (Coates-Estrada and Estrada 1986; Milton 1991; Serio-

Silva et al. 2002) and has even been suggested as a keystone tropical forest resource (Terborgh

1986). Ficus spp. are also considered forest-fringe species, found both along river edges and

forest edges (Estrada et al. 2000; Kratter et al. 2001; Andrews and Bamford 2008) which would

increase their availability in fragmented forest environments.

Initial concern for A. pigra was stimulated by Smith (1970) who suggested they prefer

"extensive, undisturbed and mesic tropical forest" (p. 365). More recent studies, however,

suggest A. pigra inhabit a wider range of evergreen and semi-evergreen forests, including

disturbed and riverine forests (Crockett 1997). Indeed, Marsh (1999) regularly observed A. pigra

using forest edges for feeding, traveling, resting and howling, while Jones (1995) suggests A.

pigra's high reproductive rates, their ability to colonize new patches and their folivorious diet of









leaves, which in comparison to flowers and fruits are an abundant and stable source of food, may

even contribute to their survival in fragmented habitats.

Black howler monkeys typically live within troop sizes under 10 individuals (Horwich and

Gebhard 1983; Ostro et al. 2001), with territory size ranging from 3 to 25 acres (Horwich 1998;

Belize Zoo 2006). Small troop size may be an adaption for surviving in fragmented habitats

(Ostro et al. 1999) and a function of resource distribution (Chapman and Chapman 1990).

However, mean troop size in continuous forest was 3.16 individuals at Muchukux, Quintana Roo

(Mexico) (Gonzales-Kirchener 1998) and 6.3 individuals at Tikal, Guatemala (Coelho et al.

1976), while in fragmented riverine forests in Belize, troop size was between 3 and 9 individuals

(Silver et al. 1998). Howlers typically have smaller home ranges (<10 ha) than other primates,

which may explain their persistence in forest fragments (Crockett and Eisenberg 1987). A. pigra

is generally found to have the lowest densities of howlers (Chapman and Balcomb 1998).

However, in reports from the Community Baboon Sanctuary, Belize, population densities were

among the highest documented in the literature for A. pigra, with population densities reported as

high as 178 individuals per km2 in 1999 (Horwich et al. 2001), up from 31.9 per km2 in 1985

(Jones and Horwich 2005). This suggests tolerance of A. pigra to habitat reduction and

fragmentation but may also suggest a high animal load on the resources present (Estrada et al.

2002)

For primates in general, body size and habitat specialization have been considered the most

important parameters related to extinction. However, diet requirements and social structure are

also important survival factors, considering howlers are still found in small forest fragments

despite being one of the largest New World primates (Marsh 1999), weighing between 15-20 lbs

/ 6-7 kg (Horwich and Lyon 1990). Black howlers are best described as "folivore-frugivores"









(Crockett and Eisenberg 1987) with studies in the Community Baboon Sanctuary, Belize

showing young leaves accounting for 37% and fruit 41% of their diet (Sliver et al.1998). In

addition, a study of 2519 trees sampled in adult tree transects of troop home ranges, 71% were

used by howlers (Marsh 1999). Bernstein et al. (1976) attributes howler adaptability to

fragmented environments following agricultural expansion in northern Columbia to their flexible

diets. It is thought that the howler is able to minimize energy expenditure through small home

ranges (and short day ranges), relatively small troop size, and highly folivorous and flexible diets

which, combined, improves conservation likelihood (Milton 1980; Estrada et al. 1999; Bicca-

Marques 2003; Fuentes et al. 2003).

Belize Forests

Deforestation and increasing human population are causing declines of fauna throughout

most of the tropics but the forests of Belize have been a concern for conservation biologists since

the 1980's (Parker et al. 1993). Beginning in the 1980's, Belize was thought to be 97% forested

with only a 0.2 % annual forest loss. During 1990-2000, however, Belize's deforestation rate

(2.3% per year) surpassed that of Central America (1.2% per year) (DiFiore 2002) and forests in

Belize now total only 59% of the total land cover (FAO 2001), with trends showing agricultural

intensification replacing forested landscapes (PfB 2000). In north-central Belize deforestation

has been more severe with only 30% of the original forest cover remaining (King et al. 1992).

The main activities encouraging deforestation and fragmentation of remaining forests in Belize

are cattle ranching, large-scale agriculture, milpas (small-scale slash and bum farming), urban

growth, and logging (Horwich and Lyon 1990).

Study Objectives

Along with retaining certain habitat areas, conservation strategies are increasingly

focusing on the spatial configurations of habitat across landscapes (Thomas et al. 1990; Pulliam









et al. 1992). How severe a disturbance is to a primate species depends on the composition and

spatial layout of remaining habitat patches, such as shape, size, isolation from other habitat

patches, and amount of edge habitat (Saunders et al. 1991; Collinge 1996). Considering some of

the most threatened primate communities now survive only in fragmented forest habitats

(Cowlishaw and Dunbar 2000; Marsh 2003), the quality and spatial characteristics of forest

fragments plays an important role in understanding how to best conserve and manage current

populations (Lindenmayer 1999; Chapman and Lambert 2000; Harcourt 1998, 2002; Fahrig

2003; Marsh 2003). To understand the tolerance of A. pigra to habitat fragmentation,

information on forest fragmentation and rates of forest loss, along with demographic information

for A. pigra populations is needed (Estrada and Coates-Estrada 1996; Cuar6n 2000). In addition,

information linking data from such sources as satellite imagery, forest cover, habitat

fragmentation, and human land-use patterns, among others, is also needed to better understand

relationships between areas of human population and primate survival (Garber et al. 2006).

This study assessed forest fragmentation within the Community Baboon Sanctuary

(CBS), Belize, a community reserve that has existed since 1985 with little monitoring of

deforestation and, more specifically, forest habitat fragmentation for the black howler monkey,

the impetus for the creation of the CBS. This study focuses on the following objectives:

1. To examine forest cover change of the CBS landscape and 500 meter river buffer from two
time periods over 15 years (1989 and 2004);

2. To assess how forest habitat for the black howler monkey has changed over this 15 year
time period and how much suitable habitat currently exists (for the year 2004), based on
minimum patch size and distance requirements; and

3. To assess the performance of the CBS as a IUCN Category IV protected area in terms of
forest cover and fragmentation results and howler monkey populations (from past
population surveys).









Methods
Study Site

The Community Baboon Sanctuary (CBS), Belize (170 33'N, 880 35'W), an IUCN

Category IV protected area, was established in 1985 to protect black howler monkey (Alouatta

pigra) populations and their forest habitat (Figure 4-1). As a Category IV protected area, the

conservation focus is defined as an "area of land and/or sea subject to active intervention for

management purposes so as to ensure the maintenance of habitats and/or to meet the

requirements of specific species" (IUCN 1994). The CBS was the effort of two American

scientists and a local non-governmental organization (Belize Audubon Society) who worked

with private landowners of 7 villages to encourage them to pledge to help protect riparian forest

landscapes (Horwich and Lyon 1998) for black howler populations. Located in the climatic

region of north-central Belize, the forests of the CBS are classified as lowland, semi-deciduous

rainforest. Today the CBS is a patchwork of secondary forests from 10-75 years old,

interspersed with cleared areas and secondary growth from 300 years of periodic logging

(Horwich and Lyon 1990).

There are roughly 220 households in 7 villages for a human population density of

-106.38 individuals per km2 (Jones and Young 2004). Although the literature cites the CBS as

an area of 4800 ha (48km2) (Horwich and Lyon 1990), this study incorporates twice this amount

(8703.54 ha) as defined by village boundaries. Although less prevalent as in the past, slash and

burn agriculture ("milpa") is still practiced within the villages, although primarily for home

consumption. Riverine areas are favored for agriculture because of their more fertile soils.

Cattle ranching (both large and small-scale) is also a common livelihood activity, with cattle

often kept by the riverside where they can easily access water.









When the CBS was established, some households signed a voluntary, written pledge to

not clear forest down to the water's edge and to leave a strip of forest between property

boundaries, ensuring greater habitat protection and connectivity for howler monkeys. Although

landowners were not initially paid to pledge, the CBS resident management committee paid

pledged landowners $125 twice (1998 and 2000) (Lash 2003). In addition, tourism focused

around the howler monkey was also established to provide residents financial incentives to

protect forests. Tourist numbers have increased dramatically in the last few years (13,000 in

2005) from the arrival of cruise ship tourism to Belize (see chapter 2). Tourism employment

includes both permanent and seasonal jobs. However, a disproportionate number of families

benefitting from tourism (13 out of 35 total in 2005) are from one village, pointing to an

inequitable distribution of tourism benefits and participation which have caused dissatisfaction

and resentment towards current CBS management (see chapter two).

Despite these concerns toward CBS management and the conservation initiatives, black

howlers are not threatened by local residents. Howlers only occasionally damage crops, and are

rarely killed as agricultural pests (Crockett 1997). Furthermore, past studies show positive views

towards howlers and howler protection, with residents recognizing their local abundance and

tourism attraction (Hartup 1994; Bruner 1992). Additionally, the howler's survival is greatly

improved as the only primate species within the CBS with little hunting or predation threats

(Jones and Young 2004; Silver et al. 1998).

The Community Baboon Sanctuary Howler Populations

Howler populations and population densities within the CBS appear to have been

expanding rapidly since 1985 (Table 4-1) from an estimated 800 individuals in 1985 to an

estimated 3000 5000 individuals in 2003 (Brocket 2003). The last population density survey









was conducted in 1997, and howler population densities were estimated as high as 178

individuals per km2 in 1999 (Horwich et al. 2001), the highest ever recorded in the literature for

A. pigra. Howler surveys were conducted using similar methodology. In 1985 and 1999,

surveys were carried out within a 4.05km2 study area (1985) and in a 0.63km2 primary study site

(from 1990 to 1999) (Jones et al. 2008). These actual counts of howlers were then multiplied by

the CBS area to estimate the total population (Horwich pers.comm. 2008). The survey

conducted in 2003 was carried out in a similar manner: 1581 individuals were counted covering

a portion of each of the 7 CBS villages.

Remote Sensing

Remote sensing enables an assessment of the CBS to protect forest habitat of the black

howler monkey (Alouattapigra) and offers a unique opportunity for long-term assessment. A

change detection analysis of the forest landscape on a spatial and temporal scale evaluated the

rates and trends of forest change over 15 years (1989 and 2004) of the CBS and within a 500

meter buffer of the Belize River (within the CBS). Image processing and spatial analyses were

performed in Erdas Imagine and ArcGIS.

A 1989 Landsat TM image and a 2004 Landsat ETM+ were used to analyze spatial

distribution and extent of forest cover within the CBS and within a 500 meter river buffer along

the Belize River. Images were taken between November and December, both considered to be

within the dry season, to decrease the impacts of seasonal variations on biophysical properties

and change detection analysis processes (Jensen 2005).

Radiometric calibration and atmospheric correction procedures (Green 2000) were

conducted to correct each Landsat band for sensor, illumination, and atmospheric sources of

variance to ensure that the change detection analysis truly detected changes at the Earth's surface









(Jensen 2005). Geometric correction of the 2004 image was performed using a 1:50,000 scale

map of the study area from the Land Information Center (LIC) in Belize (UTM Zone 16, WGS

1984). Image-to-image registration was then performed using points from the already rectified

2004 image to register the 1989 satellite image. The root mean square (RMS) error of each

registration was maintained below 0.5 pixels (<15 m).

Ground truthing of the 2004 image was conducted from September through December,

2005 within the CBS. Training sample protocol forms from the Center for the Study of

Institutions, Population, and Environmental Change (CIPEC) were used (CIPEC 1998), and

locations were recorded with a GPS (global positioning system). Other qualitative descriptions,

including photographs, were recorded for reference and comparison with classified maps and

satellite imagery. Informal interviews with landowners and personal observations added

information on the nature and extent of land uses. Training samples covered a 90 x 90 m area to

ensure that at least one full pixel fell within that particular land cover. Sixty-six training sample

points were taken (31 for "forest" and 35 for "non-forest"), including as many different types of

land cover in and around the CBS as possible. Although training samples within the CBS were

primarily taken along roads or along the Belize River, vantage and edge training sample points

were also taken in areas difficult to access. The forest class was defined as having a canopy

cover of 25% or above. This was based on two sources of data: data from a study conducted

within the CBS that estimated deciduous forest habitat to have 40-75% canopy cover and

riparian forest habitat to have 65-100% canopy cover (Jones unpubl. data) and an estimate by

Horwich (personal comm. 2008) based on knowledge of howlers' tolerances to some disturbance

and less dense forests, including their preferences for certain vegetative growth.









A hybrid supervised / unsupervised classification with 60 classes was conducted on the

2004 image, using collected training samples and GPS point data. Clouds were first removed

from both images and a mask was then applied to each image prior to classification. After

classifying the various land cover classes, non-forest classes (both natural and anthropogenic

non-forest areas) were merged into a final non-forest class (NF). The other class was a forest (F)

class. An accuracy assessment on the 2004 classified image resulted in a producer's accuracy of

86% (F) and 84% (NF) and a user's accuracy of 81% (F) and 89% (NF) for an overall

classification accuracy of 85% and an overall Kappa Statistics of 69%. Thomlinson et al. (1999)

set as target an overall accuracy of 85% with no class less than 70%. The 1989 image was

classified through comparison with signature mean plots of 2004 classes, and also contrasting

vegetation in ArcGIS using the NDVI (Normalized Difference Vegetative Index) and the thermal

band. The result of the classification process was the creation of "forest" and "non-forest"

classifications for the two image dates (Figure 4-2).

Landscape Metrics

Landscape ecology explains the ecological effects of spatial arrangements, especially

interactions between the landscape's structure and function over time. Quantification of

landscape patterns improves understanding of these interactions between landscape structure and

ecological processes (Turner et al. 2001). Measuring fragmentation (e.g., habitat fragmentation

and forest fragmentation) is one way to quantify landscape pattern. The effects of forest loss and

fragmentation can be interpreted with landscape metrics that quantify specific spatial

characteristics of patches, classes of patches, or entire landscape mosaics (McGarigal and Marks

1995; He et al. 2000). The sensitivity of landscape metrics to changes in levels of forest loss also

shows their importance in assessing and monitoring forest fragmentation (McGarigal and Marks









1995; Trani and Giles 1999). Fragstats software (McGarigal et al. 2002) was used to run

landscape metrics on the 1989 and 2004 classified images (F and NF). The following metrics

were analyzed: patch size, total patch count, mean patch area, median patch area, ENN (Patch-

level analysis) and Clumpy metrics (Class-level analysis). Given the important habitat needs

(size, number of patches) and dispersal (distance between patches, patch aggregation), these

metrics are functional metrics that explicitly measure landscape pattern that is relevant to the

species under consideration.

The Euclidean Nearest Neighbor distance (ENN) metric measures the distance (in

meters) to the nearest neighboring patch of the same type, based on shortest edge-to-edge

distance, and is used extensively to quantify patch isolation. The clumpiness index (CLUMPY)

metric measures pixel adjacencies (the frequency that a patch type appears next to another

similar patch type on the map) (McGarigal and Marks 1995). With a range between -1 and +1,

"-1" indicates the focal patch type is maximally disaggregated, "0" indicates the focal patch type

is distributed randomly, and "1" indicates the patch type is maximally aggregated. To assess the

suitability of howler monkey habitat using fragmentation metrics, the following criteria was

used:

1. A forest patch must be greater or equal to 3 acres (1.21 ha) (Horwich 1998; Belize Zoo
2006).

2. To be considered connected, forest patches must be less than or equal to 60 meters apart.
Although 50 meters appears to be the more appropriate distance, based on a studies by
Onderdock and Chapman (2000) and Pozo-Montuy and Serio-Silva (2003) and Horwich
(personal comm. 2007), 60 meters was chosen as the distance because of the 30 meter
pixel size of the satellite image used.

For statistical analysis, Chi-square tests were conducted to assess whether ENN (using

the proportion of patches that met this requirement) differed significantly (p < 0.05) across dates.









Results

In 2004, 47.61% of the CBS landscape was comprised of forest, a decrease of 23%

compared to 1989 (70.87%) (Table 4-2 and Figure 4-2), with similar results for the 500 meter

buffer of the Belize River, decreasing from 74.34% in 1989 to 50.64% in 2004 (Table 4-3 and

Figure 4-3).

Landscape Fragmentation

The total number of forest patches within the CBS landscape in 2004 (n=1323) was more

than twice that amount in 1989 (n=628), with the mean patch area in 2004 decreasing by one-

third (Table 4-4). The number of forest patches that met the 3 acre or greater area requirement

was 48 of 628 (7.64%) in 1989 and 102 of 1323 (7.71%) in 2004. Although the mean patch area

in 2004 decreased by one-third, the median patch size for both years was the same (Table 4-4).

This can be explained by several large patch sizes in 1989 that adjusted the average size.

Considering forest patches must be less than or equal to 60 meters apart to be considered

connected (howler habitat requirement), the ENN metric result indicates that in 1989, 510 of 628

(81.2%) of the CBS forest patches were within this 60 meter distance from other forest patches.

In comparison, in 2004 1025 of 1323 (77.5 %) forest patches within the CBS were within this 60

meter distance from other forest patches (Table 4-4). For patches greater than or equal to 3 acres

in size, 44 of 48 (91.7%) patches within the CBS in 1989 and 96 of 102 (94.1%) patches within

the CBS in 2004 met this criteria (Table 4-4). A Chi-square test confirmed the proportion of

CBS forest patches greater or equal to 3 acres in size that had other forest patches within 60

meters did not differ significantly (p = 0.57) across dates.

The patch level analysis of the 500 meter river buffer shows comparable patterns to the

larger CBS landscape. The total number of forest patches within the river buffer in 2004

(n=669) was greater than twice that amount in 1989 (n=267). Although the mean patch area in









2004 decreased by over two-thirds, the median patch size for both years was the same (Table 4-

4). This can be explained by several large patch sizes in 1989 that adjusted the average size.

The number of forest patches that met the 3 acre or greater area requirement was 17 of 267 total

forest patches (6.4%) in 1989 and 64 of 669 (9.6%) in 2004.

The ENN metric result indicates that in 1989, 233 of 267 (87.3%) forest patches within

the 500 meter river buffer were within this 60 meter distance from other forest patches. In

comparison, in 2004 545 of 669 (81.5%) forest patches within the 500 meter river buffer were

within this 60 meter distance from other forest patches (Table 4-4). For patches greater than or

equal to 3 acres in size, 16 of 17 (94.1%) patches within the river buffer in 1989 and 62 of 64

(96.9%) patches within the river buffer in 2004 met this criteria (Table 4-4). A Chi-square test

confirmed forest patches greater or equal to 3 acres in size within the river buffer did not differ

significantly (p = 0.59) across dates.

Clumpy values for both forest and non-forest patches only decreased slightly in 2004

compared with 1989 values (Forest = 0.6599 [1989], 0.6499 [2004]; Non-forest = 0.6602 [1989],

0.6455 [2004]). Values for both forest and non-forest patches indicate these classes are fairly

aggregated within the CBS landscape (Table 4-5). Clumpy values within the 500 meter river

buffer are similar for both forest and non-forest classes across both time periods (Table 4-5).

CONNECT metric values, however, show forest patches were 78% connected in 1989 but

dropped to only 26% connectivity in 2004. Non-forest patches were slightly more connected in

2004 (21%) compared to 1989 (14%) (Table 4-5).

Discussion

Forest cover declined for both the CBS and 500 meter river buffer by roughly 23%

between 1989 and 1994 (Table 4-2). This 23% decrease within the CBS follows similar trends

for Belize with a 20% decrease in forest cover since the early 1980's (FAO 2007). In addition,









there has been a magnitude increase in the number of total forest patches from 1989 to 2004 in

both the CBS and 500 meter buffer. Although the number of forest patches has increased,

indicating increased forest fragmentation, overall the patch size has not changed.

Although only a small proportion of forest patches meet the 3 acres or greater size

criteria, the majority of patches are highly connected to eachother, indicating dispersal potential

has not been jeopardized. Additionally, both forest and non-forest patches within the CBS

landscape and 500 meter river buffer are highly aggregated. Aggregation of forest patches is

beneficial for howler movement. However, the fact that non-forest patches are also aggregated

may impact movement across these areas and create increased fragmented 'islands' of forest and

non-forest habitats.

Current Suitable Howler Habitat

Using habitat criteria for the howler monkey (forest patches greater than or equal to 3

acres and less than or equal to 60 meters apart) to assess the current suitability of habitat, in 2004

this comprised 44.72% of the CBS landscape and 46.74% of the 500 m river buffer landscape

(Table 4-6). Considering a landscape with less than 30% habitat connectivity is considered poor

fragment connectivity (Mandujano et al. 2006), the CBS has not yet met this threshold.

Although howlers may need forest patches greater than or equal to 3 acres for survival processes

(foraging, nesting, etc.), howlers can still move through forest patches less than 3 acres in size, as

long as they are less than or equal to 60 meters apart (e.g., forest corridors for travel).

Considering this, forest patches that meet the 60 meter distance requirement from other forest

patches comprise 44.86% of the CBS landscape and 49.79% of the 500 meter buffer landscape.

(Table 4-6).









Howler Populations

As part of a re-introduction project, sixty-two monkeys were translocated from the CBS

to Cockscomb Basin Wildlife Sanctuary in Southern Belize in 1993-1994 (Koontz et al. 1993).

Despite this translation, in addition to increased deforestation and forest fragmentation of the

CBS landscape and 500 meter river buffer, black howler monkey populations have increased

from an estimated 800 individuals in 1985 to an estimated 3,000-5,000 individuals in 2003

(Brockett 2003) (Table 4-1); several factors may explain this.

First, the flexible diet ofA. pigra appears to be an important factor contributing to its

continued subsistence within the CBS. Habitat disturbance has less effect on primate species

that rely on leaves for their diet (Crockett 1997), with folivores recovering much faster from

habitat disturbance than frugivores (Johns and Skorupa 1987). A. pigra's description as a

"folivore-frugivore" (Crockett and Eisenberg 1987) and their dietary flexibility (Milton 1980;

Silver et al. 1998) probably explains their ability to subsist in a variety of habitats, including

forest fragments (Horwich and Johnson 1986; Crockett 1998; Ostro et al. 1999). Spider

monkeys, in comparison, are less flexible in food species selection and often cannot survive in

fragmented areas (Neville et al. 1988). Riviera and Calme (2005) found in the Calakmul

Biosphere Reserve, Mexico that within fragmented forest environments, howler monkeys would

diversify their diet where their preferred fruit and leaf species were absent.

Secondly, the availability of figs (Ficus spp.) within the CBS probably has a strong role

in black howler persistence. The common cohune palm (Orbigyna cohune) which is left uncut

due to difficulty in felling and its usefulness for products and shade, is highly infested by

strangler figs (42-86%) which are an important food source for the howlers (Lyon and Horwich

1996). Ficus spp. are also considered forest-fringe species, both along river edges and

fragmented forest edges (Andrews and Bamford 2008; Kratter et al. 2001; Estrada et al. 2000).









Therefore, increased fragmentation within the CBS has most likely increased Ficus spp. growth

and availability. In fact, a study by Marsh (1999) concluded that the forest fragments within the

CBS are exceptionally good habitat for the howlers because the availability ofFicus spp. and

other fruiting species found in fragments.

Thirdly, howler populations can increase dramatically from disease, hurricanes, and

drought where they, and their habitats, are protected (Crockett, 1996; Crockett and Eisenberg,

1987; Horwich and Lyon, 1987) and can exist in disturbed and fragmented forests, and in close

proximity to human populations, when there are no hunting pressures (Crockett 1997).

Considering howlers are not hunted within the CBS and have few predators, these factors may

also contribute to the growing population of howlers within the CBS. It is not well-known if the

estimated population of howlers within the CBS in 1985 (800 individuals) was recovering from a

population decline or had been stabilized at this population level for some time. Howlers

throughout Central America have undergone four known population declines that have affected

both the population sizes and the behavioral dynamics of remaining troops. Devastating

hurricanes in 1931, 1954, and 1978 swept through the CBS (Bolin 1981; Hartshorn 1984), and in

1971, a yellow fever epidemic decimated Central American howler monkeys (Baldwin 1976;

Hartshorn 1984). However, the first documented population survey of howlers within the CBS

occurred in 1985.

It should be noted that along with howler population increases within the CBS, howler

population densities have also dramatically increased over the past 20 years. Past studies within

the CBS indicate howler densities have increased from 31.9 individuals per km2 in 1985 (Jones

and Horwich 2005) up to as high as 178 individuals per km2 in 1999, overcrowding forest

fragments (Silver et al.1998; Ostro et al. 1999; Horwich et al. 2001). Additionally, the 2003 CBS









suvey (Brockett 2003) found increased overlap in troop home ranges, multi-male troops, and the

first documented observance of infanticide associated with male takeovers, all of which is

attributed to high population densities (and none of which had been observed in past surveys).

Although howlers appear to be adaptable to habitat fragmentation and have increased in

number within the CBS over the past 20 years, in the long run increased forest fragmentation

may not ensure their population viability (Bicca-Marques 2003). For example, even though

howler monkeys have been found to travel across cornfields and grasslands in Mexico (Pozo-

Montuy and Serio-Silva 2003; Mandujano et al. 2004), long-distance terrestrial movement of

arboreal primates is relatively uncommon and most likely reflects a scarcity of resources such as

food, shelter and refuge from predators (Waser et al. 1994; Bennett 1998; Olupot and Waser

2001; Baum et al. 2004). There are likely decreases in reproductive potential and inbreeding if

fragmentation impacts connectivity and prevents dispersal opportunities between forest

fragments (Crockett 1998; Estrada and Coates-Estrada 1996; Clarke et al. 2002). Neotropical

primates in isolated fragments (inhibiting migration) that experience population declines below a

certain threshold are prone to extinction (Coehlo et al. 1976).

Limitations

The distance between forest patches primates will travel is not well known or

documented within the literature and has only been estimated by a few studies, ranging from 50

m (Onderdock and Chapman 2000) to 80 m (Pozo-Montuy and Serio-Silva 2003) to 150 m

(Mandujano et al. 2006) to 2.6 km (Estrada et al. 2002). It is possible this study may have

underestimated the distance black howlers will travel between forest patches (60 meters) but the

distance was chosen with consideration from these studies' estimates and estimates by Horwich

(personal comm. 2007). Considering the 30 m pixel size of the satellite image used (Landsat),









and the Fragstats software's method for measuring distance (cell center to cell center), the

chosen distance needed to link with the 30 m pixel size.

Continued monitoring should be conducted within the CBS on both howler population

and densities and forest cover change and fragmentation to better advise community

management decisions. As metapopulation theory predicts a low probability of persistence (on a

regional scale) if occupation of fragments are limited, combined with a decrease in colonizing

empty fragments (Ovaskeinen and Hanski 2004), future research within the CBS could

complement and build on this study by identifying the occupied and unoccupied patches within

the CBS, including their size and distance to other patches, to better assess dispersal and

persistence probability.

Conclusion

This study examined forest cover change of the CBS landscape and 500 meter river

buffer covering two years over a 15 year time period (1989 and 2004) and assessed

fragmentation of forest habitat for the black howler monkey based on minimum patch size and

distance requirements. Results show a 23% decrease in forest cover within the CBS and the 500

meter buffer between 1989 and 2004, with increased fragmentation of forest habitat. However,

connectivity between habitat patches (less than or equal to 60 meters apart) is presently high

(81.5% of the 500 m buffer forest habitat and 77.5 % of CBS forest habitat) which indicates

dispersal and colonizing between most forest patches has not been jeopardized.

Reaching a verdict on the effectiveness of conservation within the CBS may be a little

more complex than merely saving forests and, therefore saving howlers within the CBS, as

increased fragmentation actually provides better habitat forficus spp. (e.g., figs), the preferred

food source for howlers. As an IUCN Category IV protected area, the aim is "...to ensure the

maintenance of habitats and/or to meet the requirements of specific species" (IUCN 1994).









Therefore, if the conservation objective is the howler monkey, one could say the CBS appears to

be succeeding. However, if the objective is forest preservation, it is not. If trends continue, at

some point deforestation and fragmentation will reach a level where dispersal among patches is

not possible or population densities reach their carrying capacity and populations begin to

decline. This may signal that the CBS should not be managed for a single (or narrow) outcome

(e.g., howlers) as IUCN Category IV protected area designation provides. With a concern that

residents have realized few financial benefits from tourism and cooperative agreements intended

to deter deforestation (pledge) (see chapter 2), this may necessitate the development or

improvement of conservation initiatives within the CBS that will result in realized collaborative

conservation action for forest preservation.











United States


Gulf of Mexico


N

W E
S


Community Baboon Sanctuary, Belize


Legend
SCBS boundary
Qrn Belize River, ,
Roads / ,


Mexico



SUL Th.m Kilometers
00.51 2 3 4

E






Belize









Figure 4-1. Map of the Community Baboon Sanctuary in Belize, Central America













































Legend
]Beize Rinver

Non Forest
No Data


Figure 4-2. CBS forested and non-forested landscape. A) in 1989 and B) in 2004


E-ll--c P..-.
Forest
SNon-Forest
I No Data













500 meter River Buffer (1989)



-Q M


rL~ LuL l5KIrneferr
0 D.5 1 2 3 4


Legend
Belize River
M Forest
M Non Forest
m No Data


500 meter River Buffer (2004)


t


IL f1 Ki:lomoners
0 05 1 2 3 4


Legend
Belize River
Forest
Non Forest
W No Daa


A B
Figure 4-3. CBS 500 meter river buffer landscape. A) in 1989 and B) in 2004









Table 4-1. CBS black howler monkey population and population density estimates
Year Howler population Source Howler density Source
(individuals) estimates (individual / km2)
1985 800 Brockett 31.9 Jones and
(2003) Horwich (2005)
1997 > 1,500 In Lash 178 (in 1999) Horwich et al.
(2003) (2001)
2003 3,000 5,000 Brockett Not available
(2003)



Table 4-2. Area (ha) and percent land cover of CBS forested and non-forested landscapes in
1989 and 2004
Year Landscape Total Area % Land
(ha)


Forest
Non-Forest

Forest
Non-Forest


6167.79 70.87%
2535.75 29.13%


4144.05
4559.49


47.61%
52.39%


Table 4-3. Area (ha) and percent land cover of forested and non-forested CBS 500 meter river
buffer landscape in 1989 and 2004
Year Landscape Total Area % Land
(ha)
1989 Forest 2231.37 74.34%
1989 Non-Forest 770.4 25.66%


Forest
Non-Forest


1520.01 50.64%
1481.76 49.36%


1989
1989

2004
2004


2004
2004









Table 4-4. Forest Patch Level Analysis of the CBS landscape and 500 meter river buffer. Forest
patch level analysis of the CBS landscape and 500 meter river buffer from two
different years (1989 and 2004) from the following metrics: number of patches > 3
acres, total number of patches, mean patch area, median patch area, # ENN patches
for total patches and for patches > 3 acres.
Landscape Year # Patches > Total # Mean Median #ENN #ENN
3 acres Patches Patch Patch Total patches >
(1.21 ha) Area (ha) Area (ha) patches 3 acres
CBS 1989 48 628 9.8213 0.09 510 44
CBS 2004 102 1323 3.1323 0.09 1025 96

River 1989 17 267 8.3572 0.09 233 16
River 2004 64 669 2.2721 0.09 545 62




Table 4-5. Class Level Analysis of the CBS landscape and 500 meter river buffer. Class level
analysis of forested and non-forested patches within the CBS landscape and 500
meter river buffer from two different years (1989 and 2004) from Clumpy metric.
Landscape Vegetation Year Clumpy
CBS Forest 1989 0.6599
CBS Non-Forest 1989 0.6602
CBS Forest 2004 0.6499
CBS Non-Forest 2004 0.6455

River Forest 1989 0.4981
River Non-Forest 1989 0.5338
River Forest 2004 0.5494
River Non-Forest 2004 0.5540









Table 4-6. Suitable howler habitat. Suitable howler habitat looking at two different criteria: A)
forest patches < 60 m from another and B) forest patches > 3 acres (1.21 ha) and
forest patches < 60 m from another) in 2004 within two different landscapes (entire
CBS area and 500 meter river buffer within the CBS).
Criteria Landscape Year % of landscape
A. Forest patch < 60 m from another CBS 2004 44.86%
River 2004 49.79%
B. Forest patch > 3 acres AND CBS 2004 44.72%
forest patch < 60 m from another River 2004 46.74%









CHAPTER 5
CONCLUSION

Although there have been several social science research studies conducted within the

CBS (Bruner 1993; Hartup 1994; Alexander 2000; Lash 2003; Jones and Young 2004), a

comprehensive study that connects household information to conservation practices, forest cover

change, and habitat fragmentation did not exist. Therefore, the overarching objective of this

dissertation was to provide an overview of conservation within the CBS. Specifically, this

research consisted of the following objectives:

Objective 1: Assess perceived benefits and place-based meanings of riparian forest landscapes,

Objective 2: Assess the relative influence of tourism and pledging on deforestation probabilities,

in addition to other locational and socio-economic variables, and

Objective 3: Assess forest fragmentation for the black howler monkey based on habitat criteria

Perceived Benefits and Place-Based Meanings of Riparian Forest Landscapes

Although results show tourism and pledging initiatives may be considered financial

failures by residents, those involved in these initiatives value, benefit from, and feel attached to

the forest for a variety of non-financial reasons. This study showed a significant relationship

exists between initiative involvement (pledging or tourism) and higher perceived benefits

(importance) and place attachment (meanings) towards riparian forests and conservation.

However, all residents interviewed, regardless of initiative involvement, agreed that riparian

forests are not providing financial benefits. Regardless, this study shows that involvement in

either conservation initiative, whether they are financially successful or not, is related to higher

conservation values and perceived community benefits and is a strong basis for conservation.









Relative Influence of Factors on Deforestation Probability

In an attempt to assess what factors may be driving deforestation or actually decreasing

deforestation probability, this study examined the relative influence of locational, land tenure,

socio-economic, socio-demographic, and conservation initiative variables. From the variables

applied to all modeled time periods, trends show areas closer to the Belize River are more likely

to be deforested, as are areas closer to road networks. Additionally, having secure land title

decreases the probability of deforestation, although this did not have strong strength of effect in

the last modeled time period (2000 2004). Looking at influential socio-economic variables

from the 2000 2004 modeled time period with strong effect strength, agricultural and cattle

activities are influential in increasing deforestation probability, while higher levels of household

head education decreased deforestation probability.

Pledging was shown to increase deforestation probabilities during the 1989 2000

modeled time period, a decrease during the 1994 2000 modeled time period, and an increase

during the 2000 2004 modeled time period. Tourism, a variable that was only able to be

accurately measured during the 2000 2004 time period, indicated an increase in deforestation

probability. Although involvement in either of these initiatives during the 2000 2004 time

period did not show a decrease in deforestation probability, the combination of being involved in

both tourism and pledging actually decreased deforestation probabilities during 2000 2004.

This indicates that having both the values of pledged residents (whether the pledge influenced

these residents or these residents had these conservation values to begin with is not known) and

the income from tourism participation may actually create a stronger connection between tourism

dollars received from the resource attraction (the howler monkey) and the habitat (forests) it is

dependent upon.









Although some of these variables have strong influence with the models created,

goodness of fit values (pseudo R2) indicate that they only explain a small proportion of

deforestation within the CBS and suggest there are other variables not included in the model that

are more influential at explaining deforestation probability within landowner parcels (e.g.,

biophysical and institutional). Nevertheless, this study helped to explore and identify the

relevant influence of some of the factors affecting deforestation.

Forest Habitat Fragmentation

Overall landscape trends within the CBS between 1989 and 2004 indicate there has been

a 23% decrease in forest cover within the CBS and 500 meter river buffer, along with increased

fragmentation of forest habitat. This coincides with the 20% decrease in forest cover for Belize

since the early 1980s (FAO 2007). Additionally, the second largest proportion of the CBS

landscape and the largest proportion of a 120 meter river buffer follows the "tending towards

deforestation" land cover trajectory. Since the 120 meter river buffer analysis outside the CBS

followed the same trajectory as the 120 meter river buffer within the CBS, riparian forests are

not anymore protected within the CBS, despite it being labeled as a "sanctuary" and considered a

protected area.

Despite increased deforestation and fragmentation within the CBS, the black howler

monkey (Alouattapigra) possesses many traits that make it adaptable to increased habitat

fragmentation. Additionally, it should be noted that howler populations have increased

dramatically over the past 20 years within the CBS, from an estimated 800 individuals in 1985 to

3,000 5,000 individuals in 2003 (Brockett 2003). A preferred food source for the howler, the

fig (Ficus spp.), is a forest-fringe species found along the river and in forest fragments.

Therefore, the fragmented forests have actually been beneficial for the howlers in providing this

important food source.









Despite increased fragmentation and deforestation, connectivity between forest patches

has remained high indicating dispersal and colonizing potential between most forest patches has

not been jeopardized. However, continuing trends of increased deforestation and fragmentation

of CBS forest habitat, along with reported increases in howler population densities, will likely

place increased pressure on these populations.

Conclusion

Conservation within the CBS may be a little more complex than simply saving forests

and, therefore saving howlers, as increased fragmentation actually provides better habitat for

ficus spp. (e.g., figs), the preferred food source for howlers. The CBS falls under the IUCN

Category IV protected area designation with the aim "...to ensure the maintenance of habitats

and/or to meet the requirements of specific species" (IUCN 1994). Under this designation, one

could say the CBS has been successful in protecting and maintaining howler populations, as

documented by increases in their population. However, if the conservation objective is forest

preservation, the 23% decrease in forest cover and increased forest fragmentation would point to

conservation failure.

The concerns for the future of the CBS are the continued trends in deforestation and

fragmentation. These trends, if continued, would eventually reach a level that impacts dispersal

among patches or where howler population densities reach a carrying capacity level and

populations would begin to decline. This may signal that the CBS should not be managed for a

single outcome (e.g., howlers) as IUCN Category IV protected area designation provides. As

deforestation is tied to livelihoods of private landowners, closer examination was given to the

two conservation initiatives (tourism and a conservation pledge) established to deter

deforestation.









In closer examination of these two conservation initiatives, the CBS is in a unique

position. A strong basis for conservation does exist and an indication that involvement in both

tourism and pledging had some influence in decreasing deforestation probability between 2000 -

2004. However, without building upon the other influential factors (e.g., financial payment for

pledged residents, distribution of tourism participation and benefits, land tenure, expanding

agriculture and cattle, etc.), these conservation initiatives will not be as effective at promoting

conservation goals within the CBS and will not be able to compete with other opportunities the

land provides. Although these conservation initiatives working together may have some

influence in slowing deforestation within the CBS, this study's findings indicate that both

conservation initiatives must be managed more effectively and equitably to have any other

significant impacts on improving people's attitudes towards riparian forests or actively helping

conserve those forests. Overall, this study reiterates the lesson that the success of any

conservation initiative must be linked to local communities benefiting from their conservation of

biodiversity.









LIST OF REFERENCES


Abdullah, S. A. and N. Nakagoshi. 2007. In Press. Forest fragmentation and its correlation to
human land use change in the state of Selangor, peninsular Malaysia. Forest Ecology and
Management.

Adams, W. and D. Hulme. 2001. Conservation and Community. Changing Narratives, Policies &
Practices in African Conservation. In: African Wildlife and Livelihoods. The Promise and
Performance of Community Conservation (D. Hulme and M. Murphree, eds), pp. 9-24,
James Currey, Oxford, UK.

Adams, W. M., R. Aveling, D. Brockington, B. Dickson, J. Elliot, J. Hutton, D. Roe, B. Vira,
and W. Wolmer. 2004. Biodiversity conservation and the eradication of poverty. Science
306:1146-1149.

Agrawal, A. and C. C. Gibson. 1999. Enchantment and disenchantment: The role of community
in natural resource management. World Development 27(4):629-649.

Alcorn, Janis B. 1993. Indigenous Peoples and Conservation. Conservation Biology 7(2): 424-
426.

Alexander, S. E. 2000. Resident attitudes towards conservation and black howler monkeys in
Belize: the Community baboon sanctuary. Environmental Conservation 27(4):341-350.

Anderson, D. H., R. Nickerson, T.V. Stein, and M.E. Lee. 2000. Planning to Provide Community
and Visitor Benefits from Public Lands. In Trends in Outdoor Recreation, Leisure, and
Tourism. ed. Gartner, W.C. and Lime, D.W., 197-212, CAB Publishing, New York, NY.

Anderson, J., J. M. Rowcliffe, and G. Cowlishaw. 2007. Does the matrix matter? A forest
primate in a complex agricultural landscape. Biological Conservation 135(2): 212-222.

Andren, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with
different proportions of suitable habitat-a review. Oikos 71: 355-366.

Andrews, P. and M. Bamford. 2008. Past and present vegetation ecology of Laetoli, Tanzania.
Journal ofHuman Evolution 54(1):78-98.


Angelsen, A. 1999. Agricultural expansion and deforestation: modelling the impact of
population, market forces and property rights. Journal of Development Economics
58:185-218.

Aylward, B. 2003. The actual and potential contribution of nature tourism in Zululand. In Nature
Tourism, Conservation, and Development in Kwazulu-Natal, South Africa (Alward, B.
and E. Lutz, eds), pp. 1-40, The World Bank.









Baldwin, L. A. 1976. Vocalizations of howler monkeys (Alouatta palliata) in Southwestern
Panama. Folia Primatologica 26:81-108.

Bardhan, P. 2002. Decentralization of governance and development. The Journal of Economic
Perspectives 16(4):185-205.

Bates, D. and T. K. Rudel. 2000. The political ecology of conserving tropical rain forests: a
cross-national analysis. Society and Natural Resources 13:619-634.

Baum, K. A., K. J. Haynes, F.P. Dillemuth, and J.T. Cronin. 2004. The matrix enhances the
effectiveness of corridors and stepping stones. Ecology 85: 2671-2676.

Belize Zoo website. http://www.belizezoo.org/zoo/zoo/mammals/how/howl.html Accessed
2/6/2006.

Belsky, J. M. 2000. The meaning of the manatee: An examination of community-based
ecotourism discourse and practice in Gales Point, Belize. In: People, Plants, & Justice.
The Politics ofNature Conservation (C. Zerner, ed), pp. 285-308, Columbia University
Press, New York.

Bem, D. 1972. Self-perception theory. In Pardini and Katzev. 1983-84.

Bennett, A. F. 1998. Movements of animals through linkages. In: Bennett, A.F. (Ed.), Linkages
in the Landscape: The Role of Corridors and Connectivity in Wildlife Conservation.
IUCN, Gland, Switzerland, pp. 67-91. In Anderson, et al., 2007.

Berkes, F. 2007. Community Based Conservation in a globalized world. PNAS 104 (39):15188-
15193.

Berstein, I. S., P. Balcaen, L. Dresdale, H. Gouzoules, M. Kavanah, T. Patterson, P. Neyman-
Warner. 1976. Differential effects of forest degradation on primate populations. Primates
17(3):401-411.

Bicca-Marques, J. C. 2003. How do howler monkeys cope with habitat fragmentation? In Marsh,
L. K. (ed.), Primates in Fragments: Ecology and Conservation, Kluwer Academic/
Plenum, New York, pp. 283-303.

Bierregaard, R. O., Jr. and V. H. Dale. 1996. Islands in an ever-changing sea: The ecological and
socioeconomic dynamics of Amazonian rainforest fragments. In Schelhas, J.; and R.
Greenberg (eds). Forest Patches in Tropical Landscapes. Island Press: California. pp.
187-204.

Binswanger, H. 1991. Brazilian policies that encourage deforestation in the Amazon. World
Development 19(7):821-829.

Bolin, I. 1981. Male parental behavior in black howler monkeys (Alouatta palliatea pigra) in
Belize and Guatemala. Primates 22.349-360.









Boo, E. 1990. Ecotourism: the potentials and pitfalls. World Wildlife Fund: Washington, D.C.

Bookbinder, M. P., E. Dinerstein, A. Rijal, H. Cauley, and A. Rajouria. 1998. Ecotourism's
support of biodiversity conservation. Conservation Biology 12(6): 1399-11404.

Booth, K. L., B. L. Driver, S.R. Espiner, and R.J. Kappelle. 2002. Managing Public Conservation
Lands by the Beneficial Outcomes Approach with Emphasis on Social Outcomes. Doc
Science Internal Series 52. Published by Department of Conservation, Wellington, New
Zealand.

Boots, B. N. and A. Getis. 1988. Point pattern analysis. Sage: Beverly Hills, CA

Brandon, K., K. Redford, and S. Sanderson (eds). 1998. Parks in Peril: People, politics and
protected areas. Washington, DC: Island Press.

Bray, D. B., Merino-Perez, L., Negreros-Castillo, P., Segura-Warnholtz, G., Torres-Rojo, J.M.,
Vester, H.F.M.. 2003. Mexico's community-managed forests as a global model for
sustainable landscapes. Conservation Biology 17:662-677.

Brechin, S. R., P. R. Wilshusen, C. L. Fortwangler, and Patrick C. West. 2002. Beyond the
square wheel: Toward a more comprehensive understanding of biodiversity conservation
as social and political process. Society andNatural Resources 15:41-64.

Brockett, R. 2003. 2003 Howler monkey census. In: Young, C. The common flora and fauna of
the Community Baboon Sanctuary. UNDP /GEF Small Grants Program. Pp. 63-65.

Brown, K., J. Mackensen, S. Rosendo, K. Viswanathan, L. Cimarrusti, K. Fernando, C.
Morsello, M. Muchagata, I. M. Siason, and S. Singh. 2005 in Ecosystems andHuman
Well-Being: Policy Responses (Millennium Ecosystem Assessment and Island Press,
Washington, DC), pp 425-465. In Berkes 2007.

Bruner, G. Y. 1993. Evaluating a model ofprimate-ownership conservation: Ecotourism in the Community Baboon
Sanctuary in Belize. Unpublished master's thesis, Georgia Institute of Technology, Athens

Burger, J., E. Ostrom, R.B. Norgaard, D. Policansky, and B.D. Goldstein. 2001. Protecting the
Commons: A fameworkfor resource management in the Americas. Island Press:
Washington, D.C.

Burkey, T. V. 1995. Extinction rates in archipelagos: Implications for populations in fragmented
habitats. Conservation Biology 9(3):527-541.

Burn, S. M and S. Oskamp. 1986. Increasing community recycling with persuasive
communication and public commitment. Journal ofApplied Social Psychology 16:29-41.

Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: A
practical information-theoretic approach. 2nd edition. New York: Springer.

Ceballos-Lascurain, H. 2001. Integrating Biodiversity into the Tourism Sector: Best Practice
Guidelines Report submitted to UNEP/UNDP/GEF/BPSP.









Chambers, R., M. Leach, and C. Conroy. 1993. Trees and savings and security of the ruralpoor.
International Institute for Environment and Development Gatekeeper Series No. 3.

Chan, K. M. A., R. M. Pringle, J. Ranganathan, C. L. Boggs, Y. L. Chan, P. R. Ehrlich, P. K.
Haff, N. E. Heller, K. Al-khafaji, and D. P. Macmynowski. 2007. When agendas collide:
Human welfare and biological conservation. Conservation Biology 21(1):59-68.

Chapman, C. A. and L. J. Chapman. 1990. Dietary variability in primate populations. Primates
31(1):121-128.

Chapman, C. A. and S. R. Balcomb. 1998. Population characteristics of howlers: Ecological
conditions or group history. International Journal ofPrimatology 19:385-403.

Chapman, C. A and J. E. Lambert. 2000. Habitat alteration and the conservation of African
primates: Case study of Kibale National Park, Uganda. American Journal ofPrimatology
50: 169-185.

Chomitz, K. and D. Gray. 1996. Roads, land use and deforestation: A spatial model applied to
Belize. The World Bank Economic Review 10(3): 487-512.

Christ, C., O. Hillel, S. Matus, and J. Sweeting. 2003. Tourism and Biodiversity: Mapping
Tourism's Global Footprint, Conservation International

Cialdini, R. B. 1985. Influence: Science and practice. Glenview, IL: Scott, Foresman In Werner,
et al. 1995.

CIPEC, 1998. Training sample protocol. Center for the Study of Institutions, Population and
Environmental Change. http://www.cipec.org/research/methods/ts 10_98.pdf

Clarke, M. R., C. M Crockett, and E. L Zucker. 2002. Mantled howler population of Hacienda
La Pacifica, Costa Rica, between 1991 and 1998: effects of deforestation. American
Journal ofPrimatology 56:155-163.

Coates-Estrada, R. and A. Estrada. 1986. Fruiting and frugivores at strangler fig in the tropical
rain forest of Los Tuxtlas, Mexico. Journal of Troipcal Ecology 2:349-357.

Coelho, A. M. Jr., C. Bramblett, L. Quick, S. Bramblett. 1976. Resource availability and
population density in primates: A socio-bioenergetic analysis of the energy budgets of
Guatemalan howler and spider monkeys. Primates 17:63-80.

Collinge, S. K. 1996. Ecological consequences of habitat fragmentation: Implications for
landscape architecture and planning. Landscape and Urban Planning 36(1):59-77.

Conway, D. and J. Cohen. 1998. Consequences of migration and remittances for Mexican
transnational communities. Economic Geography 74:26-44.

Cowlishaw, G. and R. Dunbar. 2000. Primate Conservation Biology. The University of Chicago
Press, Chicago. In Anderson et al. 2007.









Crockett, C. M. and J. F. Eisenberg. 1987. Howlers: Variations in group size and demography. In
Smuts, B.B.; D.L. Cheney; R.M. Seyfarth; R.W Wrangham; and T.T. Struhsaker (eds).
Primate Societies. University of Chicago Press, Chicago, pp. 54-68 In Crockett 1997.

Crockett, C. M. 1997. Conservation biology of the genus Alouatta. International Journal of
Primatology 19(3):549-578.

Crockett, C. 1998. Conservation biology of the genus Alouatta. International Journal of
Primatology 19:549-578.

Cuba, L. and D. M. Hummon. 1993. A place to call home: identification with dwelling,
community, and region. Sociological quarterly 34(1): 111-131.

Cuar6n, A. D. 2000. Effects of land-cover changes on mammals in a neotropical region: a
modeling approach. Conservation Biology 14:1676-1692.

Dalle, S. P., S. de Blois, J. Caballero, and T. Johns. 2006. Integrating analyses of local land-
use/land cover data for assessing the success of community-based conservation. Forest
Ecology and Management 222:370-383.

Davenport, M. A. and D. H. Anderson. 2005. Getting from sense of place to place-based
management: An interpretive investigation of place meanings and perceptions of
landscape change. Society and Natural Resources 18:625-641.

Debinski D. M. and R. D. Holt, 2000. A survey and overview of habitat fragmentation
experiments. Conservation Biology 14(2): 342-355.

DeFries, R., J. Foley, and G. P. Asner. 2004. Land use choices: balancing human needs and
ecosystem function. Frontiers in Ecology and the Environment 2:249-257.

DiFiore, S. L. 2002. Remote Sensing and Exploratory Data Analysis as Tools to Rapidly
Evaluate Forest Cover Change and Set Conservation Priorities along the Belize River,
Belize. MA thesis, Columbia University, New York, NY.

Driver, B. L. 1996. Benefits-driven management of natural areas. Natural Areas Journal
16(2):94-99.

Durand, J. and D. Massey. 1992. Mexican migration to the United States: A critical review.
Latin American Research Review 27:3-42.

Durand, J., E. Parrado, and D. Massey. 1996. Migradollars and development: A reconsideration
of the Mexican case. International Migration Review 30:423-444.

Edwards, V. M. 2004. Community Based Ecotourism as a Panacea for Protected Areas: the use
of common property theory in its analysis and development. 10th Biennial Meeting of the
IASCP. Oaxaca, Mexico.









Eisenhauer, B. W., R. S. Krannich, and D. J. Blahna. 2000. Attachments to special places on
public lands: An analysis of activities, reason for attachment, and community connection.
Society and Natural Resources 13:421-441.

Estrada, A. and R. Coates-Estrada. 1984. Fruit eating and seed dispersal by howling monkeys (A.
palliata) in the tropical rain forest of Los Tuxtlas, Mexico. American Journal of
Primatology 6:77-91.

Estrada, A. and R. Coates-Estrada. 1988. Tropical rain forest conversion and perspectives in the
conservation of wild primates (Alouatta and Ateles) in Mexico. American Journal of
Primatology 14:315-327.

Estrada, A. and R. Coates-Estrada. 1996 Tropical rain forest fragmentation and wild populations
of primates at Los Tuxtlas. International Journal ofPrimatology 5:759-783.

Estrada, A, S. Juan, T. Ortiz-Martinez, R. Coates-Estrada. 1999. Feeding and general activity
patterns of a howler monkey (Allouatapalliata) troop living in a forest fragment at Los
Tuxtlas, Mexico. American Journal ofPrimatology 48:167-183.

Estrada, A., P. Cammarano, and R. Coates-Estrada. 2000. Bird species richness in vegetation
fences and in strips of residual rain forest vegetation at Los Tuxtlas, Mexico. Biodiversity
and Conservation 9:1399-1416.

Estrada, A., A. Mendoza, L. Castellanos, R. Pacheco, S. Van Belle, Y. Garcia, and D. Mufioz.
2002. Population of the black howler monkey (Alouattapigra) in a fragmented landscape
in Palenque, Chiapas, Mexico. American Journal of Primatology 58:45-55.

Estrada, A., S. Van Belle, L. Luecke, and M. Rosales. 2006. Primate populations in the protected
forests of Maya archeological sites in southern Mexico and Guatemala. In Estrada, A.,
Garber, P.A., Pavelka, M. and Luecke, L. (Eds.), New Perspectives in the Study of
Mesoamerican Primates. Springer, NY, pp 471-488.

Fahrig, L. and G. Merriam. 1985. Habitat patch connectivity and population survival. Ecology
66(6):1762-1768.

Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annual Review of Ecology
Evolution and Systematics 34: 487-515 In Anderson et al. 2007.

FAO. Food and Agriculture Organization of the United Nations. 1993. Forest Resources
Assessment, 1990, tropical countries. Food and Agriculture Organization of the United
Nations Forestry Paper 112. Rome. In DiFiore 2002.

FAO. Food and Agriculture Organization of the United Nations. 2001. The global forests
resource assessment 2000 summary report. Committee on Forestry Paper 8b. Rome. In
DiFiore 2002.









FAO. Food and Agriculture Organization of the United Nations. 2007. National Report Belize.
FAO Corporate Document Repository. Accessed April 28, 2008.
http://www.fao.org/docrep/007/j405 b/j405 1b07.htm

Fearnside, P. M. 1986. Spatial concentration of deforestation in the Brazilian Amazon. Ambio
15:74-81.

Fischer, G., Y. Ermoliev, M. A. Keyzer, and C. Rosen-Zweig. 1996. Simulating the Socio-
Economic and Biogeophysical Driving Forces of Land-Use and Land- Cover Change:
The IIASA Land-Use Change Model. Working Paper WP-96-010. Laxenburg:
International Institute for Applied Systems Analysis. In Mertens and Lambin 2000.

Fitter, R. 1986. Wildlife for Man. How and Why ,\hn,uld We Conserve Our Species. William
Collins Sons and Co. Ltd.: London. 223 p.

Foody, G. M., S. G. Palubinska, R. M. Lucas, P. J. Curran, and M. Honzak. 1996. Identifying
terrestrial carbon sinks: classification of successional stages in regenerating tropical
forest from Landsat TM data. Remote Sensing of Environment 55: 205-216.

Fox, J., R. R. Rindfuss, S. J. Walsh, and V. Mishra, eds. 2003. People and the Environment:
Approaches for linking household and community surveys to remote sensing and GIS.
Boston: Kluwer Academic Publishers.

Freedman, J. and S. Fraser. 1966. Compliance without pressure: The foot-in-the-door technique.
Journal ofPersonality and Social Psychology 4:195-202.

Freese, C. H., P. G. Heltne, R. N. Castro, and G. Whitesides. 1982. Patterns and determinants of
monkey densities in Peru and Bolivia, with notes on distributions. International Journal
ofPrimatology 3:53-90.

Fuentes, E., A. Estrada, B. Franco, M. Magafia, Y. Docena, D. Mufioz, and Y. Garcia. 2003.
Report preliminary sobre el uso de recursos alimenticios por una tropa de monos
aulladores, Alouattapalliata, en El Parque La Venta, Tabasco, Mexico. Neotropical
Primates 11:24-29.

Funder, M. 1995. Campfire: impact and household level. A case-study of two villages in Binga
District. Prepared for the Bigna Rural District Council and MS-Zimbabwe.

Galetti, M, F. Pedroni, L. P. C. Morellato. 1994. Diet of the brown howler monkey Alouatta
fusca in a forest fragment in southeastern Brazil. Mammalia 1:111-118.

Garber, P. A., A. Estrada, and M. S. M. Pavelka. New Perspectives in the Study of
Mesoamerican Primates: Concluding Comments and Conservation Priorities In Estrada,
A., Garber, P.A., Pavelka, M. and Luecke, L. (Eds.), New Perspectives in the Study of
Mesoamerican Primates. Springer, NY, pp 563-580.









Garcia-Barrios, L. and M. Gonzalez-Espinosa. 2004. Change in oak to pine dominance in
secondary forests may reduce shifting agriculture yields: experimental evidence from
Chiapas, Mexico. Agriculture, Ecosystems and Environment 102:389-401.

Gautam, A. P., G. P. Shivakoti, and E. D. Webb. 2004. Forest cover change, physiography, local
Economy, and institutions in a mountain watershed in Nepal. Environmental
Management 33(1):48-61.

Geist, H. J. and E. F. Lambin. 2001. What drives tropical deforestation? LUCC Report Series,
No. 4. LUCC International Project Office: Louvain la Neuve, Belgium, 136 p.

Geist, H. J. and E. F. Lambin. 2002. Proximate causes and underlying driving forces of tropical
deforestation. BioScience 52:143-150.

Geoghegan, J., S. C. Villar, P. Klepeis, P. Macario Mendoza, Y. Ogneva-Himmelberger, R. R
Chowdhury, B. L. Turner II, and C. Vance. 2001. Modeling tropical deforestation in the
southern Yucatan peninsular region: comparing survey and satellite data. Agriculture,
Ecosystems and Environment 85:25-46.

Geoghegan J., L. Wainger, and N. Bockstael. 1997. Spatial landscape indices in a hedonic
framework: an ecological economics analysis using GIS. Ecological Economics 23:251-
64.

Gibson, C. C., M. A. McKean, and E. Ostrom. 2000. People and Forests. Communities,
Institituions, and Governance. MIT Press.

Gibson, C. C., F. E. Lehoucq, and J. T. Williams. 2002. Does privatization protect natural
resources? Property rights and forests in Guatemala. Social Science Quarterly 83(1):206-
225.

Gilpin, M. E. and J. M. Diamond. 1980. Subdivision of nature reserves and the management of
species diversity. Nature 285:567-568.

Githiru, M. and L. Lens. 2007. Application of fragmentation research to conservation planning
for multiple stakeholders: An example from the Taita Hills, southeast Kenya. Biological
Conservation 134(2): 271-278.

Godoy, R. A. and K. S. Bawa. 1993. The economic value and sustainable harbest of plants and
animals from the tropical forest: assumptions, hypothesis, and methods. Economic
Botany. 47(3): 215 219. In Tisdell, C.A. 1995. Issues in biodiversity conservation
including the role of local communities. Environmental Conservation 22(3):216-222.

Godoy, R., K. O'Neill, S. Groff, P Kostishack, A. Cubas, J. Demmer, K. McSweeney, J.
Overman, D. Wilkie, N. Brokaw, and M. Martinez. 1997. Household determinants of
deforestation by Amerindians in Honduras. World Development 25:977-87.









Gonzales-Kichner, J. P. 1998. Group size and population density of the black howler monkey
(Alouattapigra) in Muchukux Forest, Quintana Roo, Mexico. Folia Primatologica
69:260-265.

Goudy, W. J. 1990. Community attachment in a rural region. Rural Sociology 55:178-198.

Green, G., C. M. Schweik, M. Hanson. 2000. Radiometric calibration ofLandsat Multispectral
Scanner and Thematic Mapper images: guidelines for the global changes community.
Working Paper. Bloomington, Indiana Center for the Study of Institutions, Population,
and Environmental Change.

Guillen-Trujillo, H. and J. R. Stepp. 2005. Is Ecotourism Promoting Conservation in the
Lacandon Forest? Working Forests in the Tropics Abstract book and program: Policy
and Market Impacts on Conservation and Management. University of Florida.

Guyer, J. and E. F. Lambin.1993. Land use in an urban hinterland: Ethnography and remote
sensing in the study of African intensification. American Anthropologist 95(4):839-859.

Hanna, S., C Folke, and K. G. Maller. 1996. Property rights and the natural environment. In
Rights to Nature Island Press: Washington, D.C. pp 1-12.

Harcourt, C. S. and J. Sayer. 1996. The conservation atlas of tropical forests: The Americas.
New York: Simon and Schuster. In Southworth et al. 2004.

Harcourt, A. H. 1998. Ecological Indicators of Risk for Primates, as Judged By Species'
Susceptibility to Logging. In Anderson et al. 2007.

Harcourt, A. H. 2002. Empirical estimates of minimum viable population sizes for primates: tens
to tens of thousands? Animal Conservation 5:237-244.

Harrison, S. and E. Bruna. 1999. Habitat fragmentation and large scale conservation: what do we
know for sure. Ecography 22:225-232.

Hartshorn, G. S. 1984. Belize Country Environmental Profile: A Field Study. Belize City:
Nicolait. In James, R. A., P. L. Leberg, J. M. Quattro, and R. Vrijenhoek. 1997. Genetic
diversity in black howler monkeys (Alouattapigra) from Belize. Am. J. Phys. Anthropol
102:329-336.

Hartup, B. 1994. Community conservation in Belize: Demography, resource use, and attitudes of
participating landowners. Biological Conservation 69: 235-241.

Hayes, D. J., S. A. Sader, and N. B. Schwartz. 2002. Analyzing a forest conversion history
database to explore the spatial and temporal characteristics of land cover change in
Guatemala's Maya Biosphere Reserve. Landscape Ecology 17: 299-314.

He, H. S., B. E. DeZonia, and D. J. Mladenoff. 2000. An aggregation index (AI) to quantify
spatial patterns of landscapes. Landscape Ecology 15:591-601.









Healy, R. G. 1994. Tourist merchandise as a means of generative local benefits from ecotourism.
Journal of Sustainable Tourism 2(3):137-151.

Hobbs, R. J. 1993. Effects of landscape fragmentation on ecosystem process in the western
Australian wheatbelt. Biological Conservation 64:193-201.

Holden, S. T. 1993. Peasant household modeling: farming systems evolution and sustainability in
Northern Zambia. Agricultural Economics 9:241-67.

Horwich, R. H., and Gebhard, K. 1983. Roaring rhythms in black howler monkeys (Alouatta
pigra) of Belize. Primates 24: 290-296.

Horwich, R. H. and E. D. Johnson. 1984. Geographic distribution and status of the black howler
monkey. IUCN SSC Primate Spec. Group Newsletter 4:25-27.

Horwich, R. H. and E. D. Johnson. 1986. Geographic distribution of the black howler monkey
(Alouattapigra) in Central America. Primates 27:53-62.

Horwich, R. H. and J. Lyon. 1987. An experimental technique for the conservation of private
lands. J. Med. Primatol 17:169-176.

Horwich, R. H. 1990. How to develop a community sanctuary an experimental approach to the
conservation of private lands. Oryx 24(2):95-102.

Horwich, R. H. and J. Lyon. 1990. A Belizean Rain Forest. The Community Baboon Sanctuary.
Oranutan press: Gay Mills, WI. 420 pp.

Horwich, R. H. and J. Lyon. 1998. Community-based development as a conservation tool: the
Community Baboon sanctuary and the Gales point Manatee Project. In Primack et al.
1998

Horwich, R. 1998. Effective Solutions for howler monkey conservation. International Journal of
Primatology 19(3):579 598.

Horwich, R. H., R. C. Brockett, R. A. James, and C. B. Jones. 2001. Population growth in the
Belizean Black Howling Monkey (Alouatta pigra). Neotropical Primates 9(1): 1-7.

Hubacek, K. and J. Vazquez. 2002. The economics of land use change. International Institute for
Applied Systems Analysis. Interim Report IR-02-015.

Hulme, D. and M. Murphree. 1999. Communities, wildlife and the 'new conservation' in Africa.
Journal ofInternational Development 11:277-285.

Igoe, J. 2006. Measuring the costs and benefits of conservation to local communities. Journal of
Ecological Anthropology 10:72-77.









IUCN (World Conservation Union). 2003. IUCN Red List of Threatened Species.
http://www.iucn.org/themes/ssc/redlistarchive/redlist2003/English/profilesEn.htm,
accessed 2/6/2007.

IUCN. 1994. Guidelinesfor Protected Areas Management Categories. IUCN. Cambridge, UK
and Gland, Switzerland. 261pp.
http://www.unep-wcmc.org/protected_areas/categories/index.html. accessed 10/23/2008.

Jacobson, S. K. and R. Robles. 1992. Ecotourism, sustainable development, and conservation
education: Development of a tour guide training program in Tortuguero, Costa Rica.
Environmental Management 16(6):701-713.

James, R. A. C. 1992. Genetic variation in Belizean black howler monkeys (Alouattapigra).
Ph.D. Dissertation. Rutgers University, New Brunswick, NJ. In Jones 1995.

Jensen, John R. 2005. Introductory digital image processing: A remote sensing perspective.
Pearson Prentice Hall: NJ.

Jha, C. S. and N. V. M. Unni. 1994. Digital change detection of forest conversion of a dry
tropical Indian forest region. International Journal of Remote Sensing 15: 2543-2552.

Johns, A. D. and J. P. Skorupa. 1987. Responses of rain-forest primates to habitat disturbance: A
review. International Journal ofPrimatology 8:157-191.

Jones, C. B. 1995. Howler monkeys appear to be preadapted to cope with habitat fragmentation.
Endangered Species Update. 12:9-10.

Jones, B., and M. Murphree. 2001. The evolution of policy on community conservation in
Namibia & Zimbabwe. In African wildlife & livelihoods: The promise andperfomance of
community conservation. D. Hulme and M. Murphree, eds. 74-87. Oxford: James Currey.

Jones, C. B. and J. Young. 2004. Hunting Restraint by Creoles at the Community Baboon
Sanctuary, Belize: A Preliminary Survey. Journal ofApplied Animal Welfare Science
7(2):127-141.

Jones, C. B. and R. H. Horwich. 2005. Constructive Criticism of Community-Based
Conservation. Conservation Biology 19(4):990-991.

Jones, C. B., V. Milanov, and R. Hager. 2008. Predictors of male residence patterns in groups of
black howler monkeys. Journal of Zoology 1-7.

Jorgensen, B. S. and R. C. Stedman. 2001. Sense of place as an attitude: lakeshore owners'
attitudes toward their properties. Journal ofEnvironmental Psychology 21(3): 233-248.

Kaimowitz, D. and A. Angelsen. 1998. Economic Models of Tropical Deforestation: A Review.
Center for International Forestry Research (CIFOR).









Kaltenborn, B., H. Reise, and M. Hundeheide. 1999. National park planning and local
participation: Some reflections from a mountain region in southern Norway. Mountain
Research and Development 19:51-56.

Kangas, P., M. Shave, and P. Shave. 1995. Economics of an Ecotourism Operation in Belize.
Environmental Management 19(5):669-673.

Kapos, V. 1989. Effects of isolation on the water status of forest patches in the Brazilian
Amazon. Journal of Tropical Ecology 5:173-185.

Kappelle, R. J. 2001. Relationships between local people and protected natural areas: A case
study of Arthur's Pass and the Waimakariri Basin, NZ. Master's thesis, Human Sciences
Division, Lincoln University, Canterbury, New Zealand. In McCleave et al. 2006.

Kasarda, J. D. and M. Janowitz. 1974. Community attachment in mass society.
AmericanSociological Review 39:328-39.

Katzev, R. and T. Wang. 1994. Can commitment change behavior? A case study of
environmental actions. Journal of Social Behavior and Personality 9(1): 13-26.

Kiesler, C. A. and J. Sakumura. 1966. A test of a model for commitment. Journal of Personality
and Social Psychology 3(3):349-353.

Kimmel, J. R. 1999. Ecotourism as environmental learning. Journal ofEnvironmental
Education 30(2):40-44.

King, R. B., I. C. Baillie, T.M.B. Abell, J. R. Dunsmore, D. A. Gray, J. H. Pratt, H. R. Versey, A.
C. S. Wright, and S. A. Zisman. 1992. Land Resource Assessment of Northern Belize, vol.
1 and 2, Natural Resources Institute Bulletin, pp. 43: 1-513. In Marsh and Loiselle, 2003.

Kiss, A. 2004. Is community-based ecotourism a good use of biodiversity conservation funds?
TRENDS in Ecology and Evolution 19(5):232-237.

Klepeis, P. 2003. Development policies and tropical deforestation in the southern Yucatan
Peninsula: Centralized and decentralized approaches. Land Degradation and
Development 14: 541-561.

Koontz, F., E. Saqui, H. Saqui, and K. Glander. 1993. A Reintroduction Program for the
Conservation of the Black Howler Monkey in Belize. Endangered Species Update 10(6):
1-6.

Kratter, A. W., D. W. Steadman, C. E. Smith, C. E. Filardi, and H. P. Webb. 2001. Avifauna of a
lowland forest site on Isabel, Solomon Islands The Auk 118(2):472-483.

Krishnaswamy, J., M. C. Kiran, and K. N. Ganeshaiah, K. N. 2004. Tree model based eco-
climatic vegetation classification and fuzzy mapping in diverse tropical deciduous
ecosystems using multiseason NDVI. Remote Sensing of Environment 25:1185-1205.









Kupfer, J. A., G. P. Malanson, and S. B. Franklin. 2006. Not seeing the ocean for the islands: the
mediating influence of matrix-based processes on forest fragmentation effects. Global
Ecology and Biogeography 15:8-20.

Kyle, G., K. Bricker, A. Graefe, and T. Wickman. 2004. An Examination of recreationists'
relationships with activities and settings. Leisure Sciences 26:123-142.

Lamb, D., P. D. Erskine, and J. A. Parrotta. 2005. Restoration of degraded tropical forest
landscapes. Science 310:1628-1632.

Labmin, E. F, X. Baulies, N. Bocksteil, G. Fisher, T, Krug, R. Leemans, E. R. Moran, R. R.
Rinkfuss, Y.Santo, D. Skole, B. L.Turner II, and C. Vogel. 1999. Land-Use and Land-
Cover (LUCC) Implementation Strategy. Bonn, Germany: International
GeosphereBiosphere Programme and the International Human Dimensions Programme
on Global Environmental Change. In Olson et al. 2004.

Lambin, E. F., M. D. A. Rounsevell, H. J. Geist. 2000. Are agricultural land-use models able to
predict changes in land-use intensity? Agriculture, Ecosystems andEnvironment 82: 321-
331.

Lambin, E., B. L. Turner, H. Geist, S. Agbola, A. Angelsen, J. Bruce, O. Coomes, R. Dirzo, G.
Fischer, C. Folke, P. S. George, K. Homewood, J. Imbernon, R. Leemans, X. Li, E.
Moran, M. Mortimore, P. S. Ramakrishnan, J. Richards, H. Skanes, W. Steffen, G. Stone,
U. Svendin, T. Veldkamp, C. Vogel, J. Xu. 2001. The causes of land-use and land-cover
change: moving beyond the myths. GlobalEnvironmental Change 11:261-269.

Lambin, D. F., H. J. Geist, and E. Lepers. 2003. Dynamics of Land-Use and land-Cover Change
in Tropical Regions. Annual Review ofEnvironmental Resources 28:205-41.

Langholz, J. 1996. Economics, objectives and success of private nature reserves in sub-Suharan
Africa and Latin America. Conservation Biology 10:271-280.

Langholz, J. 2002. Privately-Owned Parks. In Making Parks Work: Strategies for Preserving
Tropical Nature. Terborgh, J; C. Van Schaik; L. Davenport; and M. Rao, eds. Island
Press, D.C., p 172-188.

Langholz, J. and K. Brandon. 2001. Privately Owned Protected Areas. In The Encyclopedia of
Ecotourism. ed. Weaver, D.B., New York: CABI Publishing, p 303-314.

Lash, G. B. 2003. Sustaining our spirit: ecotourism on privately-owned rural lands and protected
areas. PhD dissertation. University of Georgia.

Laurance, W. F. and R. O. Bierregaard, editors. 1997. Tropical forest remnants: ecology,
management and conservation offragmented communities. Chicago: University of
Chicago Press. 616 p In Estrada et al. 2002.

Laurance, W. F. 1999. Reflections on the tropical deforestation crisis. Biological Conservation
91:109-117.









Laurance, W. F., H.L. Vasconcelos, and T.E. Lovejoy. 2000. Forest loss and fragmentation in the
Amazon: implications for wildlife conservation. Oryx 34(1): 39-45.

Laurance, W. F., T. E. Lovejoy, H. L. Vasconcelos, E. M Burna, R. K. Didham, P. C. Stouffer,
C. Gascon, R. O Bierregaard, S. G. Laurance, and E. Sampaio. 2002. Ecosystem decay of
Amazonian forest fragments: a 22 year investigation. Conservation Biology 16:605-618.

Leinbach, T., and J. Watkins. 1998. Remittances and circulation behavior in the livelihood
process: Transmigrant families in South Sumatra, Indonesia. Economic Geography
74:45-63.

Lepp, A.and S. Holland. 2006. A comparison of attitudes toward state-led conservation and
community-based conservation in the Village of Bigodi, Uganda. Society and Natural
Resoures 19(7):609-623.

Leppens, J. 2005. Fishingfor tourists: Perceptions from the Stewart Island community of the
creation ofRakiura National Park. Master's thesis, Environment, Society and Design
Division, Lincoln University, Canterbury, NZ. In McCleave et al. 2006.

Lindberg, K.; J. Enriquez; and K. Sproule. 1996. Ecotourism questions: Case studies from
Belize. Annals of Tourism Research 23:543 562.

Lindenmayer, D. B. 1999. Future directions for biodiversity conservation in managed forests:
indicator species, impact studies and monitoring programs. Forest Ecology and
Management 115:277-287.

Liverman, D., E. F. Moran, R. R. Rindfuss, and P. C. Stem (Eds.). 1998. People and pixels:
Linking remote sensing and social science. Committee on the Human Dimensions of
Global Environmental Change, National Research Council. Washington, DC: National
Academy Press.

Lovejoy, T. E., R. O. Jr. Bierregaard, A. B. Rylands, J. R. Malcolm, C. E. Quintela, L. H.
Harper, K. S. Jr. Brown, A. H. Powell, G. V. N. Powell, H. O. R. Schubart, M. B. Hays.
1986. Edge and other effects on isolation on Amazon forest fragments. In Soule, M.E.
(ed.). Conservation Biology: The Science of Scarcity and Diversity. Sunderland, Mass:
Sinauer Assoc.

Lovejoy, T. E., R. O Bierregraad, K. S. Brown, L. H. Emmons, M. E. Van der Voort.1984.
Ecosystem decay of Amazon forest fragments. In Extinctions. Niteki, M.H. (ed).Chicago:
University of Chicago Press. p 295-325 In Estrada et al. 2002.

Low, S. M. 1992. Symbolic Ties that Bind: Place Attachment in the Place. In Place Attachment.
Altman, I. and S. M. Low (eds), 165-185, Plenum Press: New York.

Ludeke, A. K, R. C. Maggio, and L. M. Reid. 1990. An analysis of anthropogenic deforestation
using logistic regression and GIS. Journal ofEnvironmental Management 32:247-259.

Lusigi, W. J. 1981. New approaches to wildlife conservation in Kenya. Ambio 10:87 92.









Lyon, J. and R. H. Horwich. 1996. Modification of tropical forest patches for wildlife protection and community
conservation in Belize. In Forest Patches in Tropical Landscapes. Shelhas, J. and Greenberg,
R. (eds.). Island Press, Washington, D.C. pp, 205-230.

MacArthur, R. H. and E. O. Wilson. 1967. The Theory oflslandBiogeography. Princeton
University Press: New Jersey.

Maddala, G. S. 1983. Limited dependent and qualitative variables in econometrics. Cambridge:
Cambridge University Press.

Malmgren, L.A. 1979. Empirical population genetics of golden mantled howling monkeys
(Alouattapalliata) in relation to population structure, social dynamics, and evolution.
Ph.D. Dissertation, University of Connecticutt, Storrs. In Jones 1995.

Mandujano, S., L.A. Escobedo-Morales, and R. Palacios-Silva. 2004. Brief report on Alouatta
palliata movements among fragments in Los Tuxtlas, Mexico. Neotropical Primates
12:126-131.

Mandujano, S., L. A. Escobedo-Morales, R. Palacios-Silva, V. Arroyo-Rodriguez, and E. M.
Rodrieguez-Toledo. 2006. A metapopulation approach to conserving the howler monkey
in a highly fragmented landscape in Los Tuxtlas, Mexico. In: Estrada, A., Garber, P.A.,
Pavelka, M. and Luecke, L. (eds.), New Perspectives in the Study ofMesoamerican
Primates: Distribution, Ecology, Behavior, and Conservation. Springer, NY, pp. 513-
538.

Marsh, L. K. 1999. Ecological effect of the black howler monkey (Alouattapigra) on fragmented
forests in the Community Baboon Sanctuary, Belize. Ph.D. Dissertation. Washington
University: St. Louis, MO.

Marsh, L. K., and B. A. Loiselle. 2003. Recruitment of black howler fruit trees in fragmented
forests of Northern Belize. International Journal ofPrimatology 24:65-86.

Marsh, L. K. 2003. Primates in fragments: Ecology and conservation. Kluwer,
Academic/Plenum Publishers, New York. In Anderson et al. 2007.

Mascia, M. B., J. P. Brosius, T. A. Dobson, B. C. Forbes, L. Horowitz, M. A. McKean, and N. J.
Turner. 2003. Conservation and the social sciences. Conservation Biology 17:649-650.

McCleave, J., S. Espiner, and K. Booth. 2006. The New Zealand People-Park Relationship: An
Exploratory Model. Society andNatural Resources 19:547-561.

McCool, S. F. and S. R. Martin. 1994. Community attachment and attitudes toward tourism
development. Journal of Travel Research 22(3):29-34.

McCracken, S. D., E. S. Brondizio, D. Nelson, E. F. Moran, A. D. Siqueira, and C. Rodriguez-
Pedraza. 1999. Remote sensing and GIS at farm property level: Demography and
deforestation in the Brazilian Amazon. Photogrammetric Engineering & Remote Sensing
65:1,311-1,320.









McGarigal, K. and B. J. Marks. 1995. FRAGSTAT. Spatial analysis program for quantifying
landscape structure.USDA Forest Service General Technical Report PNW-GTR-351,122
p.

McGarigal, K., S. A. Cushman, M. C. Neel, and E. Ene. 2002. FRAGSTATS: Spatial Pattern
Analysis Program for Categorical Maps. Computer software program produced by the
authors at the University of Massachusetts, Amherst. Available at the following web site:
www.umass.edu/landeco/research/fragstats/fragstats.html

McKenzie-Mohr, D. and W. Smith. 1999. Fostering Sustainable Behavior. New Society
Publishers: Canada

Merrill, T. 1992. Belize: A Country Study. Washington: GPO for the Library of Congress.
http://countrystudies.us/belize/ Website accessed 10/2/2007.

Mertens, B., W. D. Sunderlin, O. Ndoye, and E. F. Lambin. 2000. Impact of macroeconomic
change on deforestation in south Cameroon: Integration of household survey and
remotely-sensed data. World Development 28(6):983-999.

Mertens, B. and E. F. Lambin. 2000. Land-cover-change trajectories in Southern Cameroon.
Annals of the Association ofAmerican Geographers 90(3):467-494.

Meyer, W. B. and B. L. Turner II. 1992. Human population growth and global land-use/land-
cover change. Annual Review in Ecology and Systematics 23: 39-61.

Millstein, J. S. 1977. How consumers feel about energy: Attitudes and behavior during the winter
and spring of 1976-77. Washington, DC: Federal Energy Administration. In Nickerson,
2003.

Milton, K. 1980. The foraging strategy of howler monkeys. New York: Columbia University
Press.

Milton, K. 1991. Leaf change and fruit production in six neotropical Moraceae species. Journal
ofEcology 79:1-26.

Milton, K. 1996. Effects of bot fly (Alouatta bueria) parasitism on a free-ranging howler monkey
(Alouatta palliata) population in Panama. Journal Zool. Lond 239:39-63.

Monty, R. A., E. S. Geller, R. E. Savage, and L. C. Perlmutter. 1979. The freedom to choose is
not always so choice. Journal ofExperimental Psychology: Human Learning and
Memory 5:170-178. In Nickerson 2003.

Moore, R. L. and B. L. Driver. 2005. Introduction to Outdoor Recreation. Providing and
Managing Natural Resource Based Opportunities. Pennsylvania, PA: Venutre
Publishing, Inc.









Munroe, D. K., J. Southworth, and C. Tucker. 2004. Modelling spatially and temporally complex
land cover change: the case of western Honduras. The Professional Geographer
56(4):544-59.

Murphree, M. W. 2003. Linkages in the Landscape/Seascape Stream. InstitutionalAspects of
Linkages. WPC: Durban.

Nagendra, H., C. Tucker, J. Southworth, M. Karmacharya, and B. Karna. 2004. Monitoring parks
through remote sensing: studies in Nepal and Honduras. Environmental Management
34(5):748-760.

Nagendra, H., D. K. Munroe, and J. Southworth. 2004. From pattern to process: Landscape
fragmentation and the analysis of land use/ land cover change. Agriculture, Ecosystems
and Environment 101:111-115.

Naughton-Treves, L., M. B. Holland; and K. Brandon. 2005. The role of protected areas in
conserving biodiversity and sustaining local livelihoods. Annual Review of Environment
and Resources 30:219-252.

Nelson, G. C., V. Harris, and S. Stone. 2001. Deforestation, land use, and property rights:
Empirical evidence from Darien, Panama. Land Economics 77(2):187-205.

Nepal, S. K. 2000. Tourism in protected areas. Annals of Tourism Research 27:661-681.

Nepstad, D., G. Carvalho, A. C. Barros, A. Alencar, J. Capobianco, J. Bishop, P. Moutinho, P.
Lefebvre, and U. Silva Jr. 2001. Road paving, fire regime feedbacks, and the future of
Amazon forests. Forest Ecology and Management 154:395-407.

Neville, M. K., K. E. Glander, F. Braza, A. B. Rylands. 1988. The howling monkeys, genus
Alouatta. In: Mittermeier, R. A., A. B. Rylands, A. Coimbra-Filho, G. A. B. Fonseca
(eds.). Ecology and Behavior ofNeotropical Primates, Vol.2, Washington, DC: World
Wildlife Fund, p. 349-453.

Nickerson, R. S. 2003. Psychology and Environmental Change, Lawrence Erlbaum Associates:
New Jersey.

NRC (National Research Council). 1998. Human Dimensions of Global Environmental Change:
Pua lhi uiyfor the Next Decade. Washington, D.C: National Academy Press.

Nyaupane, G. P. and B. Thapa. 2004. Evaluation of ecotourism: a comparative assessment in the
Annapurna Conservation Area Project, Nepal. Journal ofEcotourism 3(1):20-45.

Oates J. 1999. Myth and Reality in the Rain Forest: How Conservation Strategies Are Failing in
West Africa. Berkeley: University of California Press. In Brechin et al. 2002

O'Brien, T. G., M. F. Kinnaird, E. S. Dierenfeld, N. L. Conklin-Brittain, R. W. Wrangham, and
S. C. Silver. 1998. What's so special about figs? Nature 392:668.









Offerman, H. L., V. N. Dale, S. M. Pearson, O. Bierregaard Jr., and R. V. O'Neill. 1995. Effects
of forest fragmentation on neotropical fauna: current research and data availability.
Environ Rev 3:190-211. In Estrada et al. 2002.

Olson, J. M., S. Misana, D. J. Campbell, M. Mbonile, and S. Mugisha. 2004. A research
framework to identify the root causes of land use change leading to land degradation and
changing biodiversity. Land Use Change Impacts and Dynamics (LUCID) Project
Working Paper #48. Nairobi, Kenya: International Livestock Research Institute.

Olupot, W. and P. M. Waser. 2001. Activity patterns, habitat use and mortality risks of
mangabey males living outside social groups. Animal Behaviour 61:1227-1235.

Onderdock, D. and C. Chapman. 2000. Coping with Forest Fragmentation: The Primates of
Kibale National Park, Uganda. International Journal ofPrimatology 21(4):587-611.

Ostro, L. E. T.; S. C. Silver; F. Koontz; T. P. Young; and R. H. Horwich. 1999. Ranging
behavior of translocated and established groups of black howler monkeys Alouatta pigra
in Belize, Central America. Biological Conservation 87:181-190.

Ostro, L. E. T., Silver, S. C., Koontz, F. W., Horwich, R. H., and Brockett, R. 2001. Shifts in
social structure of black howler (Alouattapigra) groups associated with natural and
experimental variation in population density. Int. J Primatol 22:733-748.

Ostrom, E. 1990. Governing the Commons: The Evolution of Institutions for Collective Action.
Cambridge: Cambridge University Press.

Ostrom, E., J. Burger, C. B. Field, R. B. Norgaard, and D. Policansk. 1999. Sustainability -
revisiting the commons: local lessons, global challenges. Science 284:278-82.

Ovaskeinen, 0. and I. Hanski. 2004. Metapopulation dynamics in highly fragmented landscapes.
In: Hanski, I and O.E. Gaggiotti. 2004. Ecology, genetics, and evolution of
metapopulations. Elsevier Academic Press, Burlington, MA. In Mandujano et al. 2006

Pallak, M. S., D.A. Cook, and J. J. Sullivan. 1980. Commitment and energy conservation.
Applied Social Psychology Annual 1:235-253

Pallak, M. S. and W. Cummings. 1976. Commitment and voluntary energy conservation.
Personality and Social Psychology Bulletin 2:27-31.

Palomares, F., P. Ferreras, M. M. Ferdraini, and M. Delibes. 1996. Spatial relationships between
Iberian lynx and other carnivores in an area of south-western Spain. Journal ofApplied
Ecology 33:5-13.

Pardini, A. U. and R. D. Katzev. 1983-1984. The effects of strength of commitment on
newspaper recycling. Journal ofEnvironmental Systems 13:245-254.

Parker, T. A., III, B. K. Holst, L. H. Emmons, and J. R. Meyer. 1993. A BiologicalAssessment of
the Colombia River Forest Reserve, Toledo District, Belize, Rapid Assessment Program









Working Papers 3, Conservation International,Washington, DC. In Marsh and Loiselle
2003.

Perlmutter, L. C., K. Scharff, R. Kash, and R. A. Monty. 1980. Perceived control: A generalized
state of motivation. Motivation and Emotion 4:35-45. In Nickerson 2003.

Perz, S. 2001. Household demographic factors as life cycle determinants of land use in the
Amazon. Population Research and Policy Review 20:159-186.

PfB (Programme for Belize). 2000. Feasibility study of the proposed Northern Belize Biological
Corridors Project (NBBCP), Vol. 1, Main Report.

Pinch6n, F. J. 1997. Colonist land-allocation decisions, land use, and deforestation in the
Ecuadorian Amazon frontier. Economic Development and Cultural Change 44:707-44.

Platteau, J. 2004. Monitoring elite capture in community-driven development. Development and
Change. 35(2):223-246.

Pozo-Montuy, G. and J. C. Serio-Silva. 2003. Locomotion and feeding on the ground by black
howler monkeys (Alouattapigra) in a very fragmented habitat of Rancheria Leona
Vicario, Balancan Tabasco, Mexico. American Journal ofPrimatology 60:65.

Primack, R. B., D. Bray., H. A. Galletti, and I. Ponciano (eds). 1998. Timber, Tourists, and
Temples. Conservation and Development in the Maya Forest of Belize, Guatemala, and
Mexico. Island Press.

Prohansky, H. M., Fabian, A. K., and Kaminoff, R. 1983. Place-Identity: Physical World
Socialization of the Self. Journal ofEnvironmental Psychology 3:57-83.

Pulliam, H. R., J. B. Dunning, Jr., and J. Liu. 1992. Population dynamics in complex landscapes:
a case study. Ecological Applications 2:165-177.

Redford, K. H. 1992. The empty forest. BioScience 42(6):412-422.

Redford, K. H. and S. E. Sanderson. 2000. Extracting Humans from Nature. Conservation
Biology 14(5):1362-1364.

Rindfuss, R. R., S. J. Walsh, B. L. Turner II, J. Fox, and V. Mishra. 2004. Developing a science
of land change: Challenges and methodological issues. Proceedings of the National
Academy of Sciences (PNAS) 101(39):13976-13981.

Rivera, A. and S. Calme. Forest fragmentation and its effects on the feeding ecology of black
howlers (Alouattapigra) from the Calakmul area in Mexico. In Estrada, A., Garber, P.A.,
Pavelka, M. and Luecke, L. (eds.), New Perspectives in the Study ofMesoamerican
Primates: Distribution, Ecology, Behavior, and Conservation. Springer, NY, pp.189-
215.

Rogerson, P. A. 2005. Statistical methods for Geography. London: Sage Publications.









Roy Chowdhury, R. 2006a. Driving forces of tropical deforestation: The role of remote sensing
and spatial models. Singapore Journal of Tropical Geography 27(1):82-101.

Roy Chowdhury, R. 2006b. Landscape change in the Calakmul Biosphere Reserve, Mexico:
modeling the driving forces of smallholder deforestation in land parcels. Applied
Geography 26 (2):129-152.

Rudel, T. and J. Roper. 1997. Forest fragmentation in the humid tropics: a cross national
analysis. Singapore Journal of Tropical Geography 18:99-109.

Rutherford, G. N., A. Guisan, and N. E. Zimmermann. 2007. Evaluating sampling strategies and
logistic regression methods for modeling complex land cover changes. Journal of
Applied Ecology 44:414-424.

Rylands, A. B., R. A. Mittermeier, and L. E. Rodriguez. 1995. A species list for the new world
primates (Platyrrhini): Distribution by country, endemism, and conservation status
according to the Mace-Land System. Neotropical Primates 3 (Suppl.): 113-160.

Sader, S. A., T. Sever, J. C. Smoot, and M. Richards. 1994. Forest change estimates for the
northern Peten region of Guatemala. Human Ecology 22: 317-332.

Sader, S. A., D. J. Hayes, J. A. Hepinstall, M. Coan, and C. Soza. 2001. Forest change
monitoring of a remote biosphere reserve. International Journal of Remote Sensing
22:1937-1950.

Salafsky N., H. Cauley, G. Balachander, B. Cordes, J. Parks, C. Margolvis, S. Bhatt, C.
Encarnacion, D. Russell, and R. Margolis. 2001. A systematic test of an enterprise
strategy for community-based biodiversity conservation. Conservation Biology 15:1585-
1595.

Sanchez-Azofeifa, G. A., R. C. Harriss, and D. L Skole. 2001. Deforestation in Costa Rica: a
quantitative analysis using remote sensing imagery. Biotropica 33:378-384.

Saunders, D. A., R. J. Hobbs, and C. R. Margules. 1991. Biological consequences of ecosystem
fragmentation: a review. Conservation Biology 5:18-32.

Schelhas, J. and R. Greenberg, editors. 1996. Forest patches in tropical landscapes. Washington
D.C.:Island Press, 426 p. In Estrada et al. 2002.

Schmink, M. 2003. Communities, Forests, Markets, and Conservation. In D. Zarin, F. J. Putz,
M. Schmink, and J. Alavalapati (eds). Working Forests in the Tropics: Conservation
Through Sustainable Management? New York: Columbia University Press.

Schumaker, N. H. 1996. Using landscape indices to predict habitat connectivity. Ecology 77(4):
1210-1225.

Schwartzman, S., D. Nepstad, and A. Moreira. 2000. Arguing tropical forest conservation:
people versus parks. Conservation Biology 14(5): 1370-1374.









Schweik, C. and C. Thomas. 2002. Using Remote Sensing for Evaluating Environmental
Institutions: A Habitat Conservation Planning Example. Social Science Quarterly
83(1):244-62.

Serneels, S. and E. F. Lambin. 2001. Proximate causes of land-use change in Narok District,
Kenya: a spatial statistical model. Agriculture, Ecosystems and Environment 85:65-81.

Shafer, C. L. 1995. Values and shortcomings of small reserves. BioScience 42(2):80-88.

Sheldon, P. J. and T. Var. 1984. Resident attitudes to tourism in North Wales. Tourism
Management 5(1):224-233.

Silver, S. C., L. E. T. Ostro, C.P.Yeager, and R. Horwich. 1998. The feeding ecology of the
black howler monkey (Alouattapigra) in northern Belize. American Journal of
Primatology 45: 263-279.

Skole, D. and C. Tucker. 1993. Tropical deforestation and habitat fragmentation in the Amazon:
Satellite data from 1978 to 1988. Science 260:1905-1910.

Skole, D. 1995. Land Use and Land Cover Change: An analysis. IGBP: 4-7.

Smith, J. D. 1970. The systematic status of the black howler monkey, Alouattapigra Lawrence.
Journal ofMammalogy 51:358-369.

Southgate, D. 1990. The causes of land degradations along spontaneously expanding agricultural
frontier in the third world. Land Economics 66:93-101.

Southworth, J., H. Nagendra, and C. M. Tucker. 2002. Fragmentation of a landscape:
incorporating landscape metrics into satellite analyses of land cover change. Landscape
Research 27: 253-269.

Southworth, J., H. Nagendra, L. A. Carlson, and C. Tucker. 2004. Assessing the impact of
Celaque National Park on forest fragmentation in western Honduras. Applied Geography
24: 303-322.

Stein, T. V., D. H. Anderson, and D. Thompson. 1999. Identifying and managing for community
benefits in Minnesota State Parks. Journal ofPark and Recreation Administration
17(4):1-19.

Stem, C. J., J. P. Lassoie, D. R. Lee, D. D. Deshler, and J. W. Schelhas. 2003. Community
participation in ecotourism benefits: the link to conservation practices and perspectives.
Society and Natural Resources 16(3):387-413.

Stokols, D. and S. A. Shumaker. 1981. People in places: a transactional view of settings. In
Cognition, social behavior, and the environment. J. H. Harvey (ed), Lawrence Erlbaum
Associates: Hillsdale, NJ.









Stuart, M., V. Pendergast, S. Rumfelt, S. Pierberg, L. Greenspan, K. Glander, and M. Clarke.
1998. Parasites of Wild Howlers (Alouatta spp.) International Journal ofPrimatology
19: 493-512.

Sussman, R. W., M. G. Green, and L. K. Sussman. 1994. Satellite imagery, human ecology,
anthropology and deforestation in Madagascar. Human Ecology 22(3): 333-354.

Tai, H. 2007. Development Through Conservation: An Institutional Analysis of Indigenous
Community-Based Conservation in Taiwan. World Development 35(7): 1186-1203.

Taylor, G. 1995. The Community Approach: does it really work? Tourism Management 16(7):
487-9.

Taylor, J. E. and T. J. Wyatt. 1996. The shadow value of migrant remittances, income and
inequality in a household-farm economy. The Journal of Development Studies 32:899-
912.

Terborgh, J. 1986. Keystone plant resources in the tropical rain forest, In: M. Soule (ed.).
Conservation Biology. Sinauer Associates, Sunderland, pp. 330-344.

Terborgh, J. 2000.The Fate of Tropical Forests: A Matter of Stewardship. Conservation Biology
14(5):1358-1361.

Thomas, J. W., E. D. Forsman, J. B. Lint, E. C. Meslow, B. R. Noon, and J. Verner. 1990. A
conservation strategy for the Northern Spotted Owl: report to the interagency scientific
committee to address the conservation of the Northern Spotted Owl. In Schumaker, 1996.

Thomlinson, J. R., P. V. Bolstad, and W. B. Cohen. 1999. Coordinating methodologies for
scaling landcover classifications from site-specific to global: steps toward validating
global map products. Remote Sensing of Environment 70:16- 28.

Tisdell, C. A. 1995. Issues in biodiversity conservation including the role of local communities.
Environmental Conservation 22(3):216-222.

Trani, M. K. and R. H. Giles, Jr. 1999. An analysis of deforestation: metrics used to describe
pattern change. Forest Ecology Management 114:459-470.

Tuan, Y. F. 1980. Rootedness verses sense of place. Landscape Urban Planning 24(1):3-8.

Turner, B. L. II, D. Skole, S. Sanderson, G. Fischer, L. Fresco, and R. Leemans. 1995. Land-Use
and Land-Cover Change Science / Research Plan: International Geosphere-Biosphere
Programme.

Turner, M. G., R. H. Gardner, R. V. O'Neill. 2001. Landscape Ecology in Theory and Practice.
Springer-Verlag, New York, USA, 401 pp. In Abdullah, S.A. and N. Nakagoshi 2007.

Um, S. and J. L. Crompton. 1987. Measuring resident's attachment levels in a host community.
Journal of Travel Research 26:27-29.









Vanclay, J. K. 1995. Modeling Land Use Patterns at the Forest Edge: Feasibility of a Static
Spatial Model. In Ecological Economics Conference, pp. 78-84. Coffs Harbour, NSW,
1995, Centre for Agricul- tural and Resource Economics, University of New England,
Armidalen, NSW, Australia. In Mertens and Lambin 2000.

Vaske, J. J. and K. Korbin. 2001. Place attachment and environmentally responsible behavior.
Journal ofEnvironmental Education 32(4): 116-21.

Vogelmann, J. E. and B. N. Rock. 1988. Assessing forest damage in high-elevation coniferous
forests in Vermont and New Hampshire using Thematic Mapper data. Remote Sensing of
Environment 24: 227-246.

Wall, G. 1997. Is ecotourism sustainable? Environmental Management 21:484-491.

Walsh, S. J., R. E. Bilsborrow, S. J. McGregor, B. G. Frizzelle, J. S. Messina, W. K. T. Pan, K.
A. Crews-Meyer, G. N. Taff, and F. Baquero. 2003. "Integration of longitudinal surveys,
remote sensing time series, and spatial analyses: Approaches for linking people and
place." In People and the Environment: Approaches for linking household and
community surveys to remote sensing and GIS, eds J. Fox et al., 91-130. Boston: Kluwer
Academic Publishers.

Wang, T. H. and R. D. Katzev. 1990. Group commitment and resource conservation: Two field
experiments on promoting recycling. Journal ofApplied Social Psychology 20(4) Part 1:
265-275.

Waser, P. M., S. R. Creel, and J. R. Lucas. 1994. Death and disappearance-estimating mortality
risks associated with philopatry and dispersal. Behavioural Ecology 5:135-141.

Weaver, J. L., P. C. Paquet, and L. F. Ruggiero. 1996. Resilience and conservation of large
carnivores in the Rocky Mountains. Conservation Biology 10(4):964-976.

Weiss, J. L., D. S. Gutzler, J. E. Allred Coonrod, and C. N. Dahm. 2004. Long-term vegetation
monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal
ofArid Environments 58(2): 249-272.

Werner, C. M., J. Turner, K. Shipman, and F. S. Twitchell. 1995. Commitment, behavior, and
attitude change: An analysis of voluntary recycling. Special Issue: Green psychology.
Journal ofEnvironmental Psychology 15(3): 197-208.

West, P., J. Igoe, and D. Brockington. 2006. Parks and People: The Social Impact of Protected
Areas Annual Review of anthropology 35:251-77.

White, L., B. Curbow, M. Costanzo, and T. Pettigrew. 1983. Social psychological approaches to
promoting lifestyle and device-oriented conservation behaviors. In Pardini and Katzev
1983-1984.

Wickham, J. D., R. V. O'Neill, K. B. Jones. 2000. Forest fragmentation as an economic
indicator. Landscape Ecology 15:171-179.









Wilcox, B. A. 1980. Insular ecology and conservation. In Soule, M.E. and B. Wilcox (eds.).
Conservation Biology: An Evolutionary-Ecological Approach. Sunderland, MA: Sinauer
Assoc. pp. 95-118.

Williams, D. R., S. B. Anderson, C. D. McDonald, M. E. Patterson. 1995. Measuring place
attachment: More preliminary results. In Davenport and Anderson 2005.

Williams, D. R., M. E. Patterson, and J. W. Roggenbuck, and A. E. Watson. 1992. Beyond the
Commodity Metaphor: Examining Emotional and Symbolic Attachment to Place. Leisure
Sciences 14:29-46.

Williams, D. R. and J. J. Vaske. 2003. The Measurement of Place Attachment: Validity and
Generalizability of a Psychometric Approach. Forest Science 49(6):830-840.

Wood, C. H. and R. Walker. 1999. Tenure Security, Investment Decisions and Resource Use
Among Small Farmers in the Brazilian Amazon. Paper in S67: Population and the
Environment, Local. http://www.iussp.org/Brazil2001/s60/S67 04 Wood.pdf

World Conservation Union (IUCN). 2004. The Durban Action Plan (revised version). Presented
at IUCN 5thWorld Parks Congress, Durban S. Afr. In Naughton-Treves et al. 2005.

World Resources Institute (2005) World Resources 2005 (World Resources Institute in
collaboration with the United Nations Development Programme, United Nations
Environment Programme, and the World Bank, Washington, DC). In Berkes 2007.

Wright, P. 1993. Sustainable tourism: Balancing economic, environmental, and social goals
within an ethical framework. The journal of tourism studies 4:54-65.

Wunder, S. 2000. Ecotourism and economic incentives an empirical approach. Ecological
Economics 32(3):465-479.

Zube, E. H. and M. L. Busch. 1990. Park-people relationships: An international review.
Landscape and Urban Planning 19:117-131.









BIOGRAPHICAL SKETCH

My undergraduate degree in environmental science and past field and work experiences

have shaped my professional interests towards community-based, natural resource management

issues. In the past I have be involved with animal ecology research on the Guanaco (Lama

guanicoe) in Patagonia, southern Chile; grassroots environmental and community organizing in

Minnesota; and research developing model progressive, state, environmental legislation.

My love of travel, of languages, and of the environment has also guided my career

interests. After receiving a B.S. in environmental sciences from the University of Massachusetts,

I spent the next 6 months living and working on an Israeli kibbutz. Returning to the U.S., I

worked with US Public Interest Research Group (PIRG), a non-profit, non-partisan

environmental and consumer rights advocate organization and co-directed a campaign office in

Minneapolis, Minnesota. There I really learned the power of community organizing, working

with the media, and building coalitions. After a year with the PIRGs I had the opportunity to

work on an animal ecology research project on the Guanaco (Lama guanicoe) in Parque

Nacional Torres del Paine in Patagonia, Southern Chile in conjunction with Iowa State

University. The next year I returned to Minnesota and served as an Americorps / Vista

(Volunteers In Service To America) volunteer working as a community organizer with a tenant's

right organization organizing in manufactured (mobile) home park communities around

Minnesota.

These experiences made me realize that my passion was working with communities on

environmental conservation issues. This brought me to pursue an M.S. degree in natural

resource management / environmental education and interpretation from the University of

Wisconsin Stevens Point where I worked with a rural Mayan ejido (community) in

southeastern Mexico in the development of an ecotourism management plan. This plan was









requested as the initial organizational step to developing and implementing community-based

ecotourism within this ejido, a document for potential funders, and a framework for other

communities within the Calakmul Model Forest area interested in ecotourism development. This

plan was later used by the community to secure funding from the Rigoberta Menchu

Organization.

My M.S. research and exploratory travel within the Maya Forest region spurred my

interests in more closely examining the popularity of community conservation initiatives

combining economic development as a way to protect natural and cultural resources while also

providing for local people's needs. This led to my doctoral research within the Community

Baboon Sanctuary, Belize where I examined conservation from various perspectives.

Aside from my professional interests, in my spare time I enjoy gardening, playing music

(guitar and banjo), canoeing, and travelling.





PAGE 1

1 CONSERVATION INITIATIVES, COMMUNITY PERCEPTIONS, AND FOREST COVER CHANGE: A STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE By MIRIAM SARAH WYMAN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORID A IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

PAGE 2

2 2008 Miriam Sarah Wyman

PAGE 3

3 To the residents of the Community Baboon Sanctuary, Belize

PAGE 4

4 ACK NOWLEDGMENTS I want to thank the people in Belize who made my stay there so enjoyable : my host families ( Ms. Matilda Banner, Mr. Robert and Ms. Alma Hendy and family, Mr. Ruben and Mrs. D orla Rhaburn, Mr. Elston Wade, and Ms. Olive Thompson ) I also want to thank Ms. Jessie A ddition ally thanks go to Aaron and Rachel Wagner (Peace Corps volunteers) for all their logistical support and to my research assistants, Sharo n Hazel and Mandy Bailey, who were instrumental in helping me conduct interviews. T hanks also to the Belize Forest Department for their support of this research. Lastly, I want to also thank Dr. Robert Horwich and Dr. Gail Lash for their information and ad vice on my many questions. I want to first thank my supervisory committee ( David Bray, Martha Monroe, Brian Child, and Jane Southworth and especially my chair, Taylor Stein ) for their patience, time, and mentoring. I owe much to my friends at the Land Use and Environmental Change Institute ( LUECI ) lab at the University of Florida : Lin Cassidy, Forrest Stevens, Natalia Hoyos, Hector Castaeda and Matt Marsik. It is also to my friends who kept me sane from ultimate frisbee, to running out at San Falasco, to craft days: Yael Gichon, Katy Garland, Deb Wojick, Katie Painter, Gaby Stocks, Amy Duchelle, Dave Buck, Ellie Harrison Buck, Dave Wilsey, John Engles, Christine Archer Engles, Cara Rockwell, Chris Barloto, Mandy Bailey, Lisa Seales, Maria DiGiano, and man I also want to thank my family for all their support and for their influence that certainly played a strong role of who I am today. To my father who fostered a love of nature and the outdoors and to my mother who showed me a love of languages and traveling. You both have

PAGE 5

5 encouraged me to follow my dreams. I thank my sister Ruth and brother Dan for always being a phone call away whenever I needed to talk. I thank my husband and best friend, Matthew Catalano, who has always been an incredible source of emotional strength and support As we finish this chapter of our lives together, I look forward to many more wonderful and exciting adventures with you. Last, but not least, I thank my sister in law and close friend Jenny Kell er, who left this world much too soon. You were always an inspiration to me. It is in large part because of you that I purs ued an advanced degree, and the memory of your passion for change and positive attitude still encourages me during challenging time s today.

PAGE 6

6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 8 LIST OF FIGURES ................................ ................................ ................................ ......................... 9 ABSTRACT ................................ ................................ ................................ ................................ ... 10 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 12 Study Overview ................................ ................................ ................................ ...................... 13 Community Benefits ................................ ................................ ................................ ........ 14 Place Based Meanings ................................ ................................ ................................ ..... 15 Land Use Land Cover Change ................................ ................................ ........................ 16 Research Statement ................................ ................................ ................................ ................. 17 Importance of the Study ................................ ................................ ................................ .......... 19 2 COMMUNITY BENE FITS, PLACE BASED MEANINGS, AND CONSERVATION: A STUDY OF THE COMMUNITY BABOON SANCTUARY, BELIZE ........................... 20 Introduction ................................ ................................ ................................ ............................. 20 The Role of B enefits in Conservation ................................ ................................ ............. 23 Theoretical Framework: The Place Attachment Framework ................................ .......... 24 Study Objectives ................................ ................................ ................................ ..................... 25 Methods ................................ ................................ ................................ ................................ .. 26 Study Site ................................ ................................ ................................ ......................... 26 Data Collection ................................ ................................ ................................ ................ 32 Results ................................ ................................ ................................ ................................ ..... 34 Discussion and Implications ................................ ................................ ................................ ... 37 Pledging ................................ ................................ ................................ ........................... 38 Tourism ................................ ................................ ................................ ............................ 39 Limitations ................................ ................................ ................................ ....................... 42 Conclusion ................................ ................................ ................................ .............................. 43 3 INTEGRATING SOCIAL AND LAND USE/LAND COVER CHANGE DATA TO ASSESS DRIVERS OF DEFORESTATION: a STUDY OF THE COMMUNITY BABOON SANCTUARY, bELIZE. ................................ ................................ ...................... 53 Introduction ................................ ................................ ................................ ............................. 53 Methods ................................ ................................ ................................ ................................ .. 56 LULCC in Belize ................................ ................................ ................................ ............. 56 Study Site ................................ ................................ ................................ ......................... 57

PAGE 7

7 Household Surveys ................................ ................................ ................................ .......... 58 Remote Sensing ................................ ................................ ................................ ............... 60 Spatial Regression Models of Deforestation ................................ ................................ ... 64 Results ................................ ................................ ................................ ................................ ..... 66 CBS Land Cover Trends ................................ ................................ ................................ 66 River Buffer Trends ................................ ................................ ................................ ......... 67 Drivers of Deforestation ................................ ................................ ................................ .. 68 Model 1 (1989 1994) ................................ ................................ ............................. 68 Model 2 (1994 2000) ................................ ................................ ............................. 69 Model 3 (2000 2004) ................................ ................................ ............................. 69 Model Validation ................................ ................................ ................................ ............. 71 Discussion ................................ ................................ ................................ ............................... 73 Drivers of Deforestation ................................ ................................ ................................ .. 73 Limitations ................................ ................................ ................................ ....................... 77 Conclusion ................................ ................................ ................................ .............................. 78 4 FOREST FRAGMENTATION AND HABITAT CONSERVATION FOR THE BLACK HOWLER MONKEY: A STUDY WITHIN THE COMMUNITY BABOON SANCTUARY, BELIZE ................................ ................................ ................................ ........ 96 Primate Populations ................................ ................................ ................................ ................ 98 Belize Forests ................................ ................................ ................................ ........................ 101 Study Objectives ................................ ................................ ................................ ................... 101 Methods ................................ ................................ ................................ ................................ 103 Study Site ................................ ................................ ................................ ....................... 103 The Community Baboon Sanctuary Howler Populations ................................ ............. 104 Remote Sensing ................................ ................................ ................................ ............. 105 Landscape Metrics ................................ ................................ ................................ ......... 107 Results ................................ ................................ ................................ ................................ ... 109 Landscape Fragmentation ................................ ................................ .............................. 109 Discussion ................................ ................................ ................................ ............................. 110 Current Suitable Howler Habitat ................................ ................................ ................... 111 Howler Population s ................................ ................................ ................................ ....... 112 Limitations ................................ ................................ ................................ ..................... 114 Conclusion ................................ ................................ ................................ ............................ 115 5 CONCLUSION ................................ ................................ ................................ ..................... 123 Perceived Benefits and Place Based Meanings of Riparian Forest Landscapes .................. 123 Relative Influence of Factors on Deforestation Probability ................................ ................. 124 Forest Habitat Fragmentation ................................ ................................ ............................... 125 Conclusion ................................ ................................ ................................ ............................ 126 LIST OF REFER ENCES ................................ ................................ ................................ ............. 1 28 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 152

PAGE 8

8 LIST OF TABLES Table page 2 1 Reported Household Inc ome from the 45 households receiving remittances .................... 48 2 2 CBS tourism participation and financial income by village.. ................................ ............ 48 2 3 Results from n ominal g roup m eeting and first round interviews ................................ ...... 49 2 4 Survey sample ................................ ................................ ................................ .................... 50 2 5 Community Benef its (Importance) Means. ................................ ................................ ........ 50 2 6 Community Benefits (Attainment) Means. ................................ ................................ ........ 51 2 7 Place Attac hment of Riparian Forests Means ................................ ................................ .... 52 3 1 Preceding year/month precipitatio n information of the CBS area. ................................ ... 91 3 2 Accuracy Assessme nt of 2004 L andsat ETM+ image. ................................ ..................... 91 3 3 Change Detection Analysis of the CBS landscape.. ................................ .......................... 92 3 4 Change Detection Analysis of a 120 meter river buffer ................................ .................... 92 3 5 Deforestation probabi lity on household land parcels Model 1 (1989 to 1994) ................ 93 3 6 Deforestation probabi lity on household land parcels Model 2 (1994 to 2000) ................. 93 3 7 Deforestation probability on h ousehold land parcels Model 3 (2000 to 2004) ................ 94 3 8 Prediction results for binary logit models ................................ ................................ .......... 95 4 1 C BS black howler monkey population and population density estimates ....................... 120 4 2 Area (ha) and percent land cover of CBS forested and non forested landscapes in 19 89 and 2004 ................................ ................................ ................................ .................. 120 4 3 Area (ha) and percent land cover of forested and non forested CBS 500 meter river buffer landscape in 1989 and 2004 ................................ ................................ .................. 120 4 4 Forest Patch Level Analysis of the CBS landsca pe and 500 meter river buffer. ............ 121 4 5 Class Level Analysis of the CBS landscape and 500 meter river buffer. ....................... 121 4 6 Suitable howler habitat ................................ ................................ ................................ ... 122

PAGE 9

9 LIST OF FIGURES Figure page 2 1 Map of the Community Baboon Sanctuary and Belize River Valley area ........................ 46 2 2 Tourist Figures to the Community Baboon Sanctuary, Belize. ................................ ......... 46 2 3 Households i nvolved in tourism by village. ................................ ................................ ..... 47 3 1 Map of the Com munity Baboon Sanctuary, Belize ................................ ........................... 80 3 2 CBS parcel map of study location ................................ ................................ ..................... 81 3 3 Land cover change trends for CBS. ................................ ................................ ................... 82 3 4 Change detection analysis for 120 meter river buffer ................................ ....................... 83 3 5 Probability of deforestation as a function of distance ................................ ....................... 84 3 6 Probability of deforestation as a function of c attle ................................ ........................... 84 3 7 Probability of deforestation as a function of agriculture ................................ .................. 85 3 8 Probability of deforestation as a function of education of household head and f amily size ................................ ................................ ................................ ................................ .... 85 3 9 Probability of deforestation as a function of tenure and remittances ................................ 86 3 10 Probability of deforestation as a function of conservation initiative ................................ 86 3 11 Probability of deforestation as a function of outside (CBS) work and pasture ................ 87 3 11 Predicted versus observed pixel deforestation / stable forest for 1989 94 (Model 1). ...... 88 3 12 Predicted versus observed pixel deforestation / stable forest for 1994 2000 (Model 2). ................................ ................................ ................................ .......................... 89 3 13 Predicted versus observed pixel deforestation / stable forest for 2000 2004 (Model 3). ................................ ................................ ................................ ................................ ....... 90 4 1 Map of the Commu nity Baboon Sanctuary in Belize ................................ ...................... 117 4 2 CBS fores ted and non forested landscape. ................................ ................................ ...... 118 4 3 CBS 500 meter river buffer landscape. ................................ ................................ ............ 119

PAGE 10

10 Abstract of Dissertat ion Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy CONSERVATION INITIATIVES, COMMUNITY PERCEPTIONS, AND FOREST COVER CHANGE: A STUDY OF THE CO MMUNITY BABOON SANCTUARY, BELIZE By Miriam Sarah Wyman December 2008 Chair: Taylor Stein Major: Forest Resources and Conservation The Community Baboon Sanctuary (CBS), Belize, an IUCN Category IV protected area, was established in 1985 to protect fore st habitat for the black howler monkey ( Alouatta pigra ) Nature based tourism and a pledge were created to promote conservation. This study assess ed conservation from three perspectives : 1) the landowner (place based meanings and benefit perceptions attr ibuted to riparian forests ), 2) the landscape ( social and land use/land cover change analyses to assess deforestation drivers ), and 3) howler habitat (forest cover change and fragmentation). Methods incorporated h ousehold interviews and remote sensing to conduct change detection analys e s, landscape metric analyses and modeling using Landsat satellite imagery from 1989, 1994, 2000, and 2004. R esults show 1) a significant relationship between initiative involvement and higher perceived benefits (importance) and place attachment towards riparian forests and conservation; 2) involvement in tourism and pledging together decreas ed deforestation probability, with other influential variables including road and river distance, tenure, cattle, agriculture, and educa tion level; and 3) a 23% forest cover loss between 1989 and 2004 and increased forest fragmentation However, high connectivity exists between most forest patches and indicates dispersal potential has not been jeopardized. A ddition ally howler population s have increased dramatically in t he last 20 years

PAGE 11

11 CBS c onservation may be more complex than simply saving fore sts and, therefore saving howlers, as increased fragmentation actually provides better habitat for ficus spp. (e.g., figs), the preferred food source. Under IUCN Category IV designation, one could argue conservation success as documented by howler population increases However, if the conservation objec tive is forest preservation, the 23% forest cover decrease would signal conservation failure This indicate s the CBS should not be managed for a single outcome (e.g., howlers) As deforestation is tied to livelihoods, the two initiatives should be closer examined On one level these initiatives are a strong basis for conservation. However, bene fit and participation ineq uality exit. A ddition ally other variable s are more influential deforestation drivers Therefore, without addressing these discrepancies, this foundation is not enough to compete with the important economic opportun ities forests provide and reiterates the lesson that the success of any conservation initiative must be linked to local communities benefiting from their conservation of biodiversity.

PAGE 12

12 CHAPTER 1 INTRODUCTION The overall focus of t his dissertation examines conservation within the Community Baboon Sanctuary (CBS), Belize from three different perspectives: 1) human perceptions and values ( e.g., focusing on perceived benefits and place based meanings of riparian forest landscapes); 2) land cover change (e.g., focusing on t he influence of these initiatives on deforestation probabilities, in addition to other locational and socio economic variables ); and 3) b lack howler monkey habitat ( e.g., focusing on forest fragmentation based on howler habitat criteria ). The research is presented as three separate papers, presented in publication style for submission to academic journals. Therefore, each paper is a stand alone document, addressing different aspects of the research statement described below. he linkages between community benefits, place based meanings, and conservation program and place attachment conceptualizations as an incentive to conserving forests, in addition to the role these conservation initiatives play in managing community benefits. The second paper, use/land cover data to assess drivers of deforestation : A study of the s remote sensing and spatial modeling to quantify and analyze the relative influence of tourism and the pledge, along with locational and socio economic variables, as drivers of deforestation within the CBS over a 15 year time period (1989 2004), using inf ormation from 33 habitat conservation for the black howler monkey: A study within the Community Baboon assesses the performance of conservation within the CBS as an IUCN Category IV protected area by examin ing changes in forest cover and forest fragmentation within

PAGE 13

13 the CBS over a 15 year time period (1989 2004) from the perspective of suitable habitat for the black howler monkey, the impetus for the creation of the CBS, based on habit at criteria. Study Overview A response to deforestation worldwide has been the creation of protected areas for fragile natural and cultural resources (Primack et al. 1998; Brandon et al. 1998; Bates and Rudel 2000; Langholz 2002). Nearly 35% of Belize has been designated some type of protected area status (Primack et al. 1998). However, d esignation alone is insufficient. Many protected areas are, in only protected on paper) which have resulted in land c onflicts and continued extractive uses of the forest now deemed illegal. This inability to manage and police protected areas, coupled with an environmental justice narrative, has called attention to the needs of local people living within and around these areas with schemes for community management of natural resources advancing as an alternative option (Alcorn 1993; Primack et al 1998). Many researchers and conservation practitioners posit that conservation of tropical forests is more effective and effi cient at small scale and local level regimes and that, in certain circumstances, and under an emerging set of institutional conditions, local communities are the most effective managers of local natural resources because of their dependence, contact, and s ubsequent knowledge of local resources (Lepp and Holland 2006; Agawal and Gibson 1999; Tisdell 1995). In conjunction with conservation, c ommunity based conservation initiatives are increasingly developing revenue generating activities, using market incenti ves to promote conservation (Tisdell 1995; PfB 2000; Wunder 2000; Langholz and Brandon 2001; Murphree 2003). Many criticize, however, that economic incentives alone may not be the only factors involved in impacting land use decisions, and there is not nec essarily a connection between economic income and pro environmental behavior ( Funder 1995; Wunder 2000; Salafsky et al.

PAGE 14

14 2001; Stem et al behaviors, it is often associated with social, infrastructural, and psychological factors, as seen in the following examples: Salafsky et al. (2001) found that the projects that generated the most community support for conservation were those that provided non cash benefits. In addition, a study by Funder (1995) on the impacts of the Campfire program on two communities in evaluation of income generating projects focused more on the provided services than on the revenues generated. Such findings suggest that other types of benefits must be considered in communal approaches to management and conservation. It is attitudes towards conservation will be improved that, ultimately, will foste r pro conservation behavior. Community Benefits Research does not often examine both the economic and non economic benefits potentially associated with protected areas in developing countries. Research in the U.S., Canada, New Zealand, and Australia tha t has examined these potential benefits shows improved and more efficient planning of natural areas that directly involves the community (Driver 1996; Moore and Driver 2005). Research is needed in developing countries where community based conservation is often targeted as a solution for protecting natural areas. It is by focusing on both intangible and tangible benefits from conservation that management plans will better respond to local resident needs (Stein et al. 1999; Davenport and Anderson 2005). Fo r example, a Hulme and Murphree (1999) study on the Kuenene region of Namibia show that the intrinsic values (e.g. benefits) of wildlife and the importance of passing them on to future generations plays an important role in wildlife conservation. Also, a study by Stein et al. (1999) identifying how two state parks in northern Minnesota benefit rural

PAGE 15

15 communities showed that attracting tourism dollars to surrounding communities was just one of a variety of benefits of conservation community stakeholders felt were important. In fact, benefits such as pride were considered more important than economic benefits for stakeholders of one state park. Place Based Meanings conservation w ill better enable management to respond to local resident needs, research that examines the specific benefits residents attain from nature might not address the relationship of based m eanings framework for addressing place based meanings to natural areas is with the place attachment framework Following the expansion of protected areas wor ldwide and an interest in understanding the relationships between protected areas and local people and the social outcomes of conservation, the application of place attachment is now expanding internationally (Kaltenborn et al., 1999; Kappelle 2001; Leppen s 2005; McCleave et al 2006) and is accepted as a relevant theoretical framework to understanding these relationships between local people and protected areas (Zube and Busch 1990; Williams et al. 1992; Brandenburg and Carroll 1995). Protected area manag ers are recognizing that the successful management of parks and protected areas must consider socio cultural issues along with nature conservation (Stankey 1989). For example, following national park expansion in southern Norway, understanding the complex meanings and relationships local people develop with their surroundings has become an important management strategy when addressing contested issues and development planning (Kaltenborn et al. 1999). Furthermore, the importance of considering people park relationships has been emphasized in

PAGE 16

16 several international environmental summits, such as the Durban Accord developed at the Fifth World Parks Congress in 2003, where input and involvement from locals within and around protected areas was stressed to ensu re their needs and interests are considered when management decisions are made (IUCN World Commission on Protected Areas 2003). Land Use Land Cover Change In addition to understanding the relationships between protected areas and local people, land use / land cover change (LULCC) studies are an important component in examining community based initiatives for forest conservation. Change dynamics of land cover (i.e., the biophysical attributes of the land surface) and land use (i.e., the anthropogenic influ ences on the land) are considered one of the main driving forces of global environmental change and its research is considered fundamental to sustaina ble development efforts (Meyer and Turner 1992; NRC 1998; Lambin et al 2000; Geist and Lambin 2002). Wit hin the umbrella of LULCC research, the need to understand the relationships between cleared and forested landscape patterns and agricultural land use dynamics within tropical forests has been stressed (Lambin et al. 2000; Mertens et al. 2000; Geoghegan et al 2001 ; Klepeis 2003; Garca Barrios and Gonzlez Espinosa 2004). As trends in Belize show agricultural intensification replacing forested landscapes and forests becoming more important in creating connectivity between smaller, fragmented, isolated hab itat patches (PfB 2000), LULCC research within the CBS has an important role. Remote sensing data provide information on the differences in land cover characteristics on spatial and temporal levels and has been used on a wide range of analyses, one of whic h is forest change detec tion (Fernside 1986; Vogelmann and Rock 1988; Skole and Tucker 1993; Sader et al. 1994; Jha and Unni 1994; Foody et al 199 6; Di Fiore 2002; Southworth et al. 2004). Remote sensing has also been used extensively with ethnographic m ethods, from household

PAGE 17

17 surveys to socio economic data, to better understand the dri vers of land use change (Guyer and Lambin 1993; Sussman et al. 1994; Mertens et al. 2000; Sader et al. 2001; Hayes et al. 2002; Southworth et a l. 2002; Schweik and Thomas 20 02; Bray et al. 2003; Dalle et al. 2006). The use of remote sensing data to measure forest cover change after implementation of community based conservation initiatives has also demonstrated an objective way to evaluate the long term effectiveness of thes e initiatives (Dalle et al. 2006). Research Statement T he Community Baboon Sanctuary ( CBS ), the focus of this study, is not community based conservation as commonly discussed in the literature In most cases, the concept of community based conservation f ocuses on government owned protected area s (e.g., National Park) with people living outside its borders. In contrast, the CBS consists of private landowners who have voluntarily pledged to set aside their land and to manage it in a particular way that in creases its conservation value by creating an inter connected habitat within a large landscape. Despite the fact that the CBS has existed since 1985, little monitoring has been conducted to assess the effectiveness of the conservation initiatives in promot ing conservation and deterring deforestation. Also, research has not explained the potential influence of other factors (e.g., locational and socio economic variables); the level of deforestation and forest fragmentation that has occurred (specifically ri parian forest cover, considered critical habitat for the black howler monkey ); or based meanings of riparian forest landscapes as an incentive to conservation (the initial habitat focus of conservation within the CBS ) This dissertation hopes to address these issues through a holistic overview of conservation within the CBS to more effectively base future management decisions and contribute to a better understanding of community based init iatives for forest conservat ion. Objective 1: Assess perceived benefits and place based meanings of riparian forest landscapes,

PAGE 18

18 Objective 2: A ssess the relative influence of tourism and pledging on deforestation probabilities, in addition to other locational and socio economic vari ables, and Objective 3: Assess forest fragmentation for the black howler monkey based on habitat criteria Chapter 2 addressed the first objective and expand ed on sense of place and place attachment conceptualizations by applying a framework within a less developed country (Belize) that has only been employed in the US and a few other more developed countries (e.g., Australia). The objectives of this paper are to identify the importance and attainment of community benefits from riparian forest landscapes ( the focus of the conservation initiatives), conservation programs (nature community benefit i mportance, community benefit attainment, and attachment to riparian forests. Chapter 3 addressed the second objective conduct ed parcel level spatial model s (binary logit models) to assess the relative influence of the two conservation initiatives (nature based tourism and pledging) on deforestation probability. In addition, this paper evaluates the relative influence of other variables (locational and socio economic) driving deforestation with in the CBS, using information from thirty three landowner s and their parcels over a 15 year time period and 4 satellite image dates. Overall land cover change trends within the CBS, as well as along a 120 meter river buffer within and outside the CBS are also assessed. Chapter 4 addressed the third objective examin e d changes in forest habitat for the black howler monkey (the impetus for the establishment of the CBS). Using remote sensing of satellite imagery and landscape metrics, this study reviews the performance of the CBS as an IUCN Category IV protected area b y assessing changes in forest cover and forest fragmentation within

PAGE 19

19 the CBS and 500 meter river buffer over a 15 year period (1989 2004) and how this has impacted habitat for the black howler monkey, based on specific habitat criteria. Importance of the Study Combined, these papers provide an overview of conservation and the effectiveness of two conservation initiatives (nature based tourism and pledging) in deterring deforestation and promoting conservation within the CBS. This study takes into account human perceived benefits and place based meanings, potential drivers of deforestation and fragmentation of howler monkey habitat. It is through this triangulation of social and spatial data, from understanding the human perspective to forest cover chan ge to howler habitat fragmentation that conservation assessment and future management decisions can be more effectively made. It is also hoped that the methods employed will encourage others to also examine conservation initiatives from different perspe ctives to provide a more thorough and accurate assessment of the effectiveness of conservation. It is from here that more appropriate decision making can be made to improve the role conservation initiatives play in not only meeting conservation goals, but also in managing for community benefits, considering community based conservation is often argued in some circles, to be the solution for protecting natural areas.

PAGE 20

20 CHAPTER 2 COMMUNITY BENEFITS, PLACE BASED MEANINGS, AND CONSERVATION: A STUDY OF THE CO MMUNITY BABOON SANCT UARY, BELIZE Introduction A response to deforestation worldwide has been the creation of protected areas for fragile natural and cultural resources (Brandon et al. 1998; Langholz 2002; West et al. 2006). There has been a dramatic incre ase in the area falling under protected status within the past 25 years with current figures indicating over 100,000 protected areas worldwide, covering 11.5% of the 2 ) ( a of land and/or sea especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective der IUCN categories) are open to human use at some level ( Naughton Treves 2005). cts and continued extractive uses of the forest now deemed illegal. This inability to manage and police protected areas, coupled with an environmental justice narrative, has focused attention on the role of local communities and the decentralization of re source management and conservation, with schemes for community management of natural resources advancing as an alternative option (Agrawal and Gibson 1999; Gibson et al. 2002; Schmink 2003). Those in support of community based conservation posit that the c onservation of tropical forests is more effective and efficient at small scale and local level regimes and that, in certain circumstances, and under an emerging set of institutional conditions, local communities are the most effective managers of local nat ural resources because of their dependence, contact, and subsequent knowledge of local resources (Tisdell 1995; Agrawal and Gibson 1999; Lepp and Holland 2006).

PAGE 21

21 It is worth noting, however, that the conservation community is divided on its support of prot ected areas as they relate to the coexistence of land use to improve livelihoods and biodiversity conservation to protect ecosystem services (Brechin et al 2002; Adams et al. 2004, DeFries et al. 2004). While one side favors the community based conservatio n narrative and balancing human well being with nature conservation (Adams and Hulme 2001, Schwartzman et conservation are contrasting goals (Oats 1999; Redford and S anderson 2000; Terborgh 2000). The Millennium Ecosystem Assessment (Brown et al. 2005) and World Resources Institute (2005) recognize livelihood needs and biodiversity conservation as complementary goals and support the integration of livelihood needs and ecosystem management. Considering these new protected area directions, s ome conservationists have changed their approach to meet these goals through various strategies linking development and conservation, including integrated conservation development pro jects (ICDPs) and community based natural resource management ( Naughton Treves 2005). Considering forests can provide multiple products and services, including non timber forest products (NTFPs) and nature based tourism, community based conservation initi atives are increasingly developing revenue generating activities, using market incentives to promote conservation (Tisdell 1995; Wunder 2000; Langholz and Brandon 2001; Murphree 2003). In conjunction with an increase in protected areas, the number of priv ately owned reserves worldwide is also increasing (Langholz 1996), with those owned or operated by NGOs or communities increasingly developing nature based tourism. Reserves with nature based tourism have been categorized as 1) communally managed, by usuf ruct rights, leased or owned lands, 2) NGO managed, or 3) owners of contiguous, small size holdings jointly managing their

PAGE 22

22 lands (Langholz and Brandon 2001). In both private and common property (a form of private property where members of a recognized gr oup share rights to a resource) examples, nature based tourism initiatives within communities can be considered a common pool resource where benefits from tourists using a resource are shared by the providing community (Healy 1994). Tourism landscapes, st complex property rights with competing users exist over common pool resources (includi ng action and rules must be devised that prevent depletion or degradation of the resource (Healy 1994; Lindberg et al. 1996; Edwards 2004). Although revenue generating activities, such as ec otourism, can provide important financial benefits to communities and aid in conservation goals, financial incentives alone are not the only factors affecting land use and resource use decisions. T here is a connection between financial income and pro envir driven by non financial incentives ( Wunder 2000; Salafsky et al. 2001; Stem et al. 2003). Even complemented by s ocial, infrastructural, and psychological factors, as seen in the following examples: Salafsky et al. (2001) found that the projects that generated the most community support for conservation were those that provided non cash benefits. Furthermore, a stu dy by Funder (1995) on the impacts of the CAMPFIRE program on two communities in Zimbabwe evaluation of income generating projects focused more on the provided services than on the revenues generated. Aside from a few case studies, howe ver, there is a lack

PAGE 23

23 of good, empirical data for understanding the social impacts of protected areas and the positive and negative impacts conservation has on communities (Igoe 2006). Along this same vein of social impacts, the comparison between potenti al financial and non financial benefits associated with protected areas and conservation in developing countries is not often examined (Zube and Busch 1990, Salafsky et al. 2001). In the U.S., Canada, New Zealand, and Australia, a wider view of these pote ntial benefits shows improved and more efficient planning of natural areas that di rectly involves the community ( Stein 1999; Kappelle 2001; Davenport and Anderson 2005; McCleave et al. 2006). Based on this broad understanding of conservation incentives, a range of complementary benefits must be considered in communal benefits, argues Hulme and Murphree (1999), that attitudes toward conservation will be improved that, ultimately, will foster pro conservation behavior. The Role of Benefits in Conservation The role of identifying and managing benefits effectively in conservation is a difficult protected areas, one approach taken in this study is to look at the Benefits Based Management (BBM) framework. Although initially applied to recreation and leisure management, BBM is applicable to the broader context of amenity resources such as cultural resources, wildlife, wilderness, and scenic values, which also includes the physical, social, and psychological benefits that individuals, families, communities, and even societies at large might gain from exposure to these resources (Driver 1996; Moore a nd Driver 2005). Considering the purpose of BBM is to assist managers to better define how their actions will benefit humans or the natural environment, the concept of BBM is appropriate for my current study to better understand how to best provide commun ity benefits.

PAGE 24

24 Under the BBM framework, a benefit viewed as more desirable than a previous one; (b) maintenance of a desired condition and thereby prevention of an unwanted condition from occurring, preven tion of an undesired condition from becoming worse, or reduction of the unwanted impacts of an existing undesired p.38). This concept has often been used in research within the human dimensions of natural resource management (Anderson et al. 2000; Booth et al. 2002). Of equal importance with providing benefits from conservation, but an often overlooked part of the process, is the understanding of community b enefits attributed to natural areas that can help ensure that management plans are responsive to local resident needs (Stein 1999; Davenport and Anderson 2005). For example, research by Jones and Murphree (1999) in the Kuesene region of Namibia shows that the intrinsic values of wildlife and the importance of passing them on to future generations play an important role in wildlife conservation. Also, a study by Stein et al. (1999) on how two state parks in northern Minnesota benefit rural communities showe d that attracting tourism dollars to surrounding communities was just one of several benefits of conservation community stakeholders felt were important. In fact, benefits such as pride were considered more important than financial benefits for stakeholde rs of one state park. Theoretical Framework: The Place Attachment Framework conservation will better enable management to respond to local resident needs, research that examin es the specific benefits residents attain from nature might not address the relationship of based meanings provides an

PAGE 25

25 ural areas. One framework for addressing place based meanings of natural areas is through the place attachment framework Initially coined by Tuan, a human geographer, place attachment applies to places that gain meaning and definition through the in dividual experiences that occur within those places (Tuan 1980). The concept of place attachment has been found in various disciplines including human geography, psychology, and anthropology with the accepted basic definition as an emotional bond between people and places (Proshansky et al. 1983; Low 1992; Williams et al. 1992; Cuba and Hummon 1993; Vaske and Kobrin 2001; Williams and Vaske 2003; Kyle et al. 2004; Davenport and Anderson 2005). Research on place attachment has been conducted largely in the U.S. to examine how natural areas influence how residents feel about their community development within natural areas (Sheldon and Var 1984; Um and Crompton 1987; McCoo l and Martin 1994; Williams et al 1995). The place attachment framework, when used to understand the links between natural resource management and these emotional connections to natural landscapes, includes two constructs: place identity and place depend ence (Williams et al. 1992). The construct place identity concerns symbolic meanings of place and is based on the notion that places affect the Place dependence i physical characteristics (Stokols and Shumaker 1981; Williams et al. 1992; Williams and Vaske 2003). Study Objectives Following the expansion of protected areas worldwide, the application of place attachment is now expanding internationally, albeit primarily in more developed countries, to

PAGE 26

26 examine the relationships between protected areas and local people, and the social outcomes of conservation (Zube and Busch 1990; Kaltenborn et al. 1999; Kappelle 2001; Leppens 2005; McCleave et al. 2006). Considering the increase in protected areas (West et al. 2006) and the rise in community based conservation initiatives developing revenue generating activities to promote conservation (Tisde ll 1995; Wunder 2000; Langholz and Brandon 2001; Murphree 2003), examining the relationships between protected areas and local residents and the social outcomes of conservation has an important role; the Community Baboon Sanctuary (CBS) in Belize is one su ch example. O bjectives of this study were to assess t he social impacts of the CBS by 1. I dentifying the importance and attainment of community benefits from riparian forests, the impetus for the creation of the CBS 2. M arian forests and 3. A ssessing if involvement in one or both of the two conservation programs (nature based benefit importance, community benefit attainment, and attachme nt to riparian forests. Methods Study Site The Community Baboon Sanctuary (CBS), Belize ( 17 33 N, 88 35 W), was established in 1985 to protect one of the largest remaining populations of black howler monkeys ( Alouatta pigra America (Figure 2 1). The CBS is not community based conservation as is normally concei ved. The concept of community based conservation under the IUCN definition is based on communities next to public protected areas. The CBS, however, is a unique situation with private landowners agreeing to manage their land in a

PAGE 27

27 particular way that woul d increase its conservation value and create an inter connected habitat in a larger landscape. This effort to create a community baboon sanctuary began when two American scientists recognized the area for its howler population and the positive attitudes vi llagers had toward the howler monkeys. After approval from the villagers and Village Council to investigate the potential of creating a community based sanctuary in the area, and with support of a local non governmental organization (the Belize Audubon So ciety), the lands for this sanctuary were set aside by private landowners from seven Creole communities situated along 33 kilometers of the Belize River (Horwich and Lyon 1990). For 20 years various residents within the CBS communities have participated i n two conservation strategies: 1) a written, voluntary pledge for private landowners to leave a strip of riparian forest and forested corridors that provide habitat connectivity for howler monkey populations and 2) nature based tourism centered on the howl er monkey that provides financial incentives to landowners protect howler monkey habitat. P ledge : The private landowners who make up the CBS share a common pool resource for conservation and nature based tourism: the howler monkey. Because this resource is mobile, although tends to remain in close proximity to the Belize River, pledging landowners have and their integrity, along with the howler monkey population, d epend upon the collective action by all landowners to observe a set of rules. This collective action has been established in the form of a voluntary, written, public pledge and landowners are encouraged to sign and agree to do their part in protecting how ler monkey habitat. The concept of pledging is a form of commitment to a particular conservation practice by an individual landowner. The idea behind a landowner pledge was that by signing this

PAGE 28

28 voluntary, written pledge, landowners agree to not clear thei r land along the riverbank and to leave a forested corridor between property boundaries. River property is highly valued for its fertility, compared with other soils of the area, which reflects the location of farming in these areas. Furthermore, those r esidents with cattle and river property often maintain cattle here so cattle can easily access water. Although the pledge was not initially linked with any financial compensation with money that was collected through tourism, CBS records and research by La sh (2003) indicate that pledged landowners were paid twice (1998 and 2000 totaling ~$250 per landowner) by the CBS management at the time, but presently no residents are given any financial compensation for pledging. Because of this initial payment, pledg ed residents expect to be paid; reality now associates the pledge with financial compensation. Nature b ased t ourism : Nature based tourism centered around the howler monkey was initiated with the establishment of the CBS as a way to create a financial incen tive for residents to conserve important forest habitat. Residents involved in tourism obtain both permanent and seasonal employment, ranging from tour guiding, selling crafts, housing visitors, trail maintenance, and visitor center / museum assistance. T he CBS tourism headquarters that house the museum and visitor center are located in Bermudian Landing village. Tourist visitation to the CBS has dramatically increased in the last few years (Figure 2 2) due, almost exclusively, to the introduction of cruis e ship tourism to Belize. Decreased numbers from 2005, relative to 2004, which, subsequently, affected tourism numbers to the CBS. CBS m anagement : From its inception, management of the CBS (pledging, museum, tour guides, and education programs) was given to a local resident manager under the guidance of the

PAGE 29

29 Belize Audubon Society (BAS). In 1994, autonomy of CBS management responsibilities (e.g., all accounti ng and marketing, museum, tourism guides, etc.) was given over to a local CBS committee (Lash 2003). CBS management has changed at least seven times in its first thirteen years, with various combinations of the BAS, a local committee, and resident manager s in charge (Bruner 1993; Horwich and Lyon 1998). The only consistencies within the CBS (Lash 2003) are as follows: 1. T he body of the CBS comprised of pledged landowners 2. T he CBS headquarters (museum) housed within Bermudian Landing village 3. T he continued in volvement of one specific family within the CBS to some extent (a member of this family was selected as the first manager of the CBS) representatives from the different CBS vill ages, has managed the CBS (in 1998 the former committee was asked to resign) This committee was responsible for one of the two payments to Group, as well as the ma nager / lead tour guide position are occupied by family members from one family that has always been involved with the CBS. Another barrier to effective management of the CBS are the external influences of a negative context (such as drug use) have a pres ence within the CBS and have not been appropriately addressed or resolved. CBS v illages: Today there are 222 households within the seven villages of the CBS, comprising approximately 1500 people (Jones and Horwich 2005). Within the literature, the CBS is d esignated as a 4800 ha area (Horwich and Lyon 1990). However, this did not include the full village boundaries or account for households located on properties away from the river. Because of this inclusion within my study, the total study area encompassed 8703.54 ha (87.04 km).

PAGE 30

30 Land tenure is roughly evenly divided between titled and government leased lands (20 year leases). Despite the difference in de jure property rights, there is little variation between de facto property rights of the two land tenu re regimes; the majority of residents are long term residents, many having lived here for generations, and possess high perceived land security. African slaves) within the seven villages of the CBS. Although only comprising a few families each, the other ethnic groups represented within the seven CBS villages include Asian, Hispanic/Mayan (from Guatemala and Honduras), and Caucasian (US Mennonites). These other ethnic grou ps have migrated to the area over the past ten years for various reasons. Those leaving Guatemala and Honduras were looking for employment and land opportunities; in the late 1980s, the Chinese population increased dramatically with immigration from Hong Kong and Taiwan; and US Mennonites are increasing their presence and missionary work in rural parts of Belize (Merrill 1992). but still maintains forest cover an d some of the traditional ways of living and income generation. Information from interviewing residents reveals that although farming and other traditional land and forest use are less common today with more people choosing to work outside the home and of living in Belize City as expensive, dirty, and dangerous. The main livelihood activities of the CBS villages include: employment with nature based tourism ( primarily in the village of Bermudian Landing); small scale agriculture; small scale cattle raising; small scale coconut oil and cohune nut oil ( Orbignya cohune ) production; cashew; and outside wage employment (primarily in or around Belize City).

PAGE 31

31 There are several households in each village that have over 50 head of cattle but many residents have a few head of cattle that serve as a bank account in many ways; if someone is sick or another occasion to need cash presents itself, a cow can immediately be so ld. Agriculture is an important livelihood activity for residents of the CBS, especially for those with river property where the soils are the more fertile of the area. Slash and burn agricultural plots are locally marily are used for home consumption or local sale (within villages). The villages are located roughly 35 miles from the nearest district market where agricultural and forest products are sold, including medicinal plants and game meat (Belize City). The closest market where a good variety of agricultural products are sold is in a neighboring town en route to Belize City named Burrell Boom (located roughly 15 miles from s around their village and neighboring villages to sell along the roadside or even try to sell these goods house to house. These products range from agriculture crops, fish and game meat, and cohune and coconut oil. Collecting cashew seeds and cashew fru it for a few months every year is a period when local residents can supplement their income. At least one middle man in a neighboring town (Burrell Boom) purchases the cashew seeds from residents. Although small scale, many residents also living in villag es with cashew trees collected and roasted nuts for sale in Belize City and for visiting tourists to the CBS. Sixty three percent of the 135 households interviewed for this study have at least one family member who works outside of the CBS. The 5 year old paved road that crosses through four of the seven villages has increased bus service with access to 6 of the 7 villages several times daily (Monday through Friday) to Belize City in the mornings and returning to the CBS villages in the evening (approximat ely a 35 mile / 56 km commute). This has made living in the

PAGE 32

32 CBS villages and working in Belize City very feasible. Another important income source is remittances. One third of the interviewed population receive remittances from family members who have l eft and live and work in the U.S. From the 135 households interviewed, 45 households reported receiving remittances; together remittances totaled $95,850 BZE (approx US $ 47,925) over the course of one year, accounting for 28.5% of their total income (wag e and other) (Table 2 1). Additionally, out of the 45 households who received remittances, 11 households reported remittances as the only source of monetary income. Although the pledge and nature based tourism have existed for over 20 years within the C BS (at different levels of activity), little monitoring has been done to assess the effectiveness of benefits of riparian forests and the function of place atta chment as an incentive to conserving forests, in addition to the role that these two conservation initiatives play in managing community benefits. Considering this, it is worth examining the non financial benefits and ways residents perceive riparian fore st landscapes, along with the financial benefits that are presumed to come from tourism and pledging. The significance of assessing both importance and attainment of community benefits, as well as place based meanings attributed to riparian forest landsca pes, addresses not only what benefits residents feel are most important, but also how much they feel these benefits actually improve their livelihoods. This study will aid future planning and management to determine how to improve the integration of natur e based tourism and pledging into community development and environmental conservation strategies Data Collection Semi structured interviews and one focus group meeting were used to initially identify perceived benefits residents attributed to riparian f orests, nature based tourism, and pledging (Table 2 3). In total, 135 resident interviews from the 7 villages (61% of the CBS population,

PAGE 33

33 approximately 20 households per village) collected quantitative and qualitative data on perceived social, environment based meanings towards riparian forests within the CBS. Initially, a stratified sample was conducted with all pledged and tourism households. Twenty six households participating in tourism (out of approximately 35 total, with 12 households participating only in tourism) and 51 households participating in the pledge (out of approximately 75 total, with 37 household participating in only the pledge) agreed to participate in the study. Approximately half of those households involved in tourism are also pledged households (n = 14). The remainder of the household interviews (n = 58) were composed of randomly selected households (all non tourism / non pledged households) (Table 2 4). Questions were pr esented verbally with the head of the household (if the household was not involved in either tourism or the pledge) or with the individual who was involved with the pledge or tourism initiative. Interviewees were shown and explained the Likert type scale with the value system presented to help residents gauge the strength of the answer (e.g., very important versus somewhat important), with examples demonstrated for clarity before the interview process began. Data analyses used SPSS 11.5 to generate descri ptive statistics and T benefits and place attachment of riparian forest landscapes. Community b enefits One nine item question on community benefits asked i f riparian forests are providing benefits. Interviewees answered from an Importance category (five item Likert type scale) and an Attainment category (four item Likert type scale) developed from nominal group meetings conducted with residents, and from th e established literature (Davenport and Anderson 2005; Stein et al. 1999).

PAGE 34

34 Place a ttachment Place attachment questions consisted of a twelve item Likert type scale adapted from a variety of literature (Williams et al. 1992; and Jorgensen and Stedman 2001 ; Davenport and Anderson 2005). Based on work by Davenport and Anderson (2005), scale items fell under the following categories: Place dependence : economic stability, nature and natural processes and Place Identity : family legacy, community character, and self identity. Results The 26 residents interviewed who are participating in tourism estimated their total tourism earnings to be US $14,005.00 during the year of this study (July 2005 July 2006) (Table 2 2). Out of the 35 estimated residents known to be participating in tourism over the course of study (but not all interviewed), the largest amount of residents,13 (37%), were residents of Bermudian Landing village (the CBS and tourism headquarters) (Figure 2 3). The village with the second largest numb er of residents participating in tourism (n = 6) was Double remaining three villages had 3 or less residents participating in tourism. Community b enefits : Importance ( g ener al m eans) Overall, all benefits of riparian forest landscapes identified through focus group meetings and past literature w ere rated important (all above 3 out of 5 ) by residents (Table 2 ranked highest for impo rtance (mean = 4.6). Benefits specifically addressing quality of life (e.g., s = 4.2). = 4.1).

PAGE 35

35 Community b enefits : Attainment ( g eneral m eans) Respondents believe they are lowest mean (1.6). Based on this 6). Community b enefits : Pledging and t ourism From examining the differences between tourism only (n=12) and non tourism residents (n=123), tourism residents had slightly higher means on most perceived importance of riparian forest benefits. Considering statistically significant differences, those involved in tourism thought riparian forests were more important in (mean = 4.1 / 3.7) (Table 2 5). Under perceived attainment the lowest for tourism residents. With respect to significant differences, no differences were found for attainment of these benefits between tourism and non tourism residents (Table 2 6). From examining the differences between pledged only (n =37) and non pledged residents (n=98), pledged only residents had slightly higher means on conservation related scale items under perceived importance of riparian forest benefits. Considering statistically significant differences, those pledged only resid ents thought riparian forests were more important in 5). Under perceived attainment perceived attained benefit from riparian forest landscapes pledged residents

PAGE 36

36 for at tainment of specific benefits associated with community character and nature and natural 2 6). In comparing benefit importance means between those residents involved in both tourism and pledging (PT) (n=14) and those not involved in either (Non most important benefit from riparian forest landscapes for PT residents (mean = 4.4), while ranked fourth for Non significance between PT and Non PT residents (Table 2 6). In examining benefit attainment ranked perceived attained benefit for PT residents, although significantly higher than Non PT res idents (mean = 2.1 / 1.6). Place a ttachment : Tourism Tourism only residents (n=12) rated items tied to water quality and habitat for wildlife significantly higher than non tourism residents (n=123) (Table 2 tourism residents (mean = 7.0). The two place attachment scale items ranked the lowest by depends on riparian fore Place a ttachment : Pledging Those residents who pledged only had significantly higher to the two economic items

PAGE 37

37 ghest by pledged only residents (mean = 7.0) followed PT residents also ranked these economic questions the lowest (mean = 4.0 and 2.4). From examining statistical signific ance, PT residents ranked the following place attachment scale items significantly higher than Non Discussion and Implications While there are only slight differences between the scores for many of the scale items under perceived benefits, attained benefits, and place based meanings between residents (tourism, pledged, PT, and non ), there are some important differences and results worth noting. Although CBS residents as a whole perceive that rip arian forests are providing conservation and environmental benefits, riparian forests are not perceived to be providing substantial financial benefits (including those residents involved in tourism), based on their lowest rankings acknowledged through plac e attachment and community benefits questions. In addition, through statistical analysis, there does appear to be a significant relationship between being involved in a conservation initiative (pledging or tourism) and placing more importance in certain p erceived benefits and place based meanings (attachment) towards riparian forests and conservation.

PAGE 38

38 Pledging Results show residents who pledged only and PT residents have higher perceived benefits and place based meanings towards riparian forest landscape s This indicates that they are likely more aware of the connections and benefits of riparian forests to conservation and quality of life issues than non pledged residents. In fact, pledged only residents had significantly higher place attachment scores f or all dimensions except economic items and one community character scale item. The benefits pledged only residents believe they are attaining might help explain these results. They believe they are receiving benefits associated with health, quality of lif e, sustainability, and pride to a greater extent than non pledged residents. These correspond to place attachment items relating to water quality, history and family ties to the forest, and personal attachment to the forests. Another reason for this relati onship might be explained through the very act of making a coordination among residents, the pledge is a simple process of landowners making a written, public, and volu ntary pledge to manage their property under certain guidelines. Although these data do not show direct cause and effect relationships, past research on the concept of commitment is based on the premise that once a pledge is formally made, a bond is strengt hened between the promise and future action (McKenzie Mohr and Smith 1999). Others propose that be ignored when faced with an opportunity to demonstrate that commitment. Some scholars within the field propose that commitment functions on the feared social disapproval of others when a public commitment is not made (Wang and Katzev 1990) and the expectation on ourselves, as well as others who have made a commitm ent, to honor them completely (Katzev and Wang 1994). It is not surprising that pledged residents ranked economic scale items low

PAGE 39

39 since reality now associates the pledge with some financial payment resulting from past payments. The fact that pledged res idents are not given any financial compensation for pledging but are aware tourism is bringing in money (and many are probably aware of its growth), may explain the low scores on economic scale items. Tourism Results show residents involved in tourism onl y do not perceive tourism to be a major benefit from riparian forests, nor impact their attachment to riparian forests. CBS residents involved in tourism only were more likely to rate only three out of the lowest four benefits more important than resident unique ecosystems gre residents did not significantly differ from non tourism residents in their perception of attainment of any benefits. A surprising result was the lowest ranked scale i tem for tourism only and PT residents considering tourism residents are receiving financial revenue indirectly from these forests Under place attachment, had mean scores of 2.8 and 2.4. For perceived benefit attainment, had mean scores of 1.6 and 2.1 (Table 2 2). Nearly 13,000 tourists visited the CBS in 2005 (Figure 2 2), correlating with the time of this study, yet benefits that would be directly tied to these visitors (i.e., financial) were not perceived to be attained by tourism residents (nor non tourism residents). This may relate to perceived inequality in the distribution of tourism jobs and money that the management may wish to explore.

PAGE 40

40 Elite capture of benefits is not an uncommon occurrence within development projects (Bardhan 2002, Platteau 2004) as development projects can set off local political struggles and rent seeking opportunities (gaining control of resources) that elites can o ften easily dominate (Tai 2007). The concern with conservation initiatives is that the stakeholders who should be benefiting the most, based on their activities that impact the environment (with expectations that they will promote conservation in return), are seeing the benefits go to only certain stakeholders, such as the local political elites (Chan et al. 2007). For example, a study on community based ecotourism development in Gales Point, Belize, showed that the majority of people employed through tou rism belonged to only five households (Belsky 2000). Where tourism shows equity in benefit distribution, conservation successes have been reported. For example, The Cofan Community Ecotourism Program in Zabalo (Cuyabeno Reserve), Ecuador, where tourism be nefits have been shown to be equitably distributed, has resulted in the protection of the more rare and attractive wildlife species due to their recognition as being important for ecotourism (Ceballos Lascurain 2001). In another example, a nature based to urism project to protect wildlife within a Maasai community adjacent to Amboseli National Park, Kenya also transformed conservation attitudes of the local community (Fitter 1986). Benefits from tourism, such as employment and community development project s from concession leases, have resulted in no poaching or harassment of wildlife on the whole within the community owned lands, in contrast to neighboring areas where bush meat poaching is now rampant and causing a serious decline in wildlife (Lusigi 1981) In both these cases, the equitable distribution of tourism benefits transformed attitudes resulting in tangible conservation outcomes. Additionally, if the financial benefits from tourism are not being equally or fairly distributed throughout the CBS, then it is not likely that benefits indirectly associated with

PAGE 41

41 nature These results sh ow that Bermudian Landing village had the largest number of households participating in tourism, the same village where the CBS headquarters are located (Figure 2 3). This demonstrates the spatial distribution of tourism income within the CBS. Distance a nd travel time is likely a factor, as being involved with tourism in most situations requires coming to the CBS visitor center in Bermudian Landing village In an attempt to benefit communities outside Bermudian Landing, a Creole Heritage Museum was built with the help from Program for Belize (PfB), a Belizean non profit. For about a year PfB arranged for tourist visits but today this museum is only visited on rare occasions by school groups, arranged through the CBS some tourism money from a few school visitors, although this was the smallest amount of money earned by tourism residents during this year of field work earn ed tourism money from housing visiting US students. The same situation applies in Flowers Bank, the most rural and least accessible of the CBS villages, where one family occasionally house s visitor s. Housing visitors is an attractive job, compared to oth er tourism related jobs, as it happens infrequently (approximately 7 days per year) and is lucrative This too may be an example of elite capture as families that are better off financially are those with more developed homes and are, therefore better ab le to receive visitors. Belsky (2000) found in her study of community based ecotourism in Gales Point, Belize that l ogically, it tends to be the families in a community that are better off that are chosen to house visitors, as these households have the sa nitation and cooking facilities and additional bedroom space.

PAGE 42

42 Some residents upset over the lack of tourism benefits they are receiving have taken matters into their own hands and are developing tourism on their own properties (and also focusing on the h owler monkey and experiencing Creole culture). In some cases they are also siphoning off of tourists driving to the CBS Four households are trying to promote their own tourism efforts, at different levels and with varying success. Two are located in Sco tland Half Moon, one in Isabella Bank, and one in Flowers Bank; all households are located on the Belize River. Results suggest that tourism and place attachment have a slightly stronger relationship in the CBS than tourism and perception of benefits, wi th scale questions showing statistical explanation for this signifi cance with conservation related scale items is likely related to the fact that many of those involved in tourism, especially those employed as a tour guide or clearing trails, will have a higher tendency than those residents not involved in tourism to spen d time in and around these forest landscapes. Past research has shown that attachment to a place increased with more frequent visitation, which also fostered an increased perceived familiarity and the belief that the place was special (Williams and Vaske 2003; Davenport and Anderson 2004). Considering that the majority of residents interviewed within the CBS have at least one household member working outside (63%), the majority of residents may not have the leisure time or necessity to spend time in these landscapes. Limitations This study was not without its limitations. I took note of the non responses in my study, of which a variety of reasons exist. For example, some residents are American Mennonites who are a fairly closed group and did not want to participate in my study. However, these residents

PAGE 43

43 are not involved in pledging nor tourism and are not long time residents of the area. Other residents were not available for interviews despite repeated attempts to contact them. Additionally, some reside nts were working temporarily outside of the CBS during my research. However, considering I interviewed 26 out of the 35 residents involved in tourism, 51 out of the 75 residents involved in pledging, and a total of 135 out of 222 existing households (appr oximately 20 househ olds in each of the 7 villages) demonstrates that I incorporated a good representative sample of the area. In addition applying theoretical frameworks (e.g., place attachment) that were developed in western cultures to less developed co untries may also present some issues. However, there has been an expansion of protected areas worldwide and an interest in understanding the social outcomes of conservation Therefore it was important to attempt to expand this application with in protecte d areas in less developed countries where community based conservation is seen in some circles to be an important component for protecting natural areas. Conclusion The concern with some conservation initiatives is that the benefits (and participation) are not being distributed equally or are not going to the residents who should be the focus of these initiatives. This appears to be occurring within the CBS where there is a perception of skewed distribution of both tourism participation and benefits, si gnaling a potential elite capture of managed more effectively and equitably to have any other significant impacts on improving ests or actively helping conserve those forests. This inequality of benefits can have additional impacts on community based conservation. Where community conservation could fail is where the collective action and involvement with protecting howler monkey habitat is jeopardized. According to Burger et al.

PAGE 44

44 (2001), unless a resource provides some benefit, individuals are not apt to accept the costs involved in protecting or managing that resource. Benefits from tourism do not appear equitably distributed, no r are funds going to pledged residents for protecting howler monkey habitat on their properties, while at the same time the number of tourists are increasing (nearly 13,000 in 2005). Because of these factors, there is probably not much incentive from thos e not benefiting from tourism directly or indirectly (e.g., pledging) to participate. This could impact collective action and involvement with protecting howler monkey habitat. On another note, this research has revealed some positive points. Although t he tourism and pledging initiatives might be perceived as income generative failures by respondents, the people involved in the activities value, benefit from, and feel attached to the forest for a variety of non financial reasons. In particular, pledging residents are more highly aware of the non financial benefits and feel more attached to riparian forests. Since this study does not indicate causal patterns, it is not known if the activity helped to instill these attitudes and values, or if people with th ese existing attitudes and values were self selected for pledging. Regardless, this study shows that involvement in either conservation initiative, whether they are financially successful or not, is related to higher conservation values and perceived commu nity benefits and is a strong basis for conservation. Such perceived benefits would not have been realized without investigating place based meanings and perceived benefits and demonstrate their important role in conservation program analysis and planning As conservation policy discussions today emphasize the importance of local communities benefiting from their active role in biodiversity conservation, the findings from this study have implications for local planning and management by identifying how com munity residents believe nature based tourism and pledging provide incentives and barriers to improving livelihoods and conserving natural resources. It is this type

PAGE 45

45 of information that will aid future planning and management to determine how to improve t he integration of initiatives such as nature based tourism and pledging into community development and environmental conservation strategies.

PAGE 46

46 Figure 2 1. Map of the Community Baboon Sanctuary and Belize River Valley area (Lash 2003) Figure 2 2 Tourist Figures to the Community Baboon Sanctuary, Belize.

PAGE 47

47 Figure 2 3. Households involved in tourism by village. There are an estimated 35 households participating in tourism during the course of this study. Although only 26 w ere interviewed, the other residents involved were identified.

PAGE 48

48 Table 2 1. Reported Household Income from the 45 households receiving remittances Type of Income Amount in BZE $ Amount in US $ Percentage of total income Wage Income $163,073.00 $81,536.50 48.6% Remittances $95,850.00 $47,925.00 28.5% Other non wage income $ 76,939.00 $38,469.50 22.9% Total $335,862.00 $167,931.00 Table 2 2. CBS tourism participation and financial income by village. As reflected in this table, in Bermudian Landing the re are seven more households benefiting from tourism that declined to be part of this study (out of 135 residents interviewed). Village Name Number of CBS households involved in tourism in 2005 (interviewed) Number of CBS households involved in tourism in 2005 (not all interviewed) Total tourism income earned in 1 year (US$) by households per village Village household size (during year of data collection) Willows Bank 3 3 4,410 35 Isabella Bank 2 2 4,275 23 Bermudian Landing 6 13 2,325 39 St Pauls Ba nk 5 5 950 26 Double Head Cabbage 4 6 910 43 Scotland Half Moon 5 5 825 32 Flowers Bank 1 1 310 24 Total 26 35 14,005 222

PAGE 49

49 Table 2 3. Results from n ominal g roup m eeting and first round interviews regarding costs and benefits of pledging and tourism. Pledging Tourism Benefits Costs Benefits Costs People still abide by it / have respect for it No economic benefits of pledging Money Tourists take liberties with their safety (encourages behavior from others to take advantage of tourists) People are no t cutting down forests where baboons live Conservation limits other activities, such as hunting Jobs Endangered / threatened species (that ecotourism is focused / or sold Trees preserve the bankside (river erosion lessened and more people are becoming aware of this) land as you would want especially riverside for pasture Generate Ideas/ Learning and Educational We have to be on our tourists are around Benefits everything: protects anima ls (animals, birds) and river systems (water, fish) that humans depend on Baboons eat all (fruit trees) and there are none left for people Incentive to keep your place and your village clean and nice looking Jobs are scarce and the forest (protected thr ough pledging) allows people to have tourism on their land One has to clean up leaves (under the trees that are left from the pledge) Contacts made with those from away Note: This was later used, along with the established literature, to develop scale i tems for place attachment and benefit questions.

PAGE 50

50 Table 2 4. Survey s ample Survey s ample Number of CBS h ouseholds Tourism only 12 Pledged only 37 Pledged and Tourism (PT) Non Pledge / Non Tourism Total 14 72 135 Table 2 5. Community Benefits (Importan ce) Means. Likert Scale (1 = not very important, 5 = Community b enefits ( i mportance) Overall N=135 P&T N=14 Non PT N=121 Tourism o nly N=12 Non t ourism N=123 Pledge o nly N=37 Non p ledge N=98 Living in a heal thy environment 4.6 4.6 4.6 4.6 4.6 4.5 4.6 Providing a good quality of life 4.2 4.2 4.3 4.4 4.2 4.2 4.2 Knowing conserved natural resources exist for future generations 4.2 4.3 4.2 4.2 4.2 4.4** 4.2** A feeling that your communit y is a special place to live 4.1 4.2 4.1 4.2 4.1 4.1 4.1 Attracts tourism dollars to my community 4.1 4.4 4.1 4.2 4.1 4.1 4.1 A natural setting in which your community takes great pride 4.0 4.1 3.9 4.0 4.0 3.9 4.0 A place to conserve vari ous natural and unique ecosystems 3.9 4.1 3.8 4.1 3.6 4.0 3.8 Improved care for community aesthetics 3.8 4.1* 3.8* 4.0 3.8 3.9 3.8 A greater concern for the natural environment among residents 3.8 4.1* 3.7* 4.1** 3.7** 3.8 3.7

PAGE 51

51 Table 2 6. Commu nity Benefits (Attainment) Means. Likert Scale (1 = not attained, 4 = fully attained) ** Community b enefits ( a ttainment) Overall N=135 PT N=14 Non PT N=121 Tourism o nly N=12 Non t ourism N=123 Pledge o nly N=37 Non p ledge N=98 Living in a healthy environment 3.6 3.8 3.6 3.7 3.6 3.7 3.6 Providing a good quality of l ife 2.7 2.5 2.7 2.5 2.7 3.0** 2.6** Knowing conserved natural resources exist for future generations 3.1 3.1 3.1 3.0 3.2 3.4** 3.0** A feeling that your community is a special place to live 2.8 3.0 2.8 2.7 2.8 2.8 2.8 Attracts tourism dollars to my community 1.6 2.1** 1.6** 1.6 1.6 1.6 1.6 A natural setting in which your community takes great pride 2.6 2.9 2.6 2.7 2.6 2.9** 2.5** A place to conserve various natural and unique ecosystems 2.6 2.6 2.6 2.4 2.6 2.8 2.5 Improved care for community aesthetics 2.2 2.1 2.1 2.2 2.1 2.1 2.1 A greater concern for the natural environment among residents 2.2 2.4 2.2 2.1 2.2 2.3 2.2

PAGE 52

52 Table 2 7. Place Attachment of Riparian Forests Means. Likert scale (1 = strongly disagree, 7 = Place Attachment Items Overall PT N=14 Non PT N=121 Tourism o nly N=12 Non t ourism N=123 Pledge o nly N=37 Non p ledge N=98 These riparian forests are important in providing habitat for wildlife 6.8 6.9 6.7 7.0** 6.7** 7.0** 6.7** M strongly tied to this riparian forest 6.6 6.6 6.6 6.1 6.7 7.0** 6.5** This riparian forest contributes to the character of my community 5.9 6.4 5.9 5.8 5.9 6.4** 5.8** These forests have helped put my community on the map 5.7 6.5 5.6 5.7 5.7 5.8 5.6 This riparian forest is a special place for my family 5.6 6.5 5.5 5.3 5.6 6.0** 5.4** Many important family memories are tied to these areas 5.5 6.4 5.4 4.8 5.5 6.1** 5.3** I am very attached to this riparian forest environmen t 5.4 5.9 5.3 5.0 5.4 6.0** 5.1** I feel a sense of pride in my heritage when I am there 5.2 6.1 5.1 5.4 5.2 5.7** 5.0** These riparian forests are important in protecting water quality 4.9 5.3 4.8 5.6* 4.8* 5.4** 4.7** depe nds on riparian forests 3.7 4.0 3.6 3.8 3.7 4.0 3.6 livelihood depends on riparian forests 2.5 2.4 2.5 2.8 2.5 3.0 2.3

PAGE 53

53 CHAPTER 3 INTEGRATING SOCIAL A ND LAND USE/LAND COVER CHANGE DATA TO ASSESS DRIVERS OF DEFORESTA TION: A STUDY OF THE COMMUNI TY BABOON SANCTUARY, BELIZE. Introduction D ynamics of land cover (e.g., the biophysical attributes of the land surface) and land use (e.g., the anthropogenic influences on the land) change are considered two of the main driving forces o f global environmental change (Meyer and Turner 1992; NRC 1998; Lambin et al 2000; Geist and Lambin 2002). Understanding these dynamics help inform, manage and predict impacts from land use changes, such as carbon storage, biodiversity, and ecological s ervices (Skole 1995; Turner et al. 1995; Olson et al. 2004). Within Land Use / Land Cover Change (LULCC) research, t ropical deforestation is considered one of the most significant threats to biodiversity (Laurance 1999). To better conserve tropical fores ts the proximate causes of deforestation must be investigated, in addition to assessing forest cover and forest loss (Roy Chowdury 2006a). Therefore, r esearch is increasingly focusing on linking social survey information f rom local land managers to land c over changes (Lambin et al. 2000; Mertens et al. 2000; Geoghegan et al 2001; Klepeis 2003; Garca Barrios and Gonzlez Espinosa 2004). This study assesses forest cover trends and examine s the relative influence of factors affecting deforestation within the Community Baboon Sanctuary (CBS), Belize by linking social survey and locational information f rom local land managers to land cover change. use decisions are shaped by many factors including land chara cteristics, land ownership, household socio demographics, economic and livelihood activities and any institutions or policies that present opportunities or li mitations for a particular land use activity (Olson et al. 2004). To better understand and ident ify the causes and driving forces of deforestation at the household level, past research has focused on the

PAGE 54

54 factors of location, socio demographic, tenure, socio economic variables and conservation initiatives. Areas more suitable to agriculture, such as forests in more level areas and areas of higher soil fertility, are more likely to be deforested (Kaimowitz and Angelsen 1998; Geist and Lambin 2001; Gibson et al. 2002; Gautam et al. 2004). Locational variables, such as distance to roads (access to trans portation routes and markets) also promote deforestation (Chomitz and Gray 1996) P eople are connected to their natural environment through the system of property rights (Hanna et al. 1996). In secure land tenure can encourage def orestation; people will deforest or harvest what they can when unclear restrictions to resources exist (Wood and Walker 1999). Chambers (1993) argues that unless people have secure rights to the resources they use, people will not be motivated to manage and protect them. Overall the literature supports that secure title and control over land resources encourages organizational capacity and can be linked to sustainable forest management and improved economic opportunities ( Ostrom 1990; Godoy and Bawa 1993; Nelson et al. 2001; Mur phree 2003). Among characteristics of the individual land owner, higher education levels w ere found to decrease deforestation where it provided greater opportunity for non farm wage income ( Pinchon 1997; Irwin and Geoghegan 2001; Roy Chowdury 2006b). An other household characteristic, increasing household size, has been found to increase deforestation probability due to subsistence demand although lifecycle phases can also relate to land clearing activities (Moran 2000). The uses to which scarce land is allocated is usually determined by the relative value of alternative uses of the land. Socio e conomic drivers to deforestation, such as cattle or

PAGE 55

55 agriculture, can be linked to external market demands (Lambin et al. 2001; Hubacek and Vazquez 2002) Ana ly ses of driving forces of land use change studies worldwide have identified a gricultural expansion (ranching and/or cultivation) as the leading proximate driver, which is often accompanied by timber extraction and transportation infrastructure (Lambin et al 2001; Geist and Lambin 2002; Lambin et al. 2003). Additional factors that may influence deforestation and land use intensification can be linked to projects (government or NGO sponsored) intended to promote development or conservation (Gibson et al. 20 00; Lambin et al. 2001). C onservation policy discussions today emphasize the importance of local communities benefiting from thei r conservation of biodiversity. Increasingly, community based conservation initiatives are integrating revenue generating act ivities and market incentives with conservation (Tisdell 1995; PfB 2000; Wunder 2000; Langholz and Brandon 2001 ). Under this scenario, nature based tourism has been recognized as an approach for providing communities local financial incentives for conserv ation (Tisdell 1995; Kangas et al. 1995; Bookbinder 1998; Kimmel 1999; Langholz 2002). The impetus for many community nature based tourism projects is to reduce the local threats to biodiversity, such as unsustainable harvesting of wild plants, hunting, a nd expanding agriculture by providing socio economic alternatives to current forest depletion and unsustainable agricultural practices (Boo 1990; Lindberg et al. 1996; Wunder 2000; Nyaupane and Thapa 2004). Another factor tied to conservation strategies shown to influence conservation behavior is the act of making a commitment or pledge to conservation behaviors (Kiesler and Sakumura 1966 : 349). The theoretical foundation of commitment is based on the

PAGE 56

56 premise that once a pledge is formally made, the bond is strengthened between the promise and future action. A n important element of commitment and conservation behavior change is that over time, if a behavior continues, a change in attitude will also occur (Werner et al. 1995). Commitment theory suggests that a public, voluntary, and written pledge not to deforest should decrease the probability of deforestation. Many decisions to modify l and use are taken by the household. Therefore, this study link s remote sensing and household socio economic data to integrate factors affecting deforestation (McCracken et al. 1999). D ecision making at finer scales (e.g., the household level) has 0to be structured within a broader set of issues at coarser scales ( including the community) and policy, pricing and regulatory issues at regional, national, and even global scales (e.g., public policy and institutions, global markets and prices) (Walsh et al. 20 03). To understand land use change at more aggregated scales, research must examine individual land use decisions at the parcel level (Ludeke et al. 1990). The objectives of this study were : 1. Determine rates and trends of forest cover change within the C ommunity Baboon Sanctuary ( CBS), Belize landscape over a 15 year time period (1989, 1994, 2000, 2004); 2. Determine and compare rates and trends of forest cover change of the 120 meter riparian forest buffer landscape within and outside the CBS over a 15 year time period (1989, 1994, 2000, 2004); and 3. Evaluate the relative influence of locational, land tenure, socio demographic, socio economic, and conservation initiative variables as drivers of deforestation within the CBS from the development of spatial, stat istical models. Methods LULCC in Belize The deforestation rate (2.3% per year) in Belize surpassed that of Central America (1.2% per year) during 1990 2000, increas ing abruptly from an annual forest loss of only 0.2% in the early 1980 s (DiFiore 2002). In 2007 Belize had 79% forest cover (FAO 2007), down from 97%

PAGE 57

57 forest cover in the early 1980s. However, as of 1992, the north central part of the country retains only 30% of its original forest cover (King et al. 1992). The main drivers encouraging defore station and fragmentation of remaining forests in Belize are large scale agriculture, milpas (small scale slash and burn farming), large and small scale cattle ranching, large and small scale logging, and urban growth (Horwich and Lyon 1990). Study Site Established in 1985 through the efforts of the Belize Audubon Society and two American scientists, the Community Baboon Sanctuary ( CBS ) was created to protect habitat for the black howler monkey ( Alouatta pigra ) along the Belize River (Horwich and Lyon 199 8) (Figure 3 1). The CBS is not a conventional protected area (e.g., national park) with peop le living outside its borders. In contrast, the CBS is comprised of seven Creole villages with private landowners who have agreed to manage their land in a parti cular way that increases its conservation value The CBS totals approximately 8700 ha located in the climatic region of north centra l Belize (17 with forest cover classified as lowland, semi deciduous rainforest. An annual rainfall of 60 70 inches (150 175 cm) is typical of the region, with a pronounced dry season from February through May (Horwich and Lyon 1998). The forests within the CBS (as throughout Belize) have been periodically logged for the past 300 years and today are comprise d of secondary forests (10 75 years old) with cleared areas and secondary growth (Horwich and Lyon 1990). The main livelihood activities within the CBS villages include employment with nature based tourism (primarily in the village of Bermudian Landing); small scale agriculture; small scale cattle raising; small scale coconut oil and cohune nut oil ( Orbignya cohune ) production; cashew harvesting ; and outside wage employment (primarily in or around Belize City roughly 35 miles away ).

PAGE 58

58 Since 1985 various r esidents within the CBS communities have participated in two conservation initiatives: nature based tourism focused arou n d the howler monkey and a written, voluntary conservation pledge for private landowners to leave a strip of riparian forest and foreste d corridors that provide habitat connectivity for howler monkey populations. L ittle monitoring however has been conducted to assess the effectiveness of the se two initiatives and other factors that influence deforestation Household Surveys This study eva luated the relative influence of landowner characteristics on deforestation probability. Remote sensing data were linked with the following land and landowner characteristics: locational, land tenure, socio demographic, socio economic, and participation i n conservation initiatives. Locational : The locational factors chosen for this study include distance to the Belize River and road networks from each forested pixel. Riparian areas are often chosen for agriculture within the CBS because of their more fert ile soils. Most of the riverine and cohune palm forests of the CBS are located on alluvial soils of the Bermudian Landing Series (USDA: Vertic Europept) (Horwich and Lyon 1990). In addition, road network s throughout the CBS have increased access to Beliz e City for outside employment opportunities and markets ( roughly 35 miles away). Land t enure: T he CBS includes private (titled) and governmen t leased (20 year) landholdings. The majority of the 33 landowners interviewed have title to their land (n = 27), with six households possessing government leases. Within the CBS, as well as throughout cleared for agricu lture or livestock) (Lash 2003) and, as such, there is a disincentive to leave large tracks of forest in place

PAGE 59

59 Socio demograph i c: Two demographic variables considered were family size and education level (number of years of education) of the household head. Family size of the 33 households interviewe d ranged between 1 to 10 members (mean = 4.8). Education level of the household head for these 33 households ranged between 0 to 18 years of schooling (mean = 8 years). Socio e conomi c: Agriculture and cattle activity were the two variables examined under socio economic variables. Although not as prevalent as years past, cattle ranching (both large and small scale) and small scale agriculture (mostly for home consumption) a re common livelihood activities From the 33 households interviewed, 21 practiced a griculture in 2005, cultivating 101.5 acres (out of an approximate 2566 acres total within the 33 parcels) The majority of those with cattle have less than 50 head, but cattle serve as a type of savings account for many residents; when instant cash is nee ded for medical emergencies or events such as weddings and funerals, a cow can be sold immediately either within the villages or in Belize City. Twenty of the 33 households interviewed (61%) manage some cattle, accounting fo r a total of 432 head of cattle C attle are also often kept by the river where they can easily access water. Conservation i nitiatives: Nature based tourism and a conservation pledge were two conservation initiatives examined within the CBS. The black howler m onkey ( Allouta pigra) is t he focus of tourism within the CBS, developed to provide economic incentives for residents to protect forest landscapes (especially riparian forests). Tourism related jobs range from employment in the visitor center and museum to tour guiding, housing vis itors, and maintaining trail s involving both seasonal and permanent positions. Ten out of the 33 households interviewed have at least one family member currently involved in tourism There does appear to be some inequality of tourism benefits, with the m ajority of residents currently involved in

PAGE 60

60 tourism residing in the village of Bermudian Landing, the location of the visitor center. Still, a few residents from other CBS villages are also involved with and benefiting financially from tourism, with some r esidents even starting to develop tourism opportunities on their own lands (see chapter two). The voluntar y, written, public conservation pledge asks landowners to agree to do their part in protecting forest habitat for the howler monkey. By signing thi s pledge, landowners agree not to clear their land along the riverbank (the main focus) and to leave a forested corridor between property boundaries. Although the pledge was not initially linked with any financial reward, CBS records and researc h by Lash (2003) indicate that pledged landowners were paid twice (1998 and 2000 totaling ~$250 per landowner) by the CBS management at the time, but presently no residents are given any financial compensation for pledging. Currently, 11 out of the 33 hou seholds interviewed are involved in tourism only, 10 households are involved in pledging only, and 8 are both pledged and tourism households. Remote Sensing Because of the differe nt drivers contributing to land use decisions, understanding LULCC requires the integration of multiple disciplines and tools, in this case remote sensing and socio economic data. Remote sensing data provide s informa tion on the differences in land cover characteristics on spatial and temporal levels and have been used on a wide r ange of analyses, one of which is forest change detection (Fernside 1986; Vogelmann and Rock 1988; Skole and Tucker 1993; Sader et al. 1994; Jha and Unni 1994; Foody et al. 1996; Di Fiore 2002; Southworth et al. 2004). Remote sensing has also been used ex tensively with ethnographic methods, from household surveys to socio economic data, to better understand the drivers of land use change (Guyer and Lambin 1993; Sussman et al. 1994; Mertens et al. 2000; Sader et al.

PAGE 61

61 2001; Hayes et al. 2002; Southworth et al 2002; Schweik and Thomas 2002; Bray et al. 2003; Dalle et al. 2006). Image pre processing : Three Landsat TM satellite images and one Landsat 7 ETM+ SLC off satellite image (Path 19, Row 48) were processed from 1989, 1994, 2000, a nd 2004 to analyze land cover change within the CBS and outside landscape. To decrease errors associated with seasonal variations on biophysical properties and subsequent change detection analyses, these images were taken between November and March, corresponding with the study season (Jensen 2005). Preceding year/month climate information of the area, in particular precipitation levels, were obtained and considered for the change analysis process considering e xtremely wet or dry conditions on one of the dates can ca use serious change detection issues (Table 3 1). Each Landsat image was corrected for atmospheric, sensor, and illumination variance sources through radiometric calibration and atmospheric correction procedures (Green 2000) to ensure change detection ac corrected geometrically using a 1:50,000 scale map of the study area obtained from the Belize Land Information Center ( UTM Zone 16, WGS 1984). Points from the 2004 rectified image were then used to register the other images, maintaining the root mean square (RMS) error of each registration below 0.5 pixels (<15 m). Image classification : Training sample protocol forms from the Center for the Study of Institutions, Population, and Environmental Change (CIPEC) were used (CIPEC 1998) for ground truthing the 2004 image within the CBS between September and December, 2005. Areas to include in a training sample covered a 90 X 90 m area to ensure that at least one full pixel fel l within that particula r land cover. In total, sixty six training sample points were taken (31 for

PAGE 62

62 forest cover in and around the CBS. Locations were recorded with a GPS (global position ing system) unit and other information, such as qualitative descriptions (e.g., photographs) was recorded for reference and comparison with classified maps and satellite imagery. A class was considered ng a definition of forest that functioned both socially and physically for the CBS. Training samples within the CBS were primarily taken along roads and the Belize River but in areas difficult to access, vantage and edge training sample points were also t aken. To further aid with the training samples the nature and extent of land use was obtained through informal landowner interviews and personal observations. Before classifying the images, clouds were removed from each image to create a mask that was th en applied to all images. Training sample data and GPS points were then used to conduct a hybrid supervised / unsupervised classification using the Gaussian Maximum Likelihood technique on the 2004 image, starting with an unsupervised classification of 60 classes. Considering forest was the class interest, other non forest areas (e.g., wetlands, built, agriculture) were merged into a final class : non forest (NF) after all the spectral reflectance differences were represented. An accuracy assessment on the 2004 classified image resulted in an overall classification accuracy of 84.85% and an o verall Kappa Statistics of 69.47%, with no individual class less than 80% (Table 3 2). An overall accuracy of 85% (with no class less than 70%) has been established as a target for accuracy assessments (Thomlinson et al. 1999). The remaining images were classified through comparison with signature mean plots of 2004 classes, and also contrasting vegetation using the NDVI and thermal band of each image. The result of th (F) (NF) classifications for each image date.

PAGE 63

63 Data analysis ( c hange d etection): For the landowner property change detection analyses, a 1992 CBS property owner map (1:50,000 scale map) was georeferenced to the 2004 Landsat image in ArcMap using roads and rivers as ground control points (GCPs) maintaining a RMS error below 0.5 pixels (<15 m). Individual properties were then digitized as shapefiles in ArcMap. Out of a total of 77 river property owners, 33 landowner properties were analyzed for this study, which account ed for those landowners who were interviewed, whose properties had not changed for the entire 15 year duration, and whose property boundaries were not impacted by cloud cov erage in the satellite images (Figure 3 2). The Belize River was digitized to create a shapefile in ArcMap. There is no existing precedence for establishing river buffer widths in Belize (for wildlife use or any other ecosystem function). Specific to th e Belize River within the CBS, 120 meters has been suggested by Dr. Robert Horwich (personal comm. 2008), a primatologist familiar with the riparian forest areas of the CBS, as the approximate river buffer area of flooding and higher soil fertility. Two types of change detection analyses were conducted: a change detection analysis of the CBS area over the four image dates (1989, 1994, 2000, and 2004) and a comparison of a n 120 meter buffer of the Belize River within and outside the CBS over the four image dates. For these analyses, the Spatial Modeler function in ERDAS Imagine software was used to create change detection images using the four images as inputs to develop an image differencing algorithm as the function and create a change detection image as the output. These change detection analyses using the four image dates create d 16 change classes. To better assess general trends of forest cover change over this 15 year period the 16 change classes were grouped into five categories: stable forest, stab le non forest, tending towards deforestation (starting with F and ending in NF), tending towards reforestation (starting in NF and ending in F), and transitional.

PAGE 64

64 Spatial Regression Models of Deforestation The model of deforestation within the CBS employ s binomial logit models with the classification derived dependent variable ( stable forest versus deforestation during the two image comparison) and landscape and socio economic GIS layers as independent variables to produce a predicted probability of defor estation, as well as parameter estimates. M u nroe et al. (2004) found that binomial logit models yielded better model fit, compared to multinomial logit models, in examining land cover change in Honduras. Roy Chowdury (2006a, 2006b) also applied binomial l ogit models to understand parcel scale deforestation decisions in Southeastern Mexico. Decisions about deforestation on parcels within the CBS are informed by considerations on (1) locational factors, such as distance to roads and distance to the Belize River from each forested pixel, (2) land tenure, (3) socio economic and socio demographic factors (for model 3 only), and (4) participation in conservation initiatives (nature based tourism and pledging) Following Geoghegan et al. (2001) and Roy Chowdury (2006a, 2006b), for the classification derived dependent variable, the probability of deforestation at a pixel can be given as: Pr(y j = 1|x j ) = e 0 1 x 1 2 x 2 ____________________ 1+ e 0 1 x 1 2 x 2 W here y j = 0 if pixel j was forest in the first year of the model and remained forested in the last year of model (stable forest) or 1 if pixel j was forest in the first year of t he model and was deforested in the last year of model (deforestation) x j = value of independent (explanatory) variable at pixel j = estimated parameters (coefficients) for each independent variable that can be estimated using a binomial logit specifica tion (Maddala 1983).

PAGE 65

65 Preliminary s tatistical a nalyses: Steps were taken to assess which variables were most important for modeling deforestation for the 2000 2004 time period (model 3) based on a priori information from the literature, as well as their importance within the region and the CBS Tests of collinearity were conducted between the binary independent variables using Chi square analyses and between continuous and continuous binary interactions using correlation C onsideration was gi ven to both the p value and the magnitude of the value A value of 0.50 or greater was a measure of high correlation, following Munroe et al. (2004). After eliminating some of the independent variables due to high collinearity, a binominal logit regressio n was conducted for each of the three two year period combinations (1989 1994, 1994 2000, and 2000 2004) Model 1 (1989 1994) and model 2 (1994 2000) assessed the impacts of 4 variables (tenure, pledge, distance to river, and distance to roads), due to temporally restricted variables while model 3 (2000 2004) employed a stepwise regression and addressed other socio economic and socio demographic variables collected from household interviews conducted in 2005. Next, spatial autocorrelation of residuals for each model was assessed through calculating I value, using ArcGIS spatial statistics. Moran's I is one of the most common ways to measure spatial autocorrelation, and is defined as a measure of the correlation among neighboring obser vations in a pattern (Boots and Getis 1988) and refers to the fact that the value of a variable at one point in space is related to the value of that same variable in a nearby location. This statistic is used to evaluate the presence or absence of spatial autocorrelation and is interpreted like a correlation coefficient, with values near +1 indicating strong positive spatial autocorrelation values near 1 indicating strong negative autocorrelation, and values near 0 indicating an absence of spatial patter n (Rogerson 2005). S patial autocorrelation was expected

PAGE 66

66 to exist within the models, as it is comm on in remote sensing studies (Mu nroe et al. 2004 ) and because much of the data for this study is measured at the parcel level (socio economic data) but the un it of analysis is at the pixel level (data are a t mismatched scales). M easures of spatial pattern were included in the analysis, such as distance to the Belize River and distance to the nearest road measured from each pixel, to decrease autocorrelation (Mo I values) to 0.07, 0.06 and 0.05 for the three models. After these preliminary statistical analyses, a final model was created for each two year period combination (three models in total). All data were standardized (subtracting the mean and dividi ng by the standard deviation) to enable comparison between binary and continuous variables within each model. Measures of accuracy ( pseudo R 2 and overdispersion parameter) and model validation were then assessed for model goodness of fit. Results To ad equately address conservation success, research must first assess forest cover and were to assess land cover change trend s of the CBS landscape and land cover trends of the 120 meter river buffer within and outside the CBS If conservation loss is occurring, the proximate causes of deforestation must also be investigated ( objective, which was to determine the relati ve influence of chosen variables on deforestation probability was designed to understand these causes. CBS Land Cover Trends Covering the entire 15 year time period (1989 2004), t he largest proportion of the CBS landscape follows the stable forest t rajectory, comprising 33.4 % (2908.98 ha) of the landscape. The second largest proportion of the CBS landscape follows the tending toward deforestation trajectory, comprising 29.7% of the landscape ( 2582.79 ha ). Tending toward reforestation and

PAGE 67

67 stable non forest accounted for 18.9% (1647 ha) and 13.8% (1200.6 ha ) of the landscape, respectively with the transitional trajectory accounting for 4.1% (361.17 ha) of the landscape ( Figure 3 3 and Table 3 3). Major results indicate the CBS landscape foll ows both stable forest and deforestation trends. River Buffer Trends Although assessment of the entire CBS landscape is important as a community reserve, the river buffer is the focus of conservation with the goal of protecting habitat for the black how ler monkey ( Alouatta pigra ) (the impetus for the creation of the CBS) and can serve as a proxy for conservation within the CBS. A 120 meter Belize River buffer running through the CBS was compared to the non protected segment of the Belize River buffer r unning north and south of the CBS. The leading land Although a difference in total river distance exists, attributed to cloud coverage on the satellite images and the importance of focusing on simi lar rural areas, the major land cover changes that have occurred along the river buffer within the CBS from 1989, 1994, 2000, and 2004 are the same changes that have occurred along the river buf fer outside the CBS (Figure s 3 4 and Tables 3 4). The largest proportion of the 120 meter river buffer both inside and outside the CBS falls under the l and accounting for 30.95% (257.22 ha) of the CBS river buffer and 29.83% (99.18 h a) of the river buffer outside the CBS. A close secondary leading land cover trend was stable forest, accounting for 26.09% (216.18 ha) of the CBS river buffer and 28.1% (93.42 ha) of the outside river bu ffer. The next land cover trajectory is that pro portion tending toward reforestation accounting for 25.71% (213.66 ha) within the CBS and 23.09% (76.77 ha) outside the CBS. Stable non forest and transitional covers account for the smallest proportions of both

PAGE 68

68 river buffer landscapes, coveri ng 10.55% (87.66 ha) and 6.71% (55.8 ha) within the CBS and 9.64% (32.04 ha) and 9.34% (31.05 ha) outside the CBS. Drivers of Deforestation To determine the major drivers of deforestation within the CBS, variables were chosen a priori from the literatur e and/or based on the observations and information obtained by the research during field work. Because much of the household characteristic information (e.g., socio economic and socio demographic) was only relevant during the last time period modeled (200 0 2004), this information was not included in the two earlier models (1989 1994 and 1994 2000). The results of the three separate binomial logit models of deforestation for the periods from 1989 199 4 (model 1), 1994 2000 (model 2), and 2000 2004 (model 3) are presented in Tables 3 5, 3 6, and 3 7. These tables present the values of the parameter estimates (coefficients) with their corresponding Z value statistic and indicated significant probability Positive values of parameter estimates i ndicate that larger values of the explanatory variables increase the likelihood of deforestation (given statistical significance), while negative values indicate the opposite. B y addressing deforestation probability, the binomial logit models also address stable forest probability, covering the two dominant land cover trends within the CBS landscape and 120 meter river buffer (Table 3 3 and Table 3 4). Model 1 (1989 1994) Only those variables relevant during the 1989 1994 time period for the 33 lando wners and their parcels were analyzed in this model. These variables included distance to river from each pixel, distance to roads from each pixel, land tenure, and participation in the pledge. Distance to road was the most influential variable in the mo del. Areas further from the road and the Belize River, as well as titled tenure decreased the probability of deforestation ( p = 0.001). Participation in the pledge increased the probability of deforestation ( p = 0.01) (Table 3 5).

PAGE 69

69 Model 2 (1994 2000 ) Only those variables relevant during the 1994 2000 time period for the 33 landowners and their parcels were analyzed in this model. These variables included distance to river from each pixel, distance to roads from each pixel, land tenure, and partic ipation in the pledge. Similar to model 1, areas further from the road and the Belize River and titled tenure decreased deforestation probability. In contrast to model 1, participation in the pledge decreased the probability of deforestation ( p = 0.001) (Table 3 6), perhaps coinciding with one of the payment years for pledgers. Model 3 (2000 2004) Since surveyed data were relevant to current participants, the last model included all variables of interest. Cattle, cattle income, agriculture, education level of the household head, and tenure were the five most influential variables in this model. Increasing cattle income, education level of the household head, titled tenure, distance from road s, distance from the Belize River, family size, agricultural income, and involvement in both the pledge and tourism were significantly linked ( p = 0.001) to decreasing probabilities of deforestation. P asture also decreased deforestation probabilities but at a lower significance level ( p =0.05) C attle, agriculture remittanc es, and involvement in tourism were significantly linked ( p = 0.001) to increasing probabilities of deforestation. Working out side the CBS and involvement in the pledge also increased probabilities of deforestation but at lower significance lev els ( p = 0.05) (Table 3 7). Because of the large number of variables in this model and the large number of pixels, it is possible that many of the variables that show statistical significance in the model may not be good predictors of deforestation with in the CBS. To better assess their influence, all variables were plotted individually and examined in more detail on their strength of effect using logistic

PAGE 70

70 regression. Results show that the most influential variables in this model were distance to the B elize R iver and distance to roads (figure 3 5) cattle (figure 3 6 a ), agriculture (figure 3 7 a ), education of household head (figure 3 8 a ), and participation in both pledging and tourism (figure 3 10 ) The least influential variables in this model (with l ow predictive power) included cattle income (figure 3 6b), agricultural income (figure 3 7b), family size (figure 3 8b), tenure (figure 3 9a), remittances (figure3 9b), outside work (figure 3 11a), and pasture (figure 3 11b). Both distance to river and dis tance to roads have an approximate 50% decrease in deforestation probability (from 0.4 to 0.2) as distance increases to 2500 meters away. Owning cattle also shows a 17% difference in deforestation probability difference between those residents with cattle (39%) and those without (22%). In contrast to owning cattle, which is statistically significant and influential, an increase in cattle income only slightly decreased deforestation probability. Agriculture was also fairly influential showing an approxima te 9% decrease in deforestation probability between those carrying out agricultural practices (37%) and those not (28%). However, agricultural income, although showing a decrease in deforestation in the model, has very strength of effect when plotted. Ed ucation of household head had strong strength of effect and decreased deforestation probability by approximately 50%. In comparison, although greater family size was predicted to increase deforestation probability, results show this was not influential wi thin the CBS. Tenure, although one of the top five influential variables in the model, did not show strong strength of effect and indicated only a slight decrease in deforestation probability for those with titled land ownership. Remittances, although in creasing the probability of deforestation in the model, showed very low strength of effect when plotted. Additionally, outside (CBS) work and having pasture, two of the three least influential variables in the model, both showed very low strength of effec t when plotted. Lastly, comparing the two

PAGE 71

71 conservation initiatives (tourism and pledging), there was a 12% decrease in deforestation probability between those households involved in both pledging and tourism (26%), compared to those households not involve d in either initiative (38%). Households involved in either tourism (30%) or pledging (32%) showed a 6 8% decrease in deforestation probability compared to those households not involved in either initiative. Model Validation There are several ways to ass ess model accuracy. One indicator of model fit i s the overdispersion parameter. This parameter is useful for indicating whether the relevant model has of f reedom (Burnham and Anderson 200 2 a strong fit, parameter results were 1.13 (model 1), 1.01 (model 2), and 1.19 (model 3), indicating no issues with outliers and overall correct model choice The second model (1994 2000 ) had the highest prediction accuracy result for deforestation (74%) and stable forest (78%). The first model (1989 1994) had the second highest prediction accuracy for deforestation (68%) but the lowest prediction accuracy for stable forest (72%). The third model (2000 2004) had a prediction accuracy of 69% for deforestation and 70% for stable forest (Table 3 8). Additionally, m any LULCC modeling studies report a pseudo R 2 as the R 2 statistic as a traditional measure of fit is not easily calculated in a categorical regression framework. A pseudo R 2 statistic was calculated for each model (based on the ratio of restricted and unrestricted log likelihood function). The pseudo R 2 results were 0.116 (mode l 1), 0.063 (model 2), and 0.129 (model 3). Alt hough the model chose the most significant variables influencing the probability of deforestation, these low pseudo R 2 values signal that overall these variables are not the most influential predictors of deforestation probability and that other important variables are

PAGE 72

72 missing from the model (information that was either not available for thi s study or was not collected) that predict deforestation probability. Lastly, following other LULCC modeling studies, a predicted versus observed deforestation / stable forest map was created to assess the spatial pattern of model performance, using 50% as the threshold for the model predicted probability of deforestation to classify a p ixel as deforested (Figures 3 11, 3 12, and 3 13 ). Generally speaking, all models sh ow most incorrect predictions of deforestation (where stable forest actually occurred) located around correctly deforested pixels. In models 1 and 2 this over prediction of deforestation was likely distance related, considering that the two largest z valu ible for this over prediction. In addition, the spatial pattern of pixels where all the models over predict stable forest (where forest was actually deforested) doe s not appear necessarily random, but does not fit any distance based criteria and is difficult to interpret any consistent spatial patterns. This may indicate that other variables not captured by the models may be influencing deforestation in certain area s, or even other spatial processes that are occurring in these areas (e.g., soil maps for the region were not at the detail needed to show differentiation within the CBS). In comparison to the other models, although some correct predictions for deforesta tion in model 3 are located near roads and rivers, overall these predictions appear to be more unique to each land parcel, potentially pointing to the role of household survey derived socio economic and socio demographic variables over distance related var iables in this model (e.g., cattle and agriculture). However, there were no clear patterns or variables unique to these landowners from the model that would explain this, which also signals that other variables not included in the model are probably infl uencing deforestation within these parcels.

PAGE 73

73 Discussion Although t he two leading land cover tra jectories within the CBS were stable forest and deforestation, leading land cover trends of the 120 meter river buffer within and outside the CBS also needed to also be examined, considering the conservation focus of riparian forests. W ithin the 120 meter river buffer the leading land cover trend both within and outside the CBS was tending toward deforestation. This result of similar land cover trends inside and outside the CBS riparian buffer indicates riparian forests are not any more conserved withi n the CBS as they are outside. In addition, areas within the 120 meter river buffer are more likely to be deforested than other areas within the CBS. Following th ese analyses, modeling social survey and locational characteristics of individual landowners with land cover change provided insight into the relative influence of these factors on deforestation probability within the CBS. Drivers of Deforestation Locatio n al : As predicted, distance to river was an influential variable in all three models negatively li n ked to probabilities of deforestation (increased probabilities of deforestation the cl oser a pixel is to the river). Distance to river also had high predict ive power in model 3 (2000 2004) and supports as the leading land cover trend within the 120 meter river buffer In addition to distance to river, distance to roads in all three models was negatively related to probabilit ies of deforestation (increased probabilities of deforestation the closer a pixel is to the road) with high predictive power in model 3 (2000 2004) This follows a wealth of past research, as well as intuitive sense that infrastructure and clearing woul d take place closer to roads for access. A ccess and distance to markets is an important driver explaining contrasting patterns of land cover and land use in other areas (Chomitz and Gray 1996 on commercial agriculture and Kaimowitz and Angelsen 1998; Wick ham et al 2000; Nepstad et al 2001; and Nelson et al. 2001 on access to markets and deforestation).

PAGE 74

74 Land t enure: In all model ed time periods titled land ownership significantly decreased probabilities of deforestation as households move d from leased (l ower) to titled (higher) ownership. Although statistically significant, tenure did not have strong predictive power in model 3, indicating there were other more influential variables. Nevertheless, t he findings from these models follow the hypothesis tha t secure title and control over land resources can be linked to more sustainable forest management (Godoy and Bawa 1993; Nelson et al. 2001; Murphree 2003). Socio demographic s : E ducation level of the household head in model 3 was influential in decreas i ng deforestation probabilities and followed the prediction that higher education levels of the household head can lead to other employment and economic activities (flexibility) which put less demand on clearing land. In comparison, family size did not fo llow my prediction that larger families increase deforestation probabilities from increased subsistence needs. Roy Chowdhury (2006a) attributed larger families and lower deforestation probability to l arger households farm ing the same a rea for longer perio ds of time. Additionally, Roy Chowdhury (2006a) emphasizes that this result could occur if families are further along in their lifecycle Even though family size showed a decrease in deforestation probability, its predictive power in the model was very s mall, indicating this variable it is not a strong predictor of deforestation within the CBS, compared to other variables. Although family size among the 33 landowners ranged between 1 and 10 (mean = 4.8), this study would speculate that CBS families today do not grow the majority of their food. Because of this, family size would not considerably decrease or increase the amount of agricultural activity (and deforestation) by the household. Socio economic s : Cattle is the most influential variable in model 3 and showed high predictive power linked to an increase in deforestation probability Agriculture also had high

PAGE 75

75 predictive power on increasing deforestation probability. This presence of cattle as the leading driver of deforestation also follows in line w ith the worldwide leading proximate driver of deforestation (agricultural expansion for ranching and/or cultivation) (Lambin et al. 2001; Geist and Lambin 2002; Lambin et al. 2003). As mentioned earlier, having a few head of cattle is a good financial inve stment as one can readily sell a cow when there is an urgent need for money. Access to roads and distance to markets may be another factor encouraging cattle ranching as a good road network through most of the communities make trans portation to Belize Cit y an easy commute (roughly 35 miles). The low predictive power of cattle income in model 3 may signal that not many people sell their cattle and when they do, with the exception of a few cattle herders, the money does not get reinvested into land intensifi cation but, rather, other household needs ( e.g., emergency expenses, education, house improvements, etc ). The low predictive power of agricultural income in model 3 also indicates that few people actually sell their agricultural crops (primarily for home consumption) and when it is sold, it is not invested into deforestation. In fact, families may farm the same areas over several years, as was observed by Roy Chowdury (2006a). Conservation i nitiatives : Out of the 33 households interviewed, 11 households a re involved in tourism only, 10 households are involved in pledging only, and 8 households are involved in both tourism and pledging. Pledging, a variable that could be modeled over the three time periods, followed the transition from increasing deforesta tion probability in model 1 (1989 1994), decreasing deforestation probability in model 2 (1994 2000), and then increasing deforestation probability again in m odel 3 (2000 2004). Tourism only and pledge only residents increased deforestation probabi lity in model 3. The second chapter of this dissertation showed why tourism and the pledge might be considered financial failures for conservation,

PAGE 76

76 pointing to the inequitable distribution of tourism participation and benefits from an elite capture of ben efits by a few households since 1998 Tourism jobs and income may motivate residents to protect howler monkey habitat and deforest less. However, if benefits are not linked to ved may actually be reinvested into activities that undermine conservation efforts (e.g., cattle ranching) (Christ et al. 2003; Aylward 2003; Kiss 2004). Current dissatisfaction in the pledge can be linked to no current financial compensation when earlier payments were made in 1998 and 2000. P ledging influenc es a decrease in deforestation probability during model 2 (1994 2000), which may be explained through coincidin g with these two payment years. However, b y this same argument this decrease in deforest ation probability should have also been observed in model 3 (2000 2004), accounting for the impact from the received payment, rather than increasing deforestation probability This may signal that other influential variables in this model (e.g., cattle, ag riculture) or other variables not accounted for in the model (an indicator of the low pseudo R 2 value) may have provided greater incentive than the payment from pledging provided. In comparison to the pledge only and tourism only variables, those involv ed in both pledging and tourism decreased deforestation probabilities in model 3 and showed strong predictive power The combination of being involved in both tourism and the pledge actually decreasing deforestation probabilities may indicate that having both the values of pledged residents (whether the pledge influenced these residents or these residents had these conservation values to begin with is not known) and the income from tourism participation may actually create a stronger connection between to urism dollars received from the resource attraction (the howler monkey) and the habitat (forest) it is dependent upon. This connection can also be

PAGE 77

77 observed from chapter two of this dissertation where residents involved in both pledging and tourism had sig nificantly higher perceived benefit attainment values of tourism dollars to their communities, something tourism only and pledge only residents did not (see chapter two). Limitations T he accuracy of predicted deforestation and stable forest in all the mode ls was greater than 50%, implying that each model was likely capturing more than random variation. However, the low pseudo R 2 values revealed that the variables used together do not explain the majority of deforestation that is occurring. This indicates there are other important variables missing from the models that would help explain deforestation probability (and stable forest probability) within the CBS such as other biophysical or spatial processes (e.g., soil quality) or socio economic variables (e .g., national policy institutions). Despite the overall low explanatory power of the variables assessed in this study, there was a need to assess the influence of the two conservation initiatives and this study helped to better understand their role on def orestation probability. In addition, this study provided a better understanding of the influence of other potential drivers chosen a priori from the established literature and from time spent in the research site and region. Modeling studies conducted b y Roy Chowd h ury (2006a, 2006b) linki ng social survey data with land cover change also revealed fairly low pseudo R 2 values, indicating variables used in this study were also not explaining the majority of deforestation occurring This is an important step in better understanding data, however, and the knowledge gained can be used in subsequent studies to incorporate other factors that might be more influential. It was not possible to obtain reliable figures for population within the CBS and various macro level policy institutions that may have encouraged or discouraged land intensification practices were not known (e.g., subsidies, market changes, agricultural loans, etc.). With regard to spatial

PAGE 78

78 processes, one limitation to this study was that the Belize ARC GIS soil and geologic cover maps were not at the detail needed to show differentiation within the CBS. Further research should incorporate other factors to better explain deforestation trends within the CBS. Conclusion Relationships between humans a nd the landscape are complex, and vary greatly according to biophysical, cultural, socio political and economic perspectives. It is these interrelationships between areas such as biophysical and locational properties, land tenure economic, and socio poli tical that will allow a better understanding of drivers of LULCC (Binswanger 1991; NRC 1998; Mertens et al. 2000; Geist and Lambin 2001; Nelson et al. 2001; Hubacek and Vazquez 2002). Across the models, trends show riparian areas a re more likely to be de forested, as are areas closer to road networks. A gricultur e and cattle are the activities most influential in driving deforestation in the last modeled time period which is also linked to riparian areas, while higher levels of education for the household head decreased deforestation probability. Of statistical significance in the model but of lower influence were secure land title and pledging and tourism working together. Titled land ownership decrease d the probability of deforestation in all three mod els although did not show strong strength of effect in the last model ed time period. This indicates that it has importance in the model, but much less influence than other variables (e.g., cattle and agriculture). Similarly, pledging and tourism working together during the last modeled period indicated some level of decreased deforestation probability but not as influential as other leading drivers. The models created in this study, similar to other LULCC modeling studies, simplify complex processes at v arious dimensions and, in reality, highlight only some of the variables most likely influencing deforestation within the CBS. Nevertheless, this study helped to explore

PAGE 79

79 and identify the relevant influence of some of the factors affecting deforestation T his information can be used to assess the effectiveness of conservation initiatives and impact of other land use activities and predict future landscape change. In addition, this study will contribute to more reliable decision making with respect to conse rvation planning and landscape management and is part of an emerging focus of research coming out of the LULCC community linking social survey information from local land managers to land cover changes.

PAGE 80

80 Figure 3 1. Map of the Community Baboon Sanctu ary, Belize, Central America

PAGE 81

81 Figure 3 2. CBS parcel map of study location

PAGE 82

82 Figure 3 3. Land cover change trends for CBS.

PAGE 83

83 A B Figure 3 4. Change d etection analysis for 120 meter river buffer ou tside (A) and inside (B) the CBS.

PAGE 84

84 A B Figure 3 5. Probability of deforestation as a function of distance to (A) river and ( B) road networks in Model 3 (2000 2004). A B Figure 3 6. Probability of deforestation as a function of (A) Cattle (B) Cattle Income in Model 3 (2000 2004). Probability of Deforestatio n 0.0 0.4 0.8 0 5000 10000 15000 Cattle Income ($)

PAGE 85

85 A B Figure 3 7 Probability of deforestation as a function of A) agriculture and B) agriculture income in Model 3 (2000 2004). A A B Figure 3 8 Probability of deforestation as a function of (A) education of household head and (B) family size in Model 3 (2000 2004). Probability of Deforestation 0.0 0.4 0.8 Probability of Deforestati on 0.0 0.4 0.8 0 5 10 15 Education (years) 2 4 6 8 10 Family Size (people) 0 50 100 150 200 250 300 350 Agriculture Income ($) Probability of Deforestation 0.0 0.4 0.8

PAGE 86

86 A B Figure 3 9. Probability of deforestation as a function of A) tenure and B) remittances in Model 3 (2000 2004). Figure 3 10. Probability of deforestation as a function of conservation initiative in Model 3 (2000 2004).

PAGE 87

87 A B Figure 3 11. Probability of deforestation as a function of A) outside (CBS) work and B) pasture in Model 3 (2000 2004).

PAGE 88

88 Figure 3 11 Predicted versus observed pixel deforestation / stable forest for 1989 94 (Model 1).

PAGE 89

89 Figure 3 12. Predicted versus observed pixel deforestation / stable forest for 1994 2000 (Model 2).

PAGE 90

90 Figure 3 13 Predicted versus observed pixel deforestation / stable forest for 2000 2004 (M odel 3)

PAGE 91

91 Table 3 1. Preceding year/month precipitation information of the CBS area. To assess if rainfall patterns might impact classification, image year ra infall was compared to the 30 year average, looking at the 2 3 months prior to image month. Rainfall for the CBS is recorded at the Phillip Goldson International airport (~40 km away). Rainfall (mm) 30 Yr Ave Percentages Nov 84 96.4 227.385 42.39506 be low Oct 84 308.7 282.2663 109.3648 normal Sep 84 208.5 272.023 76.64793 below Dec 89 35.1 176.4367 19.89382 below Nov 89 196.1 227.385 86.2414 below Oct 89 286.6 282.2663 101.5353 normal Mar 94 24.9 47.28607 52.65822 below Feb 94 56 79.4 5614 70.47914 below Jan 94 185.2 137.0435 135.1395 above Mar 00 32 47.28607 67.67321 below Feb 00 32.2 79.45614 40.5255 below Jan 00 102.8 137.0435 75.01266 below Nov 04 229.2 227.385 100.7982 normal Oct 04 194.2 282.2663 68.80027 below Sep 04 195.9 272.023 72.01597 below Table 3 2. Accuracy Assessment of 2004 Landsat ETM+ image. The Produc indicates the probability of a reference pixel being correctly classified and is a classified on the map actually represents the category on the ground. This divi des the total number of correct pixels in a category by the total number of pixels that were actually classified in that category. This is an accuracy measurement between the reference data and the remote sensing derived classification map. The Kappa coe fficient represents the decrease in error obtained from the classification process compared with the error that would have been obtained from random classification. Total number trng points Number correct Producers Users Kappa Forest (1) 31 25 86.21% 80. 65% 0.6548 Non forest (2) 35 31 83.78% 88.57% 0.7399 Rainfall Percentage Category <50% Well below normal 50 90% Below normal 90 110% Normal 110 150% Above normal > 150% Well above normal

PAGE 92

92 Table 3 3. Change Detection Analysis of the CBS landscape. This covers the 4 image dates (1989, 1994, 2000, and 2004) with the 16 change trajectories aggregated into 5 land cover categories. % CBS landscape Ha Stable Forest 33.4 2908.98 Tending Towards Deforestation 29.7 2582.79 Tending Towards Reforestation 18.9 1647 Stable Non forest 13.8 1200.6 Transitional 4.1 361.17 Table 3 4. Change Detection Analysis of a 120 meter riv er buffer inside and outside the CBS. This covers the 4 image dates (1989, 1994, 2000, and 2004) with the 16 change traj ectories aggregated into 5 land cover categories. Inside the CBS Outside the CBS % landscape Ha % landscape Ha Tending to wards Deforestation 30.95 257.22 29.83 99.18 Stable Forest 26.09 216.81 28.1 93.42 Tending Towards Reforestation 25.71 213.66 23.09 76.77 Stable Non forest 10.55 87.66 9.64 32.04 Transitional 6.71 55.8 9.34 31.05

PAGE 93

93 Table 3 5. Deforestation probability on household land parcels, binomial logit regression model for Model 1 (1989 to 1994), n = 8361 pixels on land parcels belonging to 33 landowners. Variable Coefficient Std.Error Z value P value Significance (Intercept) 1.0 062 0.0271 37.0760 < 2e 16 *** Distance : road 0.5639 0.0306 18.4350 < 2e 16 *** Distance : river 0.3894 0.0351 11.0880 < 2e 16 *** Tenure 0.2329 0.0263 8.8670 < 2e 16 *** Pledge 0.0884 0.0272 3.2440 0.00118 ** *p = 0.05 **p = 0.01, *** p = 0.001; I = 0.07, pseudo R 2 = 0. 12 overdispersion parameter = 1.13 Table 3 6. Deforestation probability on household land parcels, binomial logit regression model for Model 2 (1994 to 2000), n = 6436 pixels on land parcels belonging to 33 land owners. Variable Coefficient Std. Error Z value P value Significance (Intercept) 1.3306 0.0319 41.6590 < 2e 16 *** Distance : road 0.3196 0.0358 8.9170 < 2e 16 *** Distance : river 0.1785 0.0385 4.6390 3.50E 06 *** Tenure 0.2377 0.0292 8.1540 3.5 1E 16 *** Pledge 0.1987 0.0312 6.3660 1.94E 10 *** *p = 0.05 **p = 0.01, *** p = 0.001; = 0.06 pseudo R 2 = 0.06 overdispersion parameter = 1.01

PAGE 94

94 Table 3 7 Deforestation probability on household land parcels, binomial lo git regression m odel for Model 3 (2000 to 2004 ), n = 6 895 pixels on land parcels belonging to 33 landowners. Variable Coefficient Std. Error Z value P value Significance (Intercept) 0.7209 0.0280 25.7700 < 2e 16 *** Cattle 0.7330 0.0465 15.7590 < 2e 16 *** Cattle i n come 0.5926 0.0498 11.8918 < 2e 16 *** Agriculture 0.5259 0.0491 10.7221 < 2e 16 *** Education (HH Head) 0.4011 0.0424 9.5400 < 2e 16 *** Tenure 0.3802 0.0452 8.4158 < 2e 16 *** Distance: road 0.2925 0.0354 8.2620 < 2e 16 *** Family Size 0.31 08 0.0403 7.7100 1.26E 14 *** Agriculture i ncome 0.4555 0.0695 6.5511 5.71E 11 *** Remittances 0.2907 0.0470 6.1911 5.97E 10 *** Pledge* t ourism 0.2319 0.0401 5.7860 7.21E 09 *** Distance : river 0.1703 0.0403 4.2279 2.36E 05 *** Tourism 0.1343 0.0376 3.5770 3.48E 04 *** Out side (CBS) work 0.1004 0.0342 2.9358 3.33E 03 ** Pasture 0.1057 0.0480 2.2009 2.77E 02 Pledge 0.0770 0.0355 2.1670 3.02E 02 *p = 0.05 **p = 0.01, *** p = 0.001; pseudo R 2 = 0.1 3 overdispersion para meter = 1.19

PAGE 95

95 Table 3 8. Prediction results for binary logit models Prediction type Pixel (number) Proportion Model 1 (1989 1994) Correct stable forest 5791 0.72 Incorrect stable forest 2226 0.28 Correct deforestation 236 0.68 Incorrect def orestation 108 0.31 Total 8361 Model 2 (1994 2000) Correct stable forest 5005 0.78 Incorrect stable forest 1396 0.22 Correct deforestation 26 0.74 Incorrect deforestation 9 0.26 Total 6436 Model 3 (2000 2004) Correct stable f orest 4322 0.70 Incorrect stable forest 1858 0.30 Correct deforestation 494 0.69 Incorrect deforestation 221 0.31 Total 6895

PAGE 96

96 CHAPTER 4 FOREST FRAGMENTATION AND HABITAT CONSERVA TION FOR THE BLACK HOWLER MONKEY: A ST UDY WITHIN THE COMMU NITY BABOON SANCTUARY, BELIZE Anthropogenic activities have led to forest cover loss worldwide, with forest fragmentation within developing tropical regions occurring at an alarming rate (Rudel and Roper 1997; Laurance 1999; Sanchez Azofeifa et al. 2001; Lamb et al. 2 005; Abdullah and Nakagoshi 2007). Fragmentation, defined as the breaking up of a habitat or cover type into smaller, disconnected parcels (Turner et al. 2001, p.3) affects forest habitat when large, continuous forests are divided into smaller blocks, e ither by roads, clearing for agriculture, urbanization, or other human development (Kupfer et al. 2006). The concern with extensive deforestation is the resulting further degradation, such as over hunting, ground fires, and logging (Horwich and Lyon 1990; (and often from human activity) where trees are still standing but t he species that make up the complex ecosystem are not (Redford 1992; Robinson 1996). Fragmentation affects a variety of population and community processes over a range of temporal and spatial scales with significant implications for biodiversity conservat ion (Lovejoy et al. 1986; Kapos 1989; Saunders et al. 1991; Debinski and Holt 2000; Laurance et al. 2000; Fahrig 2003; Githriu and Lens 2007). Habitat area loss and patch isolation can change predator prey dynamics, competitive interactions, and species c omposition, which may affect community structure (Fahrig and Merriam 1985; Hobbs 1993; Palomares et al. 1996; Debinski and Holt 2000) or lead to extinction of vulnerable species (Bur key 1995; Weaver et al. 1996). Characteristics that determine the principl e effects of a fragment are isolation (connectivity, surrounding landscape change, distance from other remnants, and time since isolation) and

PAGE 97

97 microclimate change (wind and edge effects, radiation, water fluxes). In addition, remnant size and shape, and p osition within the landscape can also influence the effect of fragments (Marsh 1999). In a fragmented forest, edge effect is one of the distinguishing features, defined in d deforested Landscape ecology seeks to understand spatial arrangements and their ecological effects, examining interactions between the spatial landscape structure, function, and temporal change. It is through the ident ification and quantification of landscape patterns that our understanding of these interactions between landscape structure and ecological processes develops (Turner et al. 2001). Measuring fragmentation (e.g., habitat fragmentation and forest fragmentati on) is one way to quantify landscape pattern. The effects of forest loss and fragmentation can be interpreted with landscape metrics algorithms that quantify specific spatial characteristics of patches, classes of patches, or entire landscape m osaics (Mc Garigal and Marks 1995 ). Studies on forest fragmentation have used island biogeography theory (within the landscape ecology discipline) to estimate species survival within fragments (Saunders et al. 1991; Redford 1992; Bierregaard and Dale 1996), the optim um size of fragments for species conservation (e.g., SLOSS; Single Large Or Several Small: Gilpin and Diamond 1980; Shafer 1995), and predicting species numbers (MacArthur and Wilson 1967; Wilcox 1980; Shafer 1995). Another theoretical framework for study ing forest fragmentation out of landscape ecology, metapopulation theory, assesses the impact of habitat fragmentation on population viability. This theory differs from island biogeography in that it assumes no persistent mainland habitat, but rather a net work of small patches, and also focuses on a single species. The

PAGE 98

98 importance is on dispersal among habitat fragments, where inadequate dispersal and habitat loss past a certain critical threshold will lead to extinction (Harrison and Bruna 1999). Primat e Populations Forest fragmentation has become a principle focus of conservation and ecological research on organisms in tropical regions, including primate populations (Lovejoy et al. 1984; Offerman et al. 1995; Laurance and Bierregaard 1997; Schelhas and Greenberg 1996; Harrison and Bruna 1999; Clarke et al. 2002; and Laurance et al. 2002). Research on the effects of deforestation on primates has largely focused on habitat degradation, reduction, and isolation (Andren 1994; Marsh 2003). When primate popu lations are isolated from each other due to habitat fragmentation, continued habitat decline (including human encroachment and hunting) further endangers these populations (Rylands et al. 1995; Estrada and Coates Estrada 1996; Crockett 1998; Estrada et al. 1999). How severe a disturbance is to a primate species depends on the composition and spatial layout of remaining habitat patches, such as shape, size, isolation from other habitat patches, and amount of edge habitat (Saunders et al. 1991; Collinge 1996 ). Concern for the black howler ( Alouatta pigra ) stems from substantial habitat loss (56%) with a predicted 70% population decline over the next 30 years if trends continue (IUCN 2003). A. pigra occurs in Belize, northern Guatem ala, and parts of Mexico (Campeche and Quintana Roo, northern Chiapas, and parts of Tobasco states) (Horwich and Johnson 1986). Black howler monkeys are found primarily in low altitude areas under 1,000 ft. (300m) asl, and in riparian and seasonally flood ed forests (Freese et al. 1982; Horwich and Johnson 1984; Horwich and Lyon 1990; Horwich 1998; Silver et al. 1998). Although A. pigra is classified at a low risk of extinction according to the Mace Lan de system (Rylands et al. 1995) their restricted geogr aphic distribution in habitats that are being rapid ly fragment ed and converted to agriculture and pasture place s this primate species at risk (Estrada et al. 2006).

PAGE 99

99 Some scientists believe A. pigra explains its narrow distribution compar ed to other howler species (Horwich and Johnson 1986; Estrada et al. 2002). Their association with riverine areas has been explained by the high numbers of figs ( Ficus spp. ), an important food source with fruits av ailable throughout the year (Milton 1991) that affects population and troop size (Horwich and Johnson 1986). A study by Estrada and Coates Estrada (1984) in Los Tuxtlas, Mexico found A. palliata spent an average 49% of their feeding time monthly eating Fi cus spp. fruits. Within the Community Baboon Sanctuary, Belize, Ficus spp., especially fruits and leaves of strangler figs, are an important year round food source (Estrada and Coates Estrada 1984), which also may point to howlers as important fig disperse rs in areas with high howler populations (Marsh 1999). Ficus spp. has been considered to play an important role in howler conservation (Coates Estrada and Estrada 1986; Milton 1991; Serio Silva et al. 2002) and has even been suggested as a keystone tropic al forest resource (Terborgh 1986). Fi cus spp. are also considered forest fringe species, found both along river edges and forest edges (Estrada et al. 2000 ; Kratter et al. 2001; Andrews and Bamford 2008) which would increase their availability in fragmen ted forest environments Initial concern for A. pigra was stimulated by Smith (1970) who suggested they prefer More recent studies, however, suggest A. pigra inhabit a wider range of evergreen and semi evergreen forests, including disturbed and riverine forests (Crockett 1997). Indeed Marsh (1999) regularly observed A. pigra using forest edges for feeding, traveling, resting and howling, while Jones (1995) suggests A. high reproductiv e rates, their ability to colonize new patches and their folivorious diet of

PAGE 100

100 leaves, which in comparison to flowers and fruits are an abundant and stable source of food, may even contribute to their survival in fragmented habitats. Black howler monkeys t ypically live within troop sizes under 10 individuals (Horwich and Gebhard 1983; Ostro et al. 2001), with territory size ranging from 3 to 25 acres (Horwich 1998; Belize Zoo 2006). Small troop size may be an adaption for surviving in fragmented habitats ( Ostro et al. 1999) and a function of resource distribution (Chapman and Chapman 1990). However, mean troop size in continuous forest was 3.16 individuals at Muchukux, Quintana Roo (Mexico) (Gonzales Kirchener 1998) and 6.3 individuals at Tikal, Guatemala (Coelho et al. 1976), while in fragmented riverine forests in Belize, troop size was between 3 and 9 individuals (Silver et al. 1998). Howlers typically have smaller home ranges (<10 ha) than other primates, which may explain their persistence in forest f ragments (Crockett and Eisenberg 1987). A. pigra is generally found to have the lowest densities of howlers (Chapman and Balcomb 1998). However, in reports from the Community Baboon Sanctuary, Belize, population densities were among the highest documente d in the literature for A. pigra with population densities reported as high as 178 individuals per km 2 in 1999 (Horwich et al. 2001), up from 31.9 per km 2 in 1985 (Jones and Horwich 2005). This suggests tolerance of A. pigra to habitat reduction and frag mentation but may also suggest a high animal load on the resources present (Estrada et al. 2002) For primates in general, body size and habitat specialization have been considered the most important parameters related to extinction. However, diet requirem ents and social structure are also important survival factors, considering howlers are still found in small forest fragments despite being one of the largest New World primates (Marsh 1999), weighing between 15 20 lbs / 6 7 kg (Horwich and Lyon 1990). Bla

PAGE 101

101 (Crockett and Eisenberg 1987) with s tudies in the Community Baboon Sanctuary, Belize showing young leaves accounting for 37% and fruit 41% of their diet (Sliver et al. 1998). In addition, a study of 25 19 trees sampled in adult tree transects of troop home ranges, 71% were used by howlers (Marsh 1999). Bernstein et al. (1976) attributes howler adaptability to fragmented environments following agricultural expansion in northern Columbia to their flexible diets. It is thought that the howler is able to minimize energy expenditure through small home ranges (and short day ranges), relatively small troop size, and highly folivorous and flexible diets which, combined, improves conservation likelihood (Milton 1980; Estrada et al 1999; Bicca Marques 2003; Fuentes et al 2003). Belize Forests Deforestation and increasing human population are causing declines of fauna throughout most of the tropics but the forests of Belize have been a concern for conservation b iologists since with only a 0.2 % annual forest loss. During 1990 (2.3% per year) surpassed that of Central America (1.2% per year) (DiFiore 2002) and forests in Belize now total only 59% of the total land cover (FAO 2001), with trends showing agricultural intensification replacing forested landscapes (PfB 2000). In north central Belize deforestation has been more seve re with only 30% of the original forest cover remaining (King et al. 1992). The main activities encouraging deforestation and fragmentation of remaining forests in Belize are cattle ranching, large scale agriculture, milpas (small scale slash and burn farm ing), urban growth, and logging (Horwich and Lyon 1990). Study Objectives Along with retaining certain habitat areas, conservation strategies are increasingly focusing on the spatial configurations of habitat across landscapes (Thomas et al. 1990; Pulliam

PAGE 102

102 et al. 1992). How severe a disturbance is to a primate species depends on the composition and spatial layout of remaining habitat patches, such as shape, size, isolation from other habitat patches, and amount of edge habitat (Saunders et al. 1991; Colling e 1996). Considering some of the most threatened primate communities now survive only in fragmented forest habitats (Cowlishaw and Dunbar 2000; Marsh 2003), the quality and spatial characteristics of forest fragments plays an important role in understandin g how to best conserve and manage current populations (Lindenmayer 1999; Chapman and Lambert 2000; Harcourt 1998, 2002; Fahrig 2003; Marsh 2003). To understand the tolerance of A. pigra to habitat fragmentation, information on forest fragmentation and rat es of forest loss, along with demographic information for A. pigra populations is needed (Estrada and Coates Estrada 1996; Cuarn 2000). In addition, information linking data from such sources as satellite imagery, forest cover, habitat fragmentation, and human land use patterns, among others, is also needed to better understand relationships between areas of human population and primate survival (Garber et al. 2006). This study assessed forest fragmentation within the Community Baboon Sanctuary (CBS), B elize, a community reserve that has existed since 1985 with little monitoring of deforestation and, more specifically, forest habitat fragmentation for the black howler monkey, the impetus for the creation of the CBS. This study focuses on the following o bjectives: 1. T o examine forest cover change of the CBS landscape and 500 meter river buffer from two time periods over 15 years (1989 and 2004); 2. T o assess how forest habitat for the black howler monkey has changed over this 15 year time period and how much s uitable habitat currently exists (for the year 2004), based on minimum patch size and distance requirements; and 3. To assess the performance of the CBS as a IUCN Category IV protected area in terms of forest cover and fragmentation results and howler monkey populations (from past population surveys).

PAGE 103

103 Methods Study Site The Community Baboon Sanctuary ( CBS), Belize an IUCN Category IV protected area, was established in 1985 to protect black howler monkey ( Alouatta pigra ) popu lations and t heir forest habitat (Figure 4 1). As a Category IV protected area, the conservation focus is rea of land and/or sea subject to active intervention for management purposes so as to ensure the maintenance of habitats and/or to meet the requir ements of specific species The CBS was the effort of two American scientists and a local non governmental organization (Belize Audubon Society) who worked with private landowners of 7 villages to encourage them to pledge to help protect ripa rian forest landscapes (Horwich and Lyon 1998) for black howler populations Located in the climatic region of north central Belize, the forests of the CBS are classified as lowland, semi deciduous rainforest. Today the CBS is a patchwork of secondary fo rests from 10 75 years old, interspersed with cleared areas and secondary growth from 300 years of periodic logging (Horwich and Lyon 1990). There are roughly 220 households in 7 villages for a human population density of ~106.38 individuals per km 2 (Jon es and Young 2004). Although the literature cites the CBS as an area of 4800 ha (48km 2 ) (Horwich and Lyon 1990), this study incorporates twice this amount (8703.54 ha) as defined by village boundaries Although less prevalent as in the past, slash and bur consumption R iverine areas are favored for agriculture because of their more fertile soils. Cattle ranching (both large and small scale) is also a common livelih ood activity, with cattle often kept by the riverside where they can easily access water.

PAGE 104

104 When the CBS was established some households signed a voluntary, written pledge to property boundaries, ensuring greater habitat protection and connectivity for howler monkeys. Although landowners were not initially paid to pledge, the CBS resident management committee paid pledged landowners $125 twice (1998 and 2000) (Lash 2003). In addition, tourism focused around the howler monkey was also established to provide residents financial incentives to protect forests. Tourist numbers have increased dramatically in the last few years (13,000 in 2005) from the arrival of cruise ship touri sm to Belize (see chapter 2). Tourism employment includes both permanent and seasonal jobs. However, a disproportionate number of families benefitting from tourism (13 out of 35 total in 2005) are from one village, pointing to an inequitable distribution of tourism benefits and participation which have caus ed dissatisfaction and resentment towards current CBS management (see chapter two). Despite these concerns toward CBS management and the conservation initiatives, black howlers are not threatened by lo cal residents. Howlers only occasionally damage crops, and are rarely killed as agricultural pests (Crockett 1997 ). Furthermore, past studies show positive views towards howlers and howler protection, with residents recognizing their local abundance and t ourism attraction (Hartup 1994; Bruner 1992). A improved as the only primate species within the CBS with little hunting or predation threats (Jones and Young 2004; Silver et al. 1998). The Community Baboon Sanc tuary Howler Populations Howler populations and population densities within the CBS appear to have been expanding rapidly since 1985 (Table 4 1) from an estimated 800 individuals in 1985 to an estimated 3000 5000 individuals in 2003 (Brocket 2003) The last population density survey

PAGE 105

105 was conducted in 1997, and howler population densities were estimated as high as 178 individuals per km 2 in 1999 (Horwich et al. 2001), the highest ever recorded in the literature for A. pigra Howler surveys were conducted using similar methodology. In 1985 and 1999, surveys were carried out within a 4.05km 2 study area (1985) and in a 0.63km 2 primary study site (from 1990 to 1999) (Jones et al. 2008). These actual counts of howlers were then multiplied by the CBS area to e stimate the total population (Horwich pers.comm. 2008). The survey conducted in 2003 was carried out in a similar manner: 1581 individuals were counted covering a portion of each of the 7 CBS villages. Remote Sensing Remote sensing enables an assessment of the CBS to protect forest habitat of the black howler monkey ( Alouatta pigra ) and offers a unique opportunity for long term assessment. A change detection analysis of the forest landscape on a spatial and temporal scale evaluated the rates and trends of forest change over 15 years (1989 and 2004) of the CBS and within a 500 meter buffer of the Belize River (within the CBS). Image processing and spatial analyses were performed in Erdas Imagine and ArcGIS. A 1989 Landsat TM image and a 2004 Landsat ETM+ were used to analyze spatial distribution and extent of forest cover within the CBS and within a 500 meter river buffer along the Belize River. Images were taken between November and December, both considered to be within the dry season, to decrease the impacts of seasonal variations on biophysical properties and change detection analysis processes (Jensen 2005). Radiometric calibration and atmospheric correction procedures (Green 2000) were conducted to correct each Landsat band for sensor, illuminatio n, and atmospheric sources of variance to ensure that the change detection analysis truly detected changes at the Earth's surface

PAGE 106

106 (Jensen 2005). Geometric correction of the 2004 image was performed using a 1:50,000 scale map of the study area from the Land Information Center (LIC) in Belize (UTM Zone 16, WGS 1984). Image to image registration was then performed using points from the already rectified 2004 image to register the 1989 satellite image. The root mean square (RMS) error of each registration was maintained below 0.5 pixels (<15 m). Ground truthing of the 2004 image was conducted from September through December, 2005 within the CBS. Training sample protocol forms from the Center for the Study of Institutions, Population, and Environmental Change (CIPEC) were used (CIPEC 1998), and locations were recorded with a GPS (global positioning system). Other qualitative descriptions, including photographs, were recorded for reference and comparison with classified maps and satellite imagery. Informal inte rviews with landowners and personal observations added information on the nature and extent of land uses. Training samples covered a 90 x 90 m area to ensure that at least one full pixel fell within that particular land cover. Sixty six training sample po land cover in and around the CBS as possible. Although training samples within the CBS were primarily taken along roads or along the Belize River, vantage and edge training sample points were also taken in areas difficult to access. The forest class was defined as having a canopy cover of 25% or above. This was based on two sources of data: data from a study conducted within the CBS that estimated deciduous for est habitat to have 40 75% canopy cover and riparian forest habitat to have 65 100% canopy cover (Jones unpubl. data) and an estimate by and less dense forests, inc luding their preferences for certain vegetative growth.

PAGE 107

107 A hybrid supervised / unsupervised classification with 60 classes was conducted on the 2004 image, using collected training samples and GPS point data. Clouds were first removed from both images and a mask was then applied to each image prior to classification. After classifying the various land cover classes, non forest classes (both natural and anthropogenic non forest areas) were merged into a final non forest class (NF). The other class was a fo rest (F) class. classification accuracy of 85% and an overall Kappa Statistics of 69 %. Thomlinson et al. (1999) set as target an overall accuracy of 85% with no class less than 70%. The 1989 image was classified through comparison with signature mean plots of 2004 classes, and also contrasting vegetation in ArcGIS using the NDVI (Normal ized Difference Vegetative Index) and the thermal classifications for the two image dates (Figure 4 2). Landscape Metrics Landscape ecology explains the ecologic al effects of spatial arrangements, especially landscape patterns improves understanding of these interactions between landscape structure and ecological processes (T urner et al. 2001). Measuring fragmentation (e.g., habitat fragmentation and forest fragmentation) is one way to quantify landscape pattern. The effects of forest loss and fragmentation can be interpreted with landscape metrics that quantify specific spa tial characteristics of patches, classes of patches, or entire landscape mosaics (McGarigal and Marks 1995; He et al. 2000). The sensitivity of landscape metrics to changes in levels of forest loss also shows their importance in assessing and monitoring f orest fragmentation (McGarigal and Marks

PAGE 108

108 1995; Trani and Giles 1999). Fragstats software (McGarigal et al. 2002) was used to run landscape metrics on the 1989 and 200 4 classified images (F and NF). The following metrics were analyzed: patch size, total pa tch count, mean patch area median patch area, ENN (Patch level analysis) and Clumpy metrics (Class level analysis). Given the important habitat needs (size, number of patches) and dispersal (distance between patches, patch aggregation), these metrics are functional metrics that explicitly measure landscape pattern that is relevant to the species under consideration. The Euclidean Nearest Neighbor distance (ENN) metric measures the distance (in meters) to the nearest neighboring patch of the same type, bas ed on shortest edge to edge distance, and is used extensively to quantify patch isolation. The clumpiness index (CLUMPY) metric measures pixel adjacencies ( the frequency that a patch type appear s next to another similar patch type on the map ) (McGarigal a nd Marks 1995). With a range between 1 and +1, To assess the suitabilit y of howler monkey habitat using fragmentation metrics, the following criteria was used: 1. A forest patch must be greater or equal to 3 acres (1.21 ha) (Horwich 1998; Belize Zoo 2006) 2. To be considered connected, forest patches must be less than or equal t o 60 meters apart. Although 50 meters appears to be the more appropriate distance, based on a studies by Onderdock and Chapman (2000) and Pozo Montuy and Serio Silva (2003) and Horwich (personal comm. 2007), 60 meters was chosen as the distance because of the 30 meter pixel size of the satellite image used. For statistical analysis, Chi square tests were conducted to assess whether ENN (using the proportion of patches that met this requirement) differed signif

PAGE 109

109 Results In 200 4, 47.61% of the CBS landscape was comprised of forest, a decrease of 23% compared to 1989 (70.87%) (Table 4 2 and Figure 4 2), with similar results for the 500 meter buffer of the Belize River, decreasing from 74.34% in 1989 to 50.64% in 2004 (Table 4 3 a nd Figure 4 3). Landscape Fragmentation The total number of forest patches within the CBS landscape in 2004 (n=1323) was more than twice that amount in 1989 (n=628), with the mean patch area in 2004 decreasing by one third (Table 4 4). The number of for est patches that met the 3 acre or greater area requirement was 48 of 628 (7.64%) in 1989 and 102 of 1323 (7.71%) in 2004. Although the mean patch area in 2004 de creased by one third, the median patch size for both years was the same (Table 4 4). This ca n be explained by several large patch sizes in 1989 that adjusted the average size. Considering forest patches must be less than or equal to 60 meters apart to be considered connected (howler habitat requirement), the ENN metric result indicates that in 1989, 510 of 628 (81.2%) of the CBS forest patches were within this 60 meter distance from other forest patches. In comparison, in 2004 1025 of 1323 (77.5 %) forest patches within the CBS were within this 60 meter distance from other forest patches (Table 4 4). Fo r patches greater than or equal to 3 acres in size, 44 of 48 (91.7%) patches within the CBS in 1989 and 96 of 102 (94.1%) patches within the CBS in 2004 met this criteria (Table 4 4). A Chi square test confirmed the proportion of CBS forest patc hes greater or equal to 3 acres in size that had other forest patches within 60 meters did not differ significantly (p = 0.57) across dates The patch level analysis of the 500 meter river buffer shows comparable patterns to the larger CBS landscape. The total number of forest patches within the river buffer in 2004 (n=669) was greater than twi ce that amount in 1989 (n=267). Although the mean patch area in

PAGE 110

110 2004 de creased by over two thirds, the median patch size for both years was the same (Table 4 4). This can be explained by several large patch sizes in 1989 that adjusted the average size. The number of forest patches that met the 3 acre or greater area requirement was 17 of 267 total forest patches (6.4%) in 1989 and 64 of 669 (9.6%) in 2004. The E NN metric result indicates that in 1989, 233 of 267 (87.3%) forest patches within the 500 meter river buffer were within this 60 meter distance from other forest patches. In c omparison in 2004 545 of 669 (81.5%) forest patches within the 500 meter river buffer were within this 60 meter distance from other forest patches (Table 4 4). For patches greater than or equal to 3 acres in size, 16 of 17 (94.1%) patches within the river buffer in 1989 and 62 of 64 (96.9%) patches within the river buffer in 2004 m et this criteria (Table 4 4). A Chi square test confirmed forest patches greater or equal to 3 acres in size within the river buffer did not differ significantly (p = 0. 59 ) across dates Clumpy values for both forest and non forest patches only decreased s lightly in 2004 compared with 1989 values (Forest = 0.6599 [1989], 0.6499 [2004]; Non forest = 0.6602 [1989], 0.6455 [2004]). Values for both forest and non forest patches indicate these classes are fairly aggregated within the CBS landscape (Table 4 5). Clumpy values within the 500 meter river buffer are similar for both forest and non forest classes across both time periods (Table 4 5). CONNECT metric values, however, show forest patches were 78% connected in 1989 but dropped to only 26% connectivity in 2004. Non forest patches were slightly more connected in 2004 (21%) compared to 1989 (14%) (Table 4 5). Discussion F orest cover declined for both the CBS and 500 m eter r iver buffer by roughly 23% between 1989 and 1994 (Table 4 2). This 23% decrease with in the CBS follows similar trends for Belize with a 20% decrease in forest cover In addition,

PAGE 111

111 there has been a magnitude increase in the number of total forest patches from 1989 to 2004 in both the CBS and 500 meter buff er Although the number of forest patches has increased, indicating increased forest fragmentation, overall the patch size has not changed. Although only a small proportion of forest patches meet the 3 acres or greater size criteria, the majority of patch es are highly connected to eachother, indicating dispersal potential has not been jeopardized. Additionally, both forest and non forest patches within the CBS landscape and 500 meter river buffer are highly aggregated Aggregation of forest patches is be neficial for howler movement. However, the fact that non forest patches are also aggregated may impact movement across these areas and creat of forest and non forest habitats. Current Suitable Howler Habitat Using habitat criteria for the howler monkey (forest patches greater than or equal to 3 acres and less than or equal to 60 meters apart) to assess the current suitability of habitat, in 2004 this comprised 44.72% of the CBS landscape and 46.74% of the 500 m river buffe r landscape (Table 4 6). Considering a landscape with less than 30% habitat connectivity is considered poor fragment connectivity (Mandujano et al. 2006), the CBS has not yet met this threshold. Although howlers may need forest patches greater than or e qual to 3 acres for survival processes (foraging, nesting, etc.), howlers can still move through forest patches less than 3 acres in size, as long as they are less than or equal to 60 meters apart (e.g., forest corridors for travel). Considering this, fore st patches that meet the 60 meter distance requirement from other forest patches comprise 44.86% of the CBS landscape and 49.79% of the 500 meter buffer landscape. (Table 4 6).

PAGE 112

112 Howler Populations As part of a re introduction project, sixty two monkeys w ere translocated from the CBS to Cockscomb Basin Wildlife Sanctuary in Southern Belize in 1993 1994 (Koontz et al. 1993). Despite this translation, in addition to increased deforestation and forest fragmentation of the CBS landscape and 500 meter river buf fer, black howler monkey populations have increased from an estimated 800 individuals in 1985 to an estimated 3,000 5,000 individuals in 2003 (Brockett 2003) (Table 4 1); several factors may explain this. First the flexible diet of A. pigra appears to b e an important factor contributing to its continued subsistence within the CBS. Habitat disturbance has less effect on primate species that rely on leaves for their diet (Crockett 1997), with folivores recovering much faster from habitat disturbance than frugivores (Johns and Skorupa 1987). A. pigra dietary flexibility (Milton 1980; Silver et al. 1998) probably explains their ability to subsist in a variety of habitats, includ ing forest fragments (Horwich and Johnson 1986; Crockett 1998; Ostro et al. 1999). S pider monkeys, in comparison, are less flexible in food species selection and often cannot survive in fragmented areas (Neville et al. 1988). Riviera and Calme (2005) fou nd in the Calakmul Biosphere Reserve, Mexico that within fragmented forest environments, howler monkeys would diversify their diet where their preferred fruit and leaf species were absent. Secondly, the availability of figs ( Ficus spp .) within the CBS pr obably has a strong role in black howler persistence. The common cohune palm ( Orbigyna cohune ) which is left uncut due to difficulty in felling and its usefulness for products and shade is highly infested by strangler figs (42 86%) which are an important food source for the howlers (Lyon and Horwich 1996) Ficus spp. are also considered forest fringe species, both along river edges and fragmented forest edges (Andrews and Bamford 2008; Kratter et al. 2001; Estrada et al. 2000).

PAGE 113

113 Therefore, increased frag mentation within the CBS has most likely increased Ficus spp. growth and availability. In fact, a study by Marsh (1999) concluded that the forest fragments within the CBS are exceptionally good habitat for the howlers because the availability of Ficus spp and other fruiting species found in fragments. Thirdly, howler populations can increase dramatically from disease, hurricanes, and drought where they, and their habitats, are protected (Crockett, 1996; Crockett and Eisenberg, 1987; Horwich and Lyon, 1987 ) and can exist in disturbed and fragmented forests, and in close proximity to human populations, when there are no hunting pressures (Crockett 1997). Considering howlers are not hunted within the CBS and have few predators, these factors may also contribu te to the growing population of howlers within the CBS. It is not well known if the estimated population of howlers within the CBS in 1985 (800 individuals) was recovering from a population decline or had been stabilized at this population level for some time. H owlers throughout Central America have undergone four known population declines that have affected both the population sizes and the behavioral dynamics of remaining troops. Devastating hurricanes in 1931, 1954, and 1978 swept through the CBS (Boli n 1981; Hartshorn 1984), and in 1971, a yellow fever epidemic decimated Central American howler monkeys (Baldwin 1976; Hartshorn 1984). However, the first documented population survey of howlers within the CBS occurred in 1985. It should be noted that a long with howler population increases within the CBS howler population densities have also dramatically increased over the past 20 years. Past studies within the CBS indicate howler densities have increased from 31.9 individuals per km 2 in 1985 (Jones an d Horwich 2005) up to as high as 178 individuals per km 2 in 1999, overcrowding forest fragments (Silver et al.1998; Ostro et al. 1999; Horwich et al. 2001) Additionally, the 2003 CBS

PAGE 114

114 suvey (Brockett 2003) found increased overlap in troop home ranges, mult i male troops, and the first documented observance of infanticide associated with male takeovers, all of which is attributed to high population densities ( and none of which had been observed in past survey s). Although howlers appear to be adaptable to ha bitat fragmentation and have increased in number within the CBS over the past 20 years in the long run increased forest fragmentation may not ensure their population viability (Bicca Marques 2003). For example, even though howler monkeys have been found t o travel across cornfields and grasslands in Mexico (Pozo Montuy and Serio Silva 2003; Mandujano et al. 2004), long distance terrestrial movement of arboreal primates is relatively uncommon and most likely reflects a scarcity of resources such as food, she lter and refuge from predators (Waser et al. 1994; Bennett 1998; Olupot and Waser 2001; Baum et al. 2004). There are likely decreases in reproductive potential and inbreeding if fragmentation impacts connectivity and prevents dispersal opportunities betwe en forest fragments (Crockett 1998; Estrada and Coates Estrada 1996; Clarke et al. 2002). Neotropical primates in isolated fragments (inhibiting migration) that experience population declines below a certain threshold are prone to extinction (Coehlo et al. 1976). Limitations The distance between forest patches primates will travel is not well known or documented within the literature and has only been estimated by a few studies, ranging from 50 m (Onderdock and Chapman 2000) to 80 m ( Pozo Montuy and Seri o Silva 2003) to 150 m (Mandujano et al. 2006) to 2.6 km (Estrada et al. 2002). It is possible this study may have underestimated the distance black howlers will travel between forest patches (60 meters) but the distance was chosen with consideration from (personal comm. 2007). Considering the 30 m pixel size of the satellite image used (Landsat),

PAGE 115

115 chosen distance ne eded to link with the 30 m pixel size. Continued monitoring should be conducted within the CBS on both howler population and densities and forest cover change and fragmentation to better advise community management decisions. As metapopulation theory pred icts a low probability of persistence (on a regional scale) if occupation of fragments are limited, combined with a decrease in colonizing empty fragments (Ovaskeinen and Hanski 2004), future research within the CBS could complement and build on this study by identifying the occupied and unoccupied patches within the CBS, including their size and distance to other patches, to better assess dispersal and persistence probability. Conclusion This study examined forest cover change of the CBS landscape and 50 0 meter river buffer covering two years over a 15 year time period (1989 and 2004) and assessed fragmentation of forest habitat for the black howler monkey based on minimum patch size and distance requirements. Results show a 23% decrease in forest cover w ithin the CBS and the 500 meter buffer between 1989 and 2004, with increased fragmentation of forest habitat. However, connectivity between habitat patches (less than or equal to 60 meters apart) is presently high (81.5% of the 500 m buffer forest habitat and 77.5 % of CBS forest habitat) which indicates dispersal and colonizing between most forest patches has not been jeopardized. Reaching a verdict on the effectiveness of conservation within the CBS may be a little more complex than merely saving fore s ts and, therefore saving howlers within the CBS, as increased fragmentation actually provides better habitat for ficus spp. (e.g., figs), the preferred food source for howlers. As an IUCN Category I the maintenance o f habitats and/or to meet the r (IUCN 1994).

PAGE 116

116 Therefore, if the conservation objective is the howler monkey one could say the CBS appears to be succeeding. However, if the objec tive is forest preservation, it is not. If t rends continue, at some point deforestation and fragmentation will reach a level where dispersal among patches is not possible or population densities reach their carrying capacity and populations begin to decline. This may signal that the CBS should not b e managed for a single (or narrow) outcome (e.g., howlers) as IUCN Category IV protected area designation provides. With a concern that residents have realized few financial benefits from tourism and cooperative agreements intended to deter deforestation (pledge) (see chapter 2), this may necessitate the development or improvement of conservation initiatives within the CBS that will result in realized collaborative conservation action for forest preservation.

PAGE 117

117 Figure 4 1. Map of the Community Baboon Sanc tuary in Belize, Central America

PAGE 118

118 A B Figure 4 2. CBS fores ted and non forested landscape. A) in 1989 and B) in 2004

PAGE 119

119 A B Figure 4 3. CBS 50 0 meter river buffer landscape. A) in 1989 and B) in 2004

PAGE 120

120 Tab le 4 1. C BS black howler monkey population and population density estimates Year Howler population (individuals) estimates Source Howler density (individual / km2) Source 1985 800 Brockett (2003) 31.9 Jones and Horwich (2005) 1997 > 1,500 In Lash (20 03) 178 (in 1999) Horwich et al. (2001) 2003 3,000 5,000 Brockett (2003) Not available Table 4 2. Area (ha) and percent land cover of CBS forested and non forested landscapes in 1989 and 2004 Year Landscape Total Area (h a) % Land 1989 Forest 6167. 79 70.87% 1989 Non Forest 2535.75 29.13% 2004 Forest 4144.05 47.61% 2004 Non Forest 4559.49 52.39% Table 4 3. Area (ha) and percent land cover of forested and non forested CBS 500 meter river buffer landscape in 1989 and 2004 Year Landscape Tota l Area (h a) % Land 1989 Forest 2231.37 74.34% 1989 Non Forest 770.4 25.66% 2004 Forest 1520.01 50.64% 2004 Non Forest 1481.76 49.36%

PAGE 121

121 Table 4 4. Forest Patch Level Analysis of the CBS landscape and 500 meter river buffer. Forest patch level ana lysis of the CBS landscape and 500 meter river buffer from two acres, total number of patches, mean patch area, median patch area, # ENN patches for total patches and for pat ches Landscape Year 3 acres (1.21 ha) Total # Patches Mean Patch Area (ha) Median Patch Area (ha) # ENN Total patches #ENN patches 3 acres CBS 1989 48 628 9.8213 0.09 510 44 CBS 2004 102 1323 3.1323 0.09 1025 96 Rive r 1989 17 267 8.3572 0.09 233 16 River 2004 64 669 2.2721 0.09 545 62 Table 4 5. Class Level Analysis of the CBS landscape and 500 meter river buffer. Class level analysis of forested and non forested patches within the CBS landscape and 500 meter riv er buffer from two different years (1989 and 2004) from Clumpy metric. Landscape Vegetation Year Clumpy CBS Forest 1989 0.6599 CBS Non Forest 1989 0.6602 CBS Forest 2004 0.6499 CBS Non Forest 2004 0.6455 River Forest 1989 0.4981 River Non Fores t 1989 0.5338 River Forest 2004 0.5494 River Non Forest 2004 0.5540

PAGE 122

122 Table 4 6. Suitable howler habitat. Suitable howler habitat looking at two different criteria: A) fore CBS area and 500 meter river buffer within the CBS). Criteria Landscape Year % of landscape CBS 2004 44.86% River 2004 49.79% B. For CBS 2004 44.72% River 2004 46.74%

PAGE 123

123 CHAPTER 5 CONCLUSION Although there have been several social science research studies conducted within the CBS (Bruner 1993; Hartup 1994; Alexander 2000; Lash 2003; Jones and Young 2004), a comprehensive study that connects household information to conservation practices, forest cover change, and habitat fragmentation did not exist. Therefore, t he overarching objective of this dissertation was to pr ovide an overview of conservation within the CBS Specifically, this research consisted of the following objectives: Objective 1: A ssess perceived benefits and place based meanings of riparian forest landscapes, Objective 2: A ssess the relative influence of tourism and pledging on deforestation probabilities, in addition to other locational and socio economic variables, and Objective 3: A ssess forest fragmentation for the black howler monkey based on habitat criteria Perceived Benefits a nd Place Based Me anings o f Riparian Forest Landscapes Although results show tourism and pledging initiatives may be considered financial failures by residents, those involved in these initiatives value, benefit from, and feel attached to the forest for a variety of non fin ancial reasons. This study showed a significant relationship exists between initiative involvement (pledging or tourism) and higher perceived benefits (importance) and place attachment (meanings) towards riparian forests and conservation. However, all res idents interviewed, regardless of initiative involvement, agreed that riparian forests are not providing financial benefits. Regardless, this study shows that involvement in either conservation initiative, whether they are financially successful or not, i s related to higher conservation values and perceived community benefits and is a strong basis for conservation.

PAGE 124

124 Relative Influence of Factors on Deforestation P robability In an attempt to assess what factors may be driving deforestation or actually dec reasing deforestation probability, this study examined the relative influence of locational, land tenure, socio economic, socio demographic, and conservation initiative variables. From the variables applied to all modeled time periods, t rends show areas c loser to the Belize River are more likely to be deforested, as are areas closer to road networks Additionally, having secure land title decreases the probability of deforestation, although this did not have strong strength of effect in the last modeled t ime period (2000 2004) Looking at influential socio economic variables from the 2000 2004 modeled time period with strong effect strength, a gricultural and cattle activities are influential in increasing deforestation probability while higher levels of household head education decrease d deforestation probability. Pledging was shown to i ncrease deforestation probabilities during the 1989 2000 modeled time period, a decrease during the 1994 2000 modeled time period, and an increase during the 200 0 2004 modeled time period. Tourism, a variable that was only able to be accurately measured during the 2000 2004 time period, indicated an increase in deforestation probability. Although involvement in either of these initiatives during the 2000 2 004 time period did not show a decrease in deforestation probability, the combination of being involved in both tourism and pledging actually decreased deforestation probabilities during 2000 2004. This indicates that having both the values of pledged residents (whether the pledge influenced these residents or these residents had these conservation values to begin with is not known) and the income from tourism participation may actually create a stronger connection between tourism dollars received from the resource attraction (the howler monkey) and the habitat (forests) it is dependent upon.

PAGE 125

125 Although some of these variables have strong inf luence with the models created, goodness of fit values (pseudo R 2 ) indicate that they only explain a small propor tion of deforestation within the CBS and suggest there are other variables not included i n the model that are more influential at explaining deforestation probability within landowner parcels (e.g., biophysical and institutional). Nevertheless, this stud y helped to explore and identify the relevant influence of some of the factors affecting deforestation Forest H abitat F ragmentation Overall landscape trends within the CBS between 1989 and 2004 indicate there has been a 23% decrease in forest cover withi n the CBS and 500 meter river buffer, along with increased fragmentation of forest habitat. This coincides with the 20% decrease in forest cover for Belize since the early 1980s (FAO 2007). Additionally, the second largest proportion of the CBS landscape Since the 120 meter river buffer analysis outside the CBS followed the same trajectory as the 120 meter river buffer within the CBS riparian forests are not anymore protected within the CBS, despite protected area Despite increased deforestation and fragmentation within the CBS, the black howler monkey ( A louatta pigra ) possesses ma ny traits that make it adaptable to increased habitat fragmentation Additionally, it should be noted that howler populations have increased dramatically over the past 20 years within the CBS, from an estimated 800 individuals in 1985 to 3,000 5,000 ind ividuals in 2003 (Brockett 2003). A preferred food source for the howler, the fig ( Ficus spp. ), is a forest fringe species found along the river and in forest fragments. Therefore, the fragmented forests have actually been beneficial for the howlers in p roviding this important food source.

PAGE 126

126 Despite increased fragmentation and deforestation, connectivity between forest patches has remained high indicating dispersal and colonizing potential between most forest patches has not been jeopardized. However, co ntinuing trends of increased deforestation and fragmentation of CBS forest habitat, along with reported increases in howler population densities, will likely place increased pressure on these populations. Conclusion Conservation within the CBS may be a li ttle more complex than simply saving fore sts and, therefore saving howlers, as increased fragmentation actually provides better habitat for ficus spp. (e.g., figs), the preferred food source for howlers. The CBS falls under the IUCN Category I V protected a the maintenance of habitats and/or to meet the r (IUCN 1994). Under this designation, one could say the CBS has been successful in protecting and maintaining howler populations, as d ocumented by increases in their population However, if the conservation objec tive is forest preservation, the 23% decrease in forest cover and increased forest fragmentation would point to conservation failure The concerns for the future of the CBS ar e the continued trends in deforestation and fragmentation. These trends, if continued, would eventually reach a level that impacts dispersal among patches or where howler population densities reach a carrying capacity level and populations would begin to decline. This may signal that the CBS should not be managed for a single outcome (e.g., howlers) as IUCN Category IV protected area designation provides. As deforestation is tied to livelihoods of private landowners, closer examination was given to the tw o conservation initiatives (tourism and a conservation pledge) established to deter deforestation.

PAGE 127

127 In closer examination of these two conservation initiatives, the CBS is in a unique position. A strong basis for conservation does exist and an indication t hat involvement in both tourism and pledging had some influence in decreasing deforestation probability between 2000 2004. However without building upon the other influential factors (e.g., financial payment for pledged residents distribution of touri sm participation and benefits, land tenure, expanding agriculture and cattle, etc.), these conservation initiatives will not be as effective at promoting conservation goals within the CBS and will not be able to compete with other opportunities the land pr ovides Although these conservation initiatives working together may have some c onservation initiatives must be managed more effectively and equitably to have any other conserve those forests Overall, this study reiterates the lesson that the success of any conservation initiative must be linked to local communities be nefiting from their conservation of biodiversity.

PAGE 128

128 LIST OF REFERENCES Abdullah, S. A. and N. Nakagoshi. 2007. In Press Forest fragmentation and its correlation to human land use change in the state of Selangor, peninsular Malaysia. Forest Ecology and Management Adams, W. and D. Hulme. 2001. Conservation and Community. Changing Narratives, Policies & Practices in African Conservation. In: African Wildlife and Livelihoods. The Promise and Performance of Community Conservation (D. Hulme and M. Murp hree, eds), pp. 9 24, James Currey, Oxford, UK. Adams, W. M., R. Aveling, D. Brockington, B. Dickson, J. Elliot, J. Hutton, D. Roe, B. Vira, and W. Wolmer. 2004. Biodiversity conservation and the eradication of poverty. Science 306:1146 1149. Agrawal, A. and C. C. Gibson. 1999. Enchantment and disenchantment: The role of community in natural resource management. World Development 27(4):629 649. Alcorn, Janis B. 1993. Indigenous Peoples and Conservation. Conservation Biology 7(2): 424 426. Alexander, S. E 2000. Resident attitudes towards conservation and black howler monkeys in Belize: the Community baboon sanctuary. Environmental Conservation 27(4):341 350. Anderson, D. H., R. Nickerson, T.V. Stein, and M.E. Lee. 2000. Planning to Provide Community and V isitor Benefits from Public Lands. In Trends in Outdoor Recreation, Leisure, and Tourism. ed. Gartner, W.C. and Lime, D.W., 197 212 CAB Publishing, New York, NY. Anderson, J., J. M. Rowcliffe, and G. Cowlishaw. 2007. Does the matrix matter? A forest prim ate in a complex agricultural landscape Biological Conservation 135(2): 212 222. Andren, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat a review. Oikos 71: 355 366. Andrews, P. a nd M. Bamford. 2008. Past and present vegetation ecology of Laetoli, Tanzania. Journal of Human Evolution 54(1 ): 78 98 Angelsen, A. 1999. Agricultural expansion and deforestation: modelling the impact of population, market forces and property rights. Journal of Development Economics 58:185 218. Aylward, B. 2003 The actual and potential contribution of nature tourism in Zululand. In Nature Tourism, Conservation, and Development in Kwazulu Natal, South Africa (Alward, B. and E. Lutz, eds), pp. 1 40, The World Bank

PAGE 129

129 Baldwin, L. A. 1976. Vocalizations of howler monkeys (Alouatta palliata) in Southwestern Panama. Folia Primatologica 26:81 108. Bardhan, P. 2002. Decentralization of gov ernance and development. The Journal of Economic Perspectives 16(4):185 205. Bates, D. and T. K. Rudel. 2000. The political ecology of conserving tropical rain forests: a cross national analysis. Society and Natural Resources 13:619 634. Baum, K. A., K. J. Haynes, F.P. Dillemuth, and J.T. Cronin. 2004. The matrix enhances the effectiveness of corridors and stepping stones. Ecology 85: 2671 2676. Belize Zoo website. http://www.belizezo o.org/zoo/zoo/mammals/how/how1.html Accessed 2/6/2006. Belsky, J. M. 2000. The meaning of the manatee: An examination of community based ecotourism discourse and practice in Gales Point, Belize. In: People, Plants, & Justice. The Politics of Nature Conser vation (C. Zerner, ed), pp. 285 308, Columbia University Press, New York. Bem, D. 1972. Self perception theory. In Pardini and Katzev. 1983 84. Bennett, A. F. 1998. Movements of animals through linkages. In: Bennett, A.F. (Ed.), Linkages in the Landscape: The Role of Corridors and Connectivity in Wildlife Conservation. IUCN, Gland, Switzerland, pp. 67 91. In Anderson, et al., 2007. Berkes, F. 2007. Community Based Conservation in a globalized world. PNAS 104 (39):15188 15193. Berstein, I. S., P. Balcaen, L Dresdale, H. Gouzoules, M. Kavanah, T. Patterson, P. Neyman Warner. 1976. Differential effects of forest degradation on primate populations. Primates 17(3):401 411. Bicca Marques, J. C. 2003. How do howler monkeys cope with habitat fragmentation? In Mars h, L. K. (ed.), Primates in Fragments: Ecology and Conservation Kluwer Academic/ Plenum, New York, pp. 283 303. Bierregaard, R. O., Jr. and V. H. Dale. 1996. Islands in an ever changing sea: The ecological and socioeconomic dynamics of Amazonian rainfores t fragments. In Schelhas, J.; and R. Greenberg (eds). Forest Patches in Tropical Landscapes. Island Press: California. pp. 187 204. Binswanger, H. 1991. Brazilian policies that encourage deforestation in the Amazon. World Development 19(7):821 829. Bolin I. 1981. Male parental behavior in black howler monkeys ( Alouatta palliatea pigra ) in Belize and Guatemala. Primates 22 : 349 360.

PAGE 130

130 Boo, E. 1990. Ecotourism: the potentials and pitfalls World Wildlife Fund: Washington, D.C. Bookbinder, M. P., E. Dinerstein A. Rijal, H. Cauley, and A. Rajouria. 1998. support of biodiversity conservation Conservation Biology 12(6):1399 11404. Booth, K. L., B. L. Driver, S.R. Espiner, and R.J. Kappelle. 2002. Managing Public Conservation Lands by the Beneficial Outcomes Approach with Emphasis on Social Outcomes. Doc Science Internal Series 52 Published by Department of Conservation, Wellington, New Zealand. Boots, B. N. and A. Getis. 1988. Point pattern analysis Sage: Beverly Hills, CA Brandon, K., K. Redford, and S. Sanderson (eds). 1998. Parks in Peril: People, politics and protected areas. Washington, DC: Island Press. Bray, D. B., Merino Perez, L., Negreros Castillo, P., Segura Warnholtz, G., Torres Rojo, J.M., mana ged forests as a global model for sustainable landscapes. Conservation Biology 17:662 677. Brechin, S. R., P. R. Wilshusen, C. L. Fortwangler, and Patrick C. West. 2002. Beyond the square wheel: Toward a more comprehensive understanding of biodiversity co nservation as social and political process. Society and Natural Resources 15:41 64. Brockett, R. 2003. 2003 Howler monkey census. In: Young, C The common flora and fauna of the Community Baboon Sanctuary UNDP /GEF Small Grants Program. Pp. 63 65. Brown, K J. Mackensen, S. Rosendo, K. Viswanathan, L. Cimarrusti, K. Fernando, C. Morsello, M. Muchagata, I. M. Siason, and S. Singh. 2005 in Ecosystems and Human Well Being: Policy Responses (Millennium Ecosystem Assessment and Island Press, Washington, DC), pp 425 465. In Berkes 2007. Bruner, G. Y. 1993. Evaluating a model of primate ownership conservation: Ecotourism in the Community Baboon Sanctuary in Belize. Burger, J., E. Ostrom, R.B. N orgaard, D. Policansky, and B.D. Goldstein. 2001. Protecting the Commons: A framework for resource management in the Americas. Island Press: Washington, D.C. Burkey, T. V. 1995. Extinction rates in archipelagos: Implications for populations in fragmente d habitats. Conservation Biology 9(3):527 541. Burn, S. M and S. Oskamp. 1986. Increasing community recycling with persuasive communication and public commitment. Journal of Applied Social Psychology 16:29 41. Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: A practical information theoretic approach 2 nd edition. New York: Springer. Ceballos Lascurain, H. 2001. Integrating Biodiversity into the Tourism Sector: Best Practice Guidelines Report submitted to UNEP/UNDP/GEF/BPSP

PAGE 131

131 Chambers, R., M. Leach, and C. Conroy. 1993. Trees and savings and security of the rural poor. International Institute for Environment and Development Gatekeeper Series No. 3. Chan, K. M. A., R. M. Pringle, J. Ranganathan, C. L. Boggs, Y. L. Chan, P. R Ehrlich, P. K. Haff, N. E. Heller, K. Al khafaji, and D. P. Macmynowski. 2007. When agendas collide: Human welfare and biological conservation. Conservation Biology 21(1):59 68. Chapman, C. A. and L. J. Chapman. 1990. Dietary variability in primate popul ations. Primates 31(1):121 128. Chapman, C. A. and S. R. Balcomb. 1998. Population characteristics of howlers: Ecological conditions or group history. International Journal of Primatology 19:385 403. Chapman, C. A and J. E. Lambert. 2000. Habitat alteratio n and the conservation of African primates: Case study of Kibale National Park, Uganda. American Journal of Primatology 50: 169 185. Chomitz, K. and D. Gray. 1996. Roads, land use and deforestation: A spatial model applied to Belize. The World Bank Econo mic Review 10(3): 487 512. Christ C., O Hillel S Matus and J Sweeting 2003 Tourism and Biodiversity: Mapping s Global Footprint, Conservation International Cialdini, R. B. 1985. Influence: Science and practice. Glenview, IL: Scott, Foresman In Werner, et al. 1995. CIPEC, 1998. Training sample protocol. Center for the Study of Institutions, Population and Environmental Change. http://www.cipec.org/research/methods/ts10_98.pdf Clarke, M. R., C. M Crockett, and E. L Zucker. 2002. Mantled howler population of Hacienda La Pacifica, Costa Rica, between 1991 and 1998: effects of deforestation. American Journal of Primatology 56:155 163. Coates Estrada, R. and A. Estrada. 1986. Frui ting and frugivores at strangler fig in the tropical rain forest of Los Tuxtlas, Mexico. Journal of Troipcal Ecology 2:349 357. Coelho, A. M. Jr., C. Bramblett, L. Quick, S. Bramblett. 1976. Resource availability and population density in primates: A socio bioenergetic ananlysis of the energy budgets of Guatemalan howler and spider monkeys. Primates 17:63 80. Collinge, S. K. 1996. Ecological consequences of habitat fragmentation: Implications for landscape architecture and planning. Landscape and Urban Plan ning 36(1):59 77. Conway, D. and J. Cohen. 1998. Consequences of migration and remittances for Mexican transnational communities. Economic Geography 74:26 44. Cowlishaw, G. and R. Dunbar. 2000. Primate Conservation Biology. The University of Chicago Press Chicago. In Anderson et al. 2007.

PAGE 132

132 Crockett, C. M. and J. F. Eisenberg. 1987. Howlers: Variations in group size and demography. In Smuts, B.B.; D.L. Cheney; R.M. Seyfarth; R.W Wrangham; and T.T. Struhsaker (eds). Primate Societies. University of Chicago P ress, Chicago, pp. 54 68 In Crockett 1997. Crockett, C. M. 1997. Conservation biology of the genus Alouatta International Journal of Primatology 19(3):549 578. Crockett, C. 1998. Conservation biology of the genus Alouatta. International Journal of Prima tology 19:549 578. Cuba, L. and D. M. Hummon. 1993. A place to call home: identification with dwelling, community, and region. Sociological quarterly 34(1):111 131. Cuarn, A. D. 2000. Effects of land cover changes on mammals in a neotropical region: a mo deling approach. Conservation Biology 14:1676 1692. Dalle, S. P., S. de Blois, J. Caballero, and T. Johns. 2006. Integrating analyses of local land use/land cover data for assessing the success of community based conservation. Forest Ecology and Management 222:370 383. Davenport, M. A. and D. H. Anderson. 2005. Getting from sense of place to place based management: An interpretive investigation of place meanings and perceptions of landscape change. Society and Natural Resources 18:625 641. Debinski D. M. an d R. D. Holt, 2000. A survey and overview of habitat fragmentation experiments. Conservation Biology 14(2): 342 355. DeFries, R., J. Foley, and G. P. Asner. 2004. Land use choices: balancing human needs and ecosystem function. Frontiers in Ecology and the Environment 2:249 257. DiFiore, S. L. 2002. Remote Sensing and Exploratory Data Analysis as Tools to Rapidly Evaluate Forest Cover Change and Set Conservation Priorities along the Belize River, Belize. MA thesis, Columbia University, New York, NY. Driver B. L. 1996. Benefits driven management of natural areas. Natural Areas Journal 16(2):94 99. Durand, J. and D. Massey. 1992. Mexican migration to the United States: A critical review. Latin American Research Review 27:3 42. Durand, J., E. Parrado, and D. Massey. 1996. Migradollars and development: A reconsideration of the Mexican case. International Migration Review 30:423 444. Edwards, V. M. 2004. Community Based Ecotourism as a Panacea for Protected Areas: the use of common property theory in its analys is and development. 10th Biennial Meeting of the IASCP. Oaxaca, Mexico.

PAGE 133

133 Eisenhauer, B. W., R. S. Krannich, and D. J. Blahna. 2000. Attachments to special places on public lands: An analysis of activities, reason for attachment, and community connection. So ciety and Natural Resources 13:421 441. Estrada, A. and R. Coates Estrada. 1984. Fruit eating and seed dispersal by howling monkeys ( A. palliata) in the tropical rain forest of Los Tuxtlas, Mexico. American Journal of Primatology 6:77 91. Estrada, A. and R Coates Estrada. 1988. Tropical rain forest conversion and perspectives in the conservation of wild primates (Alouatta and Ateles) in Mexico. American Journal of Primatology 14:315 327. Estrada, A. and R. Coates Estrada. 1996 Tropical rain forest fragment ation and wild populations of primates at Los Tuxtlas. International Journal of Primatology 5:759 783. Estrada, A, S. Juan, T. Ortz Martnez, R. Coates Estrada. 1999. Feeding and general activity patterns of a howler monkey ( Allouata palliata) troop livin g in a forest fragment at Los Tuxtlas, Mexico. American Journal of Primatology 48:167 183. Estrada, A., P. Cammarano, and R. Coates Estrada. 2000. Bird species richness in vegetation fences and in strips of residual rain forest vegetation at Los Tuxtlas, M exico. Biodiversity and Conservation 9 :1399 1416. Estrada, A. A. Mendoza, L. Castellanos, R. Pacheco, S. Van Belle, Y. Garca, and D. Muoz. 2002. Population of the black howler monkey (Alouatta pigra) in a fragmented landscape in Palenque, Chiapas, Mexic o. American Journal of Primatology 58:45 55. Estrada, A., S. Van Belle, L. Luecke, and M. Rosales. 2006. Primate populations in the protected forests of Maya archeological sites in southern Mexico and Guatemala. In Estrada, A., Garber, P.A., Pavelka, M. an d Luecke, L. (Eds.), New Perspectives in the Study of Mesoamerican Primates Springer, NY, pp 471 488. Fahrig, L. and G. Merriam. 1985. Habitat patch connectivity and population survival. Ecology 66(6):1762 1768. Fahrig, L. 2003. Effects of habitat fragmen tation on biodiversity. Annual Review of Ecology Evolution and Systematics 34: 487 515 In Anderson et al. 2007. FAO. Food and Agriculture Organization of the United Nations. 1993. Forest Resources Assessment, 1990, tropical countries. Food and Agriculture Organization of the United Nations Forestry Paper 112. Rome. In DiFiore 2002. FAO. Food and Agriculture Organization of the United Nations. 2001. The global forests resource assessment 2000 summary report. Committee on Forestry Paper 8b. Rome. In DiFiore 2002.

PAGE 134

134 FAO. Food and Agriculture Organization of the United Nations. 2007. National Report Belize. FAO Corporate Document Repository. Accessed April 28, 2008. http://www.fao.org/docrep/007/ j4051b/j4051b07.htm Fearnside, P. M. 1986. Spatial concentration of deforestation in the Brazilian Amazon. Ambio 15: 74 81. Fischer, G., Y. Ermoliev, M. A. Keyzer, and C. Rosen Zweig. 1996. Simulating the Socio Economic and Biogeophysical Driving Forces of Land Use and Land Cover Change: The IIASA Land Use Change Model. Working Paper WP 96 010. Laxenburg: International Institute for Applied Systems Analysis. In Mertens and Lambin 2000. Fitter, R. 1986. Wildlife for Man. How and Why Should We Conserve Our Species William Collins Sons and Co. Ltd.: London. 223 p. Foody, G. M., S. G. Palubinska, R. M. Lucas, P. J. Curran, and M. Honzak. 1996. Identifying terrestrial carbon sinks: classification of successional stages in regenerating tropical forest from Land sat TM data. Remote Sensing of Environment 55: 205 216. Fox, J., R. R. Rindfuss, S. J. Walsh, and V. Mishra, eds. 2003. People and the Environment: Approaches for linking household and community surveys to remote sensing and GIS. Boston: Kluwer Academic Publishers. Freedman, J. and S. Fraser. 1966. Compliance without pressure: The foot in the door technique. Journal of Personality and Social Psychology 4:195 202. Freese, C. H., P. G. Heltne, R. N. Castro, and G. Whitesides. 1982. Patterns and determinan ts of monkey densities in Peru and Bolivia, with notes on distributions. International Journal of Primatology 3:53 90. Fuentes, E., A. Estrada, B. Franco, M. Magaa, Y. Docena, D. Muoz, and Y. Garca. 2003. Reporte preliminar sobre el uso de recursos ali menticios por una tropa de monos aulladores, Alouatta palliata en El Parque La Venta, Tabasco, Mxico. Neotropical Primates 11:24 29. Funder, M. 1995. Campfire: impact and household level. A case study of two villages in Binga District. Prepared for the Bigna Rural District Council and MS Zimbabwe. Galetti, M, F. Pedroni, L. P. C. Morellato. 1994. Diet of the brown howler monkey Alouatta fusca in a forest fragment in southeastern Brazil. Mammalia 1:111 118. Garber, P. A., A. Estrada, and M. S. M. Pavelka. New Perspectives in the Study of Mesoamerican Primates: Concluding Comments and Conservation Priorities In Estrada, A., Garber, P.A., Pavelka, M. and Luecke, L. (Eds.), New Perspectives in the Study of Mesoamerican Primates Springer, NY, pp 563 580.

PAGE 135

135 Garc a Barrios, L. and M. Gonzlez Espinosa. 2004. Change in oak to pine dominance in secondary forests may reduce shifting agriculture yields: experimental evidence from Chiapas, Mexico. Agriculture, Ecosystems and Environment 102:389 401. Gautam, A. P., G. P Shivakoti, and E. D. Webb. 2004. Forest cover change, physiography, local Economy, and institutions in a mountain watershed in Nepal. Environmental Management 33(1):48 61. Geist, H. J. and E. F. Lambin. 2001. What drives tropical deforestation? LUCC Repo rt Series, No. 4. LUCC International Project Office: Louvain la Neuve, Belgium, 136 p. Geist, H. J. and E. F. Lambin. 2002. Proximate causes and underlying driving forces of tropical deforestation. BioScience 52:143 150. Geoghegan, J., S. C. Villar, P. Kl epeis, P. Macario Mendoza, Y. Ogneva Himmelberger, R. R Chowdhury, B. L. Turner II, and C. Vance. 2001. Modeling tropical deforestation in the southern Yucatn peninsular region: comparing survey and satellite data. Agriculture, Ecosystems and Environment 85:25 46. Geoghegan J., L. Wainger, and N. Bockstael. 1997. Spatial landscape indices in a hedonic framework: an ecological economics analysis using GIS. Ecological Economics 23: 251 64. Gibson, C. C., M. A. McKean, and E. Ostrom. 2000. People and Forests. Communities, Institituions, and Governance. MIT Press. Gibson, C. C., F. E. Lehoucq, and J. T. Williams. 2002. Does privatization protect natural resources? Property rights and forests in Guatemala. Social Science Quarterly 83(1):206 225. Gilpin, M. E. an d J. M. Diamond. 1980. Subdivision of nature reserves and the management of species diversity. Nature 285:567 568. Githiru, M. and L. Lens. 2007. Application of fragmentation research to conservation planning for multiple stakeholders: An example from the Taita Hills, southeast Kenya. Biological Conservation 134(2): 271 278. Godoy, R. A. and K. S. Bawa. 1993. The economic value and sustainable harbest of plants and animals from the tropical forest: assumptions, hypothesis, and methods. Economic Botany. 47( 3): 215 219. In Tisdell, C.A. 1995. Issues in biodiversity conservation including the role of local communities. Environmental Conservation 22(3):216 222. McSweeney, J. Overman, D. W ilkie, N. Brokaw, and M. Martinez. 1997. Household determinants of deforestation by Amerindians in Honduras. World Development 25:977 87.

PAGE 136

136 Gonzales Kichner, J. P. 1998. Group size and population density of the black howler monkey ( Alouatta pigra ) in Muchuk ux Forest, Quintana Roo, Mexico. Folia Primatologica 69:260 265. Goudy, W. J. 1990. Community attachment in a rural region. Rural Sociology 55:178 198. Green, G., C. M. Schweik, M. Hanson. 2000. Radiometric calibration of Landsat Multispectral Scanner and Thematic Mapper images: guidelines for the global changes community. Working Paper. Bloomington, Indiana Center for the Study of Institutions, Population, and Environmental Change. Guilln Trujillo, H. and J. R. Stepp. 2005. Is Ecotourism Promoting Conserv ation in the Lacandon Forest? Working Forests in the Tropics Abstract book and program: Policy and Market Impacts on Conservation and Management University of Florida. Guyer, J. and E. F. Lambin.1993. Land use in an urban hinterland: Ethnography and rem ote sensing in the study of African intensification. American Anthropologist 95(4):839 859. Hanna, S., C Folke, and K. G. Maller. 1996. Property rights and the natural environment. In Rights to Nature Island Press: Washington, D.C. pp 1 12. Harcourt, C. S. and J. Sayer. 1996. The conservation atlas of tropical forests: The Americas. New York: Simon and Schuster. In Southworth et al. 2004. Harcourt, A. Susceptibility to Logging. In Anderson et al. 2007. Harcourt, A. H. 2002. Empirical estimates of minimum viable population sizes for primates: tens to tens of thousands? Animal Conservation 5:237 244. Harrison, S. and E. Bruna. 1999. Habitat fragmentation and large scale conservation: what do we know for sure. Ecography 22:225 232. Hartshorn, G. S. 1984. Belize Country Environmental Profile: A Field Study. Belize City: Nicolait. In James, R. A., P. L. Leberg, J. M. Quattro, and R. Vrijenhoek. 1997. Genetic diversity in black howler monk eys ( Alouatta pigra) from Belize. Am. J. Phys. Anthropol 102:329 336 Hartup, B. 1994. Community conservation in Belize: Demography, resource use, and attitudes of participating landowners. Biological Conservation 69: 235 241. Hayes, D. J., S. A. Sader, an d N. B. Schwartz. 2002. Analyzing a forest conversion history database to explore the spatial and temporal characteristics of land cover change in Landscape Ecology 17: 299 314. He, H. S., B. E. DeZonia, and D. J. Mladen off. 2000. An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology 15:591 601.

PAGE 137

137 Healy, R. G. 1994. Tourist merchandise as a means of generative local benefits from ecotourism. Journal of Sustainable Tourism 2(3):137 151. Hob bs, R. J. 1993. Effects of landscape fragmentation on ecosystem process in the western Australian wheatbelt. Biological Conservation 64:193 201. Holden, S. T. 1993. Peasant household modeling: farming systems evolution and sustainability in Northern Zambi a. Agricultural Economics 9:241 67. Horwich, R. H., and Gebhard, K. 1983. Roaring rhythms in black howler monkeys ( Alouatta pigra ) of Belize. Primates 24: 290 296. Horwich, R. H. and E. D. Johnson. 1984. Geographic distribution and status of the black howl er monkey. IUCN / SSC Primate Spec. Group Newsletter 4:25 27. Horwich, R. H. and E. D. Johnson. 1986. Geographic distribution of the black howler monkey ( Alouatta pigra) in Central America. Primates 27:53 62. Horwich, R. H. and J. Lyon. 1987. An experimen tal technique for the conservation of private lands. J. Med. Primatol 17:169 176. Horwich, R. H. 1990. How to develop a community sanctuary an experimental approach to the consrervation of private lands. Oryx 24(2):95 102. Horwich, R. H. and J. Lyon. 199 0. A Belizean Rain Forest. The Community Baboon Sanctuary Oranutan press: Gay Mills, WI. 420 pp. Horwich, R. H. and J. Lyon. 1998. Community based development as a conservation tool: the Community Baboon sanctuary and the Gales point Manatee Project. In P rimack et al. 1998 Horwich, R. 1998. Effective Solutions for howler monkey conservation. International Journal of Primatology 19(3):579 598. Horwich, R. H., R. C. Brockett, R. A. James, and C B. Jones. 2001. Population growth in the Belizean Black Howli ng Monkey ( Alouatta pigra). Neotropical Primates 9(1):1 7. Hubacek, K. and J. Vazquez. 2002. The economics of land use change. International Institute for Applied Systems Analysis. Interim Report IR 02 015. Hulme, D. and M. Murphree. 1999. Communities, wi Journal of International Development 11:277 285. Igoe, J. 2006. Measuring the costs and benefits of conservation to local communities. Journal of Ecological Anthropology 10:72 77.

PAGE 138

138 IUCN (World Conservation Union ). 2003. IUCN Red List of Threatened Species. http://www.iucn.org/themes/ssc/redlist_archive/redlist2003/English/profilesEn.htm accessed 2/6/2007. IUCN. 199 4. Guidelines for Protected Areas Management Categories. IUCN. Cambridge, UK and Gland, Switzerland. 261pp http://www.unep wcmc.org/protected_areas/categories/index.html a cc essed 10/23/2008. Jacobson, S. K. and R. Robles. 1992. Ecotourism, sustainable development, and conservation education: Development of a tour guide training program in Tortuguero, Costa Rica. Environmental Management 16(6):701 713. James, R. A. C. 1992. G enetic variation in Belizean black howler monkeys ( Alouatta pigra) Ph.D. Dissertation. Rutgers University, New Brunswick, NJ. In Jones 1995. Jensen, John R. 2005. Introductory digital image processing: A remote sensing perspective. Pearson Prentice Hall: NJ. Jha, C. S. and N. V. M. Unni. 1994. Digital change detection of forest conversion of a dry tropical Indian forest region. International Journal of Remote Sensing 15: 2543 2552. Johns, A. D. and J. P. Skorupa. 1987. Responses of rain forest primates to habitat disturbance: A review. International Journal of Primatology 8:157 191. Jones, C. B. 1995. Howler monkeys appear to be preadapted to cope with habitat fragmentation. Endangered Species Update. 12:9 10. Jones, B., and M. Murphree. 2001. The evolutio n of policy on community conservation in Namibia & Zimbabwe. In African wildlife & livelihoods: The promise and perfomance of community conservation D. Hulme and M. Murphree, eds. 74 87. Oxford: James Currey. Jones, C. B. and J. Young. 2004. Hunting Res traint by Creoles at the Community Baboon Sanctuary, Belize: A Preliminary Survey. Journal of Applied Animal Welfare Science 7(2):127 141. Jones, C. B. and R. H. Horwich. 2005. Constructive Criticism of Community Based Conservation. Conservation Biology 19(4):990 991. Jones, C. B., V. Milanov, and R. Hager. 2008. Predictors of male residence patterns in groups of black howler monkeys. Journal of Zoology 1 7. Jorgensen, B. S. and R. C. Stedman. 2001. S attitud es toward their properties. Journal of Environmental Psychology 21(3): 233 248. Kaimowitz, D. and A. Angelsen. 1998. Economic Models of Tropical Deforestation: A Review Center for International Forestry Research (CIFOR).

PAGE 139

139 Kaltenborn, B., H. Reise, and M. Hundeheide. 1999. National park planning and local participation: Some reflections from a mountain region in southern Norway. Mountain Research and Development 19:51 56. Kangas, P., M. Shave, and P. Shave. 1995. Economics of an Ecotourism Operation in Beli ze. Environmental Management 19(5):669 673. Kapos, V. 1989. Effects of isolation on the water status of forest patches in the Brazilian Amazon. Journal of Tropical Ecology 5:173 185. Kappelle, R. J. 2001. Relationships between local people and protected na tural areas: A case Division, Lincoln University, Canterbury, New Zealand. In McCleave et al. 2006. Kasarda, J. D. and M. Janowitz. 1974. Community attachment in mass soc iety. AmericanSociological Review 39:328 39. Katzev, R. and T. Wang. 1994. Can commitment change behavior? A case study of environmental actions. Journal of Social Behavior and Personality 9(1):13 26. Kiesler, C. A. and J. Sakumura. 1966. A test of a model for commitment. Journal of Personality and Social Psychology 3(3):349 353. Kimmel, J. R. 1999. Ecotourism as environmental learning. Journal of Environmental Education 30(2):40 44. King, R. B., I. C. Baillie, T.M.B. Abell, J. R. Dunsmore, D. A. Gray, J H. Pratt, H. R. Versey, A. C. S. Wright, and S. A. Zisman.1992. Land Resource Assessment of Northern Belize vol. 1 and 2, Natural Resources Institute Bulletin pp. 43: 1 513. In Marsh and Loiselle, 2003. Kiss, A. 2004. Is community based ecotourism a go od use of biodiversity conservation funds? TRENDS in Ecology and Evolution 19(5):232 237. Klepeis, P. 2003. Development policies and tropical deforestation in the southern Yucatn Peninsula: Centralized and decentralized approaches. Land Degradation and Development 14: 541 561. Koontz, F., E. Saqui, H. Saqui, and K. Glander. 1993. A Reintroduction Program for the Conservation of the Black Howler Monkey in Belize. Endangered Species Update 10(6): 1 6. Kratter, A. W ., D. W. Steadman, C. E. Smith, C. E. Filardi, and H. P. Webb 2001. Avifauna of a lowland forest site on Isabel, Solomon Islands The Auk 118(2):472 483. K rishnaswamy, J., M. C. Kiran, and K. N. Ganeshaiah, K. N. 2004. Tree model based eco climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multiseason NDVI. Remote Sensing of Environment 25: 1185 1205.

PAGE 140

140 Kupfer, J A., G. P. Malanson, and S. B. Franklin. 2006. Not seeing the ocean for the islands: the mediating influence of matrix based processes on forest fragmentation effects. Global Ecology and Biogeography 15:8 20. Kyle, G., K. Bricker, A. Graefe, and T. Wickm relationships with activities and settings. Leisure Sciences 26:123 142. Lamb, D., P. D. Erskine, and J. A. Parrotta. 2005. Restoration of degraded tropical forest landscapes. Science 310:1628 1632. Labmin, E. F, X. Baulies, N. Bocksteil, G. Fisher, T, Krug, R. Leemans, E. R. Moran, R. R. Rinkfuss, Y.Santo, D. Skole, B. L.Turner II, and C. Vogel. 1999. Land Use and Land Cover (LUCC) Implementation Strategy. Bonn, Germany: International Geosphere_Biosphere Programm e and the International Human Dimensions Programme on Global Environmental Change. In Olson et al. 2004. Lambin, E. F., M. D. A. Rounsevell, H. J. Geist. 2000. Are agricultural land use models able to predict changes in land use intensity? Agriculture, Eco systems and Environment 82: 321 331. Lambin, E., B. L. Turner, H. Geist, S. Agbola, A. Angelsen, J. Bruce, O. Coomes, R. Dirzo, G. Fischer, C. Folke, P. S. George, K. Homewood, J. Imbernon, R. Leemans, X. Li, E. Moran, M. Mortimore, P. S. Ramakrishnan, J. Richards, H. Skanes, W. Steffen, G. Stone, U. Svendin, T. Veldkamp, C. Vogel, J. Xu. 2001. The causes of land use and land cover change: moving beyond the myths. Global Environmental Change 11:261 269. Lambin, D. F., H. J. Geist, and E. Lepers. 2003. D ynamics of Land Use and land Cover Change in Tropical Regions. Annual Review of Environmental Resources 28:205 41. Langholz, J. 1996. Economics, objectives and success of private nature reserves in sub Suharan Africa and Latin America. Conservation Biolog y 10:271 280. Langholz, J. 2002. Privately Owned Parks. In Making Parks Work: Strategies for Preserving Tropical Nature Terborgh, J; C. Van Schaik; L. Davenport; and M. Rao, eds. Island Press, D.C., p 172 188. Langholz, J. and K. Brandon. 2001. Privately Owned Protected Areas. In The Encyclopedia of Ecotourism. ed. Weaver, D.B. New York: CABI Publishing, p 303 314. Lash, G. B. 2003. Sustaining our spirit: ecotourism on privately owned rural lands and protected areas. PhD dissertation. University of Georg ia. Laurance, W. F. and R. O. Bierregaard, editors. 1997. Tropical forest remnants: ecology, management and conservation of fragmented communities Chicago: University of Chicago Press. 616 p In Estrada et al. 2002. Laurance, W. F. 1999. Reflections on the tropical deforestation crisis. Biological Conservation 91:109 117.

PAGE 141

141 Laurance, W. F., H.L. Vasconcelos, and T.E. Lovejoy. 2000. Forest loss and fragmentation in the Amazon: implications for wildlife conservation. Oryx 34(1): 39 45. Laurance, W. F., T. E. Lo vejoy, H. L. Vasconcelos, E. M Burna, R. K. Didham, P. C. Stouffer, C. Gascon, R. O Bierregaard, S. G. Laurance, and E. Sampaio. 2002. Ecosystem decay of Amazonian forest fragments: a 22 year investigation. Conservation Biology 16:605 618. Leinbach, T., an d J. Watkins. 1998. Remittances and circulation behavior in the livelihood process: Transmigrant families in South Sumatra, Indonesia. Economic Geography 74:45 63. Lepp, A.and S. Holland. 2006. A comparison of attitudes toward state led conservation and co mmunity based conservation in the Village of Bigodi, Uganda. Society and Natural Resoures 19(7):609 623. Leppens, J. 2005. Fishing for tourists: Perceptions from the Stewart Island community of the creation of Rakiura National Park nment, Society and Design Division, Lincoln University, Canterbury, NZ. In McCleave et al. 2006. Lindberg, K.; J. Enriquez; and K. Sproule. 1996. Ecotourism questions: Case studies from Belize. Annals of Tourism Research 23:543 562. Lindenmayer, D. B. 19 99. Future directions for biodiversity conservation in managed forests: indicator species, impact studies and monitoring programs. Forest Ecology and Management 115:277 287. Liverman, D., E. F. Moran, R. R. Rindfuss, and P. C. Stern (Eds.). 1998. People an d pixels: Linking remote sensing and social science. Committee on the Human Dimensions of Global Environmental Change, National Research Council. Washington, DC: National Academy Press. Lovejoy, T. E., R. O. Jr. Bierregaard, A. B. Rylands, J. R. Malcolm, C. E. Quintela, L. H. Harper, K. S. Jr. Brown, A. H. Powell, G. V. N. Powell, H. O. R. Schubart, M. B. Hays. 1986. Edge and other effects on isolation on Amazon forest fragments. In Soul, M.E. (ed.). Conservation Biology: The Science of Scarcity and Div ersity. Sunderland, Mass: Sinauer Assoc. Lovejoy, T. E., R. O Bierregraad, K. S. Brown, L. H. Emmons, M. E. Van der Voort.1984. Ecosystem decay of Amazon forest fragments. In Extinctions. Niteki, M.H. (ed).Chicago: University of Chicago Press. p 295 325 In Estrada et al. 2002. Low, S. M. 1992. Symbolic Ties that Bind: Place Attachment in the Place. In Place Attachment. Altman, I. and S. M. Low (eds), 165 185, Plenum Press: New York. Ludeke, A. K, R. C. Maggio, and L. M. Reid. 1990. An analysis of anthropoge nic deforestation using logistic regression and GIS. Journal of Environmental Management 32: 247 259. Lusigi, W. J. 1981. New approaches to wildlife conservation in Kenya. Ambio 10:87 92.

PAGE 142

142 Lyon, J. and R. H. Horwich. 1996. Modification of tropical forest patches for wildlife protection and community conservation in Belize. In Forest Patches in Tropical Landscapes Shelhas, J. and Greenberg, R. (eds.). Island Press, Washington, D.C. pp, 205 230. MacArthur, R. H. and E. O Wilson. 1967. The Theory of Island Biogeography. Princeton University Press: New Jersey. Maddala, G. S. 1983. Limited dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press. Malmgren, L.A. 1979. Empirical population genetics of golden mantled howling monk eys ( Alouatta palliata) in relation to population structure, social dynamics, and evolution. Ph.D. Dissertation, University of Connecticutt, Storrs. In Jones 1995. Mandujano, S., L.A. Escobedo Morales, and R. Palacios Silva. 2004. Brief report on Alouatta palliata movements among fragments in Los Tuxtlas, Mexico. Neotropical Primates 12:126 131. Mandujano, S., L. A. Escobedo Morales, R. Palacios Silva, V. Arroyo Rodrguez, and E. M. Rodreguez Toledo. 2006. A metapopulation approach to conserving the howle r monkey in a highly fragmented landscape in Los Tuxtlas, Mexico. In: Estrada, A., Garber, P.A., Pavelka, M. and Luecke, L. (eds.), New Perspectives in the Study of Mesoamerican Primates: Distribution, Ecology, Behavior, and Conservation. Springer, NY, pp 513 538. Marsh, L. K. 1999. Ecological effect of the black howler monkey ( Alouatta pigra ) on fragmented forests in the Community Baboon Sanctuary, Belize. Ph.D. Dissertation. Washington University: St. Louis, MO. Marsh, L. K., and B. A. Loiselle 2003. R ecruitment of black howler fruit trees in fragmented forests of Northern Belize. International Journal of Primatology 24:65 86. Marsh, L. K. 2003. Primates in fragments: Ecology and conservation Kluwer, Academic/Plenum Publishers, New York. In Anderson e t al. 2007. Mascia, M. B., J. P. Brosius, T. A. Dobson, B. C. Forbes, L. Horowitz, M. A. McKean, and N. J. Turner. 2003. Conservation and the social sciences. Conservation Biology 17:649 650. McCleave, J., S. Espiner, and K. Booth. 2006. The New Zealand Pe ople Park Relationship: An Exploratory Model. Society and Natural Resources 19:547 561. McCool, S. F. and S. R. Martin. 1994. Community attachment and attitudes toward tourism development. Journal of Travel Research 22(3):29 34. McCracken, S. D., E. S. Bro ndizio, D. Nelson, E. F. Moran, A. D. Siqueira, and C. Rodriguez Pedraza. 1999. Remote sensing and GIS at farm property level: Demography and deforestation in the Brazilian Amazon. Photogrammetric Engineering & Remote Sensing 65:1,311 1,320.

PAGE 143

143 McGarigal, K. and B. J. Marks. 1995. FRAGSTAT. Spatial analysis program for quantifying landscape structure.USDA Forest Service General Technical Report PNW GTR 351,122 p. McGarigal, K., S. A. Cushman, M. C. Neel, and E. Ene. 2002. FRAGSTATS: Spatial Pattern Analysis P rogram for Categorical Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: www.umass.edu/landeco/research/fragstats/fragstats.html McKenzie Mohr, D. and W. Smith. 1999. F ostering Sustainable Behavior. New Society Publishers: Canada Merrill, T. 1992. Belize: A Country Study Washington: GPO for the Library of Congress. http://countrystudies.us/belize/ We bsite accessed 10/2/ 2007. Mertens, B., W. D. Sunderlin, O. Ndoye, and E. F. Lambin. 2000. Impact of macroeconomic change on deforestation in south Cameroon: Integration of household survey and remotely sensed data. World Development 28(6):983 999. Mertens, B. and E. F. Lambin 2000. Land cover change trajectories in Southern Cameroon. Annals of the Association of American Geographers 90(3):467 494. Meyer, W. B. and B. L. Turner II. 1992. Human population growth and global land use/land cover change. Annual Review in Ecology and Systematics 23: 39 61. Millstein, J. S. 1977. How consumers feel about energy: Attitudes and behavior during the winter and spring of 1976 77. Washington, DC: Federal Energy Administration. In Nickerson, 2003. Milton, K. 1980. The foraging strategy of howler monkeys. New York: Columbia University Press. Milton, K. 1991. Leaf change and fruit production in six neotropical Moraceae species. Journal of Ecology 79:1 26. Milton, K. 1996. Effects of bot fly ( Alouatta bueria) parasitism on a free ranging how ler monkey (Alouatta palliata) population in Panama. Journal Zool. Lond 239:39 63. Monty, R. A., E. S. Geller, R. E. Savage, and L. C. Perlmutter. 1979. The freedom to choose is not always so choice. Journal of Experimental Psychology: Human Learning and Memory 5:170 178. In Nickerson 2003. Moore, R. L. and B. L. Driver. 2005. Introduction to Outdoor Recreation. Providing and Managing Natural Resource Based Opportunities. Pennsylvania, PA: Venutre Publishing, Inc.

PAGE 144

144 Munroe, D. K., J. Southworth, and C. Tu cker. 2004. Modelling spatially and temporally complex land cover change: the case of western Honduras. The Professional Geographer 56 (4) : 544 59. Murphree, M. W. 2003. Linkages in the Landscape/Seascape Stream Institutional Aspects of Linkages. WPC: Dur ban. Nagendra, H., C. Tucker, J. Southworth, M. Karmacharya, and B. Karna. 2004. Monitoring parks through remote sensing: studies in Nepal and Honduras. Environmental Management 34(5):748 760. Nagendra, H., D. K. Munroe, and J. Southworth. 2004. From patt ern to process: Landscape fragmentation and the analysis of land use/ land cover change. Agriculture, Ecosystems and Environment 101:111 115. Naughton Treves, L., M. B. Holland; and K. Brandon. 2005. The role of protected areas in conserving biodiversity and sustaining local livelihoods. Annual Review of Environment and Resources 30 :219 252. Nelson, G. C., V. Harris, and S. Stone. 2001. Deforestation, land use, and property rights: Empirical evidence from Darin, Panama. Land Economics 77(2):187 205. Nepal, S. K. 2000. Tourism in protected areas. Annals of Tourism Research 27:661 681. Nepstad, D., G. Carvalho, A. C. Barros, A. Alencar, J. Capobianco, J. Bishop, P. Moutinho, P. Lefebvre, and U. Silva Jr. 2001. Road paving, fire regime feedbacks, and t he future of Amazon forests. Forest Ecology and Management 154:395 407. Neville, M. K., K. E. Glander, F. Braza, A. B. Rylands. 1988. The howling monkeys, genus Alouatta In: Mittermeier, R. A., A. B. Rylands, A. Coimbra Filho, G. A. B. Fonseca (eds.). Ec ology and Behavior of Neotropical Primates, Vol.2, Washington, DC: World Wildlife Fund, p. 349 453. Nickerson, R. S. 2003. Psychology and Environmental Change Lawrence Erlbaum Associates: New Jersey. NRC (National Research Council). 1998. Human Dimension s of Global Environmental Change: Pathways for the Next Decade. Washington, D.C: National Academy Press. Nyaupane, G. P. and B Thapa. 2004. Evaluation of ecotourism: a comparative assessment in the Annapurna Conservation Area Project, Nepal. Journal of Ecotourism 3(1):20 45. Oates J. 1999. Myth and Reality in the Rain Forest: How Conservation Strategies Are Failing in West Africa. Berkeley: University of California Press. In Brechin et al. 2002 G., M. F. Kinnaird, E. S. Dierenfeld, N. L Conk lin Brittain, R. W. Wrangham, and S. Nature 392:668.

PAGE 145

145 Offerman, H. L., V. N Dale, S. M. Pearson, O. Bierregaard Jr., and R. of forest fragmentation on neotropical fauna: current resea rch and data availability. Environ Rev 3:190 211. In Estrada et al. 2002. Olson, J. M., S. Misana, D. J. Campbell, M. Mbonile, and S. Mugisha. 2004. A research framework to identify the root causes of land use change leading to land degradation and chang ing biodiversity. Land Use Change Impacts and Dynamics (LUCID) Project Working Paper #48. Nairobi, Kenya: International Livestock Research Institute. Olupot, W. and P. M. Waser. 2001. Activity patterns, habitat use and mortality risks of mangabey males l iving outside social groups. Animal Behaviour 61:1227 1235. Onderdock, D. and C. Chapman. 2000. Coping with Forest Fragmentation: The Primates of Kibale National Park, Uganda. International Journal of Primatology 21(4):587 611. Ostro, L. E. T.; S. C. Silve r; F. Koontz; T. P. Young; and R. H. Horwich. 1999. Ranging behavior of translocated and established groups of black howler monkeys Alouatta pigra in Belize, Central America. Biological Conservation 87:181 190. Ostro, L. E. T., Silver, S. C., Koontz, F. W. Horwich, R. H., and Brockett, R. 2001. Shifts in social structure of black howler ( Alouatta pigra ) groups associated with natural and experimental variation in population density. Int. J. Primatol 22:733 748. Ostrom, E. 1990. Governing the Commons: The E volution of Institutions for Collective Action. Cambridge: Cambridge University Press. Ostrom, E., J. Burger, C. B. Field, R. B. Norgaard, and D. Policansk 1999. Sustainability revisiting the commons: local lessons, global challenges. Science 284: 278 82. Ovaskeinen, O. and I. Hanski. 2004. Metapopulation dynamics in highly fragmented landscapes. In: Hanski, I and O.E. Gaggiotti. 2004. Ecology, genetics, and evolution of metapopulations. Elsevier Academic Press, Burlington, MA. In Mandujano et al. 2006 Pallak, M. S., D.A. Cook, and J. J. Sullivan. 1980. Commitment and energy conservation. Applied Social Psychology Annual 1:235 253 Pallak, M. S. and W. Cummings. 1976. Commitment and voluntary energy conservation. Personality and Social Psychology Bulletin 2:27 31. Palomares, F., P. Ferreras, M. M. Ferdraini, and M. Delibes. 1996. Spatial relationships between Iberian lynx and other carnivores in an area of south western Spain. Journal of Applied Ecology 33:5 13. Pardini, A. U. and R. D. Katzev. 1983 1984. The effects of strength of commitment on newspaper recycling. Journal of Environmental Systems 13:245 254. Parker, T. A., III, B. K. Holst, L. H. Emmons, and J. R. Meyer. 1993. A Biological Assessment of the Colombia River Forest Reserve, Toledo Distri ct, Belize Rapid Assessment Program

PAGE 146

146 Working Papers 3, Conservation International,Washington, DC. In Marsh and Loiselle 2003. Perlmutter, L. C., K. Scharff, R. Kash, and R. A. Monty. 1980. Perceived control: A generalized state of motivation. Motivation an d Emotion 4:35 45. In Nickerson 2003. Perz, S. 2001. Household demographic factors as life cycle determinants of land use in the Amazon. Population Research and Policy Review 20:159 186. PfB (Programme for Belize). 2000. Feasibility study of the proposed N orthern Belize Biological Corridors Project (NBBCP), Vol. 1, Main Report. Pinchn, F. J. 1997. Colonist land allocation decisions, land use, and deforestation in the Ecuadorian Amazon frontier. Economic Development and Cultural Change 44:707 44. Platteau, J. 2004. Monitoring elite capture in community driven development. Development and Change. 35(2):223 246. Pozo Montuy, G. and J. C. Serio Silva. 2003. Locomotion and feeding on the ground by black howler monkeys ( Alouatta pigra ) in a very fragmented habit at of Rancheria Leona Vicario, Balancan Tabasco, Mexico. American Journal of Primatology 60:65. Primack, R. B., D. Bray., H. A. Galletti, and I. Ponciano (eds). 1998. Timber, Tourists, and Temples. Conservation and Development in the Maya Forest of Belize Guatemala, and Mexico. Island Press. Prohansky H. M., Fabian, A. K., and Kaminoff, R. 1983. Place Identity: Physical World Socialization of the Self. Journal of Environmental Psychology 3:57 83. Pulliam, H. R., J. B. Dunning, Jr., and J. Liu. 1992. Popu lation dynamics in complex landscapes: a case study. Ecological Applications 2:165 177. Redford, K. H. 1992. The empty forest. BioScience 42(6):412 422. Redford, K. H. and S. E. Sanderson. 2000. Extracting Humans from Nature. Conservation Biology 14(5):136 2 1364. Rindf uss, R. R., S. J. Walsh, B. L. Turner II, J. Fox, and V. Mishra. 2004. Developing a science of land change: Challenges and methodological issues. Proceedings of the National Academy of Sciences ( PNAS) 101(39):13976 13981. Rivera, A. and S. Cal me. Forest fragmentation and its effects on the feeding ecology of black howlers ( Alouatta pigra) from the Calakmul area in Mexico. In Estrada, A., Garber, P.A., Pavelka, M. and Luecke, L. (eds.), New Perspectives in the Study of Mesoamerican Primates: Dis tribution, Ecology, Behavior, and Conservation. Springer, NY, pp. 189 215. Rogerson, P. A. 2005. Statistical methods for Geography. London: Sage Publications.

PAGE 147

147 Roy Chowdhury, R. 2006a. Driving forces of tropical deforestation: The role of remote sensing an d spatial models. Singapore Journal of Tropical Geography 27( 1):82 101. Roy Chowdhury, R. 2006b. Landscape change in the Calakmul Biosphere Reserve, Mexico: modeling the driving forces of smallholder deforestation in land parcels. Applied Geography 26 (2) : 129 152. Rudel, T. and J. Roper. 1997. Forest fragmentation in the humid tropics: a cross national analysis. Singapore Journal of Tropical Geography 18:99 109. Rutherford, G. N., A. Guisan, and N. E. Zimmermann. 2007. Evaluating sampling strategies and log istic regression methods for modeling complex land cover changes. Journal of Applied Ecology 44:414 424. Rylands, A. B., R. A. Mittermeier, and L. E. Rodriguez. 1995. A species list for the new world primates ( Platyrrhini ): Distribution by country, endemi sm, and conservation status according to the Mace Land System. Neotropical Primates 3 (Suppl.):113 160. Sader, S. A., T. Sever, J. C. Smoot, and M. Richards. 1994. Forest change estimates for the northern Petn region of Guatemala. Human Ecology 22: 317 332. Sader, S. A., D. J. Hayes, J. A. Hepinstall, M. Coan, and C. Soza. 2001. Forest change monitoring of a remote biosphere reserve. International Journal of Remote Sensing 22:1937 1950. Salafsky N., H. Cauley, G. Balachander, B. Cordes, J. Parks, C. Marg olvis, S. Bhatt, C. Encarnacion, D. Russell, and R. Margolis. 2001. A systematic test of an enterprise strategy for community based biodiversity conservation. Conservation Biology 15:1585 1595. Sanchez Azofeifa, G. A., R. C. Harriss, and D. L Skole. 2001. Deforestation in Costa Rica: a quantitative analysis using remote sensing imagery. Biotropica 33:378 384. Saunders, D. A., R. J. Hobbs, and C. R. Margules. 1991. Biological consequences of ecosystem fragmentation: a review. Conservation Biology 5:18 32. Sc helhas, J. and R. Greenberg, editors. 1996. Forest patches in tropical landscapes. Washington D.C.:Island Press, 426 p. In Estrada et al. 2002. Schmink, M. 2003. Communities, Forests, Markets, and Conservation. In D. Zarin, F. J. Putz, M. Schmink, and J. Alavalapati (eds). Working Forests in the Tropics: Conservation Through Sustainable Management? New York: Columbia University Press Schumaker, N. H. 1996. Using landscape indices to predict habitat connectivity. Ecology 77(4): 1210 1225. Schwartzman, S., D. Nepstad, and A. Moreira. 2000. Arguing tropical forest conservation: people versus parks. Conservation Biology 14(5): 1370 1374.

PAGE 148

148 Schweik, C. and C. Thomas. 2002. Using Remote Sensing for Evaluating Environmental Institutions: A Habitat Conservation P lanning Example. Social Science Quarterly 83(1):244 62. Serneels, S. and E. F. Lambin. 2001. Proximate causes of land use change in Narok District, Kenya: a spatial statistical model. Agriculture, Ecosystems and Environment 85:65 81. Shafer, C. L. 1995. V alues and shortcomings of small reserves. BioScience 42(2):80 88. Sheldon, P. J. and T. Var. 1984. Resident attitudes to tourism in North Wales. Tourism Management 5(1):224 233. Silver, S. C., L. E. T. Ostro, C.P.Yeager, and R. Horwich. 1998. The feeding ecology of the black howler monkey ( Alouatta pigra ) in northern Belize. American Journal of Primatology 45: 263 279. Skole, D. and C. Tucker. 1993. Tropical deforestation and habitat fragmentation in the Amazon: Satellite data from 1978 to 1988. Science 26 0 :1905 1910. Skole, D. 1995. Land Use and Land Cover Change: An analysis. IGBP: 4 7. Smith, J. D. 1970. The systematic status of the black howler monkey, Alouatta pigra Lawrence. Journal of Mammalogy 51:358 369. Southgate, D. 1990. The causes of land degr adations along spontaneously expanding agricultural frontier in the third world. Land Economics 66:93 101. Southworth, J., H. Nagendra, and C. M. Tucker. 2002. Fragmentation of a landscape: incorporating landscape metrics into satellite analyses of land c over change. Landscape Research 27: 253 269. Southworth, J., H. Nagendra, L. A. Carlson, and C. Tucker. 2004. Assessing the impact of Celaque National Park on forest fragmentation in western Honduras. Applied Geography 24: 303 322. Stein, T. V., D. H. And erson, and D. Thompson. 1999. Identifying and managing for community benefits in Minnesota State Parks. Journal of Park and Recreation Administration 17(4):1 19. Stem, C. J., J. P. Lassoie, D. R. Lee, D. D. Deshler, and J. W. Schelhas. 2003. Community pa rticipation in ecotourism benefits: the link to conservation practices and perspectives Society and Natural Resources 16(3):387 413. Stokols, D. and S. A. Shumaker. 1981. People in places: a transactional view of settings. In Cognition, social behavior, and the environment J. H. Harvey (ed), Lawrence Erlbaum Associates: Hillsdale, NJ.

PAGE 149

149 Stuart, M., V. Pendergast, S. Rumfelt, S. Pierberg, L. Greenspan, K. Glander, and M. Clarke. 1998. Parasites of Wild Howlers (Alouatta spp.) International Journal of Prim atology 19: 493 512. Sussman, R. W., M. G. Green, and L. K. Sussman. 1994. Satellite imagery, human ecology, anthropology and deforestation in Madagascar. Human Ecology 22(3): 333 354. Tai, H. 2007. Development Through Conservation: An Institutional Analy sis of Indigenous Community Based Conservation in Taiwan. World Development 35(7):1186 1203. Taylor, G. 1995. The Community Approach: does it really work? Tourism Management 16(7): 487 9. Taylor, J. E. and T. J. Wyatt. 1996. The shadow value of migrant rem ittances, income and inequality in a household farm economy. The Journal of Development Studies 32:899 912. Terborgh, J. 1986. Keystone plant resources in the tropical rain forest, In: M. Soul (ed.). Conservation Biology. Sinauer Associates, Sunderland, p p. 330 344. Terborgh, J. 2000.The Fate of Tropical Forests: A Matter of Stewardship. Conservation Biology 14(5):1358 1361. Thomas, J. W., E. D. Forsman, J. B. Lint, E. C. Meslow, B. R. Noon, and J. Verner. 1990. A conservation strategy for the Northern Spo tted Owl: report to the interagency scientific committee to address the conservation of the Northern Spotted Owl. In Schumaker, 1996. Thomlinson, J. R., P. V. Bolstad, and W. B. Cohen. 1999. Coordinating methodologies for scaling landcover classifications from site specific to global: steps toward validating global map products. Remote Sensing of Environment 70:16 28. Tisdell, C. A. 1995. Issues in biodiversity conservation including the role of local communities. Environmental Conservation 22(3):216 222. Trani, M. K. and R. H. Giles, Jr. 1999. An analysis of deforestation: metrics used to describe pattern change. Forest Ecology Management 114:459 470. Tuan, Y. F. 1980. Rootedness verses sense of place. Landscape Urban Planning 24(1):3 8. Turner, B. L. II, D. Skole, S. Sanderson, G. Fischer, L. Fresco, and R. Leemans. 1995. Land Use and Land Cover Change Science / Research Plan: International Geosphere Biosphere Programme. Turner, M. G., R. H. Gardner, R. Landscape Ecology in Theory and Pr actice Springer Verlag, New York, USA, 401 pp. In Abdullah, S.A. and N. Nakagoshi 2007. Um, S. and J. L. Crompton. 1987. Measuring resident's attachment levels in a host community. Journal of Travel Research 26:27 29.

PAGE 150

150 Vanclay, J. K. 1995. Modeling Land Us e Patterns at the Forest Edge: Feasibility of a Static Spatial Model. In Ecological Economics Conference, pp. 78 84. Coffs Harbour, NSW, 1995, Centre for Agricul tural and Resource Economics, University of New England, Armidalen, NSW, Australia. In Merten s and Lambin 2000. Vaske, J. J. and K. Korbin. 2001. Place attachment and environmentally responsible behavior. Journal of Environmental Education 32(4): 116 21. Vogelmann, J. E. and B. N. Rock. 1988. Assessing forest damage in high elevation coniferous fo rests in Vermont and New Hampshire using Thematic Mapper data. Remote Sensing of Environment 24: 227 246. Wall, G. 1997. Is ecotourism sustainable? Environmental Management 21:484 491. Walsh, S. J., R. E. Bilsborrow, S. J. McGregor, B. G. Frizzelle, J. S. Messina, W. K. T. Pan, K. A. Crews remote sensing time series, and spatial analyses: Approaches for linking people and People and the Environment: Approaches for lin king household and community surveys to remote sensing and GIS eds J. Fox et al., 91 130. Boston: Kluwer Academic Publishers. Wang, T. H. and R. D. Katzev. 1990. Group commitment and resource conservation: Two field experiments on promoting recycling. Jou rnal of Applied Social Psychology 20(4) Part 1: 265 275. Waser, P. M., S. R. Creel, and J. R. Lucas. 1994. Death and disappearance estimating mortality risks associated with philopatry and dispersal. Behavioural Ecology 5:135 141. Weaver, J. L., P. C. Paq uet, and L. F. Ruggiero. 1996. Resilience and conservation of large carnivores in the Rocky Mountains. Conservation Biology 10(4):964 976. Weiss, J. L., D. S. Gutzler, J. E. Allred Coonrod, and C. N. Dahm. 2004. Long term vegetation monitoring with NDVI i n a diverse semi arid setting, central New Mexico, USA. Journal of Arid Environments 58(2): 249 272 Werner, C. M., J. Turner, K. Shipman, and F. S. Twitchell. 1995. Commitment, behavior, and attitude change: An analysis of voluntary recycling. Special Issue: Green psychology. Journal of Environmental Psychology 15(3):197 208. West, P., J. Igoe, and D. Brockington. 2006. Parks and People: The Social Impact of Protected Areas Annual Review of anthropology 35:251 77. White, L., B. C urbow, M. Costanzo, and T. Pettigrew. 1983. Social psychological approaches to promoting lifestyle and device oriented conservation behaviors. In Pardini and Katzev 1983 1984. Wickham, J. conomic indicator. Landscape Ecology 15:171 179.

PAGE 151

151 Wilcox, B. A. 1980. Insular ecology and conservation. In Soul, M.E. and B. Wilcox (eds.). Conservation Biology: An Evolutionary Ecological Approach. Sunderland, MA: Sinauer Assoc. pp. 95 118. Williams, D. R., S. B. Anderson, C. D. McDonald, M. E. Patterson. 1995. Measuring place attachment: More preliminary results. In Davenport and Anderson 2005. Williams, D. R., M. E. Patterson, and J. W. Roggenbuck, and A. E. Watson. 1992. Beyond the Commodity Metaphor: Examining Emotional and Symbolic Attachment to Place. Leisure Sciences 14:29 46. Williams, D. R. and J. J. Vaske. 2003. The Measurement of Place Attachment: Validity and Generalizability of a Psychometric Approach. Forest Science 49(6):830 840. Wood, C. H. and R. Walker. 1999. Tenure Security, Investment Decisions and Resource Use Among Small Farmers in the Brazilian Amazon. Paper in S67: Population and the Environment, Local. http://www.iussp.org/Brazil2001/s60/S67_04_Wood.pdf. World Conservation Union (I UCN). 2004. The Durban Action Plan ( revised version ). Presented at IUCN 5thWorld Parks Congress, Durban S. Afr. In Naughton Treves et al. 2005. World Resources Institute (2005) World Resources 2005 (World Resources Institute in collaboration with the Unite d Nations Development Programme, United Nations Environment Programme, and the World Bank, Washington, DC). In Berkes 2007. Wright, P. 1993. Sustainable tourism: Balancing economic, environmental, and social goals within an ethical framework. The journal o f tourism studies 4:54 65. Wunder, S. 2000. Ecotourism and economic incentives an empirical approach. Ecological Economics 32(3):465 479. Zube, E. H. and M. L. Busch. 1990. Park people relationships: An international review. Landscape and Urban Planning 19:117 131.

PAGE 152

BIOGRAPHICAL SKETCH My undergraduate degree in e nvironmental s cience and past field and work experiences have shaped my professional interests towards community based, natural resource management issues. In the past I have be involved with animal ecology research on the Guanaco ( Lama guanicoe) in Patagonia, southern Chile; grassroots environmental and community organizing in Minnesota; and research developing model progressive, state, environmental legislation. My love of travel, of langua ges, and of the environment has also guided my career interests. After receiving a B.S. in e nvironmental s ciences from the University of Massachusetts, I spent the next 6 months living and working on an Israeli kibbutz. Returning to the U.S., I worked wi th US Public Interest Research Group (PIRG), a non profit, non partisan environment al and consumer rights advocate organization and co directed a campaign office in Minneapolis, Minnesota. There I really learned the power of community organizing, working with the media, and building coalitions. After a year with the PIRGs I had the opportunity to work on an animal ecology research project on the Guanaco ( Lama guanicoe) in Parque Nacional Torres del Paine in Patagonia, Southern Chile in conjunction with Io wa State University. The next year I returned to Minnesota and served as an Americorps / Vista right organization organizing in manufactured (mobile) home park c ommunities around Minnesota. These experiences made me realize that my passion was working with communities on environmental conservation issues. This brought me to pursue an M.S. degree in n atural r esource m anagement / e nvironmental education and i nter pretation from the University of Wisconsin Stevens Point where I worked with a rural Mayan ejido (community) in southeastern Mexico in the development of an ecotourism management plan. This plan was

PAGE 153

requested as the initial organizational step to develop ing and implementing community based ecotourism within this ejido, a document for potential funders, and a framework for other communities within the Calakmul Model Forest area interested in ecotourism development. This plan was later used by the communit y to secure funding from the Rigoberta Menchu Organization. My M.S. research and exploratory travel within the Maya Forest region spurred my interests in more closely examining the popularity of community conservation initiatives combining economic develop ment as a way to protect natural and cultural resources while also This led to my doctoral research within the Community Baboon Sanctua ry, Belize where I examined conservation from various perspectives Aside from my pr ofessional interests, in my spare time I enjoy gardening, playing music (guitar and banjo), canoeing, and travelling