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Species Richness and Habitat Preference of Large Vertebrates in the Central Suriname Nature Reserve

Permanent Link: http://ufdc.ufl.edu/UFE0022158/00001

Material Information

Title: Species Richness and Habitat Preference of Large Vertebrates in the Central Suriname Nature Reserve
Physical Description: 1 online resource (54 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: habitat, large, species, suriname
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Two important concepts for understanding community diversity are species richness and habitat preference. These concepts are also of great utility in assessing the effects of human disturbance on biodiversity, management and for making environmental policy decisions. The Central Suriname Nature Reserve, a world heritage biodiversity site, is a prime location for collecting baseline data on large vertebrates. The reserve has had no significant hunting, mining or timber harvest in over a century and scant data have been collected since the 1970s. I provide the first estimates of predictors of species richness and habitat preference available for large vertebrates. These evaluations are based on five years of continuous study by the Monkey-field crew from 1,666 km of a line-transect census, 70.5 km of a phenological survey, and 747 walks/days of opportunistic sightings. Numbers of fruiting and flowering trees, rainfall, temperature, and leaf cover were used as predictors of species richness. Habitat preference is based on observed and expected encounters of species in the three habitat types (plateau, liana, and swamp). The analysis shows that the strongest predictor of species richness is plant productivity followed by temperature and rainfall. Our data suggest that habitat preference of large vertebrates is influenced by predator avoidance, interspecies interactions, both positive and negative, and food availability. The particulars of the data set are site specific, but likely critical baseline data for other sites in Suriname and in the Guiana Plateau geographic region. The general patterns and methodologies presented here can be used as models for other research.
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.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Boinski, Sue.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022158:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022158/00001

Material Information

Title: Species Richness and Habitat Preference of Large Vertebrates in the Central Suriname Nature Reserve
Physical Description: 1 online resource (54 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: habitat, large, species, suriname
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Two important concepts for understanding community diversity are species richness and habitat preference. These concepts are also of great utility in assessing the effects of human disturbance on biodiversity, management and for making environmental policy decisions. The Central Suriname Nature Reserve, a world heritage biodiversity site, is a prime location for collecting baseline data on large vertebrates. The reserve has had no significant hunting, mining or timber harvest in over a century and scant data have been collected since the 1970s. I provide the first estimates of predictors of species richness and habitat preference available for large vertebrates. These evaluations are based on five years of continuous study by the Monkey-field crew from 1,666 km of a line-transect census, 70.5 km of a phenological survey, and 747 walks/days of opportunistic sightings. Numbers of fruiting and flowering trees, rainfall, temperature, and leaf cover were used as predictors of species richness. Habitat preference is based on observed and expected encounters of species in the three habitat types (plateau, liana, and swamp). The analysis shows that the strongest predictor of species richness is plant productivity followed by temperature and rainfall. Our data suggest that habitat preference of large vertebrates is influenced by predator avoidance, interspecies interactions, both positive and negative, and food availability. The particulars of the data set are site specific, but likely critical baseline data for other sites in Suriname and in the Guiana Plateau geographic region. The general patterns and methodologies presented here can be used as models for other research.
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.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Boinski, Sue.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022158:00001


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PAGE 1

SPECIES RICHNESS AND HABITAT PREFEREN CE OF LARGE VERTEBRATES IN THE CENTRAL SURINAME NATURE RESERVE By CARRIE LYNNE VATH A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2008 1

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2008 Carrie Lynne Vath 2

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To my parents, family and friends 3

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ACKNOWLEDGMENTS This thesis would not be possible without Dr. Sue Boinskis unwavering support. I would also like to thank my supervisory committee, Dr s. Sue Boinski, Mary Christman and Madan Oli, for assisting me throughout the process. I must also thank my fellow lab mates who provided crucial support. I would like to thank Dr. Cooke and the Teaching Center for their financial and emotional support. Finally, thanks go out to my Safari West family, Peter and Nancy Lang who provided me with invaluable learning opportuniti es, my family and friends for believing in me and helping me towards my goals. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................8 ABSTRACT ...................................................................................................................... ...............9 CHAPTER 1 INTRODUCTION ............................................................................................................... ..11 2 MATERIALS AND METHODS ...........................................................................................15 Site Description ......................................................................................................................15 Data Collection .......................................................................................................................17 Analyses ...................................................................................................................... ............20 3 RESULTS ..................................................................................................................... ..........22 Species Richness .....................................................................................................................22 Plant Phenology ......................................................................................................................22 Predictors of Species Richness ...............................................................................................24 Line Transect .................................................................................................................24 Temperature and rainfall ..........................................................................................24 Leaf cover .................................................................................................................25 Fruiting and flowering ..............................................................................................25 Opportunistic Sightings ...................................................................................................25 Temperature and rainfall ..........................................................................................25 Leaf cover ................................................................................................................26 Fruiting and flowering ..............................................................................................26 Pooled Data .....................................................................................................................26 Temperature and rainfall ..........................................................................................26 Leaf cover .................................................................................................................26 Fruiting and flowering ..............................................................................................27 Habitat Preference ............................................................................................................ ......27 Detectibility ............................................................................................................................28 4 DISCUSSION ................................................................................................................. .......34 Assessing Consistency of Survey Protocols with the Assumptions of Line-transect Methods ...............................................................................................................................35 Species Richness .....................................................................................................................36 Predictors of Species Richness ...............................................................................................37 5

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Habitat Preference ............................................................................................................ ......40 Detectability ................................................................................................................. ...........42 Conclusions .............................................................................................................................45 APPENDIX ...................................................................................................................... ..............46 LIST OF REFERENCES ...............................................................................................................49 BIOGRAPHICAL SKETCH .........................................................................................................54 6

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LIST OF TABLES Table page 1-1. Factors hypothesized to infl uence species richness, inte rpreted from Currie (1999) .............12 2-1. Characteristics of habita t types for line transect censu s in Raleighvallen, Central Suriname Nature Reserve, Suriname .................................................................................20 2-2. Characteristics of habita t used in opportunistic sighti ngs census in Raleighvallen, Central Suriname Nature Reserve, Suriname ....................................................................20 3-1. Rare species seen by sampling method in Raleighvallen, during 2000-2005 ........................24 3-2. Predictors of species richness based on p-values from line-transect data ..............................25 3-3. Predictors of species richness based on p-values from opportunist ic sightings data .............26 3-4. Predictors of species richness ba sed on p-values from pooled data .......................................27 3-5. Observed and expected encounters in habitat types, 2, and adjusted residuals for primate species (indicated by initials of Latin name) using both sampling methods ........29 3-6. Observed and expected encounters in habitat types, 2, and adjusted residuals for terrestrial mammal species (ind icated by initials of Latin name) using both sampling .....30 3-7. Observed and expected encounters in habitat types, 2, and adjusted residuals for birds and arboreal mammal species (indicated by initials of Latin name) using both ...............31 3-8 Number of species encounter s in the bamboo habitat ............................................................32 3-9. Detectability of species from line-transect data .....................................................................33 4-1. Overall predictors of species richness using line-transec t, opportunistic sightings, and pooled data .........................................................................................................................34 4-2. Adjusted residuals results on which species appeared more or less than expected in habitat types by sampling method ......................................................................................34 7

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LIST OF FIGURES Figure page 2-1. Map of Suriname, highlighting Ce ntral Suriname Nature Reserve ........................................16 2-2. Average rainfall and temperatur e in Raleighvallen during 2000-2005. .................................16 2-3. Map (a) line-transect labeled as Voltz berg trail (7km) and map (b) opportunistic sighting area (3km2) with first 3km of line-transect highlighted in Raleighvallen. ...........18 3-1. Species accumulation curves using two sampling methods in Raleighvallen, 2000-2005. ...23 3-2. Average number of trees fruiting and flowering in Raleighvallen during 2000-2005. ..........23 8

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Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science SPECIES RICHNESS AND HABITAT PREFEREN CE OF LARGE VERTEBRATES IN THE CENTRAL SURINAME NATURE RESERVE By Carrie Lynne Vath May 2008 Chair: Sue Boinski Major: Interdisciplinary Ecology Two important concepts for understanding comm unity diversity are species richness and habitat preference. These concepts are also of great utility in assessing the effects of human disturbance on biodiversity, mana gement and for making environmental policy decisions. The Central Suriname Nature Reserve, a world heri tage biodiversity site, is a prime location for collecting baseline data on large vertebrates. The reserve has had no significant hunting, mining or timber harvest in over a century and scant data have been collected since the 1970s. I provide the first estimates of predictors of species ri chness and habitat preference available for large vertebrates. These evaluations are based on five years of continuous study by the Monkey-field crew from 1,666 km of a line-transect census, 70.5 km of a phenological survey, and 747 walks/days of opportunistic sightings. Number s of fruiting and flowering trees, rainfall, temperature, and leaf cover were used as predic tors of species richness Habitat preference is based on observed and expected en counters of species in the three habitat types (plateau, liana, and swamp). The analysis shows that the strongest predictor of species richness is plant productivity followed by temperature and rainfall. Our data suggest that habitat preference of large vertebrates is influenced by pr edator avoidance, interspecies interactions, both positive and 9

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10 negative, and food availability. The particulars of the data set are si te specific, but likely critical baseline data for other sites in Suriname a nd in the Guiana Plateau geographic region. The general patterns and methodologies presented here can be used as models for other research.

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CHAPTER 1 INTRODUCTION Two important concepts for understanding comm unity diversity are species richness and habitat preference. These concepts are also of great utility in assessing the effects of human disturbance on biodiversity, mana gement and for making environm ental policy decisions. Most conservation planning involving th e selection of reserves is based on one or a few species (Simberloff 1988); often the most charismatic and/or those species considered umbrella, flagship, or keystone are used(C aro & ODoherty 1999). Reserve ne tworks selected in this way may be ineffective for the conservation of othe r, non-target species (G atson & Rodrigues 2001). Species richness or habitat preference become obvious tools for overcoming this problem when considering conservation management plans, assessing the effects of human disturbance on biodiversity and for making environmental policy decisions. In this study we define species richness as the number of distinct species present in our study area. Many hypotheses have been proposed for why certain areas have more species than others (Table 1-1 provided by Currie 1991). The energy hypothesis as proposed by Hutchinson (1959) states that the abundance of terrestrial organisms, as a whole, must be limited by their supply of energy. The energy available to animals consists of the production of food items that can be included in the diet of the group in question (Wright 1983). Hawkins et al. (2003) divides the energy hypothesis into the produc tivity and ambient-energy hypothesis. The productivity hypothesis states that the level of diverse resource biomass in an ecosystem limits animal species richness. Productivity is defined as the net primary productivity of plants or the secondary productivity of consumers (Connell & Orias 1964). Ambient-energy hypothesis proposes that the animal species richness of a region is directly controlled by the total average energy available. We are going to test these hypothesis respectiv ely using measures of 11

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energy closely related to the level of primary pr oduction in a region, annual rainfall, leaf cover, average temperature and number of trees fruiting and flowering. Table 1-1. Factors hypothesized to influence species richness, interpre ted from Currie (1999) Factor Rationale 1. Climate Mild conditions allow more species 2. Climatic variability Constancy permits specialization 3. Habitat heterogeneity Biologically or physically complex habitats provide more niches 4. History Prolonged time permits more complete colonization and evolution of new species 5. Energy Partitioning of energy among species limits richness 6. Competition a. Competition favors reduced niche breadth b. Competitive exclusion eliminates species 7. Predation Predation mainta ins unexploited niche breadth 8. Disturbance Moderate disturbance hinders competitive exclusion Line transects have been ex tensively used throughout fore sted tropics as a means of calculating relative abundance, density estimates, and species richness of a wide variety of vertebrates (Bennett et al. 2001, Thomas 1991, Rahbek & Graves 2001). A sampling effort which yields at least 40 and preferably 60-80 en counters for a given target species has been recommended (Burnham et al. 1980). However, useful comparisons between areas and/or habitats have been possible with fewer encounte rs. Our study advocates the combining of linetransect and opportunistic sightings methods because it increases th e rate and size of an area that can be effectively surveyed. When describing an area using either line-transect or opportunistic sightings the detection probability of species must be taken into ac count. Detection probability is defined as the probability that a member of the species of interest is included in the count at the given time or location (MacKenzie & Kendall 2002). Failure to detect species when they are present at a site is not uncommon in field surveys (Gu & Swihart 2 004). The vast majority of wildlife-habitat 12

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models that use presence-absence as a response vari able have assumed that if a species occurs at a site, it will be detected. This assumption has the effect of equating detection probability to one. The Guiana Shield is a Precambrian eroded base, sweeping from the Orinoco Delta in Venezuela to the Amazon Delta, beyond Amapa, in Brazil (de Granville 1988). The vegetation of the Guiana Plateau is comprised primarily of variants of tropical fo rests (de Granville 1988) resulting in high levels of plan t endemism that characterize the forests of the Guiana Shield (Lehman 2000). Vertebrate frugivores are the dominant group of large animals in tropical forests (Haugaasen & Peres 2007). Information on the large vertebrates of Suriname is scant. Walsh and Gannon (1967) were some of the first to descri be the large vertebrates in Suriname. They described the mammals that were rescued and/or rec overed from a flooding of the large lowland area during the construction of the Af obaka Dam. Studies on deer (Branan et al. 1985) and primate (Norconk et al. 2003) species have also been collect ed in Suriname. The primates of Raleighvallen, the location of our study, have been the subject of only a few reports ( Mittermeier 1976, Mittermeier & van Roosma len 1976, Fleagle & Mittermeier 1980, Fleagle et al. 1981, van Roosmalen et al. 1988, and Baal et al. 1988), most of which were derived from a single survey (March 1976February 1977). The other large vertebrate s within Raleighvallen have been ignored. In 2000, The Central Suriname Nature Reserve (CSNR) incorporated smaller preserves to protect 1.6 million ha of tropical forest in west central Suriname and the upper watershed of the Coppaname River. Raleighvallen is approximately 78,000 ha and is located in the northern part of the reserve on the Coppename piedmont. Th e reserves flora and fauna are virtually undisturbed, and includes a full component of pred ators, including felids, raptors and snakes. No 13

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significant hunting, mining, or timber harvest has o ccurred in more than a century. Information on species richness in an undistur bed tropical forest can act as a useful model when trying to protect areas similar to Raleighvallen in the Gu ianan Shield. The data can also be used for comparisons with disturbed forests, mainly to see how disturbance changes species richness levels or habitat preferences. The principal aims of this study are to dete rmine species richness levels, what predicts species richness in Raleighvallen, and to quantify patterns of diffe rential habitat use among these species. The specific aspects of habitat use examin ed are forest type. Three distinct floristic associations are recognized: plat eau, liana, and swamp. Census data also provide the baseline for more detailed socioecological and behavioral studies (Butynski 1990, Struhsaker 1975) essential for effective long term management of the site. 14

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CHAPTER 2 MATERIALS AND METHODS Site Description Available data are from five years of con tinuous line-transect and opportunistic sightings sampling, collected at a well established study site in the Central Suriname Nature Reserve, Raleighvallen, Suriname. The site encompasse s ~ 3 km2 and is bounded on the northern and western aspects by the eastern bank of the Coppename River. Raleighvallen is part of the larger Central Suriname Nature Reserve (4 71 N, 56 21 W; 30 m altitude) consisting of 1.6 million ha of primary tropical forest (Figure 2-1). We have classified the fore st structure of our field site into four distinct habitats and ranked them by physical complexity (Boinski et al in prep): 1) Plateau forest: Not affected by seasonal flooding of the rivers, usually possible to distinguish three to four storie s (the highest being up to 60 m) lianas are not individually abundant and plateau forest has more fruit and flower producing tree species. 2) Liana forest: Does not usually exceed 20 m in height, richer in lianas than plateau forest and has fewer Boegroe maka palms, tall trees wi th a wide circumference do occur but are widely separated, space between trees is filled with dens e tangles of lianas and vines, and liana tangle itself rarely exceeds 10-15 m in height. 3. Swamp forest: Soil stays moist to wet thr oughout the year, lianas and epiphytes are not common, but stilt root trees ( Euterpe oleraceae ) are. 4) Bamboo patches: continuous, dens e, homogenous patches of bamboo ( Guadua latifolia ). Annual average rainfall in Suriname is 2200 mm, average temperature is 27C; with a short rainy season in December-January, long wet season in March-August, and a dry season in September-November (Baal et al. 1988). 15

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STINASU Figure 2-1. Map of Suriname, highlighting Central Suriname Nature Reserve Rainfall at the Monkey-Forest field cam p in Raleighvallen, between 2000 and 2005 averaged 1967mm, and the minor dry and wet seasons exhibit marked variation in cumulative rainfall, onset, end and duration. We see a shor t rainy season in December-January, a short dry season February-March, a long wet season April-July and a long dry season August-November. Minimum and maximum temperatures at the Monkey-Forest field camp are noted daily at 18:00 h local time and averaged 23.7-28.9, C (Figure 2-2). 0 2 4 6 8 10 12 14Jan Feb M a rc h April M a y J u ne J u ly Aug Sep t Oct Nov D e cMonthAverage Rainfall (mL)24.5 25 25.5 26 26.5 27 27.5 28Average Temperature (C) Rainfall Temperature Figure 2-2. Average rainfall and temper ature in Raleighva llen during 2000-2005. 16

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Data Collection We collected census data using a double-observer dependent line-transect method. The double observer method is when two observers walk a line-transect in a single file keeping no more than 3m between them. The second observer notes any observations th at the first observer missed. The roles are then reversed for the return trip on the line-transect. An existing pathway that runs North to South for 7 km (approximately 1 m wide) makes up our line-transect (Figure 2-3a). This path is maintained and guarde d by the Suriname Nature Conservation agency (STIANSU). The trail is also used by tourists to reach the Voltzberg-Inselberg, a 240m dome shaped granite inselberg. Kauffman (2008) f ound that 1,300 tourists used the trail during 2006, which she believes is much higher than previous years. Because the trail is maintained the usual 1 m visibility on each side of the transect was ex panded to 2 m. Observers walked the census line beginning at 0600-0730 h at an average speed of about 1 km h-1, recording all sightings of large vertebrates (>250g). The number of censuses con ducted per month ranged from 2 to 7, with an average of 3.9 per month. The line-transect was not done during rainy weather because this would affect the intrinsic detectab ility of different species. Cens us data collected during October 2000-September 2005 resulted in 238 walks (1,6 66km) with 1,182 animal sightings along the single 7km transect. For each animal sighting we recorded time, species, estimated number of individuals, how observed or detected (audio or visual cues), pe rpendicular distance, grid location along the linetransect, predator avoidance behavior, habi tat type, duration of observation and/or why observation ended. Observers were trained by experi enced field assistants. Transect markers are 50m-150m apart rather than being equidistant. Examples of transect markers are: streams, boulders, unique trees, and other distinctive points in the landscape. For th is study only the first 17

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three habitat types (plateau, liana, and swamp) were used (Table 2-1.). Bamboo habitat was not used in analysis due to insu fficient animal encounters. (A) (B) Figure 2-3. Map (a) line-transect labeled as Voltzberg trail (7km) and map (b) opportunistic sighting area (3km2) with first 3km of line-transect highlighted in Raleighvallen. The opportunistic sightings occurred throughout the 3km2 site (Figure 2-3b). Opportunistic animal sightings occurred when field assistan ts collected phenology surv eys, cleared trails, 18

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searched for Cebus apella troops, visited the harpy eagle ne st site, hiked around on their days off, and whenever they were in the forest and not following a monkey troop. Sightings were recorded from November 2000-September 2005. A to tal of 747 walks/days had recordings that resulted in 1,640 large vertebrate sightings. When a sighting occurr ed, species, number of individuals seen, habitat type, a nd location were record ed. Table 2-2 shows the available habitat that was surveyed and how much of the habitat had sightings. Phenological data was obtained at monthly inte rvals during the last week of every month; from October 2000 through September 2005 resulting in 47 survey walks (70.5km). The survey was conducted on 1.5 km network of trails esta blished to haphazardly cross through the four habitat zones within the m onkey-forest field site (3km2).A set of trees with a diameter at breast height (DBH) of greater than 20 cm and within 1 m of each side of the trail were aluminumtagged, mapped and identified beginning in May 1998 by local tree spotters and botanists. Due to tree falls, tree deaths and the a ddition of new trees the number of trees in the survey ranged from 135-229 with an average of 175 trees. Liana and plat eau forest combined represented more than 90% of the phenological survey area. Presence and absence of ground fruit, mature and immature, overall fruit cover, mature and immature, flowers, flower buds, leaf cover, and presence of rotten or processed fruits were recorded using a scale of 1-4, 4 being 75-100%, 1 be ing 025%,. Trees were scored as flowering or fruiting if flowers/fruits were vi sible in at least 25% of the crown. 19

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Table 2-1. Characteristics of ha bitat types for line transect ce nsus in Raleighvallen, Central Suriname Nature Reserve, Suriname Habitat Total quadrants on transect Percent of total area Total sightings Number of species encountered Plateau 41 23 454 19 Liana 116 66 696 19 Swamp 19 11 33 12 Table 2-2. Characteristics of ha bitat used in opportunistic sightings census in Raleighvallen, Central Suriname Nature Reserve, Suriname Habitat Total quadrants in study site Quadrants with sightings Percent of total area Total sightings Number of species encountered Plateau 401 199 49.6 1007 32 Liana 174 100 57.5 482 28 Swamp 20 14 70 157 22 Bamboo 40 21 52.5 86 18 Analyses Total species richness in the reserve was dete rmined as number of distinct species seen over time using both line-transect and opportunis tic sightings. Species were combined into 4 distinct groups: Primates (include s all primate species), Rodents ( Myorocta exilis and Dasyprocta punctata ), Birds ( Psophia crepitans, Crax alector and Harpia harpyja ), and Other Mammals (includes carnivores, ungulates, and sciuridae). Other bird species (guans and tinamous) were encountered but could not be reliab ly identified and were removed from the data set. Species were also divided into arboreal and terrestrial groups Regression models were used to test which variables were the best predicto r of species richness. Th e explanatory variables used are total trees fruiting (tre es having both mature and immature fruit present) and flowering (mature flowers and flower buds), temperature, ra infall, and leaf cover. Chi squared test the compared the distribution of sp ecies among vertebrate groups (p rimates, terrestrial mammals, and arboreal mammals and birds) and different habitat types assumi ng no selection, i.e., proportional to the availability of habitat types within the study site and along the transect route. 20

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21 The adjusted residual equation was used to test if there was significant preference towards or against habitat types: (Oij Eij) /[Eij) (1-Oi.)(1-O.j)] where Xxx means X subscripted with xx and Oij is the observed value in the ith row, jth column Eij is the expected value of the ce ll in the ith row, jth column Oi. is the observed row total for the ith row O.j is the observed column total for the jth column Species detectability was calculated using DI STANCE program version 5.0 (Thomas et al. 2006). Data input into the program consisted of es timates of cluster size, perpendicular distance, line-transect length, observer, and habitat type. Th e program is designed to determine the best fit probability of detection function based on the es timated perpendicular distances by generating a key function and a series expansion. The best-fit model is based on the smallest Akaikes Information Criterion (AIC) value (Buckland et al. 1993).

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CHAPTER 3 RESULTS Species Richness A total of 1,182 animal sightings were recorded from line-trans ect data collected from October 2000 through September 2005. Twen ty-one species were seen with one additional new species being encountered ever y year after 2002. The use of opportunistic sightings resulted in 1,640 animal sightings wi th a total of thirty-four species seen. An accumulation curve of richness is shown in Figure 3-1. The five most commonly sighted speci es using the line transect method are Cebus apella, Dasyprocta punctata, Atel es paniscus, Saguinas midas, and Saimiri sciureus. These species accounted for 854 (72%) of th e 1,182 sightings. The opportunistic sighting method has Dasyprocta puncata, Alouatta seniculus, Psophia crepitans, Myorocta exilis and Cebus apella as the most sighted species accounting for 917 (55%) of the 1,640 sightings. The seven most commonly sighted species in order of frequency using pooled data are Dasyprocta punctata Cebus apella Alouatta seniculus Saguinas midas, Ateles paniscus Crax alector, and Psophia crepitans. These species accounted for 1,989 (70%) of the 2,829 pooled sightings. Many rare sp ecies were encountered but their low encounter rates prohibited any analysis (Table 3-1). Plant Phenology The 135-229 phenology trees monitored included 41 families and 72 genera. The most abundant families are Areaceae, Mi mosaceae, Cecropiaceae, Strelitziaceae, Sapotaceae, Burseraceae, Apocynaceae, Lecythidaceae, Meli aceae, and Tiliaceae. The emergence of fruits commenced during the start of the long dry season (AugustNovember), with fruiting peaking in Octobe r. Flowers and flower buds began to appear 22

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in December at the start of th e short wet season. Flowers peaked in March, the end of the short wet season (Figure 3-2). 0 5 10 15 20 25 30 35 40 Species richnessNumber of sampling occasions Opportunistic Sightings Line-transect Figure 3-1. Species accumulation curves usi ng two sampling methods in Raleighvallen, 2000-2005. 0 5 10 15 20 25 JanFebMarAprMayJunJulAugSepOctNovDecAverage number of trees fruiting or floweringMonth Fruiting Flowering Figure 3-2. Average number of trees fruiting and flowering in Ralei ghvallen during 2000-2005. 23

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Table 3-1. Rare species seen by sampli ng method in Raleighvallen, during 2000-2005 Species Line-transect Opportunistic sightings Cyclopes didactylus 0 1 Speothos venaticus 0 2 Felis wiedii 0 2 Myrmecophaga tridactyla 0 3 Potos flavus 0 3 Hydrochaeris hydrochaeris 0 4 Didelphi marsupialis 0 4 Nausa nausa 0 4 Felis yagouroundi 0 4 Felis pardalis 0 7 Dasypus novemcinctus 0 19 Bradypus tridactylus 1 3 Panthera onca 1 5 Cebus olivaceus 1 15 Tapirus terrestris 3 31 Eira barbara 5 38 Predictors of Species Richness Data were analyzed by sampling method and by pooling both data sets. The count per unit effort (CPUE) is species seen divi ded by total walks. This value was then modeled against: average rainfall and te mperature from 2000-2005, average leaf cover (based on the 1-4 scale, 4 =75-100% cover, 1 =0-25% cover) from the phenological surveys, and total trees fruiting and floweri ng divided by total phenological survey walks. Line Transect (Table 3-2) Temperature and rainfall Temperature (p=0.0545) and rainfall (p= 0.4215) have no signif icant predicative value on species richness. 24

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Leaf cover Leaf cover (p= 0.9569) had no significance in predicative value w ith encounter of species guilds (primate, rodents, birds, or ot her mammal) or by forest level (arboreal or terrestrial) groups. Fruiting and flowering Fruiting (p=0.0333) had predictive power on species richness but when tested against species guild and forest level no si gnificance was detected. Flowering (p=0.1922) has no significant predictive pow er on species richness. Table 3-2. Predictors of speci es richness based on p-values from line-transect data Temperature Rainfall Leaf cover Fruiting Flowering All Species 0.0545 0.4215 0.9569 0.0333 0.1922 Guilds Primate 0.2287 0.6021 0.7037 0.1280 0.1528 Rodent 0.0970 0.0916 0.8636 0.1241 0.9779 Bird 0.1185 0.3365 0.7675 0.1116 0.2575 Other Mammals 0.9041 0.8179 0.4050 0.9610 0.7146 Forest Level Arboreal 0.1847 0.9445 0.8237 0.1323 0.1030 Terrestrial 0.1276 0.1276 0.9261 0.8690 0.7105 Opportunistic Sightings (Table 3-3) Temperature and rainfall Temperature (p=0.0123) has a predictive va lue on determining species richness. The other mammal (p= 0.0072) guild and terres trial (p= 0.0288) group are most affected by temperature. Rainfall (p=0.3317) fails to have any predictive value. 25

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Leaf cover Leaf cover (p=0.0271) is shown to be significantly pr edictive with the opportunistic sightings data. When species are divided into gu ilds and forest level groups no significance is found. Fruiting and flowering The opportunistic data shows fruiting (p=0.0004) has significance with the other mammal (p=0.0024) guild and arboreal (p=0.0459) and terrestrial (p=0.0041) groups. Flowering (p=<0.0001) shows significance with the primates (p= <0.0001) and bird (p=0.0314) guilds. Forest level analysis re veals flowering only ha s significance with arboreal (p= <0.0001) species. Table 3-3. Predictors of speci es richness based on p-values from opportunistic sightings data Temperature Rainfall Leaf cover Fruiting Flowering All Species 0.0123 0.3317 0.0271 0.0004 <0.0001 Guilds Primate 0.2443 0.7527 0.5010 0.1365 <0.0001 Rodent 0.3499 0.5335 0.6161 0.1935 0.2470 Bird 0.5424 0.6727 0.0936 0.4073 0.0314 Other mammals 0.0072 0.2970 0.2032 0.0024 0.7254 Forest Level Arboreal 0.1954 0.9076 0.1972 0.0459 <0.0001 Terrestrial 0.0288 0.1367 0.0724 0.0041 0.1779 Pooled Data (Table 3-4) Temperature and rainfall Temperature (p=0.0280) has predictive va lue on terrestrial species (p=0.0085). Rainfall (p=0.1624) has a pred icative value on terrestri al species (p=0.0334). Leaf cover Leaf cover (p=0.0929) is not significant with guilds or forest level groups. 26

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Fruiting and flowering Fruiting (p=<.0001) has a si gnificant predictive value on arboreal (p=0.0009) and terrestrial (p=0.0018) species. The primate (p=0.0001) and bird (p=0.0014) guilds are also influenced by fruiting. Flowering (p =0.0623) has predictive value on arboreal (p=0.0281) species and the primate (p =0.0070) and bird (p=0.0022) guilds. Table 3-4. Predictors of species richness based on p-values from pooled data Temperature Rainfall Leaf cover Fruiting Flowering All Species 0.028 0.1624 0.0929 <0.0001 0.0623 Guilds Primate 0.2832 0.2601 0.7001 0.0001 0.007 Rodent 0.0925 0.1964 0.1432 0.0815 0.5405 Bird 0.4801 0.7665 0.1195 0.0014 0.0022 Other Mammals 0.0598 0.2485 0.2595 0.2269 0.1463 Forest Level Arboreal 0.3922 0.7644 0.2563 0.0009 0.0281 Terrestrial 0.0085 0.0334 0.1334 0.0018 0.8117 Habitat Preference An association between habitat and species is seen with the line-transect data (DF=28, 2= 94.513, p= <0.0001) and the opport unistic sightings (DF=34, C= 103.743, p= <0.0001). Table 3-5, Table 36, and Table 3-7 shows all 2 and adjusted residuals ((Oij Eij) /[Eij) (1-Oi.)(1-O.j)]) va lues between species and habitat type. Alouatta seniculus, Ateles paniscus, and myorocta exilis are seen more than expected in plateau habitat while Cebus apella Crax alector, and Psophia crepitans are seen less than expected. Cebus apella and Crax alector are seen more than expected and Alouatta seniculus, Ateles paniscus, and myorocta exilis are seen less than expected in liana habitat. Alouatta seniculus is seen more than expected and cebus apella and myorocta 27

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28 exilis are seen less than expected in the sw amp habitat. The bamboo habitat had 86 sightings but due to low sample size no st atistical analysis was done (Table 3-8). Detectability Table 3-9 displays the results from the detectability analysis. Alouatta seniculus, Cebus apella, and Pithecia pithecia have the highest detection rates and Myorocta exilis, Psophia crepitans and Dasyprocta puncata have the lowest detection rates.

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Table 3-5. Observed and expected enc ounters in habitat types, 2, and adjusted residuals for primat e species (indicated by initials of Latin name) using both sampling methods from census data collect ed in Raleighvallen, Central Suriname Nature Reserve, Suriname Line Transect Opportunistic Sightings Habitat C.s.a C.a.b A.s.c S.s.d A.p.e S.m.f P.p.g C.s. C.a. A.s. A.p. S.m. P.p. Plateau 11 82 31 33 91 43 7 23 79 101 24 80 24 6 103 21 43 53 49 6 18 91 96 15 75 28 2.41 4.55 4.65 2.66 27.2 0.77 0 0.9 1.6 0.3 4.2 1.1 0.7 1.64 -2.6*2.3+-1.6 6.3+-0.9 0.43 1.2 -1.3 0.6 2.3+ -1 -1 Liana 6 179 24 79 46 80 10 6 65 32 2 25 18 10.5 158 33 67 81 75 10 9 44 46 7 17 13 1.98 2.55 2.71 2.12 15.3 0.29 0.03 1.1 9.8 4.5 4.2 3.7 1.3 -1.5 2.2+-1.7 1.6 -4.3*0.65 -0.2 -1 3.5+-2.2*-1.9*229 1.4 1 9 1 2 1 5 1 2 6 25 0 4 5 Swamp 0.49 7 1 3 3 3 0.49 3 16 15 2 5 4 0.51 0.34 0.2 0.4 2.05 0.62 0.51 0.3 5.1 6 2.5 0.5 0 1 1 -0.4 -0.6 -1.5 0.93 0.98 -1 -2.2*2.9+ -1.4 -0.4 0.5 Total 18 270 57 114 138 128 18 31 150 158 26 58 47 Note. + = species seen more than expected, *=species se en less than expected based on adjusted residuals. aChiropotes satanus bCebus apella cAlouatta seniculus dSaimiri sciureus eAteles paniscus fSaguinas midas gPithecia pithecia

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Table 3-6. Observed and expected enc ounters in habitat types, 2, and adjusted residuals for terre strial mammal species (indicated by initials of Latin name) using both sampling methods from censu s data collected in Raleighva llen, Central Suriname Nature Reserve, Suriname Line Transect Opportunistic Sightings Habitat M.e.a D.p.b T.t.c T.p.d M.a.e M.e. D.p. T.t. T.p. M.a. T.te.f 21 75 3 3 9 75 298 23 28 33 22 15 78 3 3 6 55 301 20 24 38 18 Plateau 2.06 0.14 0.06 0.06 1.32 7 0 0.26 0.4 0.7 0.52 15.4 -0.4 -0.2 -0.2 1.1 2.9 -0.8 0.68 0.8 -0.8 0.96 19 120 6 6 7 15 143 10 10 22 8 23 120 5 5 9 26 146 10 12 18 9 Liana 0.87 0 0.09 0.09 0.61 5.2 0.1 0 0.4 0.6 0.13 -1 0 0.36 0.36 -0.8 -2.230 -0.3 0 -0.5 1 -0.3 0 9 0 0 0 1 55 1 3 8 1 1 5.5 0.24 0.24 0.43 8 48 3 3 6 3 Swamp 1.09 2.06 0.24 0.24 0.43 7 0.9 1.61 0.2 0.6 1.35 -1 2 -0.45 -0.5 -0.6 -2.5 1.5 -1.1 0 0.9 -1.1 Total 40 204 9 9 16 90 496 34 41 63 31 Note. + = species seen more than expected, *=species se en less than expected based on adjusted residuals. aMyorocta exilis bDasyprocta punctata cTayassu tajacu dTayassu peccary eMasama americana fTapirus terrestris

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31Table 3-7. Observed and expected enc ounters in habitat types, 2, and adjusted residuals for bi rds and arboreal mammal species (indicated by initials of Latin name) using both sampling met hods from census data collected in Raleighvallen, Central Suriname Nature Reserve, Suriname Line Transect Opportunistic Sightings Habitat C.a.a P.c.b T.t.c C.a. H.h.d P.c. S.a.e T.t. E.b.f Plateau 20 16 2 45 27 54 31 15 23 30 21 3 46 23 54 36 24 22 3.75 1.58 0.4 0.1 0.65 0.009 0.82 4 0 -2* -1.8 -0.5 -0.2 0.85 0 -0.8 -1.8 0.2 Liana 59 40 5 20 10 26 23 18 9 47 33 4 22 11 26 17 12 10 3.02 1.24 0 0.3 0.12 0.009 1.6 2.9 0.3 1.9+ 0.66 0.5 -0.4 -1.9 0 1.5 1.7 -0.3 Swamp 1 1 1 12 1 10 6 8 5 2 1 0.2 7 3 8 5 3 3 0.65 0.2 2.8 2.7 1.97 0.17 0 4 0.5 -0.8 -0.59 1.9 2 -1.2 0.75 0.46 3 1.1 Total 80 57 8 77 38 90 60 41 37 Note. Note. + = species seen more than expected, *=speci es seen less than expected based on adjusted residuals. aCrax alector bPsophia crepitans cTamandua tetradactyla dHarpia harpyja eSciurus aestuans fEira barbara

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Table 3-8 Number of species encoun ters in the bamboo habitat Species Number of encounters Dasyprocta punctata 37 Crax alector 14 Cyclopes didactylus 4 Mazama americana 4 Sciurus aestuans 4 Tamandua tetradactyla 4 Psophia crepitans 3 Tayassu tajacu 3 Cebus apella 2 Dasypus novemcinctus 2 Nausa nausa 2 Eira barbara 1 Felis pardalis 1 Harpia harpyja 1 Myorocta exilis 1 Panthera onca 1 Saguinas midas 1 Saimiri sciureus 1 Total 86 32

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Table 3-9. Detectabil ity of species from line-transect data Species Number of observations Key function Adjustment AIC Detectability Myorocta exilis 38 HazardRate Cosine 148.26 94.5 Dasyprocta punctata 99 HazardRate Cosine 825.5 84.0 Tayassu tajacu 20 HazardRate Cosine 116.81 69.0 Tayssu peccary Psophia crepitans 58 HazardRate Cosine 252.26 86.7 Crax alector 77 HazardRate Cosine 322.66 79.3 Saguinas midas 123 Uniform Cosine 721.4 31.9 Saimiri sciureus 90 HazardRate Cosine 512.79 72.8 Cebus apella 192 HazardRate Cosine 1147.83 16.5 Pithecia pithecia 18 Uniform Cosine 106.54 24.2 Chiropotes satanus 11 Uniform Cosine 65.91 72.9 Alouatta seniculus 54 Uniform Cosine 370.81 13.2 Ateles paniscus 131 HalfNormal Cosine 872.17 39.2 33

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CHAPTER 4 DISCUSSION We were able to identify key va riables in large vertebrate sp ecies richness (Table 4-1) and determined that various species show hab itat preference (Table S4-2) in Raleighvallen, Suriname. Raleighvallen is so little disturbed and has high habitat heterogeneity that the baseline data collected with the combination of line-tran sect and opportunistic sightings methods provides taxon information of what should theore tically be seen th roughout Suriname. Table 4-1. Overall predictors of species richness using line-tr ansect, opportunistic sightings, and pooled data Variable Prediction Temperature Predicts terrestrial species & other mammals sightings Rainfall Weakly predicts terrestrial detectability Leaf cover Does not influence guild or forest level vertebrate sightings Fruiting Predicts arboreal, terrestrial, primate, bird and other mammal sightings Flowering Predicts arboreal, pr imate and bird encounters Table 4-2. Adjusted residuals re sults on which species appeared more or less than expected in habitat types by sampling method Line-Transect More than expected Less than expected Plateau Liana Swamp Plateau Liana Swamp A. seniculus C. apella C. apella A. paniscus A. paniscus C. alector C. alector M. exilis Opportunistic Sightings More than expected Less than expected Plateau Liana Swamp Plateau Liana Swamp A. paniscus C. apella A. seniculus A. seniculus C. apella M. exilis S. midas A. paniscus M. exilis M. exilis 34

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Assessing Consistency of Survey Protocols with the Assumptions of Line-transect Methods The basic assumptions underlying density a nd detection estimation from line-transect sampling are (following Peres 1999) : (1) all animals on the transect line must be detected; (2) animals are detected at their in itial location, prior to any moveme nt in response to the observer and the animal is not counted twice; (3) animals of target species move slowly relative to the speed of the observer; (4) distances from the tran sect are measured accura tely; (5) detections are independent event. Our line-transect is a pre-existing trail that is maintained by the local park agency STINASU. The trail is the only access to the Vo ltzberg-Inselberg which is a tourist attraction. Less than 200 tourists per month used the trail in 2006 and Kauffman (2008) determined that the presence of tourists does not ne gatively affect the presence of primates along the path. We therefore felt confident that th e tourist traffic would not influe nce our detectability of species sighting data. The trails maintenance and a visual field of 2m on each side of the line-transect paired with the negligible impact of tourist presence we feel that we did not introduce any violation of assumption (1). If animals respond to the presence of th e observer before being detected, sighting distances may be biased (assumption (2)). Because animals usually respond by fleeing, violation of assumption (2) usually causes sighting distances to be biased towards larger values. Our linetransect allowed for relatively quiet movement by observers; data was usually collected on the first animal detected and occurred before animal s gave alarm calls, indicat ing the detection of the observer. The presence of touris ts could increase species habituation, which in turn would decrease the flee response and increase the probabili ty that animals are only counted once and at their initial location. Kauffman ( 2008) reports that all primate speci es in Raleighvallen fled and alarm called less the more habituated the troop. 35

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Having the observers move slowly decreases th e chance of violating assumption (3). The double-observer dependent sampling method does viol ate assumption (5) in that detections are not independent events. The lack of data heap ing (the observed rounding of detection distances to set numbers, i.e. 5, 10, 15 etc.) seen in our da ta reflects that assumpti on (4) was not violated. To determine the detection probability of vari ous species from the line-transect data we used DISTANCE software. This software is used to estimate abundance and as a result it also computes the detection probabilities. A single line-trasnect is not sufficient to calculate accurate abundance estimates so we only report the detection probabilities. The detect ability of species is used as a descriptive tool to explain our outco mes of species richness based on presence/absence data. Species Richness Numerous methods have been proposed fo r estimating species richness in a community (Palmer 1990). Our use of presence/absence da ta collected from the line-transect and opportunistic sightings data rev ealed that the opportunistic si ghting method attained a greater number of species primarily due to its higher le vels of effort (Fig. 3-1). Gotelli and Colwell (2001) state that raw species ri chness counts or higher taxon c ounts can be validly compared only when taxon accumulation curves have reached an asymptote. A species accumulation curve is a plot of the cumulative number of species di scovered within a defined area, as a function of some measure of the effort expended to find them (Colwell & Coddington 1994). The opportunistic sightings reached an asymptote afte r 380 sampling occasions and if given the same amount of effort it is assumed that the line-tran sect should also reach an asymptote as the two areas surveyed should have the same levels of species overlap. The greater level of species richness determ ined by the opportunistic sightings may be a result of the detection of s hy and elusive species being seen in areas that had less human 36

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disturbance; probably due to the use of less frequently traveled paths. Time of day might be a contributing factor to the disparity of speci es richness between th e two methods. The linetransect was completed by early afternoon but opportunistic sightings occurred until dusk, increasing the odds of encountering nocturnal sp ecies beginning their ni ghtly activities (the opportunistic sightings encountered tw o species that are nocturnal). Many species defend territories and this could limit the number of individuals in an area that can be encountered. The line-transect may ha ve been part of a range for only one felid or canid; whereas, the opportunistic sightings may have covered multiple individuals territories increasing the likelihood of an encounter. The opportunistic sightings also covered a 3km2 site while the single line-transect was only 7km x 2m in length. The effort of sampling is also a factor, with 747 days/walks being conduc ted versus 238 on th e line-transect. Recommendations for conservation depend on th e information of interest. If levels of species richness are the primary concern than the use of opportunist ic sightings are best suited for low budgets and limited time. If abundance estim ates and species richness are the goal than the use of multiple line-transects and increased sampling effort are recommended. Predictors of Species Richness Species richness is undoubtedly influenced by many factors. There is evidence (reviewed by Begeon et al. 1990) that most of the process listed in Table 1-1 influence species richness, at least locally under some circumst ances. In this study we looked at the proximate mechanisms (climate (rainfall and temperature), leaf cover, and plant productiv ity) as possible predictors of species richness. It has been argued that regions with more stable conditions permit more species. Currie (1991) believes that one can reject the hypothesis that annual variability of climate per se has any important effect on richness. Currie (1991) found that terrestrial vertebrate richness was closely 37

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related to potential ev apotranspiration (PET), temperature, and solar radiation. Other studies found that a correlation between animal richness a nd environment were linked with temperature, sunshine, and solar radiation (Schall & Pinka 1978, Turner et al. 1987). Using temperature as a proximate mechanis m for species richness in Raleighvallen we found that it had a predictive value with the opportunistic si ghtings (p=0.0123) and the pooled data (p=0.0280) but not on the line-transect data (p=0.0545). Te rrestrial vertebrates (p=0.0288) and the other mammal guild (p=0.0072) (Table 33) were affected by temperature with the opportunistic data but only the te rrestrial (p=0.0085) guild had signi ficance with the pooled data. The pooled data set found that rainfall (p=0.1624) also has a significant predictive value for terrestrial vertebrates (p=0.0334) (Tab le 3-4). The lack of predictive value with the transect data could be a result of small sample size, yet ev en when the data was pooled it did not have increased predicative value on guilds and forest le vel groups. This could i ndicate that key species that are influenced by temperature are missing from the line-transect data. The ambient-energy hypothesis states that endotherms usually maintain themselves at a higher temperature than the environment, a highe r ambient temperature promotes faster growth of individuals and populations; and the higher bi omass will, in turn, promote greater species richness (Turner et al. 1996). Our data from Raleighvallen sh ows that increases in temperature lead to behavioral changes, such as increased activity, which increase s the number of species encountered. Leaf cover is used as a proxy for canopy c over in this study. We hypothesized that an increase in leaf cover would increase the sightings of all specie s. Arboreal species should have a higher encounter frequency due to the ability to potentially move more freely in the understory and terrestrial species should also travel more because of total coverage. 38

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Leaf cover is shown to have predictive va lue with the opportunistic sightings (p=0.0271) data but when species were divided by guilds an d forest level no predictive value was detected. The results could indicate that th e division of species by guilds and forest level is not detailed enough to determine which animals are most sensitive to leaf cover. The species energy hypothesis proposes that species richness is lim ited by the total or average amount of energy entering into an ecosystem. A sub-area of this hypothesis is the productivity hypothesis. The producti vity hypothesis states that the level of resource production in an ecosystem limits animal species richness. South American mammals support the productivity version of the species-energy hypothesis (Ruggiero & Kitz berger 2004). Using number of trees fruiting and fl owering as a mode of ecosystem production we found that fruiting and flowering could be used as an effective predic tor of species richness. Fruiting was seen to be significant with the arboreal and terrestrial forest level groups in the opportunistic sightings and pooled data sets. The opportunist ic sightings data showed that fruiting influenced the other mammal (p=0.0024) guild. Fruiting was also shown to influence the primate (p=0.0001) and bird (p=0.0014) guilds using the pooled data set. Ou r results corroborate Mittermeier and van Roosmalen (1981) findings that fruit makes up the majority of plant material consumed by the primate species in Raleighvallen; and therefore, their detection might be related to increases in food availability. The other mammal guild is made up of insectivores, carnivores, and frugivores. The other mammal and bird guilds speci es richness in Raleighvallen is predictive because the frugivorous species are reliant on the fruits and the carnivores increased hunting on more active prey species is also dependent on the fruits. Flowering influenced the primate, bird, a nd arboreal groups usi ng the opportunistic sightings and pooled data sets. The influence of flowers on the primate, bird and arboreal groups 39

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makes intuitive sense as these are the only animal s that are able to reach the flowers in the canopy. Habitat Preference The two different sampling methods reveal pertinent information about which habitats the species prefer. Species will have different reasons for preferring one habitat over another and our data shows that certain species were observe d in habitats more and less than would be expected (Table 3-5, Table 3-6, Ta ble 3-7). The distinction in hab itat preference could be a result of different evolutionary and ecological factors. It was found that Cebus apella and Crax alector were encountered more than expected in liana habitat and less than exp ected in the plateau habitat. Alouatta seniculus Ateles paniscus and Myorocta exilis were found more than expected in the plateau and less in the liana habitat. A. senculus was also seen more than expected in the swamp habitat. Although, our data did not find a preference of habitat type by Saimiri sciureus, Mittermeier and van Roosmallen (1981) and Frechette (2007) found that they were observed in liana more than any other habitat type. Possible explanations for C. apella and S. sciureus preference for the liana habitat could be predator avoidance and interspe cies association. Predation risk is a strong selective force that affects many aspects of animal behavior as well as having important repercussions on prey morphology and life history (Sih 1987, Lima & Dill 1990, Lima 1998, Stanford 2002). Lima and Dill (1990) argue that predation risk influences what, when and where to eat, which means that animal behavior is closely tied to predator behavior as well as local ecology. The liana habitat offers the greatest amount of cover and protection agai nst ambush aerial predators, such as the harpy eagle ( Harpia harpyja ). Frechette (2007) found that S. sciureus had a strong interspecies association with C. apella. These mixed-species groups may deter predators because predators may be less inclined to attack a larger gr oup of animals (Fitzgibbon 1990). The formation of 40

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mixed-species groups dilutes the predation risk to an individual because of the increase in group size. The increase in group si ze also increases combined vigi lance, which in turn can allow individuals more time to forage and conduct social behavior. Mittermeier and van Roosmalen (1981) found that S. sciureus had a high level of association with C. apella because it is a highly manipulative forager. C. apella regularly break branches, rips off bark and tears through leaf debris creating an increase of flushed insects accessible to S. sciureus It is a common for C. apella to forage on hard husked fruits and then observe S. sciureus foraging on the remains. This associ ation not only helps with predator avoidance but it also increases the nutritional variety in the S. sciureus diet. Crax alector is a poorly studied species in the tropic s. It is believed that they play an important role in the dispersal of seeds (S trahl & Grajal 1991). Borges (1999) found that C. alector was most abundant in the secondary forests of Brazil. We believe that the more than expected presence of C. alector in the liana habitat is most li kely due to an association with C. apella and the acquisition of fallen fruits. The more than expected presence of Ateles paniscus and Alouatta seniculus in plateau habitat matches the findings of Sussman and Phi llips-Conroy (1995). This could be related to interspecies avoidan ce and food availability. A. paniscus and A. seniculus have the largest body size of the primates in Suriname. This large bod y size makes adults and juveniles unsuitable prey items for the aerial predators negating the need for high amounts of foliage cover. Mittermeier and van Roosmalen (1981) found that A. paniscus and A. seniculus were the most dependent on plateau forest for food causing th em to prefer the plateau habi tat for nutritional requirements. These two primates were encountered less than e xpected in the liana habitat because they might have been avoiding an association with Cebus apella C. apella has been observed displaying 41

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aggressive behaviors, throwing sticks, pulling tails, and shaking branches, towards both of these species causing them to leave the area (personal observation). The antago nistic behavior of C. apella and low levels of fruit options in the lia na habitat could be another reason for these species preference of plateau habitat. Dubost and Henry (2006) determined that Myorocta exilis stomach contents were composed mainly of plateau forest fruits. Our obse rvation of their more than expected presence in the plateau habitat could be a result of their diet. Alouatta seniculus was observed more than expected in the swamp habitat. The swamp has a higher abundance of Euterpe Oleracea and Socrata exorhiza which A. seniculus has been observed eating. The abundance of food and lack of competition with other species could be enough incentive for their preference of this habitat type or maybe they are being pushed into this suboptimal habitat by the other primate species. We have w itnessed successful harpy eagle predation on A. seniculus infants when in the swamp habitat. Therefore, the risk of infant predation does not appear to outweigh the othe r benefits associated with this habitat. Detectability One of the key components of using line-transe ct data is the observers ability to detect target species. Our study implemented the doubleobserver dependent method to insure that new field assistants were equally proficient at their detection and identification skills. The majority of the field assistants had never worked in the neot ropics; and for many of th em this was their first time performing line-transect surveys. The double-observer method allowed for the inexperienced assistants to be trained on animal identification by an experienced team member. The inexperienced assistants were also paired wi th an experienced team member so that search images and acoustic cues, such as alarm-calls patterns of branch crashes and other escape maneuver information was properly transmitted. 42

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Detectability of species along the line-transect was analyzed using DISTANCE 5.0 software. A sample size minimum of 40 encounter s is required to get more accurate estimates. Our sample sizes ranged from 11-192 encounters. Table 3-9 shows our probability of detection for the various species tested. Although there was insufficient line-transect sample sizes we still ran the detectability tests. The greatest detection probability was with Cebus apella and Alouatta seniculus. Our lowest detection probability was with Myorocta exilis and Psophia cerpitans. Regardless of sampling method, observers will detect some species more easily than others. Gu and Swihart (2004) believe that failures to detect a species at occupied sites can lead to poorly formulated habitat models and thus to erroneous predictions of a species response to habitat change. Species that are less easily detected tend to live in small and/or more closely aggregated social groups, frequent tangles of liana or dens e understory vegetation, and make relatively little noise (Whitesides et al. 1988). Innate animal behavior, habitu ation, and habitat type could be three of the contributing factors for our low dete ction probabilities. An increase in group size increases detection (Quinn 1981, Freese et al. 1982) and solitary animal s are therefore harder to detect. A prime example from our data is Bradypus tridactylus the three-toed sloth. It was primarily observed in the plateau habitat a nd is a slow moving, well camouflaged, and quiet animal. These behaviors make it very easy for observers to miss it. A study by Mongomery and Sunquist (1973), on Barro Colorado Island, found that the three-toed sloth may reach a density of 7.6 animals per hectare. In spite of its high densit y, the animal was so cryptic that it was rarely seen and impossible to census (Eisenberg & Thorington 1973). We had only four sloth encounters during the five years of survey but we know from observations and collection of kill 43

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residue from the local harpy eagle nest site that three-toed sloths are very abundant (Boinski, personal communication). Species that flee loudly will often be detected over species that remain silent and motionless. Mild levels of hab ituation might increase de tection due to the animals lack of flee response. C. apella and A. seniculus often paid little to no atten tion to the observers and did not flee as the observers approached. Habitat type can either help or hinder species detection. The plateau habitat had the highest count s of animal encounters and the be st overall visibility. I think that in Raleighvallens case animal behavior and habituation is a greater factor in detectability than habitat type. Future work should include the addition of mo re line-transects, evaluating elevation and distance from water as potential predictors of species richness, and creating a phenological survey along the line-transect tr ail to gain a more well rounded picture of what is happening in the forest. In this study all fruit was pooled together, it would be interesting to see the influences of mature versus immature fruits on speci es detectability. Robinson and Redford (1986) proposed that the amount of potentially available energy de pends on the availability of appropriate resources and whic h resources are appropriate de pends on the animals diet. Recording what the animals were eating and what trees they were in or near when detected would also be valuable information. Determining tr ee species richness in Ra leighvallen is also an important step. Andrews and OBrien (1999) found th at variability in the plant species richness alone accounted for 75% of the variability in ma mmal species richness. Tying both of these other works together could disentangle the ambiguity in the relationship between mammal species richness and productivity, as it might increase or decline with increase d habitat productivity 44

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45 (Rosenzweig 1997). Looking at specif ic trees and trying to determin e which tree species have a greater influence on the community structur e would also be beneficial information. Conclusions Climate and plant productivity were found to be the proximate mechanisms that influenced species richness in Raleighvallen. Habita t preference could be in fluenced by predator avoidance, interspecies associa tion or avoidance, and food availa bility. The detec tion of species is thought to be a result of leve ls of innate animal behaviors, habituation, and habitat type.

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APPENDIX 46 Species encountered, frequency of encounters, trophic guild, and u se of forest level of pooled data censused at Raleighvallen, Central Suriname Nature Reserve, Suriname. Species encountered are expr essed as total number of sightings per census walked and species frequency of encounter is total sightings/total sampling effort. Species are listed within orders and families according to their body size. Species English name Individuals encountered (pooled) Frequency of encounter Guilda Forest levelb Plateau Liana Swamp MAMMALS Primates Callitrichidae Saguinas midas Golden-hand tamarin 72 105 9 19% Fr/In A Cebidae Saimiri sciureus Squirrel monkey 37 80 3 12% Fr/In A Cebus apella Brown capuchin 116 224 14 36% Fr/Sp/In/Vp A Cebus olivaceus Weeper capuchin 6 1 0 1% Fr/Sp/In/Vp A Pithecia pithecia White-face sakis 31 28 10 7% Sp/Fr A Chiropotes satanus Bearded sakis 34 12 3 5% Sp/Fr A Alouatta seniculus Red howler monkey 66 69 6 14% Fo/Fr A Ateles paniscus Spider monkey 115 48 1 17% Fr A Total primates 477 567 46 Xenarthra Myrmecophagidae Cyclopes didactylus Silky anteater 1 3 0 0% A/In A Tamandua tetradactyla Southern tamandua 17 23 9 5% A/In A Myrmecophaga tridactyla Giant anteater 1 1 1 0% A/In T Dasypodidae Dasypus novemcinctus 9-banded armadillo 14 2 0 2% A/In T Bradypodidae Bradypus tridactylus 3-toed sloth 3 1 0 0% Fo A

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Species English name Individuals encountered (pooled) Frequency of encounter Guilda Forest levelb Plateau Liana Swamp Rodentia Sciuridae Sciurus aestuans Guianan squirrel 33 28 6 7% Sp/Fr A Dasyproctidae Myorocta exilis Red acouchy 95 34 1 13% Sp/Fr T Dasyprocta punctata Red rumped agouti 372 263 64 71% Sp/Fr T Hydrochaeridae Hydrochaeris hydrochaeris Capybara 4 0 0 0% Fo/Fr T Carnivoria Procyonidae Nausa nasua Coati 2 0 0 0% In/Vp/Fr SA Mustelidae Eira barbara Tayra 26 11 5 4% Fr/In/Vp SA Pteronura brasiliensis Giant otter 30 3 0 3% Felidae T Leopardus wiedii Margay 0 2 0 0% Vp T Leopardus pardalis Ocelot 5 0 1 1% Vp T Felis yagouroundi Jaguarundi 2 2 0 0% Vp T Panthera onca Jaguar 0 5 0 1% Vp T Canidae Speothos venaticus Bush dog 2 0 0 0% Vp Procyonidae Potos Flavus Kinkajou 3 1 1 1% Ne/Fr A 47

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48 Species English name Individuals encountered (pooled) Frequency of encounter Guilda Forest levelb Plateau Liana Swamp Ungulates Perissodactyla Tapiridae Fr/Fo T Tapirus terrestris Tapir 22 10 2 3% Artiodactyla Tayassuidae Pecari tajacu Collard peccary 26 16 1 4% Fr/Sp/In T Tayassu pecari White-lipped peccary 31 16 3 5% Sp/Fr/In T Cervidae Mazama americana Red brocket deer 42 29 8 8% Fr/Fo T Total other mammals 719 440 100 BIRDS Cracidae Crax alector Black currasow 65 75 13 16% Fr/Sp SA Psophiidae Psophia crepitans Grey-winged trumpeter 70 66 11 15% Fr/In SA Accipitridae Harpia harpyja Harpy eagle 27 10 1 4% Vp A Total birds 162 151 25 Total 1370 1168 81 a Fr = frugivore, Fo = folivore, Sp = seed predator, Ne = necti vore A = anteater, In = insectivore, Vp = vertebrate predator b A = arboreal, T = terrestrial, SA = semi-arboreal (scansorial)

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LIST OF REFERENCES ANDREWS, P., & O'BRIEN, E. 2000. Climate, vegetation, and predictable gradients in mammal species richness in southern Africa. Journal of Zoology London 251: 205-231. BAAL, F.L.J., MITTERMIER, R.A., & VAN ROOSMALEN, M.G.M. 1988. Primates and protected areas in Suriname. Oryx 22: 7-14. BEGON, M., HARPER, J.L., & TOWNSEND, C.R. 1990. Ecology: individuals, populations and communities 2nd ed. Sinauer, Sunderland, MA. BENNETT, C.L., LEONARD, S., & CARTER, S. 2001. Abundance, diversit y, and patterns of distribution of primates on the Ta piche River in Amazonian Peru. American Journal of Primatoogy 54: 119-126. BORGES, S.H. 1999. Relative use of secondary forests by Cracids in Central Amozonia. Ornitologia Neotropical 10: 77-80. BRANAN, W.V, WERKOVEN, M.C. M., & MARCHINTON, R.L. 1985. Food habits of brocket and white-tailed deer in Suriname. The Journal of Wildlife Management 49: 972-976. BUCKLAND, S.T., ANDERSON, D.R., BURNHAM, K.P., LAAKE, J.L., BORCHERS, D.L., & THOMAS, L. 2001. Introduction to Distance Sampling: Estimating Abundance of Biological Populations. Oxford University Press, New York. BURNHAM, K.P., ANDERSON, D.R., & LAAKE, J.L. 1980. Estimation of density from line transect sampling biological populations. Wildlife Monographs 72: 1-202. BUTYNSKI, T.M. 1990. Comparitive ecology of blue monkeys (Cercopithecus mitis) in highand low-density subpopulations. Ecology Monographs 60: 1-26. CARO, T.M., & ODOHERTY, G. 1999. On the use of surrogate species in conservation biology. Conservation Biology 13: 805-814. COLWELL, R., & CODDINGTON, J. 1994. Estima ting terrestrial biodiversity through extrapolation. Philosophical Transactions Royal Society of London 345: 101-118. CONNELL, J.H., & ORIAS, E. 1964. The ecolo gical regulation of species diversity. The American Naturalist 98: 399-414. CURRIE, D. 1991. Energy and large-scale patterns of animal-and plantspecies richness. The American Naturalist 137: 27-49. DE GRANVILLE, J. 1988. Phytogeographical char acteristics of the Guianan forests. Taxon 37: 578-594. 49

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ROSENZWEIG, M.L., 1997. Species diversity in space and time Cambridge University Press, Cambridge. RUGGIERO, A., & KITZBERGER, T. 2004. Envi ronmental correlates of mammal species richness in South America: effects of spat ial structure, taxonomy and geographic range. Ecography 27: 401-416. SCHALL, J.J., & PIANKA, E.R. 1978. Geographi cal trends in the numbers of species. Science 201: 679-686. SIH, A. 1987. Predators and prey lifestyles: An evolutionary and ecological overview. Pp. 203224 in Kerfoot, W.C. & Sih, A. (eds.) Predation: Direct and i ndirect impacts on aquatic communities. University Press of New England, Hanover, NH. SIMBERLOF, D. 1988. The contribution of populat ion and community biology to conservation science. Annual Review of Ecology and Systematics 19: 473-511. STANFORD, C. 2002. Avoiding predat ors: expectations and evid ence in primate antipredator behavior. International Journal of Primatology 23: 741-757. STRAHL, S.D., & GRAJAL, A. 1991. Conservation of large frugivores and the management of Neotropical protected areas. Oryx 25: 50-55. STRUHASKER, T.T. 1975. The red colobus monkey The University of Chicago Press, Chicago SUSSMAN, R., & PHILLIPS-CONROY, J. 1995. A surv ey of the distribution and density of the primates of Guyana. International Journal of Primatology 16: 761-791. THOMAS, L., LAAKE, J.L., STRINDBERG, S., MARQUES, F.F.C., BUCKLAND, S.T., BORCHERS, D.L., ANDERSON, D.R., BURNHAM, K.P., HEDLEY, S.L., POLLARD, J.H., BISHOP, J.R.B., & MARQUES, T. A. 2006. Distance 5.0. Release x1. Research Unit for Wildlife Population Assessment, Un iversity of St. Andrews, UK. http://www.ruwpa.stand.ac.uk/distance/ THOMAS, S.C. 1991. Population densities and patterns of habitat use among anthropoid primates of the Ituri Forest, Zaire. Biotropica 23: 68-83. TURNER, J.R., GATEHOUSE, C.M., & COREY, C. A. 1987. Does solar energy control organic diversity? butterflies, moths, and the British climate. Oikos 48: 195-205. TURNER, J. R. G., LENNON, J. & GREENWOOD, J. J. D. 1996. Does climate cause the global biodiversity gradient? Pp. 199-220 in Hochberg, M. E., Clobert, J. and Barbault, R. (eds), Aspects of the genesis and ma intenance of biological diversity Oxford Univ. Press, New York. 52

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BIOGRAPHICAL SKETCH Carrie Vath was born and raised in Santa Ro sa, California. She received a B.S. in zoology and a minor in anthropology from Humboldt State University. After graduation, Carrie spent one year as a field assi stant for Dr. Sue Boinski studyin g brown capuchins in Suriname. She entered graduate school at the Univ ersity of Florida du ring the fall of 2006.