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Riparian Zone Management in Coastal Plain Streams

Permanent Link: http://ufdc.ufl.edu/UFE0022401/00001

Material Information

Title: Riparian Zone Management in Coastal Plain Streams Multi-Scale Effects of Habitat Fragmentation
Physical Description: 1 online resource (206 p.)
Language: english
Creator: Griswold, Marcus
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: bmp, drought, forestry, logging, macroinvertebrates, quality, riparian, water
Environmental Engineering Sciences -- Dissertations, Academic -- UF
Genre: Environmental Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Riparian zones act as filters for nutrients and sediment, and provide food and habitat for terrestrial and aquatic organisms. Preserving riparian structure in headwater streams is critical to protecting local and downstream aquatic biota. Forestry practices along streams are capable of degrading riparian zone function, leading to increased sediment and nutrient inputs, limiting organic matter availability, and altering light and temperature levels in streams. The effects of forestry practices on aquatic invertebrate communities were evaluated in coastal plain streams by experimentally manipulating two harvest regimes in headwater streams based on Georgia?s best management practices. Though the primary goal of the study was to relate anthropogenic disturbances to water quality, a drought occurring prior to the study created degraded streams with low invertebrate abundance and diversity. The drought resulted in streambeds with large amounts of stored organic matter and nutrients, that became available with re-wetting. A core set of species appeared immediately following drought in the streams, reflecting a shared species pool. These species shared resilient traits, including short life cycles and resistance to desiccation, which allowed for rapid recovery from disturbance. However, temporal shifts in biological traits reflected a more stable hydrologic regime over time. As communities recovered, a shift occurred from individuals that were small, sclerotized, and abundant in drift, to those that were larger, soft-bodied, and rare in drift, indicating that the habitat was more favorable. Thus, such shifts in trait structure and the role of natural disturbances need to be accounted for when bioassessment programs are implemented. To evaluate the effects of logging on streams, macroinvertebrates were sampled in reference and harvest streams before and after an experimental harvest. In response to harvest, communities shifted from detritivores to herbivores, following a shift in the food source from organic matter to algae and macrophytes. This change was most apparent in the thinned SMZ, where chlorophyll a was 50-100% higher than in the intact SMZ and reference streams. In general, changes in community structure were most apparent the first year following the harvest and began to follow a trajectory of recovery over the next four years. Interestingly, multimetric indices of water quality based on macroinvertebrates suggested more favorable conditions in the most disturbed treatment (Thinned SMZ). This relates to increases in food quality, due to an increase in algae and macrophytes, and a decrease in C:N ratios in terrestrially derived leaves. However, invertebrates in the thinned SMZ were represented by species preferring to live in sand, highlighting the increased isolation of patches apparent in these reaches. Observational and experimental field work was used to determine the effects of altered habitat amount and type on macroinvertebrate colonization and movement patterns. Macrophyte patches were more complex, stable, and trapped higher quantities of organic matter; attracting more diverse invertebrate communities than leaf packs. Patch size was a determinant of community structure for habitat specialists, where shredders were more common in large leaf packs and scrapers more common in large macrophytes. This reflected the higher biomass of chlorophyll a in macrophytes and bacteria in leaf packs. However, in general, invertebrate abundance and taxon richness decreased with increasing patch size. This indicates unfavorable conditions in larger patches, not evidenced by changes in dissolved oxygen or canopy cover. Behavioral experiments utilizing a habitat specialist (Trichoptera: Anisocentropus) and generalist (Pleuroceridae: Elimia) invertebrate indicated that the availability of both macrophytes and leaf packs is preferred by both groups and decreases emigration rates from landscapes. Thus, the increased diversity of habitats created by harvest potentially balanced the effects of habitat fragmentation and isolation. This was achieved by the addition of stable macrophyte patches that provided habitat islands, decreasing isolation and storing organic matter. Deforestation potentially has detrimental consequences for aquatic an terrestrial organisms, fragmenting in-stream habitat and the terrestrial landscape. Evidence from this study indicates that properly managed riparian zones effectively maintain water quality in small coastal plain streams. However, community composition shifted in the thinned SMZ and did not completely recover within five years. This suggests that harvest within the established riparian zone may eliminate habitat specialists, especially those consuming leaf litter, while replacing them with opportunistic species. Although water quality was preserved, managers should consider the consequences of reducing habitat specialists and its potential effects on food-web structure.
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 Marcus Griswold.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Crisman, Thomas L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022401:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022401/00001

Material Information

Title: Riparian Zone Management in Coastal Plain Streams Multi-Scale Effects of Habitat Fragmentation
Physical Description: 1 online resource (206 p.)
Language: english
Creator: Griswold, Marcus
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: bmp, drought, forestry, logging, macroinvertebrates, quality, riparian, water
Environmental Engineering Sciences -- Dissertations, Academic -- UF
Genre: Environmental Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Riparian zones act as filters for nutrients and sediment, and provide food and habitat for terrestrial and aquatic organisms. Preserving riparian structure in headwater streams is critical to protecting local and downstream aquatic biota. Forestry practices along streams are capable of degrading riparian zone function, leading to increased sediment and nutrient inputs, limiting organic matter availability, and altering light and temperature levels in streams. The effects of forestry practices on aquatic invertebrate communities were evaluated in coastal plain streams by experimentally manipulating two harvest regimes in headwater streams based on Georgia?s best management practices. Though the primary goal of the study was to relate anthropogenic disturbances to water quality, a drought occurring prior to the study created degraded streams with low invertebrate abundance and diversity. The drought resulted in streambeds with large amounts of stored organic matter and nutrients, that became available with re-wetting. A core set of species appeared immediately following drought in the streams, reflecting a shared species pool. These species shared resilient traits, including short life cycles and resistance to desiccation, which allowed for rapid recovery from disturbance. However, temporal shifts in biological traits reflected a more stable hydrologic regime over time. As communities recovered, a shift occurred from individuals that were small, sclerotized, and abundant in drift, to those that were larger, soft-bodied, and rare in drift, indicating that the habitat was more favorable. Thus, such shifts in trait structure and the role of natural disturbances need to be accounted for when bioassessment programs are implemented. To evaluate the effects of logging on streams, macroinvertebrates were sampled in reference and harvest streams before and after an experimental harvest. In response to harvest, communities shifted from detritivores to herbivores, following a shift in the food source from organic matter to algae and macrophytes. This change was most apparent in the thinned SMZ, where chlorophyll a was 50-100% higher than in the intact SMZ and reference streams. In general, changes in community structure were most apparent the first year following the harvest and began to follow a trajectory of recovery over the next four years. Interestingly, multimetric indices of water quality based on macroinvertebrates suggested more favorable conditions in the most disturbed treatment (Thinned SMZ). This relates to increases in food quality, due to an increase in algae and macrophytes, and a decrease in C:N ratios in terrestrially derived leaves. However, invertebrates in the thinned SMZ were represented by species preferring to live in sand, highlighting the increased isolation of patches apparent in these reaches. Observational and experimental field work was used to determine the effects of altered habitat amount and type on macroinvertebrate colonization and movement patterns. Macrophyte patches were more complex, stable, and trapped higher quantities of organic matter; attracting more diverse invertebrate communities than leaf packs. Patch size was a determinant of community structure for habitat specialists, where shredders were more common in large leaf packs and scrapers more common in large macrophytes. This reflected the higher biomass of chlorophyll a in macrophytes and bacteria in leaf packs. However, in general, invertebrate abundance and taxon richness decreased with increasing patch size. This indicates unfavorable conditions in larger patches, not evidenced by changes in dissolved oxygen or canopy cover. Behavioral experiments utilizing a habitat specialist (Trichoptera: Anisocentropus) and generalist (Pleuroceridae: Elimia) invertebrate indicated that the availability of both macrophytes and leaf packs is preferred by both groups and decreases emigration rates from landscapes. Thus, the increased diversity of habitats created by harvest potentially balanced the effects of habitat fragmentation and isolation. This was achieved by the addition of stable macrophyte patches that provided habitat islands, decreasing isolation and storing organic matter. Deforestation potentially has detrimental consequences for aquatic an terrestrial organisms, fragmenting in-stream habitat and the terrestrial landscape. Evidence from this study indicates that properly managed riparian zones effectively maintain water quality in small coastal plain streams. However, community composition shifted in the thinned SMZ and did not completely recover within five years. This suggests that harvest within the established riparian zone may eliminate habitat specialists, especially those consuming leaf litter, while replacing them with opportunistic species. Although water quality was preserved, managers should consider the consequences of reducing habitat specialists and its potential effects on food-web structure.
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 Marcus Griswold.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Crisman, Thomas L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022401:00001


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RIPARIAN ZONE MANAGEMENT IN COASTAL PLAIN STREAMS: MULTI-SCALE
EFFECTS OF HABITAT FRAGMENTATION





















By

MARCUS WAYNE GRISWOLD


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 Marcus Wayne Griswold




























To those who helped me balance my life. To my wife Ann, for her adventurous spirit and her
attempts to reduce my carbon footprint. To Leif for the changes he will inspire. To my mother
for the gift of learning, teaching, compassion, and independence. To my family for their support
and sense of home that will never fade.









ACKNOWLEDGMENTS

I would like to thank my advisor, T.L. Crisman, for his guidance and insight into my research

as well as giving me numerous opportunities to expand my knowledge base. I benefited greatly from

discussions with my committee B. Bolker, R. Holt, and W. Wise and their experience in a large

breadth of disciplines.

I am grateful to those who helped me find myself and my mentoring skills throughout this

journey. I thank those who let me pry my way into their research, just to discover something new

and to those who reminded me that everyone has something to contribute. Included in this, I thank

those who assisted with the fieldwork, and torturous days and nights of sorting: R. Sandidge, M.

Domberg, O. Stem, K. Alvarez, C. Cruz, L. Burhans, M. Diedrick, and M. Bell. I would like to thank

Scott Terrell for his willingness to share data and Rebecca Winn for the initiation of the preharvest

work.









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 ................................ ............................................................ 12

CHAPTER

1 INTRODUCTION ............... ................. ........... .............................. 14

Overview of forestry practices in southeastern U.S. .................. .........................................14
Buffer Zones and A quatic Ecosystem s............................................................................. ... 15
Buffer Zones and W ater Q quality ....................... .... ............ ..... ............... ....15
Current Status of Riparian Zone Management in the Southeastern U. S .......................17
Habitat Fragm entation and Forestry Practices.................................... ........................ 18

2 IMPACTS OF CLIMATIC STABILITY ON THE STRUCTURAL AND
FUNCTIONAL ASPECTS OF MACROINVERTEBRATE COMMUNITIES AFTER
SE V E R E D R O U G H T ......... .. ............. .............................................................................20

Introduction .............. .... ......... .... ................ ...... .. .............................. 20
M materials and M methods ...................................... .. .......... ....... ...... 22
Site Description .......................... ............................22
Hydrologic and Environmental Variables.................. .... .......... ...............23
Inv ertebrate Sam pling .......................................................................... .....................24
B biological T raits ........................................... ........................... 25
Statistical A naly sis ........................................................................26
Environmental variables........................................................ 26
Ordination: species com position and traits ................................... ............... ..27
R e su lts ........................... .. ..................... ......................... ................ 2 8
Hydrologic and Clim atic Patterns ............................................................................28
Environm mental V ariables .......................................................... ................... 29
B enthic M acroinvertebrates.................................................. ............................... 30
C om m unity succession.................................................. ............................... 30
Com m unity stability .................. ................ ..... ................... .. ............
T axonom ic C om position ......................................... .. .. ..............................................3 1
W etland-F ed stream (W F ) ............................................................... ... .....................3 1
Seep-Fed stream (SF) ........................ ................ ................... .. ...... 32
B biological T raits ........................................... ........................... 33
W etland-Fed stream ....................................... .... .... ................33
S e ep -F e d store am ................................................................................................. 3 4
D iscu ssio n ................... ...................3...................5..........










E nvironm mental V aviation ................ ........... ...........................................................36
Temporal Variation and Successional Patterns in Taxonomic Abundance...................38
Tem poral V ariation in Traits ........................................................................ 39
Drought Prediction .................... ........................... ......... 41

3 TESTING BMP EFFECTIVENESS FOR SMALL COASTAL PLAIN STREAMS
USING MACROINVERTEBRATES AS BIOINDICATORS ...........................................56

Introduction ................ ........................................56
M materials and M methods ...................................... .. .......... ....... ...... 59
S ite D e sc rip tio n ............................................................................................................... 5 9
G e o lo g y ................................................................5 9
V eg etatio n ................................................................5 9
C lim ate ..............................................................................6 0
H y d ro lo g y .......................................................................................6 0
Experimental Harvest ................................. .......................... ..........61
Physical and Biological M easurem ents ................................................................... 62
Physical m easurem ents .............................................................. 63
E n erg y so u rc e s ................................................................................................... 6 3
M acro in v erteb rates ............................................................................................. 6 4
B io lo g ic al T raits ................................................................................................. 6 5
D ata A n a ly sis ............................................................................................................. 6 5
E n erg y so u rc e s ................................................................................................... 6 5
E nvironm ental v ariables..................................................................................... 66
M acro in v erteb rates ............................................................................................. 6 6
R e su lts ................... ...................6...................7..........
E n e rg y S o u rc e ........................................................................................................... 6 7
E nv ironm mental V ariab les ........................................................................................... 6 8
Macroinvertebrates ................................................................ ...............69
S tab ility ................................................................6 9
Taxonomic composition ................................. .......................... .. ....... 69
B io lo g ical traits ................................................................7 2
D iscu ssio n ................... ...................7...................4..........
E energy Sources ............................................................................................... ....... 74
Environmental Variables ................................. ........................... ... .......78
M acroinvertebrates ...........................................................................................80
Anthropogenic disturbance in the face of natural disturbances................... ................ 82

4 EFFECTS OF PATCH TYPE, QUALITY, AND SIZE ON MACROINVERTEBRATE
C O M M U N ITY STR U C TU R E ...................................................................................... 104

Introduction ......... ....... ......................... ............. 104
M materials and M methods ...............................................................106
Field Sampling of Patches ...... .................... ........ ........106
F field E x p erim ent ............................................................................................... 109
D ata A analysis ............... ...... ........ ................................... .......... .....110
Field observations .............................................................. 110


6










Experim ental m manipulation of patches ............................................................... 110
R e su lts ................... ...................1.............................0
Field Observations ................. ..... ........ .......................... 10
Field Experiment ............... ......... ................... 113
R e g re ssio n s ........................................................................................................ 1 1 5
D iscu ssio n ......... ....... .............. .........................................................................1 1 5
Patch Complexity ............... ......... .................... 116
Patch Stability .............. ......... ............................................................................. 117
P watch Q quality .............. ........ .................................................................... 118
P a tc h S iz e ................................................................................................................. 1 2 1

5 HABITAT SELECTION IN FRAGMENTED LANDSCAPES: COMPARING
GENERALISTS TO SPECIALISTS ........... .............................151

In tro d u ctio n ................... ...................1.............................1
M materials and M methods ...............................................................153
Stu dy O organism s ...............................................................153
B behavioral O observations ............................................................154
C o lo n iz a tio n ............................................................................................................. 1 5 7
R e su lts ................... ...................1.............................8
M o v e m e n t ................................................................................................................. 1 5 8
A nisocentropu s .................................................. .......... ..................... 158
E lim ia ......................... ...............................................................................158
C o lo n iz a tio n ............................................................................................................. 1 5 9
D discussion ....................................... .............................................. 159

6 C O N C L U S IO N S ............................................................................................................. 17 2

LIST OF REFEREN CES .............. .................................................................................... 175

BIO GR A PH ICA L SK ETCH ...............................................................206





















7









LIST OF TABLES


Table page

2-1 Definition and codes for biological traits and modalities..........................................43

2-2 Mean annual values for environmental variables for the wetland-fed (WF) and seep-
fe d ........................................................... ............................... . 4 4

3-1 Biological trait definitions and m odalities ..................................... .......... ............... 86

3-2 Results of multiple regressions for chlorophyll a biomass and benthic organic matter
(BOM). Significance ofR2 values is given by (P < 0.05), ** (P < 0.01), *** (P <
0.001). ................ ...... ................... .......................... ......... 87

3-3 Average environmental conditions for winter sampling periods in reference (A,D),
thinned SMZs (B1,C1), and intact SMZs (B2,C2). Data are for pre-harvest (2001-
2003) and post-harvest (2004-2008) ........................................... ........................... 88

3-4 Indicator values for watersheds A and B based on taxonomic composition. Groups
are defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest
thinned SMZ (3), and post-harvest intact SMZs (4). .................. ........................ 89

3-5 Indicator values for watersheds C and D based on taxonomic composition. Groups
are defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest
thinned SMZ (3), and post-harvest intact SMZs (4). .................. ........................ 90

3-6 Indicator values for watersheds A and B based on biological traits. Groups are
defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SM Z (3), and post-harvest intact SM Zs (4). .............. .................. ......................... 91

3-7 Indicator values for watersheds C and D based on biological traits. Groups are
defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SM Z (3), and post-harvest intact SM Zs (4). .............. .................. ......................... 92

4-1 Multiple regressions for leaf packs averaged over all time periods for the
observational study. ......................... ......................... .... .................. 124

4-2 Multiple regressions for Ludwigia averaged over all time periods for the
observational study. ......................... ......................... .... .................. 125

4-3 Multiple regressions for the field experiment averaged over all treatments for each
invertebrate m etric. .................................... .. ........... ...... ... ... 126









LIST OF FIGURES


Figure page

2-1 Plot of Standardized Precipitation Index (SPI) values for southwestern Georgia, from
19 56 to 2 0 0 7 ........................................................................... 4 5

2-2 Hydrograph based on mean daily discharge (m3/s) for each stream..............................46

2-3 Temporal variability of Bray-Curtis stability values for environmental variables in
W F and SF ( SE)....................................................................... ... ....... ...... 47

2-4 Temporal changes in taxon richness and invertebrate abundance ....................................48

2-5 Changes in compositional stability (Bray-Curtis distance) in WF and SF ( SE)............49

2-6 Linear regression of SPI values versus taxonomic stability. .............................................50

2-7 Changes in trait stability (Bray-Curtis distance) in WF and SF ( SE) ..........................51

2-8 NMDS ordinations of logl0-abundance in site-year space and taxon-space for WF.
Time periods are indicated by different symbols. Ordination plots of taxa are based
on w eighted-averaging ......................................... ....... ... ...... ... ............ 52

2-9 NMDS ordinations ofloglO-abundance in site-year space and taxon-space for SF.
Time periods are indicated by different symbols. Ordination plots of taxa are based
on w eighted-averaging ......................................... ....... ... ...... ... ............ 53

2-10 NMDS ordinations of biological traits in site-year space and trait-space for WF.
Time periods are indicated by different symbols. Ordination plots of taxa are based
on w eighted-averaging ............... ........................ ............... ............ 54

2-11 NMDS ordinations of biological traits in site-year space and trait-space for SF. Time
periods are indicated by different symbols. Ordination plots of taxa are based on
w eighted-averaging .................. ...............................................................55

3-1 Topographic map and aerial photo of the four study watersheds (A-D). ..........................93

3-2 Average chlorophyll a biomass (+SE) during the wet (May-September) and dry
season (October-April) from 2004-2008 in reference, thinned SMZs, and intact SMZ
stream s after h arv est. .............................................................................. ....................94

3-3 C:N ratios of leaf fall from the riparian zone in reference and harvested watersheds
before (2001-2003) and after (2004-2007) harvest........... .... ..................95

3-4 Average ammonia (NH4) concentrations (+SE) in reference, thinned SMZs, and
intact SMZ streams. Harvest treatments were applied prior to the third sampling
p period ......................................................... ....................................96









3-5 Stream condition index (SCI) scores (SE) for reference, thinned SMZs, and intact
SMZ streams. Samples below the red line indicate poor water quality, those above
the red line, fair water quality, and those above the blue line, good water quality. ..........97

3-6 Taxonomic stability (+SE) for reference, thinned SMZs, and intact SMZ streams. .........98

3-7 Trait stability (SE) for reference, thinned SMZs, and intact SMZ streams ...................99

3-8 NMDS of taxonomic composition in watersheds A and B in pre-harvest (1) and in
post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)................100

3-9 NMDS of taxonomic composition in watersheds C and D in pre-harvest (1) and in
post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)................101

3-10 NMDS of biological traits in watersheds A and B in pre-harvest (1) and in post-
harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)......................102

3-11 NMDS of biological traits in watersheds C and D in pre-harvest (1) and in post-
harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)......................103

4-1 Total biomass of chlorophyll a (mg) ( SE) in each patch type ..................................... 127

4-2 Total number of bacterial cells (1 X 106) ( SE) in each patch type.............................128

4-3 Bacterial biomass (pg C/cm3) ( SE) in each patch type........................... .............129

4-4 Number of bacterial cells per cm3 (1 X 106) ( SE) in each patch type ........................130

4-5 Chlorophyll a biomass (mg/cm3) ( SE) in each patch type............. .................131

4-6 Volume-weighted taxon richness (Taxa/cm3) (+ SE) in each patch type ......................132

4-7 Volume weighted invertebrate density (Individuals/cm3) ( SE) in each patch type......133

4-8 Proportion of filtering invertebrates ( SE) in each patch type..................................134

4-9 Proportion of leaf mass decomposed ( SE) in relation to patch type and disturbance. .135

4-10 Amount of leaf mass decomposed (g) ( SE) in relation to initial patch mass. ..............136

4-11 CPOM trapped in patches ( SE) in relation to patch size. ...........................................137

4-12 Average amount of coarse particulate organic matter (g) ( SE) trapped in each
patch type. ................................................................................ 138

4-13 Average amount of coarse particulate organic matter (g) ( SE) trapped in patches by
disturbance type. ........................................................................ 139









4-14 Average amount of fine particulate organic matter (g) ( SE) trapped in each patch
based on disturbance. ........................................................... ...... .......... 140

4-15 Average amount of fine particulate organic matter (g) ( SE) trapped in each patch
ty p e ........................ .. .. ......... .. .. .................................................... 14 1

4-16 Average number of invertebrate individuals (+ SE) in each patch type......................142

4-17 Average number of invertebrate individuals (+ SE) in each patch based on initial
p watch m a ss............. ......... .. .. ......... .. .. ....................................................14 3

4-18 Average number of taxa ( SE) in each patch in relation to initial patch mass..............144

4-19 Proportion of scrapers ( SE) in each patch based on initial patch mass ......................145

4-20 Proportion of shredders (+ SE) in each patch based on initial patch mass....................146

4-21 Proportion of shredders (+ SE) in each patch based on patch type and disturbance. ......147

4-22 Proportion of filterers (+ SE) in each patch based on initial patch mass......................148

4-23 Proportion offilterers (+ SE) in each patch type. ... ...... ...................................... .....149

4-24 Proportion of collector-gatherers ( SE) in each patch type ....................................150

5-1 Microlandscape designs used in the behavioral and colonization experiments.
Liriodendron leaf packs (brown squares) and Ludwigia macrophyte patches at A) 10
B) 20, and C) 30 percent cover. .............................................. ............................ 165

5-2 Average deviation from a correlated random walk ( SE) (CRW) (Rdiff) for
A nisocen trop us............................................................................................ .166

5-3 Average probability ( SE) of each turn being in the same direction for
Anisocentropus................................... .................................. ..........167

5-4 Average correlation ( SE) between turning angles for Anisocentropus. .......................168

5-5 Average net squared displacement ( SE) of Anisocentropus in microlandscapes.........169

5-6 Mean step length ( SE) in each landscape for Elimia.............................................. 170

5-7 Average deviation ( SE) from a correlated random walk (Rdiff) for Elimia...............171









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

RIPARIAN ZONE MANAGEMENT IN COASTAL PLAIN STREAMS: MULTI-SCALE
EFFECTS OF HABITAT FRAGMENTATION

By

Marcus Wayne Griswold

August 2008

Chair: Thomas Crisman
Major: Environmental Engineering Sciences

Riparian zones filter nutrients, sediment, and provide food and habitat for terrestrial and

aquatic organisms. Georgia's forestry practices were evaluated in coastal plain streams by

manipulating harvest regimes in headwater streams. Macroinvertebrate and their food sources

were sampled before and after harvest.

A drought occurring prior to the study degraded streams, depressing invertebrate

abundance and diversity. A core set of species appeared immediately following drought,

displaying short life cycles and resistance to desiccation, allowing for rapid recovery from

disturbance. Communities shifted from small, sclerotized individuals abundant in drift, to those

that were larger, soft-bodied, and rare in drift, indicating more favorable habitat.

In response to harvest, communities shifted from detritivores to herbivores, following

shifts in food availability from organic matter to algae and macrophytes. This was most apparent

immediately following harvest and followed a trajectory of recovery over the next four years.

Interestingly, multimetric indices of water quality based on macroinvertebrates suggested more

favorable conditions in the most disturbed treatment. This relates to increases in food quality,

due to an increase in algae and macrophytes, and a decrease in C:N ratios in terrestrially derived









leaves. However, invertebrates in the thinned SMZ were represented by species preferring to

live in sand, highlighting the increased isolation of patches apparent in these reaches.

At the microhabitat scale, macrophyte patches were more complex, stable, and trapped

higher quantities of organic matter; attracting more diverse invertebrate communities than leaf

packs. Shredders were more common in large leaf packs and scrapers more common in large

macrophytes. This reflected the higher biomass of chlorophyll a in macrophytes and bacteria in

leaf packs. This was supported during a behavioral study utilizing a habitat specialist and

generalist where the availability of both macrophytes and leaf packs was preferred by both

groups and decreased emigration rates from landscapes. Increased diversity of habitats created

by harvest potentially balanced the effects of habitat fragmentation and isolation.

Evidence from this study indicates that properly managed riparian zones effectively

maintain water quality in small coastal plain streams. However, managers should consider the

consequences of reducing habitat specialists and its potential effects on food-web structure.









CHAPTER 1
INTRODUCTION

Overview of forestry practices in southeastern U.S.

Managed forests practices comprise a significant land area within the U.S., thus their

proper management has broad scale consequences for biodiversity and ecosystem functions.

Previous disregard for these ecosystems resulted in loss of nearly 120 million hectares of

forested land in the U.S. from 1630-2005, of which 40 million was lost in the southeastern U.S.

(Alvarez, 2007). Currently, approximately 59 % of land in the southeastern U. S. is forested,

with 98% managed for timber (Alvarez, 2007), representing more than 10% of timberland in the

U.S. In Georgia alone, there are 9.5 million hectares of commercial forest land, comprising an

area covering nearly 67% of the state (Georgia Forestry Commission, 1999). Additionally, the

Coastal Plain is extremely productive, with the fastest pine growth rates in the country, thus

attracting forestry operations. (Demmon, 1951).

Historically, logging has occurred along rivers and streams, in part to facilitate

downstream transport of timber, with little regard for preserving stream habitat or biota.

However, following enactment of the Clean Water Act in 1972, land managers recognized the

importance of protecting water quality. In recent years, nonpoint-source (NPS) pollution has

become one of the greatest threats to U.S. water quality as point sources were eliminated or

controlled (USEPA, 2003). Silviculture accounts for 5,900 km of impaired rivers and streams in

the U.S. and is ranked 9th of the 10 leading sources of nonpoint pollution of rivers and streams in

the South (West, 2002). Currently, two percent of all assessed stream kilometers (7% of all

impaired kilometers) are considered degraded through forestry activities (US EPA, 2000). In

addition, 53 % of the freshwater supply, originates on forestlands (e.g., headwaters) (Alvarez,









2007), and proper management strategies are necessary to protect local and downstream water

quality.

Buffer Zones and Aquatic Ecosystems

Buffer Zones and Water Quality

Riparian buffer zones (streamside management zones) are forested areas along streams

meant to protect biotic integrity and water quality. Riparian zones act as important ecotones for

aquatic systems, providing food for aquatic (e.g., organic matter and terrestrial insects) and

terrestrial organisms (e.g., emerging aquatic adults) (Nakano et al., 1999), shading, temperature

regulation, and woody debris; providing the basis for invertebrate community structure (Kiffney

et al., 2003). Small headwater streams are closely linked to the riparian zone since they are

relatively narrow and shaded by forest canopy (Cummins, 1974; Hynes, 1975; Vannote, 1980;

Moore and Richardson, 2003). They account for 70-80 % of total watershed area in the U.S. and

export organic matter (OM), sediment, prey items, and nutrients downstream (Meyer and

Wallace, 2001; Kiffney et al., 2003).

Logging and thinning of vegetation in the riparian zone reduce detrital input to streams

over time. The extent of this reduction is influenced by the remaining canopy cover in the

riparian buffer zone. Decreased canopy cover leads to increased light and temperature (e.g.,

Swift and Messer, 1971) in stream channels, and may increase primary productivity, shifting

production from heterotrophic to autotrophic processes (Hartman and Scrivener, 1990; Fuchs et

al., 2003). In faster high gradient streams this process leads to dominance by algal communities,

while in low-gradient, coastal plain streams it results in a mix of macrophyte and algal growth

(Noel et al., 1986; Kedzierski and Smock, 2001). This change typically results in increased

density, biomass and diversity of macroinvertebrates and can shift macroinvertebrate dominance

from shredders to grazers (Jackson et al., 2001; Kedzierski and Smock, 2001; Fuchs et al., 2003).









Such a shift in foodweb structure potentially alters ecosystem function (e.g., decomposition) and

higher trophic levels, limiting food availability for detritivores.

Watershed-level disturbances alter runoff regimes and evapotranspiration rates. Logging

potentially alters the hydrologic regime, such that increased surface runoff contributes sediment

and nutrients to the affected streams. The primary hydrological influence of harvesting and

thinning is increased water yield due to decreased evapotranspiration that typically in harvest

treatments is 69 to 210 mm/year (Beasley and Granillo, 1982; Williams et al., 1999; McBroom et

al., 2002; Grace et al., 2003). This change in hydrology may ultimately homogenize

microhabitats and exclude invertebrates that prefer slow flow.

Clearcut watersheds typically have large sediment yields, potentially clogging fish gills

and smothering invertebrate habitat. Gurtz and Wallace (1984) found that abundance of many

invertebrate taxa in habitats susceptible to sediment deposition (i.e., pools and sandy reaches)

declined in a stream draining a recently clear-cut watershed, whereas those taxa in less

susceptible habitats (i.e. steep-gradient, boulder outcrops) increased. This emphasizes the need

for proper management of riparian zones in coastal plain streams as they are primarily low

gradient systems dominated by extensive sandy reaches, with few outcroppings. In addition,

creation of buffer zones decreases potential for sediment movement by promoting sheet flow

rather than channelized flow across the landscape.

Harvest related changes in nutrient export affect the abundance and diversity of aquatic

invertebrates. Macroinvertebrate abundance may initially increase as nutrients fuel algal growth,

providing food to a typically resource-limited grazer population. However, Miltner and Rankin

(1998) found a negative relationship between water quality indices based on macroinvertebrates

and increased nutrient concentrations, especially in low order streams. Additionally, harvest-









related increased nitrogen may accelerate leaf litter decomposition, altering organic matter

dynamics and potentially limiting resources available for detritivore populations (Bormann et al.,

1974; Likens et al., 1978; Martin et al., 2000; Swank et al., 2001).

However, these changes tend to be short-lived, with water chemical parameters

recovering within one to two years (Corbett et al., 1978; Martin and Pierce, 1980; Arthur et al.,

1998). Vowell (2001) did not find any change in water chemistry in Florida when Best

Management Practices (BMPs) were utilized nor did Adams (1995) in South Carolina.

However, neither study connected long-term pre or post harvest data, nor did they selectively

harvest within the buffer zone, an acceptable practice in Florida and Georgia (Georgia Forestry

Commission, 1999).

Current Status of Riparian Zone Management in the Southeastern U.S.

Regulations for Stream Management Zone (SMZ) width vary among states, however, most

rely on watershed slope as a predictor of sediment inputs following harvest. Although Georgia

recommends a buffer width for a perennial stream beginning at 12.2 meters (40 feet), with

increases as slope of the adjacent watershed increases (Georgia Forestry Commission, 1999),

current regulations allow for limited harvest within the SMZ. Such harvest, known as thinning or

partial harvesting, may be conducted until either there is a minimum of 11.5 square meters of

basal area per hectare (50 square feet of basal area per acre) or 50% canopy cover remaining.

Aust and Blinn (2004) examined published research on the effects of forest practices on water

quality in the southeastern U.S. for the previous 20 years. They concluded that forestry BMPs

were effective for minimizing potentially negative effects of forest practices on water quality, but

needed to be refined to reflect site specific conditions in the southeast. Impacts of logging on

stream biota have been well studied in high gradient streams in the northwest and the eastern

Appalachians of the U.S., but little emphasis has been placed on small, low gradient streams in









the southeastern part of the country. Furthermore, the effects of partial harvest within SMZs on

water quality are not well documented. More research is necessary to fill in gaps that currently

exist regarding BMP effectiveness in the coastal plain and effects of partial harvesting within

SMZs.

Habitat Fragmentation and Forestry Practices

Forestry practices potentially have adverse effects on communities by limiting dispersal

between watersheds, eliminating suitable environmental conditions, and altering predator-prey

dynamics. Even with current regulations for stream water quality, clear cutting of a watershed

down to the buffer zone commonly occurs. Although this can maintain local biodiversity,

dispersal across this newly created, potentially hostile landscape may be difficult for small

organisms such as invertebrates and amphibians (Hughes et al., 1996; Fagan, 2002; Briers et al.,

2004).

Although distance between watersheds can serve as a template for determining

population structure and species composition (e.g., Harding, 2003), locally influenced

microhabitats may be the strongest drivers of community structure at the reach and microhabitat

scales. Indirect effects of logging or riparian zone modification lead to changes in microhabitat

structure in streams. This was clearly demonstrated in afforested agricultural streams that

displayed an 87 % reduction in the leaf litter storage compared to forested streams (Benstead and

Pringle, 2004). Similarly, Noel et al.(1986) found that 50% of logged streams were covered by

macrophytes, while unlogged reference streams had only 10% macrophyte cover. Thus, a

gradient of tree removal from the riparian zone should change the physical and biotic structure of

the stream in a predictable manner.

In logged streams, leaf pack formation is often slow, resulting in increased patch isolation

and fragmentation. Rooted macrophytes, however, become more abundant in logged streams









and are more stable, contributing to a less dynamic streambed landscape. Thus, macrophytes

may support more permanent coexisting species, while leaf packs may support more transient,

inferior competitors. Colonization of streambeds by macrophytes, coupled with decreased

allochthonous input to logged streams, may alter the availability patches for stream biota.

Key gaps in the current literature lie primarily within their temporal and spatial scales.

Most studies have limited data on pre-harvest conditions in the watershed, especially true of

studies in the southern coastal plain (Smock et al., 2001). Water chemistry and biotic

communities may vary significantly on a temporal scale, knowledge of which is required to

determine whether changes following logging are related to natural or anthropogenically related

disturbance.

Many studies focus on changes in taxonomic structure of the biotic community.

However, changes may be linked more to biological traits that are sensitive to changes in habitat

structure (e.g., habitat templet sensu Southwood, 1978; Townsend and Hildrew, 1994). Studies

also are limited to the reach scale, whereas organisms disturbed in the riparian zone may be

affected at the microhabitat scale. Thus, the objectives of this study were to:

1) Determine the impact of two logging regimes considered acceptable in the Georgia BMP
manual on stream communities through changes in water quality, taxonomic and trait
composition, and the role of natural variation (e.g., drought) on the recovery process
(Chapters 2 and 3).

2) Link changes in habitat-scale, community composition to changes in patch availability at
the microhabitat scale (Chapter 4).


3) Relate small scale patterns of dispersal for instream habitat fragmentation in a habitat
specialist and generalist invertebrate species (Chapter 5)









CHAPTER 2
IMPACTS OF CLIMATIC STABILITY ON THE STRUCTURAL AND
FUNCTIONAL ASPECTS OF MACROINVERTEBRATE COMMUNITIES AFTER
SEVERE DROUGHT

Introduction

Natural disturbances regulate community structure and ecosystem function, and

thus play a crucial role in shaping aquatic and terrestrial communities (Sousa, 1984; Resh

et al., 1988). Aquatic ecosystems are especially vulnerable to extreme climatic changes,

such as drought, because these disturbances alter flow regimes, water chemistry, and

ultimately, the biotic community (Wood and Petts, 1999). The long-term effects of

drought on the economy, wildlife habitat, and recreation occur as ramp disturbances over

periods of years (sensu Lake, 2003), as opposed to the effects of flooding events, which

subside after weeks or months. The frequency and predictability of droughts are generally

low. However, when drought does occur, it can potentially act as a destabilizing agent for

aquatic communities. The forecast for climate change suggests increased frequency of

extreme events, particularly drought, over the next century (Wetherald and Manabe,

2002; Kundzewicz et al., 2007). Increased intensity and frequency of natural disturbances

will ultimately affect ecosystem stability and influence organisms' resistance and

resilience to change.

During extreme drought, streams typically form a series of disconnected pools

and lose evidence of surficial flow over time, a response that can potentially reset the

aquatic community. Furthermore, toxic accumulation of nutrients and waste (Towns

1985, 1991; Closs and Lake 1995; Dahm et al., 2003), coupled with increased

temperature (Matthews, 1998) and lowered dissolved oxygen (Stanley, 1997; Golladay

and Battle, 2002), add stress to the remaining species pools. Species survival after









drought depends on specific life history traits, including resistance to desiccation and an

ability to colonize habitats rapidly through drift and aerial migration or oviposition

(Williams, 1987, 1996; Boulton, 1989). Further colonization reflects subsequent changes in

water chemistry, habitat availability, and resource base following flow resumption.

Biological traits are more informative indicators of ecosystem function than are

changes in abundance of individual species, and they are expected to change across a

gradient of anthropogenic and natural disturbances (Charvet et al., 2000; Dole'dec et al.,

1999; Statzner, Hildrew and Resh, 2001). However, species loss decreases the ability of

ecosystems to resist disturbances and leads to lowered stability (Hooper et al., 2005).

Therefore, an integrative approach should utilize both species composition and biological

traits to predict community responses to disturbances (Richards et al., 1997) Biological

traits are regulated at a hierarchy of scales, with environmental filters (e.g., climate and

geology) creating a template for traits that are present in a specific region (Townsend and

Hildrew, 1994; Poff, 1997). Thus, a subset of traits is expected to respond to disturbances

within a certain region. For example, species that are resilient to disturbance display a

series of traits, including small size and multiple generations per year, that allow them to

expand their population densities rapidly (Townsend and Hildrew, 1994). As functional

redundancy is common among stream invertebrates, biological traits can be compared

across large regions to understand the large-scale impacts of anthropogenic change

(Statzner et al., 2004).

This study utilized a six-year (2001-2007) dataset of macroinvertebrates from

headwater streams after an intense drought in the southeastern U.S. (1998 to 2002) to

characterize inter-year successional patterns following flow restoration relative to water









quality and climatic parameters, biological traits and taxonomic composition, and

community stability. Biological traits were expected to respond similarly in the two

streams because they are adjacent headwater streams in the same basin and have access to

the same species pool. Additionally, traits were anticipated to respond primarily to local

environmental variation (e.g., water quality parameters) as a reflection of large-scale

environmental filters. However, changes in regional climatic data are expected to

structure the overall successional pattern of the community.

Materials and Methods

Site Description

The two study streams were located in southwestern Georgia (30049'N /

84037'W), approximately 16 km south of Bainbridge in the Coastal Plain physiographic

province. They lie within the Dry Creek watershed, which discharges to the Flint River

approximately 22 km upstream of the Jim Woodruff Dam of Lake Seminole. Surface

water flow in this basin is lowest from September to November and peaks during January

to April due to higher rainfall and decreased evapotranspiration (Couch et al., 1996).

Streams and rivers in the Coastal Plain receive substantial amounts of groundwater

because they are typically deeply incised into underlying aquifers (Couch et al., 1996).

These streams were first order (width 1.25m), perennial, groundwater-influenced, low

to medium gradient, with sand-dominated substrate (DsoWF = 0.54mm, DsoSF =

0.71mm). The wetland-fed stream (WF) has a broader, flatter valley floor with several

lateral wetlands and drained a catchment of 26.2 ha with a gradient of 1.96%. The seep-

fed stream (SF) was more incised with a steeper, v-shaped valley, a 43.9 ha drainage

basin and a 2.11% gradient (Summer et al., 2003). Both watersheds are forested with WF

dominated by Nyssa biflora, Liriodendron tulipifera, Pinus taeda, and Quercus alba, and









SF dominated by Pinus glabra, Fagus grandifolia, Liriodendron tulipifera, and Quercus

nigra.

Hydrologic and Environmental Variables

The climate of the region is characterized by warm, humid summers, and mild

winters. Average temperatures in January, the coldest month of the year, range from

2.80C to 16.30C. July is the hottest month, with average temperatures ranging from

21.5C to 33.50C (SERCC, 2004). Mean annual precipitation is 1412 mm, with June

having the highest mean rainfall (152.1 mm) and October the lowest (77.5 mm) (SERCC,

2004). Summer rains are usually short, with high intensity events giving way to low

intensity frontal events from late fall to early spring. Due to close proximity to the Gulf

of Mexico, heavy rainfall associated with hurricanes and tropical storms is not unusual in

late summer.

Drought characteristics were based on regional precipitation data and flow data

from both study streams. Flow data were obtained from in-stream parshal flumes and

ISCO (Teledyne Isco, Lincoln, NE, USA) samplers (Summer et al., 2003) beginning in

2001. A standardized precipitation index (SPI) (McKee et al., 1995) was calculated to

assess the frequency and duration of droughts in the region based on monthly

precipitation averages for southwest Georgia (National Climatic Data Center, 2007). This

index is preferable over the Palmer drought severity index because it is easier to interpret,

more realistic over the long-term, and does not depend on a normal distribution of

precipitation (Guttman, 1999). SPI values less than one indicate a water deficit, and those

above one an excess. SPI values were calculated based on 3-, 12-, and 48-month running

averages to determine the presence of short-term, intermediate, and long-term droughts,









respectively. For example the three-month index for November 2002 is the average of

August, September, and October 2002.

Water temperature was measured from October 2001 through February 2007 with

an Onset HOBO temperature logger (Pocasset, MA), programmed to record

temperature every 15 minutes. Water chemistry and meteorological measurements have

been collected by other investigators as part of the Dry Creek Study, and these data were

available for use in this study. Monthly in-situ measurements for dissolved oxygen,

specific conductance, temperature, pH, and turbidity were made at eight sites (two per

stream) with portable meters. Grab samples were taken from a midstream location and

analyzed for inorganic nitrogen, inorganic phosphorus, and ammonium. Specific details

of data collection and sample analysis are in Jones et al.(2003). Values were In (X+1)

transformed prior to analysis to normalize data.

Invertebrate Sampling

Benthic macroinvertebrates were collected from four sample reaches (two per

stream, separated by 50 meters) with a 500-tm-mesh D-frame net (0.3 m wide) in

December and February for six consecutive years beginning December 2001, which

marked return of flowing water in both streams. Twenty samples (- 0.5 m) were taken

from each reach for a total of 3.1 m2 area sampled from all available habitats and were

combined into a single sample. Samples were preserved in 95% ethanol and identified to

genus using regional and national keys(Pescador et al., 1995; Epler, 1995;1996; Merritt

and Cummins, 1996; Pescador et al., 2000; Gelhaus, 2002; Richardson, 2003).

Chironomid larvae were quantitatively subsampled, mounted and identified following

Epler (1995) and Merritt and Cummins (1996).









Biological Traits

Nine biological traits were selected to characterize body morphology (i.e., size,

body shape, body armoring), life history (i.e., voltinism, resistance to desiccation),

mobility (i.e., occurrence in drift), and ecology (i.e., rheophily, habits, feeding

preferences) (Table 1). These were anticipated to vary in response to changes in

precipitation and display low statistical and phylogenetic dependence (Poff et al., 2006).

Some desired traits were omitted due to the lack of available information (e.g.,

fecundity), particularly within the chironomid genera. The nine biological traits were

divided into 30 modalities ranging from two to six levels per trait. Trait information was

collected from the literature (e.g., Viera et al., 2006), as well as through communication

with taxonomic experts. Trait information was coded at the generic level, except for some

Diptera and non-insect taxa, which were coded at the family or order level, respectively.

Where information on a particular trait could not be obtained for a taxon (in <5 % of

cases), zero scores were entered for each category so it did not influence overall results

(Chevenet, Doledec and Chessel, 1994). Individual taxa were then scored for the extent to

which they displayed the categories of these traits using a 'fuzzy coding' procedure

(Chevenet et al., 1994). Fuzzy coding allows taxa to exhibit trait categories to different

degrees (Chevenet et al., 1994) to take account of intraspecific variations in trait

expression (Charvet et al., 2000). The scoring range of 0 to 3 was adopted, with 0 being

no affinity to a trait category and 3 being high affinity. Traits were rescaled as

proportions (sum = 1), such that for each trait modality, values ranged from 0 (no affinity

among individuals for the modality) to 1 (all individuals had exclusive affinity for the

modality) and modalities summed to 1 for each trait. To describe the functional

composition of communities in terms of density of individuals, the proportion of each









category per trait was multiplied by the invertebrate abundances. This resulted in a trait-

by-site array that contained the density of individuals for each trait category for each site;

density was transformed (ln(x+l)) to approximate a normal distribution for the statistical

analyses.

Statistical Analysis

Environmental variables

Environmental variables were analyzed over time with repeated measures

ANOVA (SAS Institute, 2002). When differences were significant, post-hoc analysis was

conducted using Tukey's test and Bonferroni corrections. Additionally, environmental

stability was assessed by calculating Bray-Curtis distances (Bray and Curtis, 1957)

between adjacent years. Bray-Curtis distances are a measure of dissimilarity with values

ranging from 0 to 1. Zero denotes identical samples; thus, higher values denote lower

compositional stability. This measure is computed as:


DRh Z= a-, I


where DRh is the distance between samples i and h.

Stability

Compositional stability of invertebrate communities was examined separately for

the two streams between pairs of successive years. Stability was measured by calculating

Bray-Curtis distances between adjacent years based on abundance data and biological

traits. ANOVA was used to examine between year differences in compositional and traits

stability scores for the streams. The relationship between Bray-Curtis values and flow

and SPI values were regressed to assess the impact of hydrologic scale on community and

trait stability.









Ordination: species composition and traits.

Nonmetric multidimensional scaling (NMDS; Kruskal, 1964) was used to

explore temporal patterns in species composition and biological traits. NMDS is an

ordination method based on ranked distances between samples, and it is highly suitable

for ecological data that typically contain numerous zero values. First, a distance matrix

was constructed using Sorensen's metrics. To reduce the chance of local optima

(Legendre and Legendre, 1998; McCune, Grace and Urban, 2002), an initial ordination

with 1000 runs was conducted, and the ordination with the lowest stress value was used

as the starting configuration for NMDS. Stress is the square root of the ratio of the

squared differences between a monotonic transformation of the calculated

dissimilarities/distances and the plotted distances and the sum of the plotted distances

squared. The number of dimensions retained was evaluated after inspecting the stress

(goodness of fit) of solutions with dimensions 1 through 6, with values close to 0 being a

good fit of the data. Significance was assessed by conducting Monte Carlo tests using

999 runs of randomized data in the final ordination. A P-value was calculated as a

function of the number randomized runs that resulted in a stress less than or equal to the

observed stress (McCune and Mefford, 1999). Ordinations were performed separately for

each stream because preliminary analysis indicated that differences between sites masked

any temporal effects. Ordinations were performed on species abundances and abundance-

weighted biological traits individually.

A multi-response permutation procedure (MRPP; McCune and Grace 2002) was

used to test for significant differences in taxonomic composition and biological trait

structure over time at each stream. MRPP is a nonparametric method that examines the









null hypothesis of no difference between two or more apriori defined groups. The test

statistic A describes the degree of within-group homogeneity compared with that

expected by chance. MRPP was based on In (x+1) transformed abundance data and the

Bray-Curtis coefficient. Indicator species analysis (IndVal; Dufrene and Legendre 1997)

was used to identify significant indicator species discriminating among the time periods

for the species composition and biological trait data. IndVal is based on a comparison of

relative abundance and relative frequencies of taxa in different apriori groups. Good

indicator taxa are those occurring at all sites in a given group and never in any other

groups (Dufrene and Legendre, 1997). The indicator value ranges from zero to 100 and is

maximized when all individuals occur within a single group of sites. The significance of

the indicator values for each taxon was tested by Monte Carlo tests with 1000

permutations. All ordinations, MRPP, and indicator species analyses were performed in

PC-Ord ver. 5 (McCune and Mefford, 1999).

Results

Hydrologic and Climatic Patterns

SPI values ranged from -2.54 to 4.29 during the 50 year period from 1956 to

2006 in southwest Georgia (Fig. 1). Values greater than 2 are classified as extremely wet

and values below -2 as extremely dry (Guttman, 1999). Mean values for the 3-, 12-, and

48-month SPI during the 1998-2002 drought were -0.25 (SD = 1.06), -0.29 (SD =

1.42), and 0.55 (SD = 0.86) respectively. The drought prior to the study period (1998-

2002) was the worst of the past 50 years and the third worst of the past 100 years,

exceeded only by droughts from 1930 to 1935 and 1938 to 1944 (Barber and Stamey,

2000). The 1998-2002 drought had serious impacts on streams and rivers in the region,









with the number of zero-flow days reaching 20-50 year recurrence levels and the Flint

River displaying record low daily flows (Barber and Stamey, 2000).

The current study (late 2001 to 2007) occurred during a period of average

precipitation, with slightly above-average SPI values for months 3 and 12 (i.e., 0.13, SD

= 1.02 and 0.14, SD = 1.00, respectively) and a slightly below-average SPI value for

month 48 (i.e., -0.33, SD = 1.22). Additionally, hydrographs recorded flow throughout

most of the sampling period (Fig. 2), and the number of zero-flow days progressively

decreased over time in both streams, indicating a period of stream recovery. However,

SPI values in 2006-2007 indicate a return to a drought period, an observation supported

by occurrence of a substantial drought in Georgia in 2007-2008.

Environmental Variables

Although highly variable, environmental stability was relatively high throughout

the study, with Bray-Curtis values ranging from 0.03 to 0.15 (Fig. 3). Most

environmental parameters fluctuated over time regardless of changes in precipitation or

discharge (Table 2), however, some parameters changed significantly with time.

Ammonia remained low throughout most of the study, but doubled in the third year in

both streams (F5,41 = 2.3, P = 0.05). Values for pH were variable, but were highest

immediately following drought, decreasing thereafter (F5,41 = 4.7, P < 0.01).

Additionally, WF remained more acidic than SF throughout the study. Orthophosphate

decreased over time (F5,41 = 5.4, P = 0.02), but increased again in the 2006-2007

sampling period. In general, conductivity decreased following flow resumption (F5,41 =

2.3, P = 0.05) but increased again during the 2006-2007 sampling period. Temperature

decreased by four degrees over the study period (F5,41 = 5.1, P < 0.001), ranging from









120C to 160 C. Leaf fall peaked in the first year following the drought, but was reduced

by 50% the following year (F5,41 = 2.6, P = 0.04).

Benthic Macroinvertebrates

Community succession

Although the two streams differed extensively in terms of successional patterns

following drought, a number of species responded similarly at both sites. A core set of

taxa were present throughout the six-year sampling period at both sites including

Ceratopogonidae (Bezzia), Chironomidae (Parametriocnemus, Polypedilum, Tanytarsus,

Tribelos, Zavrelimyia), Decapoda (Cambaridae), Tabanidae (Chrysops), and Tipulidae

(Pilaria). Similarities in the second year included Chironomidae (Cantopelopia,

Orthocladiinae) and Ptychopteridae (Bittacomorpha), while those in the fourth and fifth

year of sampling included Trichoptera (Lepidostoma), Hemiptera (Microvelia), and

Odonata (Boyeria). The sixth year was the first year that no additional taxa were found

(Appendices 1 and 2).

Taxon richness increased significantly over time (F4,30 = 122.73, P < 0.001),

primarily during the initial three years of the study (Fig. 2-4A), but was consistently

lower in WF (F1,30 = 56.65, P < 0.001). However, taxon richness saturated with the same

number of taxa occurring from the fourth to the sixth year. Temporal progression of

abundance was more humped shaped, decreasing after the fourth year. Invertebrate

abundance increased similarly in both streams through time (F4,30 = 8.68, P < 0.001)(Fig.

4B), but WF consistently had significantly fewer individuals than SF (F1,30 = 19.94, P <

0.001).









Community stability

Bray-Curtis values for taxonomic composition decreased progressively from

2001 to 2006, with increased stability over time at both sites. However, Bray-Curtis

values decreased during the 2006 to 2007 period, indicating a change in community

structure to an earlier period (Fig. 2-5). Communities were more stable in wetter than

drier periods, as indicated by the negative relationship between Bray-Curtis values and

SPI values (Fig. 2-6). For SF, stability was significantly related to both local and regional

hydrologic and climatic indicators, however, stronger relationships existed with flow (R2

= 0.33, P<0.001) and the 48-month SPI (R2 = 0.5, P< 0.001). Only long-term 48-month

SPI values were related to stability in WF, with a similar negative relationship between

SPI values and stability.

Biological traits were relatively stable over time, and low Bray-Curtis values

suggested that traits were more stable than taxonomic composition (Fig. 2-7), while those

for WF were only significantly correlated with the intermediate 12-month SPI (R2 = 0.2,

P = 0.02). Biological traits for SF were not significantly correlated with local hydrologic

or regional climatic variables.

Taxonomic Composition

Wetland-Fed stream (WF)

NMDS ordination (stress = 10.8, P = 0.001) explained 88.4% of the variance in

the dataset, with 22%, 36%, and 31% explained by Axis 1, 2, and 3 respectively. Overall,

the ordination indicated temporal separation of species composition (Fig. 2-8) and was

supported by significant differences between all time periods (MRPP, A = 0.5, P< 0.001).

Axis 1 was primarily represented by local variables including pH (r = -0.5), dissolved

oxygen (r = -0.5), and turbidity (r = -0.4). The genera Calopteryx (r = -0.6), Chironomus









(r = 0.6), Chrysops (r = 0.6), Eukiefferiella (r = 0.7), Lepidostoma (r = 0.6), and

Pycnopsyche (r = 0.7) were most strongly correlated with Axis 1. Axis 2 was most related

toboth local and large-scale variables including pH (r = -0.4), dissolved oxygen (r = 0.4),

and the 12-month (r = 0.4) and 48-month SPI (r = 0.7). The genera Agabus (r = 0.7),

Boyeria (r = 0.66), Conchepelopia (r = 0.6), Erioptera (r = 0.8), Microtendipes (r = 0.7),

and Orthocladius/Cricotopus (r = 0.7) were most strongly related to Axis 2. Axis 3 was

correlated with dissolved oxygen (r = -0.5), and 48-month SPI (r = -0.5). The genera

Caecidiota (r = -0.6), Microvelia (r = -0.8), and Smitia (r = -0.7) were strongly

correlated with Axis 3.

No significant indicator species were found in the WF stream for the first three

years following drought. Taxonomic indicators of temporal change (P < 0.05) included

genera indicative of the fourth year such as Corethrella, Stenochironomus, Polypedilum,

Pseudolimnophila, Cordulegaster, Lepidostoma, and Scirtidae. Those having a maximum

indicator value for the fifth year were primarily predators and included

Cryptochironomus, Alotanypus, Clinotanypus, Bezzia, Alluadomyia, and Laevapex.

Those in the last year of the study included Larsia and Erioptera.

Seep-Fed stream (SF)

NMDS ordination (stress = 12.9, P = 0.001) explained 90.2% of the variance in

the SF dataset, with 77% and 13% explained by Axes 1 and 2, respectively. Overall, the

ordination indicated separation of species composition with time (Fig.9) and was

supported by significant differences between all time periods (MRPP, A = 0.5, P<

0.0001). Axis 1 was primarily represented by o-phosphate (r = -0.6), N02/NO3 (r = -0.4),

dissolved oxygen (r = 0.8), flow (r = 0.6), 3-month (r = 0.4) and 48-month (r = 0.7) SPI.









The genera Alluaudomyia (r = 0.6), Bezzia (r = 0.7), Corynoneura (r = 0.7),

Stempellinella (r = 0.6), Thienemaniella (r = 0.8), and Zavriella (r = -0.8) were most

strongly correlated with Axis 1. Axis 2 was most related to pH (r = 0.7), dissolved

oxygen (r = -0.5), and leaffall (r = 0.5). The genera Neoporus (r = -0.7),

Parachaetocladius (r = -0.6), Sphaerium (r = -0.6), and Pycnopsyche (r = -0.5) were

most strongly related to Axis 2.

Significant indicator species for the second year included Allocapnia, Helichus,

Parachaetocladius, and Stenelmis. The third year was mostly represented by shredders

and scrapers including Anisocentropus, Cordulegaster, Eurylophella, Habrophlebiodes,

Ophiogomphus, Pseudolimnophila, and Stempellinella. The indicators in the fourth year

included Baetidae, Psychoda, Scirtidae, Tribelos, and Zavrelimyia. The fifth year was

represented by Caenis, Calopteryx, Diplectrona, Microvelia, Nippotipula,

Rheotanytarsus, and Stenonema. The last year of the study was represented by

Corynoneura.

Biological Traits

Wetland-Fed stream

NMDS ordination (stress = 11.5, P = 0.001) explained 87.2% of the variance in

the dataset, with 53%, 10%, and 25% explained by Axes 1, 2, and 3 respectively.

Temporal changes were supported by overall significant differences between time periods

(MRPP, A = 0.3, P< 0.0001) (Fig. 10). However, pairwise comparisons indicated weak

changes in traits over time. Axis 1 was primarily represented by specific conductance (r =

-0.4) and 12-month SPI (r = 0.5) and thus related to intermediate temporal changes. Soft

bodied (arl, r=0.9), fast flow preferring (r3, r = 0.6), sprawlers (h4, r = 0.6) with bluff

and tubular shapes (sh2, r = 0.8) were positively correlated with Axis 1. Sclerotized (ar2,









r = -0.9), slow flow preferring (r2, r = -0.6), streamlined traits (shl, r = -0.8) were

negatively correlated with Axis 1. Axis 2 was negatively correlated with pH (r = -0.4).

Burrowers (h2, r = 0.8) were strongly correlated with Axis 2. Axis 3 was most related to

local, short-term variables including tss (r = -0.6), dissolved oxygen (r = 0.5),

temperature (r = -0.5), and 3-month SPI (r = 0.4). Collector-gatherers (trl, r = 0.8) with

several generations per year (v3, r = 0.6) were positively related to Axis 3. Those with

one generation a year (v2, r = -0.7), hard shells or cases (ar3, r = -0.7), and a predatory

lifestyle (tr5, r = -0.8) were negatively related to Axis 3

Analysis of indicator species showed that early colonizers had sclerotized, tubular

or bluff bodies and are abundant in drift. Later years were characterized by species that

cling to the substrate, rarely drift, and are hard shelled or made a case.

Seep-Fed stream

NMDS ordination (stress = 7.9, P = 0.001) explained 97% of the variance in the dataset,

with 80% and 17% explained by Axes 1 and 2, respectively. Overall, the ordination

indicated separation of species composition with time (Fig. 11) and was supported by

significant effects of time on trait composition (MRPP, A = 0.4, P< 0.0001). Axis 1 was

most related to leaf fall (r = 0.5) and the 48-month SPI (r = 0.4). Small (sl, r = 0.8) soft-

bodied (arl, r = 0.9) bluff or tubular (sh2, r = 0.8) individuals that gather food (trl, r =

0.8), with more than one generation per year (vl, r = 0.8), abundant in drift (dfl, r = 0.8),

and sprawled (h4, r = 0.6) or climbed (h6, r = 0.6) over the substrate were positively

related to Axis 1. Shredders (tr4, r = -0.7) and scrapers/herbivores (tr3, r = -0.7)

uncommon in drift (dfl, -0.8) with medium (s2, r = -0.6) to large (s3, r = -0.5)

streamlined (shl, r = -0.8) and with sclerotized (ar2, r = -0.8) or shelled (ar3, r = -0.8)









bodies and less than one generation per year (vl, r = -0.8) were negatively related to Axis

1. Axis 2 was correlated with N03/NO2 (r = 0.4). Small individuals (sl, r = 0.5) lacking

resistance to desiccation (d2, r = 0.8) with more than one generation per year (v3, r =

0.5), are common in drift (df2, r = 0.7), prefer fast flowing water (r3, r = 0.7) and cling to

substrates (hl, r = 0.8) were positively related to Axis 2. Medium-sized (s2, r = -0.7)

individuals rare in drift (dfl, r = -0.6) resistant to desiccation (dl, r = -0.8) with one

generation per year (v2, r = -0.5) that prefer slow flowing water (r2, r = -0.5), are

predators (tr5, r = -0.6), and burrow into the substrate (h2, r = -0.8) were negatively

related to Axis 2.

Indicator traits in the first two years included scrapers/herbivores with hard shells

or cases that climb on substrate. Those in the third year included genera with less than

one generation per year and not resistant to desiccation. The last two years following the

drought were represented by predators and skaters preferring fast flowing water.

Discussion

Few studies have attempted to dissect the functional and structural responses of

aquatic communities to a severe, unpredictable drought event (Boulton and Lake, 1992;

Wood and Petts, 1999; Wright et al., 2001; Churchel and Batzer, 2007). Studies on the

impacts of short-term wet and dry season cycles have provided insight into predictable

climatic variation, primarily in Mediterranean and arid climates (Gasith and Resh, 1999;

Acuna et al., 2005; Beche, McElravy and Resh, 2006; Bonada et al., 2006). In this study,

regional precipitation indices (SPI) were good predictors of temporal changes in both

taxonomic composition and biological trait structure in perennial streams. Communities

became more stable over time and were significantly more stable in wet, rather than dry,

years. Temporal changes in community composition and trait structure resulted in a









rapidly stabilizing community within the first three to four years after drought, producing

highly stable and persistent communities in the fourth and fifth years.

Stability was maintained throughout the occurrence of a large discharge event 4-6

months before collection of the fifth-year samples (Fig. 2). Recolonization after flood

events is rapid, limiting effects to short-term changes in abundance and community

composition (Townsend, Doledec and Scarsbrook, 1997). Beche, McElravy and Resh

(2006) also found that invertebrate communities and trait characteristics were more stable

in wet, rather than dry, season communities and postulated that droughts have more

severe long-term consequences than flooding for invertebrate communities.

Traits changed less with time than taxonomic composition and were more stable.

This may be a product of the high functional redundancy existing among aquatic

invertebrates (Poff, 1997; Lamouroux, Doledec and Gayraud, 2004). For example,

although climatic variation can change species presence, multiple species share similar

traits, allowing taxa to survive during changing conditions. The role of local and regional

abiotic filters are discussed below in relation to temporal changes in structural (e.g.,

taxonomic) and functional (e.g., traits) aspects of invertebrate communities as a result of

a disturbance imposed by a long-term drought.

Environmental Variation

Environmental stability was relatively high but highly variable throughout the

study, with Bray-Curtis values ranging from 0.03 to 0.15 (Fig. 3). However, local water

chemistry variables did not follow changes in precipitation or flow. This may be linked to

high connectivity to the floodplain and oxygenation of the hyporheic zone; these

interactions are typically lost during severe drying events (Boulton, 2003; Lake, 2003)









Droughts act on local stream variables by concentrating nutrients and organic

matter, and potentially increasing temperature (Closs and Lake, 1995; Stanley, Fisher and

Grimm, 1997; Matthews, 1998; Golladay and Battle, 2002; Dahm, 2003). A decrease in

o-phosphate following drought reflected flushing of stored nutrients during increased

flow periods (Dahm, 2003). Ammonia peaked in the third year in both streams, reflecting

increased microbial activity and organic matter. Massive amounts of organic matter are

typically stored in the stream channel and floodplain during drought. Initial flushes from

early flow events may not have been enough to carry organic matter from the floodplain

into the stream, however, a large flow event in the spring prior to the third sampling

period likely made a large amount of organic matter available. Baldwin (2005) also

suggested that peaks in ammonia following drying events might have originated from

dead bacterial cells. As in other studies, a coupled decrease in water temperature and

increase in discharge led to higher overall dissolved oxygen values (Stanley, Fisher and

Grimm, 1997; Matthews, 1998; Golladay and Battle, 2002). Conductivity also decreased

with time, reflecting dilution of concentrated ions typically found during drought

(Stanley, Fisher and Grimm, 1997; Caruso, 2002; Line et al., 2006) and may have been

linked to greater contribution of groundwater versus surface flow found during dry

periods (Rider and Belish, 1999; Caruso, 2002).

Limited precipitation and water availability in the riparian zone altered local

landscape dynamics. Leaf fall within the riparian zone decreased following the drought,

indicating a recovery period from the drought, as trees often drop their leaves during

periods of moisture deficit (Escudero and del Arco, 1987). Although this may provide

more resources for invertebrates, leaf quality may be lower and thus limit decomposition.









Temporal Variation and Successional Patterns in Taxonomic Abundance

Broad-scale measures of macroinvertabrate communities were responsive to

temporal changes in environmental conditions. Overall abundance was more responsive

to short-term environmental variation than were taxa richness or stability. Taxa richness

was lowest immediately following drought, peaking in the 2004-2005 sampling period.

Changes in taxa richness have been linked to disturbance history in relation to short-term

and long-term droughts (Beche, 2006). As flow regimes recover, more favorable

conditions exist including increased habitat availability and heterogeneity, higher

dissolved oxygen levels, and dilution of nutrients.

A set of nine core taxa existed in both streams immediately following drought

forming a regional species pool adapted to extreme conditions. Most either have multiple

generations per year or a desiccation resistant stage. Crayfish typically respond to

drought by creating deeper burrows, which may also provide other species a refuge from

receding water levels (Boulton, 1989). The chironomid genus, Polypedilum makes

cocoons to resist periods of drying (Hinton, 1960). The presence of coleopteran adults

and hemipterans in WF immediately following drought reflect their ability to survive

outside of the stream and rapidly colonize via aerial dispersal (Ortega et al., 1991;

Wissinger, 1997).

Changes in taxonomic composition were linked to both local- and large-scale

environmental variables. Dissolved oxygen and pH were most linked to changes in

taxonomic conditions for local variables, while long-term 12- and 48-month precipitation

most influenced overall changes in taxonomic composition in WF. Low pH values in WF

excluded entire taxonomic groups, including Ephemeroptera and Plecoptera. Dissolved

oxygen is often posited to be a controlling variable for invertebrate communities in









streams and is closely related to water quality. The relationship of this variable with long-

term SPI values indicates the advantage of incorporating regional climatic data into

bioassessment protocols.

Temporal Variation in Traits

Traits were more related to local abiotic variables than to flow or long-term

precipitation indices. Initially, traits may be filtered by large-scale factors, including

climate and geology (Poff, 1997); thus at the smaller scale of two adjacent watersheds,

traits may vary locally. Across small, physiographically homogeneous regions (e.g.,

watersheds, ecoregions), sites are likely to be located within a single regional species

pool (Zobel, 1997). Thus, as predicted by the habitat templet model (Southwood, 1977;

1988; Townsend and Hildrew 1994), local characteristics at the reach scale directly

influence biological traits.

Traits responded predictably to changes in local environmental conditions. As pH

increased and nutrients decreased, species less likely to drift became more common in the

stream reaches. Initial availability of nitrogen and phosphorous allowed for early

colonization of scrapers (e.g., Boulton, 1991), as algal sources within the stream

accumulated on available substrate. However, this effect was not apparent in WF,

reflecting the lower productivity of grazers typically associated with colored, acidic

streams (Rosemond et al., 1992). Additionally, shredders became more common in the

second and third year, as previously exposed patches of organic matter became

submerged. In addition, species typically classified as detritivores (e.g., nemourid

stoneflies) may consume algal biomass, assuming the role of scrapers, especially in

streams with lower pH (Ledger and Hildrew, 2005). In a comparison of rivers affected by

drought in Italy, Fenoglio et al.(2007) documented an increase in collectors and a









decrease in shredders and scrapers with increased drought duration, suggesting a

predictable cyclic change in feeding habits with drought.

After a major disturbance, body size is hypothesized to increase as communities

stabilize. Accordingly, medium-sized species became more common as the community

stabilized, while smaller species were more common during the less-stable time periods.

Small body size is often related to shorter-life cycles, and might therefore serve as a

resilience trait. However, small body size may also allow for exploitation of refugia such

as the hyporheic zone during droughts or floods (Townsend, 1989), serving as a potential

source of colonizers (Dole-Olivier, Marmonier and Beffy, 1997). Thus, small body size

may also be useful for resisting impacts of disturbance (e.g., Townsend, Doledec and

Scarsbrook, 1997).

Organisms with longer life cycles require more stable habitat and water

chemistry. Adaptations to high variability were less common by the third year of

sampling, when species commonly had uni- or semivoltine life cycles and lacked

adaptations for resisting desiccation. Additionally, hardening of the exoskeleton reduces

mortality during periods of drying and floods. Sclerotized and hard-shelled organisms

were more common during the first two years after drought, while traits favoring soft-

bodied organisms became more common with time. Although there was a general trend

toward species lacking resistance to desiccation, many species in the streams appeared to

be adapted to some level of drying through a desiccation-resistant or diapause stage.

Although many traits responded predictably to the drought, streamlined

individuals were more common immediately following drought, reflecting the abundance

of adult dytiscid beetles and amphipods as early colonizers. Dytiscid beetles colonize









across large areas via aerial dispersal, while amphipods may persist in refugia by

aestivating in moist sediments or disperse through underground routes (Wiggins et al.,

1980; Harris and Roosa, 2002). In small coastal plain streams, discharge is lower than in

many montane headwater streams, thus streamlined bodies may not be necessary to resist

flow forces. However, within four years, species preferring fast flow, such as clingers,

became more abundant, suggesting that behavioral rather morphological adaptations to

flow may be a distinguishing trait of coastal plain streams.

Drought Prediction

A major hurdle that is often encountered when assessing impacts of extreme,

unpredictable events on aquatic ecosystems is the availability of data prior to the

disturbance (Lake, 2000; Lake, 2003). Although long-term datasets (>10 years) are

increasingly common in ecology, many geographical regions lack such data. Long-term

datasets allow for the prediction of drought via precipitation indices, changes in stability

and trait composition. The SPI utilized in this study indicated a trend toward a major

drought prior to the occurrence of such an event (Fig. 1). However, the 24-month SPI

may bemost relevant since most invertebrate life cycles require months to years. Values

fell toward 2001 levels in 2006-2007, and a drying period was evident after the last

sampling period. This observation is further supported by the occurrence of a severe

drought in the same region during 2007-2008 (U.S. Drought Monitor,

http://www.drought.unl.edu/dm/archive.html). Thus, use of long-term regional

precipitation data, which is more widely available than discharge and ecological data,

may provide a unique opportunity to study pre- and post-recovery aspects of extreme

events.









Stability of species composition decreased in both streams in 2006-2007,

reflecting the oncoming drought. This change was more striking in WF than SF, likely

because SF is buffered by groundwater inputs, while WF is dependent on surface water

inputs from a wetland headwater. Traits were relatively stable over the study period, but

decreased in the wetland-fed stream from 2005-2007. Additionally, predators and species

common in drift became more abundant in 2006-2007. Predators are linked to

disturbance and become more common in disturbed or degraded streams as resources for

other guilds are patchy (Rawer-Jost et al., 2000). This suggests return to a disturbed

condition where organisms have the ability to emigrate if environmental conditions

become suboptimal.

Biological traits have been advocated as good indicators of disturbance in aquatic

ecosystems (i.e. Doledec, Statzner and Bournard, 1999). One associated issue is whether

they predict changes in disturbance regime more effectively than taxonomic structure or

they are a complementary aspect that should be examined in disturbance ecology and

biomonitoring programs (Doledec and Statzner, 2008). The results are unclear, as studies

across biomes suggest they are more, less or equally as informative than taxonomic

structure (Stevens et al., 2003; Finn and Poff, 2005; Heino, 2007, Hoeinghaus,

Winemiller and Birnbaum, 2007). Although less apparent than changes in taxonomic

structure, stability of biological traits in this study indicated a disturbance during the

drought period and the potential for another disturbance during the 2006-2007 sampling

period. Thus, traits may be useful indicators of disturbance that can be compared across

watersheds. One caveat to this is that functional traits are thought to be relatively

insensitive to natural variation (Charvet et al., 2000; Statzner et al., 2001; 2005). The










current study focused primarily on natural variation in climatic conditions and indicated

changes in trait composition as a result of this variation. Thus, additional effort should be

devoted to distinguishing the effects of natural and anthropogenic disturbances when

devising biological monitoring programs.


















Table 2-1. Definition and codes for biological traits and modalities.

Trait Code Modality Trait Code Modality
Voltinism v1 Semivoltine Habit hi Clingers


Drying Resistance

Drift


Armoring


Maximum Size


Rheophily


Univoltine
Multivoltine
Absent
Present
Rare
Common
Abundant
Soft
Sclerotized
Case/Shell
Small (<9mm)
Medium (9-16mm)
Large (>16mm)
Standing
Slow
Fast


h2
h3
h4
h5
h6
Trophic trl
tr2
tr3
tr4
tr5
Shape shl
sh2


Burrowers
Swimmer
Sprawler
Skater
Climber
Gatherer
Filterer
Scraper/Herbivore
Shredder
Predator
Streamlined
Not Streamlined
(Bluff, Tubular)












Table 2-2. Mean annual values for environmental variables for the wetland-fed (WF) and seep-fed (SF) streams


Year Flow TSS NH4 o- NO2/NO3 Total Total pH SC DO Turbidity Temperature Leaffall
(L/s) (g/L) (pg/L) phosphate (pg/L) Phosphorous Nitrogen (uS/cm) (mg/L) (NTU) (C) (g/m2)
(pg/L) (pg/L) (pg/L)


WF 2001- 0.99 0.015 2.48 2.73 1.08 8.22 238.00 5.53 42.28 4.47 1.78 16.13 34.29
2002
2002- 2.52 0.001 6.28 1.75 0.00 3.69 278.28 4.73 30.60 7.34 0.19 12.15 12.29
2003
2003- 1.04 0.017 11.97 1.85 0.00 13.26 345.87 5.03 35.95 4.51 1.18 16.08 19.26
2004
2004- 1.76 0.003 2.88 2.49 2.34 4.90 233.30 4.87 24.90 7.62 1.23 12.00 21.26
2005
2005- 1.47 0.013 6.20 1.78 0.00 16.94 343.30 5.35 26.85 6.87 1.10 13.63 30.19
2006
2006- 2.58 0.008 3.93 3.01 0.00 9.61 291.87 5.11 33.68 8.99 0.63 13.05 24.55
2007


SF 2001- 0.02 0.004
2002
2002- 2.74 0.004
2003
2003- 3.07 0.008
2004
2004- 3.39 0.003
2005
2005- 5.36 0.016
2006
2006- 3.90 0.001
2007


45.46

27.24

23.74

18.86

12.43

25.69


77.00

51.25

51.75

39.00

30.25

27.36


212.46

285.97

237.73

232.05

218.54

203.76


84.03

94.85

70.90

74.98

60.93

82.80


15.68

12.73

15.90

11.73

13.05

12.05


38.25

16.23

22.18

26.06

29.76

25.84
















A

















' 1__r im r IU v '



B l II



E T





I --


U,

-1


















U,


CO CO 0 ) ~ O C U CN. 0 N ~ ) C CN. 0) (
UOU O CO CO CO N. N. N. O O O O O 0 0 0 0 0 0


CO CO 0 n UO CO 0 CN U0 N.- O CN U0 N. 0) CN ^- N. 0) T- ^- C
0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0) 0 0


Figure 2-1. Plot of Standardized Precipitation Index (SPI) values for southwestern Georgia,
from 1956 to 2007. A) 3-month, B) 12-month, and C) 48-month. Values above 2
indicate an extremely wet year, while values below -2 indicate an extremely dry year.


3


2


1

0


1



















































014 B

0 13

0 12

011

01

-009

OOOB
0 08
o6

007

0 006

005

004

00 3

002

001


7r232001 1127,001 4612002 V8 2002 12?12002 4/12003 730,2003 12/4,2003 4382004 8112004 12,112004 4/112005 7,2912005 12/412005 4/42006 8112006 12112006






Figure 2-2. Hydrograph based on mean daily discharge (m3/s) for each stream. A) stream with

wetland headwater (WF) and B) stream with seep headwater (SF).
















0.14


0.12


0.1 -




0.04






0.02


0
Figure 2-3.
0 -






Figure 2-3.


-m- WF
-e-SF


01-02 02-03 03-04 04-05 05-06 06-07


Temporal variability of Bray-Curtis stability values for environmental variables in
WF and SF ( SE).














-- WF A
-- SF
50



40 -


I-

40
1--
20



10 -



0
2001 2002 2003 2004 2005 2006




1800
B
1600 -4-WF
-B- SF
1400

1200

= 1000

800

600

400

200

0
0 -------------------------------
2001 2002 2003 2004 2005 2006





Figure 2-4. Temporal changes in taxon richness and invertebrate abundance. A) taxon richness
and B) abundance values (per 3.1m2) (SE) for individual years.















-- WF
0.6 -e- SF


S0.5
U


a 0.4






m 0.2


o.1


0
01-02 02-03 03-04 04-05 05-06 06-07




Figure 2-5. Changes in compositional stability (Bray-Curtis distance) in WF and SF (+ SE).

















48-month SPI
12-month SPI
0.7
A 3-month SPI
Linear (3-month SPI) R2 = 0.11
0.6 Linear (12-month SPI) R2 = 0.14
Linear (48-month SPI) R2 = 0.49

0.5


- 0.4





A A 0.2 A
ANA 0.2-


A0.1.


A I


A ~~Iii, *U


Ur A*
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2

SPI
0.8

B & 48-month SPI
0.7 m 12-month SPI
A 3-month SPI
Linear (3-month SPI) R2 = 0.18
S0.6 Linear (12-month SPI) R2 0.21
-Linear (48-month SPI) R2 = 0.51

0.5



0.4










^- 0.10

0 m


-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2
SPI


Figure 2-6. Linear regression of SPI values versus taxonomic stability. A) Wetland-Fed (WF)
and B) Seep-Fed streams.


A


AU














0.16
--- WF
0.14 --- SF


0.12

0.1

U

.o 0.08

U
.o.o6
0.06



0.04


0.02


0

01-02 02-03 03-04 04-05 05-06 06-07





Figure 2-7. Changes in trait stability (Bray-Curtis distance) in WF and SF (+ SE).



















- 01-02
A 02-03
03-04
04-05
m 05-06
S06O-07


no **
-SPI12


SPC \ 3 PI44
DO


+ +


-0 .5 .


























D.s .
os


















*OS.








-02 -


Sr


Figure 2-8. NMDS ordinations of logl0-abundance in site-year space and taxon-space for WF.

Time periods are indicated by different symbols. Ordination plots of taxa are based on

weighted-averaging.


1 .5 -


0n


C~ r,rr'

J4 llr
,' +4* f 4
ch.
+ +Hr +
fi:". tA~ih;. ".M! Afima.


C^*^ fe ^ "yi ,..
,,^ -E- r "'"l^ "-g
rk+.ll'i


""* rn,- 'I **'p
V F Xi i -h
*- -A, 4e:, .,
(, ~ a tC*1 he* (la .
*NI the
1: + u ng.
4ff, Lie I.M '.l
+ + V


1.4,:
Ki^~* rr l























LF




Oph_ NN

M


* 01-02

A 02-03

o03-04

* 04-05

*05-06
o 06-07


p *.


SPL4





0] "--_


-21J -1nj O. 1.0


Figure 2-9. NMDS ordinations oflogl0-abundance in site-year space and taxon-space for SF.
Time periods are indicated by different symbols. Ordination plots of taxa are based on
weighted-averaging.


-25 -15 -05 5 15


as







CN


L *.J
CI:f.


'OL~
:ci,
~ ~.p
* ~n
















A




DO
SPB



so A *0 -SPM2
ON
On
m01-02 Tr
A02-03 Te
003-04 .ts
04-05
+05-06
S06-07
-1'5
-25 -15 -05 OS 1.5
Atis 1
Aadml







+
0.ID







mJ rd
""'+ aa














-025 -0.15 -DS D05 0.15

AXs 1





Figure 2-10. NMDS ordinations of biological traits in site-year space and trait-space for WF.
Time periods are indicated by different symbols. Ordination plots of taxa are based on
weighted-averaging.














*01-02
SA02-03
03-04
.*04-05
A" 05-06
A-* 306-07


I S P 4.I










0.15









D+
Sa


a:
D.15





1.1+ +,













.-0.2 D D2
,,Ik





Axis I








Figure 2-11. NMDS ordinations of biological traits in site-year space and trait-space for SF.
Time periods are indicated by different symbols. Ordination plots of taxa are based on
weighted-averaging.
-0.15










weighted-averaging.









CHAPTER 3
TESTING BMP EFFECTIVENESS FOR SMALL COASTAL PLAIN STREAMS
USING MACROINVERTEBRATES AS BIOINDICATORS

Introduction

Headwater streams are tightly coupled with the surrounding riparian landscape.

Thus, changes in the structure of the riparian zone can affect water quality of larger

streams and rivers, since they are heavily influenced by headwater streams that feed them

(Meyer and Wallace, 2001). Headwater streams make up a majority of channel length

within stream networks and serve important ecological and biological functions by

delivering water, sediment, organic material, prey items, and nutrients to downstream

reaches (Sidle et al., 2000; Gomi et al., 2001; Meyer and Wallace, 2001; Wipfli and

Gregovich, 2002). As the importance of ecosystem services, such as water quality and

biodiversity, becomes more widely recognized, the need to protect aquatic resources

increases. Thus, proper management of terrestrial landscapes must take into account

needs of aquatic organisms and communities.

Numerous studies have found significant impacts of logging on physical and

chemical aspects of streams, including reduced large woody debris in streams (Golladay,

Webster and Benfield, 1987), increased sediment input (Beschta, 1978), discharge

(Hartman and Scrivener, 1990), nutrient inputs (Likens et al., 1969; McClurkin et al.,

1985), and decreased shading resulting in higher water temperature (Swift and Messer,

1971; Webster and Waide, 1982). Elevated light, temperature and nutrient concentration

can increase algal biomass within the stream, shifting the base of the food web from

allochthonous to autochthonous sources (Likens et al., 1970; Wallace and Gurtz, 1986;

Bilby and Bisson, 1992). The extent and impact of these effects are influenced by









geology, soils and vegetation of the catchment, the extent to which the riparian buffer

strip remains after logging, stream discharge, and channel gradient and morphology.

Changes in abiotic characteristics of a stream following logging can affect the

structure and function of the stream community, including periphyton (Lowe, Golladay

and Webster, 1986), fish (Garman and Moring, 1993) and macroinvertebrates. Logging

activities can disrupt stream invertebrate communities, but the magnitude and trajectory

of effects vary. Increased light penetration and warmer temperatures from canopy

removal, and nutrient enrichment in runoff from ground disturbance, increase aquatic

invertebrate density and/or biomass in streams (Newbold et al., 1980; Murphy et al.,

1981; Hawkins et al., 1982; Wallace and Gurtz, 1986; Campbell and Doeg, 1989; Brown

et al., 1997). Fine sediment loading, particularly in watersheds with steep slopes, can

reduce invertebrate populations following logging (Growns and Davis 1994, Waters

1995, Wood and Armitage 1997), clogging tracheal gills, and burying food sources. In

many cases, invertebrate communities shift from shredders to grazers (algae consumer) or

detritivores (collector-gatherer) (Haefner and Wallace 1981; Gurtz and Wallace, 1984;

Webster et al., 1992).

Although Stone and Wallace (1998) found shifts in dominance of taxa, there was

no loss oftaxa in logged versus unlogged sites. They posited that measures of taxon

richness may be useful for indicating presence of pollutants, but not for more discrete

disturbances. Long-term impacts of clear cutting were documented decades later,

stemming from recovery of riparian vegetation and canopy cover (Growns and Davis,

1991; Stout et al., 1993; Stone and Wallace 1998).









Although there are exceptions (e.g., Wallace and Gurtz, 1986), most studies

examining effects of riparian zone management on streams last only a few years, with

only a year of pre-harvest data, limiting the predictive power of post-harvest data.

Perhaps the assumption is that management activities are only important if they

supercede natural variation in environmental conditions. However, catastrophic

disturbances such as hurricanes and droughts potentially alter impacts of human induced

disturbances. Thus, it is important to incorporate natural disturbances into studies of

anthropogenic disturbances in aquatic ecosystems to generate more general predictions of

disturbance (Ward, 1998).

The impacts of forest management activities on aquatic ecosystems have been

well studied in the Northwest and Mid-Atlantic U.S., where there are steep slopes and

high-gradient streams, but little effort has been placed on streams in the Southeast coastal

plain (Stone and Wallace 1998; Kedzierski and Smock, 2001). These low-gradient

streams have shallow slopes and finer sediment (sand and silt) than montane streams and

thus are likely to respond differently to logging. Even fewer studies have investigated the

impact of logging within buffer zones (e.g, Kreutzweiser et al., 2005) even though this is

an acceptable practice throughout the Southeast (e.g., Georgia Forestry Commission,

1999). Additionally, it appears that no study has utilized biological traits, other than

feeding guilds, to understand impacts of forestry practices. The goal of this study was to

test the effectiveness of Georgia's best management practices for forestry along streams.

This was assessed through multiple years of pre and post-harvest sampling of

macroinvertebrates, water quality parameters, and invertebrate food sources.











Materials and Methods


Site Description

Four study watersheds were located within International Paper's Southlands

experimental forest in southwestern Georgia within the Dry Creek watershed, which

discharges to the Flint River. The first order headwater streams were labeled from A to D

(Fig. 3-1) since they did not have official nomenclature. Watersheds A and B were

shallow, floodplain influenced, wetland-fed streams, while C and D were incised, seep-

fed streams.

Geology

The watersheds were located on the Pelham escarpment between the Tifton

upland and Dougherty plain. Soils of the study sites were dominated by Ultisols. Riparian

soils were comprised of Chiefland and Esto series, which feature well drained fine sands

over clay loams. The lower slopes comprised Eustis series soils, which were loamy sands

over sandy loams and classified as somewhat excessively well drained. Upland soils were

Wagram, Norfolk, Lakeland, Orangeburg, and Lucy series, which are generally well

drained loamy sands over sandy clay loams, with the exception of the Lakeland Unit,

which has a sandy texture throughout and is characterized as excessively well drained

(USDA, 1939). This transitional area has bluffs and deep ravines that create cool

microclimates supporting rare plant species with northern affinities (Wharton, 1978).

Vegetation

Species composition of the vegetation was similar among watersheds. The upland

consisted of mature, planted pine, and the riparian areas were mixed pine and hardwoods.









Species dominating the overstory in riparian areas were: Nyssa biflora, Liriodendron

tulipifera, Pinus glabra, Magnolia virginiana, Fagus grandifolia, Liquidambar

styraciflua, Quercus nigra, and Quercus michauxii. Magnolia grandiflora was most

common in watersheds C and D (International Paper unpublished data). The upland of

each watershed was dominated by Pinus taeda, which was established at varying times

by hand planting. The midstory of all watersheds was generally composed of Carpinus

caroliniana, Ostrya virginiana, Acer rubrum, Acer barbatum, and Oxydendrum

arboretum. Magnolia pyramidata occurred in riparian areas and midslopes of watersheds

C and D.

Climate

The climate of the region is characterized by warm, humid summers and mild

winters with average annual precipitation of 1412 mm (SERCC, 2007). Temperatures

range from an average maximum of 33.5C to a minimum of 2.8 C. June has the highest

mean rainfall (152.1 mm) and October the lowest (77.5 mm) (SERCC, 2007). Summer

rains are usually short, high intensity events giving way to low intensity frontal events

from late fall to early spring. Due to proximity to the Gulf of Mexico, spin-off from

hurricanes and tropical storms in late summer is not unusual. Drought conditions

occurred during 1998-2002 and resulted in an accumulated rainfall deficit of 711-1270

mm in parts of southwestern Georgia (see Chapter 2).

Hydrology

Surface water flow in the Apalachicola-Chattahoochee-Flint river basin is lowest

from September to November and peaks during January to April due to higher rainfall

and decreased evapotranspiration (Couch et al., 1996). Streams and rivers in the Coastal

Plain receive substantial groundwater because they are typically deeply incised into









underlying aquifers (Couch et al., 1996). The study streams are first order, groundwater-

influenced, low to medium gradient, and have sand-dominated substrate. In-stream

habitat includes coarse woody debris, undercut banks, leaf packs, and fine roots.

Fiberglass parshall flumes (Tracom Inc., Atlanta, GA) were placed at the downstream

end of each reach. The four study watersheds average 39 ha, with average annual

discharge of 1.5 L/s prior to harvest (Summer et al., 2003; Summer unpublished data).

Experimental Harvest

The statistical design was BACI (Before After Control Impact) using a paired

watershed design, with two treatment and two reference first-order watersheds varying in

area from 24 to 44 ha. Watershed pairs were determined based on landscape morphology

and vegetative community, and treatment watersheds were randomly selected within each

pair. Watersheds A and B formed the first pair, with Watershed B selected for treatment.

Watersheds C and D formed the second pair, with Watershed C selected for treatment.

Each watershed was divided into an upstream and downstream reach, separated by at

least 50 m.

The reference watersheds did not receive silviculture treatments during the study

period. The remaining two watersheds were clearcut after 27 months of baseline data

collection (June 2001 to September 2003). Post harvest data collection continued until

February 2007. In treatment watersheds, the SMZ in the upstream reach was left intact

(intact SMZ), while 50% basal area was removed in the downstream portion (thinned

SMZ). SMZ widths were determined according to minimum recommendations in

Georgia BMP manual(Georgia Forestry Commission, 1999). Slopes less than 20%

received a 40 foot (12m) buffer and while those greater than 20% received a 70 foot

(21m) buffer.









Physical and Biological Measurements

Eight 50m sample reaches, two per watershed, were established 30.8 m

upstream of hydrology flumes. Three transects were established perpendicular to the

thalweg within each reach at 15, 30, and 45m to serve as in-stream data collection points

for physical measurements including channel cross-sections, canopy cover, and percent

cover of in-stream habitat. A survey of habitat unit and channel characteristics was

conducted longitudinally within established macroinvertebrate sample reaches once

before harvest (December 2001) and once after (October 2004). A 50 m fiberglass tape

was placed in the thalweg of the stream, along which boundaries between habitat unit

types (riffle, run, glide, pool, backwater pool, step, and undercut bank) were determined

and physical characteristics recorded. A backwater pool was defined as being slower and

deeper than a glide but lacking characteristics of a pool, such as scouring, deposition, and

presence of a deep section followed by a shallow tail downstream (i.e. measurable

residual pool depth). For each unit type, length, wetted width, and maximum water depth

were recorded. For steps and pools, a step height and residual pool depth were taken. The

length and diameter of channel obstructions (e.g., wood, roots) were recorded when the

object was primarily responsible for pool formation. The number of functional (e.g.,

ability to change stream morphology) and non-functional wood pieces greater than 10 cm

in diameter was recorded, and texture of the streambed (e.g., sand, silty-sand) was

visually assessed.

Habitat data were converted into percent cover, to define major habitat types to be

sampled for macroinvertebrates. Canopy photos were taken at each transect once before

and once after harvest with a digital camera fitted with a 180 hemispherical fisheye lens

to calculate % canopy cover.









Physical measurements

Water temperature was measured from October 2001 through February 2007 with

an Onset HOBO temperature logger (Pocasset, MA), programmed to

record temperature at 15 minute intervals. Stream flow, water chemistry, and

meteorological measurements were collected by other investigators and technicians as

part of the Dry Creek Study, and these data were available for use in this study. Stream

stage and discharge were recorded every 15 minutes by Isco Model 4320 Bubbler Flow

Meters at six sites: one in the stream at the outlet of watersheds A, B, C, D, and one in the

upstream portion of watersheds B and C (Summer, 2003). Monthly in-situ measurements

for dissolved oxygen, specific conductance, temperature, pH, and turbidity were made at

the downstream portion of each reach with portable meters. Grab samples of water were

also taken and analyzed for inorganic nitrogen, inorganic phosphorus, and ammonium

(Jones et al., 2003).

Energy sources

Sixteen leaf litter traps (surface area 0.26 m2 each) were positioned within the

riparian area: streambank (6), 10 m from the stream (6), and 20 m from the stream (4).

Following harvest, leaf litter traps 20 m from the stream were beyond the SMZ, while the

10 m samples were within but near the edge of the SMZ. Leaf litter was collected

monthly and dried at 600C for 48 hours and sorted into pine, hardwood, small woody

debris, and mast. A subsample of leaf litter from riparian zone samples was used for

nutrient analysis. Three samples were combined from each reach on a quarterly basis

(May, September, December, and February) and ground to a fine powder. A 3-5 mg

subsample was then analyzed for C:N ratios using a Carlo-Erba CNS analyzer.









Within each stream reach, ten randomly selected locations were sampled monthly

following harvest for periphyton, benthic organic matter (BOM), and macrophytes from

2003-2007. At each sampling point, a 0.25 m2 sampling quadrat was randomly tossed

onto the streambed. Periphyton and BOM samples were collected by inserting petri

dishes (17.34 cm2) into the streambed (Tett et al., 1978). Chlorophyll a was analyzed

spectrophotometrically (Sartory and Grobbekaar, 1984) to estimate periphyton biomass.

The contents of additional petri dishes were dried at 60 C for at least 48 hours, weighed,

burned at 550 C for five hours, and reweighed for ash-free dry weight determination after

cooling. Macrophytes were sampled by removing all vegetation above the sediment

surface that existed within a 0.25 m2 quadrat. These were then rinsed and dried at 600C.

BOM was square root transformed, and chlorophyll a was log-transformed prior to

statistical analysis.

Macroinvertebrates

Benthic macroinvertebrates were collected within established sample reaches with

a 500-pm-mesh D-frame net (0.3 m wide) using a multi-habitat sampling procedure

(Barbour et al., 1999) during December and February from 2001 to 2007. Within each

reach, 20 sampling sweeps (-3.1 m2) were made through all habitat types including sand,

woody debris, fine roots, and leaf packs. Samples were placed in 1 L bottles, preserved in

95 % Ethanol and returned to the lab for processing. Macrophytes were included after

2003 because they became a significant habitat type in the treatment watersheds. All

samples were processed by washing organic debris (leaves and woody debris) with water

onto a 500-pm-mesh sieve. Larval Chironomidae were subsampled (randomly selected

100 individuals) and mounted in CMC mounting media for both voucher specimens and

identification to genus. Macroinvertebrates were enumerated and identified to genus or









species using local and regional keys (Pescador et al., 1995; Epler, 1995;1996; Merritt

and Cummins, 1996; Pescador et al., 2000; Gelhaus, 2002; Richardson, 2003).

Biological Traits

Fourteen biological traits were selected to characterize body morphology (size,

body shape, body armoring, respiration), life history (voltinism, resistance to desiccation,

eggs cemented to substrate, and development and hatch times), mobility (occurrence in

drift), and ecology (rheophily, behavior, feeding preferences, microhabitat preference)

(Table 3-1) to delineate responses to changes in disturbance regime (Poff et al., 2006).

Some desired traits were omitted due to the lack of available information (e.g.,

fecundity), particularly for chironomid genera. The fourteen biological traits were divided

into 49 modalities ranging from two to seven levels per trait. Trait information was

collected from literature (Viera et al., 2006), as well as through communication with

taxonomic experts in the United States. Traits were coded and analyzed as in Chapter 2.

Data Analysis

Energy sources

Changes in leaf fall C:N ratios, periphyton, and BOM with time and treatment

were analyzed with repeated measures ANOVA (SAS Institute, 2002). Seasonal impacts

of harvest on periphyton biomass were assessed by grouping time periods into by wet or

dry seasons. The wet season was defined as May September, while the dry season was

October April. Multiple regressions were utilized to relate changes in BOM and

chlorophyll a in relation to environmental variables for each treatment. To reduce

impacts of multicollinearity on the regression model, Pearson's correlations were

calculated for each pair of environmental variable, and values greater than 0.6 were

removed. This resulted in pH and orthophosphate being removed from the dataset.









Environmental variables

Environmental variables were analyzed over time with repeated measures

ANOVA (SAS Institute, 2002). Since macroinvertebrate samples were taken during the

winter/spring period, only environmental data from this period were analyzed. When

differences were significant, post-hoc analysis was conducted using Tukey's test and

Bonferroni corrections. Additionally, environmental stability was assessed by calculating

Bray-Curtis distances (Bray and Curtis, 1957) between adjacent years. These measure

dissimilarity with values ranging from 0 to 1. Zero denotes identical samples; thus, higher

values denote lower stability and unity implies complete turnover.

Macroinvertebrates

The Florida Stream Condition Index (SCI) combines metrics that respond to

changes in human induced disturbance to yield a score reflecting water quality (Florida

Department of Environmetal Protection, 2004). Higher values indicate better water

quality. SCI values were analyzed by time and treatment effects using repeated measures

ANOVA (SAS Institute, 2002).

Stability of invertebrate communities

Compositional stability of invertebrate communities was examined for streams

between pairs of successive years (e.g., 1 vs 2, 2 vs 3, etc.). Stability was measured by

calculating Bray-Curtis distances between adjacent years based on abundance data and

biological traits. ANOVA then was used to examine between year differences in

compositional and biological trait stability scores for the streams.

Ordination: species composition and traits

Nonmetric multidimensional scaling (NMDS; Kruskal, 1964) was used to explore

temporal patterns in species composition and biological traits as in Chapter 2. Since the









experiment was designed as a paired watershed study (A paired with B and C with D),

ordinations were performed on the pairs separately. For comparing treatments, pre-

harvest samples were grouped together and compared with post-harvest reference and

treatment reaches. Ordinations were performed on species abundances and abundance

weighted biological traits individually.

A multi-response permutation procedure (MRPP; McCune and Grace, 2002) was

used to test for significant differences in taxonomic composition and biological trait

structure over time at each stream. Indicator species analysis (IndVal; Dufrene and

Legendre 1997) was used to identify significant indicator species discriminating among

the time periods for the species composition and biological trait data. All ordinations,

MRPP, and indicator species analyses were performed in PC-Ord ver. 5 (McCune and

Mefford, 1999).

Results

Energy Source

Benthic algal biomass estimated from chlorophyll a differed significantly between

treatments (F2,2834 = 102.4, P < 0.001) and seasons (F1,2834 = 40.8, P < 0.001) was twice

as high in the selective harvest treatment as in the reference and intact treatments during

the dry season (0.04 vs. 0.08 mg/m2). In the wet season, chlorophyll a was 50% greater

in the selective treatment compared to reference and intact treatments (Fig. 3-2).

Chlorophyll a was best predicted by phosphorous in the reference streams, conductivity

in the thinned SMZs, and was not predicted by any variable in the intact SMZ streams.

(Table 3-2).

BOM differed significantly between treatments (F1, 1992 = 66.5, P < 0.001),

increasing along a gradient from selective (12.5 0.5 g/m2) to intact (17.4 0.7 g/m2) to









reference (22.8 + 0.6 g/m2) treatments. Significant regressions were found for all

treatments, but were explained by different predictors. BOM was best predicted by

conductivity, oxygen, and turbidity in reference streams, by flow and ammonia in thinned

SMZs, and by flow and turbidity in intact SMZs (Table 3-2).

C:N ratios in leaf fall were generally high, ranging from 40 to 70. Values were

similar in the reference streams between pre and post harvest samples, but decreased

significantly after harvest in the intact (F1, 36 = 12.8, P < 0.01) and thinned (F1, 36 = 4.2, P

< 0.05) SMZs (Fig. 3-3).

Environmental Variables

Ammonia (F2,82 = 31.8, P < 0.001), total nitrogen (F2,82 = 55.8, P < 0.001), and

total phosphorous (F2,82 = 3.2, P < 0.05) varied significantly with harvest, but not over

time. Ammonia peaked three years following harvest, with levels 9 times higher than the

reference streams in the intact SMZ treatment and 6 times higher in the thinned SMZ

treatment (Fig. 3-4). Total nitrogen also peaked in the third year following harvest, with

values increasing by twenty percent in the harvested watersheds. Total phosphorous

peaked in the third year in the harvested watersheds, but was always lower than in the

reference watersheds (Table 3-3).

Dissolved oxygen levels increased over time (F4,82 = 13.9, P < 0.001) and ranged

from values of 5 9 mg/L, but were not affected by harvest. Temperature changed

significantly over time (F4,82 = 11.2, P < 0.001), ranging from 13-18 C. Although

changes relative to harvest were not significant, winter temperatures were 1-2 C higher

in treatment streams following harvest.

Flow increased over the course of the study (F4,82 = 5.7, P < 0.001) as

precipitation increased, more so in harvested watersheds than reference watersheds (F2,82









= 15.5, P < 0.001) after harvest. Flow ranged from 0.5 to 3.5 L/s in reference streams but

reached levels of 7.5 and 10 L/s in intact SMZ and thinned SMZ treatments, respectively.

Turbidity varied significantly over the course of the study (F4,82 = 2.6, P < 0.05), but did

not have any discernible temporal pattern. However, values increased significantly

following harvest (F2,82 = 22.1, P < 0.001), doubling in intact SMZs and tripling in

thinned SMZs compared with the reference in the first year following harvest (Table 3-3).

Macroinvertebrates

SCI values became more positive over time and with more extensive harvest,

indicating better water quality. These increases were most notable in selective harvest,

followed by intact SMZs and reference sites (Fig. 3-5).

Stability

Taxonomic stability increased significantly over time in all treatments (F5,88 = 6.7,

P < 0.001) as Bray-Curtis values decreased (Fig. 3-6). Trends in trait stability did not

change significantly with site or treatment over the course of the study. However, higher

Bray-Curtis values in the intact SMZ indicate higher species turnover (Fig. 3-7).

Taxonomic composition

Watersheds A (Reference) and B (Harvested). NMDS ordination (stress = 11.8,

P = 0.001) explained 89 % of the variance in the dataset, with 38 %, 11 %, and 40 %

explained by Axes 1, 2, and 3 respectively. Overall, the ordination indicated a distinct

separation of community composition based on harvest levels (Fig. 3-8) and was

supported by significant differences between reference and harvest samples (MRPP, A =

0.3, P< 0.001). However, post-harvest samples from thinned and intact SMZs were not

different. Axis 1 was primarily represented by total nitrogen (r = 0.8), ammonia (r = 0.5),

conductivity (r = 0.8), pH (r = 0.5), flow (r = 0.6), and turbidity (r = 0.8). The genera









Alotanypus (r = -0.6), Nippotipula (r = 0.5), Crangonyx (r = -0.8), Habrophlebiodes (r =

0.6), Helichus (r = 0.6), Stenelmis (r = 0.7), and Sphaerium (r = 0.6) were most strongly

correlated with Axis 1. Axis 2 was most related to dissolved oxygen (r = 0.5),

Nanocladius (r = 0.6), Parametriocnemus (r = 0.6), Bezzia (r = 0.6), and Erioptera (r =

0.5). Axis 3 was correlated with dissolved oxygen (r = 0.6), flow (r = 0.5), leaf fall (r = -

0.5), Cryptochironomous (r = 0.7), Polypedilum (r = 0.5), Conchepelopia (r = 0.6),

Alluaudomyia (r = 0.6), Simulium (r = 0.6), Sphaerium (r = 0.8), and Tanytarsus (r = 0.7).

For watersheds A and B, drought impacts separated along axis 3 of the NMDS, with

positive values leading to a recovery from disturbance. Harvest effects separated along

Axis 1, with positive values indicating the harvest induced disturbance.

Only one chironomid species, Parachaetocladius, was a significant species for

pre-harvest samples. By contrast, seven species were significant indicators for reference

streams after harvest. These were primarily predators or those consuming organic matter

and included Alotanypus, Caecidiota, Corethrella, Crangonyx, Ptilostomis, Sciomyzidae,

and Stenochironomus. Thirteen species were indicators for the thinned SMZ treatment.

They occupied a range of trophic habits and included Ablabesmyia, Calopteryx,

Cheumatopsyche, Cryptochironomous, Habrophlebiodes, Hemerodromia, Orthocladius,

Paralauterborniella, Peltodytes, Sphaerium, Stenelmis, Tanytarsus, and Theinemaniella.

Indicator species reflective of the intact SMZ treatment were primarily predators and

shredders including, Anisocentropus, Procladius, and Hexatoma (Table 3-4).

Watersheds C (Harvested) and D (Reference). NMDS ordination (stress = 12.9,

P = 0.001) explained 88 % of variance in the dataset, with 39 %, 31 % and 18 %

explained by Axes 1, 2, and 3, respectively. Overall, the ordination indicated separation









of the invertebrate communities by harvest regime (Fig. 3-9) and was supported by

significant differences between reference and harvest sites, but not between thinned and

intacts SMZs. Axis 1 was primarily represented by ammonia (r = 0.5), total phosphorous

(r = -0.5), dissolved oxygen (r = 0.6), flow (r = 0.7), and leaf fall (r = -0.4). Polypedilum

(r = 0.5), Tanytarsus (r = 0.5), Tribelos (r = 0.8), Simulium (r = 0.5), Habrophlebiodes (r

= 0.6), and Diplectrona (r = 0.5) were most strongly correlated with Axis 1. Axis 2 was

most related to ammonia (r = -0.5), total nitrogen (r = -0.5), and turbidity (r = -0.6).

Nippotipula (r = 0.6), Pseudolimnophila (r = 0.7), Bezzia(r = 0.8), Chrysops (r = 0.6),

Stenelmis (r = 0.6), and Helichus (r = 0.7) were most strongly related to Axis 2. Axis 3

was most related to total nitrogen (r = 0.6). Stempellinella (r = -0.6), Tanytarsus (r = -

0.6), Corynoneura (r = -0.6), Thienemaniella (r = -0.7), Stenelmiss (r = 0.6), and Helichus

(r = 0.7) were most strongly related to Axis 3. For watersheds C and D, Axis 1 of the

NMDS appears related to both disturbances, with drought samples having lower values

than reference, which had lower values than harvest samples.

Significant indicator taxa for the pre-harvest samples were primarily predators

and collector-gathers, including Parachaetocladius, Hexatoma, and Leptophlebia.

Eighteen taxa were significant indicators for the reference streams after the harvest

occurred, primarily consisting of predators and shredders. Four taxa were indicators for

the thinned SMZ treatment. All were primarily scrapers and collector gatherers and

included Decapoda (Cambaridae), Brillia, Elimia, and Paracladopelma. The indicator

taxa reflective of the intact SMZ treatment were predators, scrapers, filterers, gatherers,

and shredders, including, Cryptochironomous, Polypedilum, Stenochironomous,

Tanytarsus, Tribelos, Molanna, Triaenodes, Laevapex, and Hexagenia (Table 3-5).









Biological traits

Watersheds A (Reference) and B (Harvested). NMDS ordination (stress = 14.3,

P = 0.001) explained 91.1% of the variance in the dataset, with 66 % and 25 % explained

by Axis 1 and 2 respectively. Overall, the ordination indicated separation of community

composition with harvest regime (Fig.3-10) and was supported by significant differences

between reference and harvest sites, but not between thinned and intact harvest

treatments (MRPP, A = 0.2, P< 0.01). Axis 1 was primarily represented by ammonia (r =

-0.4), total nitrogen (r = -0.5), dissolved oxygen (r = -0.6), and flow (r = -0.4). Traits

positively associated with Axis 1 included burrowers (h2, r = 0.7) and collector-gatherers

(trl, r = 0.8), with sclerotized bodies (ar2, 0.7) and slow-hatching eggs (ht2, r = 0.8), that

are abundant in drift (df3, r = 0.6) and live in gravel (mh3, r = -0.7) and woody debris

(mh6, r = 0.7). Those negatively associated with Axis 1 included medium-sized (s2, r = -

0.7) sprawlers (h4, r = -0.6), filterers (tr2, r = -0.7), and herbivores (tr3, r = -0.6), with

less than one generation per year (vl, r = -0.6) and fast-hatching (htl, r = -0.7) cemented

eggs (ecl, r = -0.6) living in sand (mhl, r = -0.7) or rocks (mh2, r = -0.7). Axis 2 was

most related to total nitrogen (r = -0.4) and turbidity (-0.5). Traits positively associated

with Axis 2 included small (sl, r = 0.7), soft-bodied (arl, r = 0.7) individuals with

cutaneous respiration (rsl, r = 0.7), and rapid development rates (dsl, r = 0.7). Those

negatively associated with axis 2 included large (s3, r = -0.6) shredders (tr4, r = -0.6)

with tracheal gills (rs2, r = -0.8), slow development (ds2, r = -0.6) less than one

generation per year (vl, r = -0.6), and cemented eggs (ecl, r = 0.6).

Traits indicative of pre-harvest samples included sclerotized (ar2) collector-

gatherers (trl) and swimmers (h3) common in drift (df3), with long hatching (ht2) and

development (ds2) times. Those indicative of the reference streams in the post-harvest









period included bluff (sh2), soft-bodied (arl) predators (tr5) with short development

times (dsl) living in plant matter (mh4). Species in the thinned SMZ treatment were

medium-sized (s2) sprawlers (h4), living in sand (mhl) and gravel (mh3) substrate.

Species in the intact SMZ treatment included filterers (tr2) with semi-voltine life cycles

(vl) that are rare in drift (dfl) (Table 3-6).

Watersheds C (Harvested) and D (Reference). NMDS ordination (stress = 11.1,

P = 0.001) explained 95.1% of variance in the dataset, with 81 % and 15 % explained by

Axes 1 and 2, respectively. Overall, ordination did not indicate separation of community

composition by harvest (Fig.3-11) although MRPP did indicate significant differences

between reference and harvest samples. Axis 1 did not strongly relate to any

environmental variables. Shredders (tr4, r = 0.7) and swimmers (h3, r = 0.7) with tracheal

gills (rs2, r = 0.8), cemented eggs (ecl, r = 0.8), long development (ds2, r = 0.8) and

hatch times (ht2, r = 0.8) in fast turbulent water (r4, r = 0.7) with streamlined (shl, r = -

0.8), sclerotized (ar2, r = 0.9) bodies univoltine life cycles (v2, r = 0.5), living in detritus

(mh5, r = 0.7) were positively related to Axis 1. Collector-gatherers (trl, r = -0.6) and

sprawlers (h4, r = -0.6) with cutaneous respiration (rsl, r = -0.9) bluff bodies (sh2, r =

0.8) multivoltine life cycles (v3, r = -0.6), short development (dsl, r = -0.9) and hatch

times (htl, r = -0.9), abundant in drift (df3, r = -0.7), small (sl, r = -0.7), soft-bodies (arl,

r = -0.8) were negatively related to Axis 1. Axis 2 did not relate to any environmental

variable. Large-bodied (s3, r = 0.8) individuals were positively related to axis 2. Small

bodied (sl, r = -0.7), burrowers (h2, r = -0.7) not common in drift (dfl, r = -0.8) were

negatively associated with axis 2.









Traits indicative of pre-harvest samples included individuals with mid-length

hatching (ht2) and development times (ds2), semivoltinism (v2), sclerotized bodies (ar2),

swimmers (h3) and shredders (tr4), residing in silt substrate (mh7). Species in reference

streams during the post-harvest period included predators (tr5) respiring via spiracles or

plastrons living in detritus (mh5). Species in the thinned SMZ treatment included

herbivores (tr3) preferring sandy substrate (mhl). Species in the intact SMZ treatment

included individuals without cemented eggs living in woody debris (Table 3-7).

Discussion

The need for properly managed watersheds has become clear as estuaries and

deltas become inundated with sediment, nutrients, and chemical pollutants (Justic et al.,

1993; Long et al., 1994). Proper management of small streams will contribute

significantly to reductions in the downstream transport of these materials since headwater

streams account for 80 % of all stream miles (Gomi et al., 2002). Historically, logging

has been the most prominent land use in headwater streams, highlighting the importance

of protecting these systems during this practice. In this study, the impacts of logging in

Georgia's coastal plain had small, but significant impacts on aquatic communities and

their food sources. Although strong bottom-up effects occurred in the disturbed streams;

in general best management practices effectively protected the streams during clearcut

harvest.

Energy Sources

Terrestrially derived organic matter is the primary resource in many headwater

streams (e.g., Vannote et al., 1980). In the southeastern U.S., this food base is available

throughout the year due to the long growing season and may be less limiting in

undisturbed streams than in temperate zones (Roberts, 2002). In this study, leaf fall









quantity and quality was altered by harvest as well as natural disturbances. A severe

drought prior to the study led to a sharp decline in riparian leaf fall in all streams, likely

due to physiological responses of vegetation to changes in precipitation regimes.

Following harvest, a decline in leaf fall occurred in the harvested watersheds, while

reference sites continued to accumulate litter. Thus, the decrease in habitat and food

availability was accentuated in response to both the pulse and press disturbances.

Additionally, lower C:N ratios in rapidly growing herbaceous litter in the thinned SMZs

may have given invertebrates access to higher quality food.

The decrease in leaf fall was directly related to less storage of BOM in harvested

watersheds. As expected, a decrease in canopy in the logged sites decreased organic

matter inputs and availability, and increased algal and macrophyte biomass. Studies have

found logged sites to have significantly lower leaf biomass than reference streams when

no buffer strip was established (Golladay et al., 1989; Stout et al., 1993). However, this

study shows a clear loss in organic matter storage even with the retention of a protected

buffer zone. Although leaf fall from riparian vegetation is closely related to BOM, the

contributing area may depend on watershed characteristics. Lateral inputs into the stream

(Fisher and Likens, 1973) emphasize the importance of maintaining a wide buffer zone.

Additionally, leaves are carried into the stream with surface runoff. Thus, the extent of

the buffer zone may influence organic matter, altering food and habitat availability for

aquatic organisms.

Although less BOM storage is linked to changes in canopy cover, factors

affecting decomposition rates may play a role in BOM loss. In many streams

microorganisms and invertebrates are primarily responsible for decomposition (Petersen









et al., 1989), but this process is additionally linked to abiotic conditions. Less BOM was

stored in the sediment with increases in flow, ammonia, conductivity, and dissolved

oxygen. However, these changes were related to factors unique to harvest treatments. In

reference streams, a negative relationships with BOM and conductivity, dissolved

oxygen, and turbidity suggest an interaction between abiotic and biotic factors affecting

loss. As dissolved oxygen levels increased, higher decomposition rates may have been

responsible for decreases in BOM. This was likely related to an increase in microbial

biofilm and invertebrate abundance and diversity typically found at higher dissolved

oxygen levels (Allan, 1995). Decreases in conductivity were linked to flushing of the

streams as flow was restored following the drought. Additionally, drying of the

streambed releases S042- as reduced sulfur is oxidized, leading to an increase in

conductivity (Bayley et al., 1986; Devito, 1999). This increase reduces the solubility of

carbon, thus decreasing decomposition rates (Clark et al., 1005) and potentially reducing

invertebrate abundance.

In the harvested watersheds, the strong negative relationship found between BOM

and flow, suggests the loss of BOM is controlled primarily by physical factors.

Movement of organic matter and sediment occurs during most storm events in sandy-

bottomed, coastal plain streams and is more pronounced in the clearcut streams due to

increased runoff and peak flow (Golladay et al., 1987). Ultimately, this leads to trapping

of litter in discrete, spatially variable habitats, such as debris dams (Palmer et al., 1996).

Although flow was an important predictor of BOM storage, ammonia and turbidity also

played a role. In the streams with an intact SMZ, BOM increased as the water became

more turbid. Reaches draining the intact SMZ retained silt from upstream sections,









leading to habitat smothering, clogging biofilm and gills of macroinvertebrates (Allan,

1995). In the thinned SMZ, stored BOM decreased with increasing levels of ammonia,

reflecting the contribution of bacteria to leaf litter decomposition. Thus, discrete changes

in the physical structure of the stream due to harvest potentially limit ecosystem function

and food resources.

Although forested headwater streams obtain most of their energy from

allochthonous sources, periphyton is expected to become the dominant food and habitat

source as canopy cover is eliminated. In our study, streams with intact buffer zones did

not differ from reference streams, however, streams in thinned reaches had periphyton

biomass nearly double that of reference streams. Murphy et al.(1986) reported that

clearcut streams averaged 130% greater periphyton biomass than buffered and old growth

streams. Additionally, Brosofske et al.(1997) showed that logging practices that affect the

width of riparian reserves along streams also alter the amount of light reaching the stream

surface.

However, other factors may interact with photosynthetically active radiation to

determine standing stock of periphyton. In a study examining the impacts of selective

harvest in Canada, periphyton biomass increased both as light levels and water

temperature increased and buffer width narrowed (Kiffney et al.2003). Additionally,

foodweb structure (Wootton and Power, 1993; Hillet al., 1995) and nutrients (Hillebrand,

2002) can also be important in controlling algal accrual. In the reference streams,

chlorophyll a increased with increasing total phosphorous. In general, small headwater

streams are nutrient limited (phosphorous and nitrogen) (Elwood et al., 1981) and thus

periphyton responds rapidly to any increase in the water column. Additionally, Hart and









Robinson (1990) found strong bottom-up effect of phosphorous addition in streams

linking increased scraper abundance with higher periphyton biomass, emphasizing the

importance of nutrients in changing community structure. However, none of the

measured variables had a strong relationship with periphyton in the harvested streams,

indicating increases in light may be the primary factor contributing to periphyton biomass

in harvested streams.

Although few variables explained changes in periphyton due to harvest, discharge

levels in these streams were linked to the the type of primary production established in

these streams. Low flow in low-gradient compared to montane streams may allow for

growth of macrophytes as well as macroalga. Colonization by the macrophyte, Ludwigia

repens, in the harvested streams increased attachment surfaces available for algal cells.

Kedzierski and Smock (2001) found an increase in the macrophyte Sparganium and the

algal species Chara in response to logging in coastal plain streams in Virginia, which

they linked to increased macroinvertebrate abundance and biomass. They found that this

macrophyte served as an ideal attachment site for filterers (e.g., Simulidae and

Rheotanytarsus), thus increasing microhabitat diversity in logged reaches. Long-term

availability of periphyton and macrophytes may influence invertebrate community

structure years after logging, since overstory canopy cover will take years to decades to

limit light penetration (Fuchs et al., 2003).

Environmental Variables

Water temperature frequently increases in logged areas and has complex effects

on life cycles of stream biota (Hogg andWilliams, 1996). For example, it influences the

rate at which eggs develop and juvenile fish and invertebrates grow, which, in turn,

determines voltinism, rates of growth, and productivity (Allan, 1995; O'Hop et al., 1984;









Wallace and Gurtz 1986). Both winter and summer temperatures were 1-2 C higher in

treatment than reference streams following harvest, indicating long-term effects on biota.

While temperatures peaked at 18 oC during winter sampling periods, temperatures

exceeding 26C were common in the treatment watersheds in the late summer, potentially

excluding cool-water adapted invertebrates and fish. However, this did not result in

lower dissolved oxygen concentrations in the treatment watersheds, in part due to the

increased growth of macrophytes present throughout the water column. Additionally,

since a 1-2C is the predicted increase in temperature resulting from climate change

(Kundzewicz et al., 2007), the long-term effects of this temperature change may be useful

for predicting changes in temperature on aquatic biota.

Buffer zones along streams are expected to retain nutrients (Polyakov et al.,

2005), allowing them to be taken up by vegetation and assimilated into the terrestrial

ecosystem. However, ammonia levels tripled or quadrupled following harvest, increasing

from 10-15 pg/L to 30-50 ig/L. The U.S. EPA standard for ammonia is 27 pg/L

(USEPA, 1999), the threshold for potential toxicity for aquatic biota. Surprisingly,

concentrations were higher in the intact SMZ than in the thinned SMZ. In the intact SMZ,

runoff may still reach the streams, but is more likely retained with fine particles and

organic matter, contributing to bacterial production. Additionally, retention of silt in these

streams likely reduced benthic oxygen, leading to more ammonia. Ammonia adsorbs to

silt-clay fractions in streams (Silva and Williams, 2001) and may increase retention in

these reaches. Additionally, a prescribed bum in the watersheds may have also

contributed ammonia to the streams (Knoepp and Swank 1993). However, in the thinned









SMZs there appeared to be a balance between substrate flushing and inputs from runoff

so that benthic silt levels were reduced.

Macroinvertebrates

Both taxonomic and trait composition are expected to change in response to large

scale disturbances. The taxonomic similarity within streams increased over time

regardless of treatment. This was linked to recovery of the invertebrate community

following a long term drought (Griswold et al., 2008). Biological traits were stable over

the course of the study; however, there were trends related to harvest. Statzner et

al.(2004) also found that traits were relatively stable over large temporal and spatial

scales in Europe. This stability may be linked to the finite number of traits that are

available within a region based on climate and geologic features. However, strong

changes in environmental conditions are likely to alter stability of trait composition.

Winter flow values continued to escalate in the harvested watersheds over the final two

years, nearly doubling the flow rate compared to the reference watersheds. A decrease in

trait stability during this period in the treatment watersheds suggests that disturbed sites

may be less resistant to change. However, the extension of the study over a longer period

would be necessary to determine if this is the case.

Harvest led to a shift in dominant species associated with changes in the food base

and environmental conditions. The species responding to harvest in watersheds B and C

were different taxonomically, but shared similar ecological roles. For example, species

responding to harvest consumed benthic periphyton or organic matter present within the

water column. In watershed B this included sphaeriid clams, elmid beetles, and mayflies,

while in watershed C blackflies (Simulium), Tanytarsus midges, and mayflies

(Habrophlebiodes) increased in abundance. This shift to from detritus to algae and fine









matter is common in streams impacted by forest activities (e.g., Noel et al., 1986).

Differences in species composition between the harvested watersheds are likely linked to

habitat stability and flow regime.

The greatest structural and functional changes occurred in the thinned SMZs,

resulting in the lowest BOM and canopy cover, and the highest periphyton biomass.

Species in the thinned SMZs preferred to live in sand and were larger than in the other

stream reaches. This preference for sand reflects the regular scouring and lack of organic

matter in the thinned treatments. Additionally, larger body sizes and abundance of

herbivores are likely related to greater availability of periphyton in these treatments. Most

studies link herbivore abundance to increased periphyton biomass as a result of logging

(Gurtz and Wallace 1984).

The intact SMZ was dominated by filterers (e.g., Simulium), likely linked to

enhanced transport of organic matter from the clearcut section of this watershed.

Blackflies require faster flow and a stable source of attachment, conditions provided by

larger substrate particle size and abundant macrophytes present in watershed C. The

sphaeriid clams present in watershed B prefer slow flow and burrow in the fine sediment.

Fine particulates may enter the stream through bank erosion, or lateral inputs from runoff

and resuspension providing additional food (Anderson and Sedell, 1979). Harvested

watersheds typically export significantly more particulate organic matter than

undisturbed reference watersheds (Webster et al., 1990). Additionally, species living in

woody debris were an important component in this treatment. Windthrow resulting from

the 2004 hurricanes provided organic matter to this system that may have been flushed

out in the thinned treatment.









Invertebrates in the reference streams shared traits indicative of an undisturbed

forested headwater coastal plain stream. In general, species were soft-bodied and bluff,

indicating lower flow and less scouring. When left undisturbed, streams in this region

have riparian zones that limit high peak flows during storm events in these streams. For

example, soft-bodied tipulid larvae have limited ability to resist scouring and are easily

washed downstream. Thus, species with this trait are adapted to low-gradient,

undisturbed streams. Additionally, species in the reference streams were more likely to

prefer living in plant material derived from the riparian zone and thus are closely linked

to the riparian zone. Thus, biological traits were accurate predictors of functional

changes occurring in watersheds following a logging disturbance.

The utility of using biological traits and fuzzy coding for linking trophic habits

to disturbance lies in the catholic food preferences of many invertebrates. Species

historically thought to be shredders supplement their diet with algae, especially when this

food source becomes dominant (Zah et al., 2001). This flexibility in food choice may

limit the ability of bioassessment protocols to detect disturbance. However, many species

rely heavily on a primary food source, and little is known of their reproductive capacity

when faced with a less preferred food choice. Additionally, traits are stable over

interannual periods, allowing for more flexible sampling protocols (Snook and Milner,

2002). Thus, analysis of trophic habitat, combined with fuzzy coding, which allows

species to be assigned to multiple groups, will ultimately enhance the robustness of

sampling programs.

Anthropogenic disturbance in the face of natural disturbances

Water quality indices derived from ecological and taxonomic information on

aquatic invertebrates should be responsive to a gradient of disturbances within and









between streams. For instance, many water quality indices were initially derived to

understand downstream effects of points sources such as sewage (Kolkwitz and Marsson,

1909). However, the challenge to create indices that respond to non-point sources as well

as multiple stressors has brought this approach to the extent of its limits. In these indices,

lower values reflect poor water quality (e.g., pollution tolerant organisms), while high

values indicate good water quality (e.g., pollution sensitive species). However, the

Florida SCI was not responsive to the harvest treatments, suggesting the harvest streams

had better water quality than the reference streams two years after the harvest. The SCI

was highly responsive to natural disturbances, and values increased from poor water

quality to excellent water quality as streams responded to restoration of flow and

precipitation following the 1998-2002 drought..

A strong relationship existed between SCI scores and both flow and dissolved

oxygen, the primary factors responsible for recovery of invertebrate communities

following drought (Chapter 2). Harvest created a diverse range of microhabitats (e.g.,

light and temperature patches), likely providing more niches for other species.

Additionally, discharge was greater in the selective harvest treatment, which may have

buffered these streams from any drying over the course of the study. Lastly, as

periphyton levels increased in the selective harvest treatment, increased Ephemeroptera

abundance drove the SCI scores higher since this group tends to be a good indicator of

water quality.

The SCI has not been able to differentiate between reference and disturbed

streams in other cases. Vowell (2001) did not find evidence that the SCI was able to

discriminate between reference and logged sites in Florida. In a survey of 167 headwater









streams in Oregon, Herlihy et al.(2005) also found that environmental variation was a

stronger driver of changes in taxonomic composition than logging history. Further

support exists for the short-tem impact of harvest on streams. Kreutzweiser et al.(2005)

only found an initial peak in scrapers and filterers immediately following harvest in

watersheds with selective harvest. They also found that taxonomic structure differed

among headwater streams with similar characteristics within the same basin, providing

further support for the use of biological traits in bioassessment. Given the predicted

increase in natural disturbances, the value of these indices becomes questionable for

detecting anthropogenic disturbances. However, they have been used successfully for

detecting large disturbances such as urbanization and agricultural practices.

Describing and understanding variability in stream systems is difficult because

processes and patterns vary at different spatial and temporal scales (Wiens et al., 1986;

Roth et al., 1996; Allan and Lammert, 1999). Assemblages can vary at small spatial

scales, yet appear stable, or at least resilient, at larger scales (Rahel, 1990). This

phenomenon has been referred to as the shifting mosaic, steady-state model (Clark, 1991;

Moloney and Levin, 1996). The study streams were exposed to two press disturbances

and at least one pulse disturbance over a decade. The former included a drought lasting

from 1998-2002, logging in 2003, and a hurricane in 2004. The enhanced discharge

resulting from the storms did not influence taxonomic composition or trait structure.

However, the impacts of harvest and drought, discussed here and in Chapter 2, indicate

that natural variability needs to be taken into account when attempting to link changes in

land use to changes in structural and functional aspects of aquatic ecosystems.









Changes in forestry management practices over the past couple decades have

driven the need to understand impacts of logging along streams on water quality and

biodiversity. The assumption cannot be made that simply leaving a few trees along the

stream will protect it from land use within the watershed. Thus, more state management

programs have incorporated watershed slope into the equation for determining buffer

width (e.g., Georgia Forestry Commission, 1999). This study found evidence for long-

term impacts of properly managed SMZs on aquatic biodiversity and basal resources.

However, these effects were most pronounced in the first year following harvest. Thus,

models examining the impacts of SMZ management must incorporate direct and indirect

effects of forestry activities.



























Table 3-1. Biological trait definitions and modalities.


Trait Code Modality IlTrait Code Modality


Life History
Voltinism


Drying Resistance

Eggs cemented to substrate

Development Time


Egg Hatch Time


Mobility
Drift


Morphology
Armoring


Maximum Size


Shape


Respiration


Semivoltine
Univoltine
Multivoltine
Absent
Present
Yes
No
< 6 weeks
< 1 year
> 1 year
< 1 week
< 1 month
> 1 month

Rare
Common
Abundant

Soft
Sclerotized
Case/Shell
Small (<9mm)
Medium (9-16mm)
Large (>16mm)
Streamlined
Not Streamlined
(Bluff, Tubular)
Cutaneous
Tracheal Gills
Spirales/Plastron


Ecology
Habit






Trophic





Rheophily



Microhabitat


h1
h2
h3
h4
h5
h6
trl
tr2
tr3
tr4
tr5
rl
r2
r3
r4
mhl
mh2
mh3
mh4
mh5
mh6
mh7


Clingers
Burrowers
Swimmer
Sprawler
Skater
Climber
Gatherer
Filterer
Scraper/Herbivore
Shredder
Predator
Standing
Slow
Fast Laminar
Fast Turbulent
Sand
Rock
Gravel
Macrophyte/Algae
Detritus
Woody debris
Silt




















Table 3-2. Results of multiple regressions for chlorophyll a biomass and benthic organic
matter (BOM). Significance ofR2 values is given by (P < 0.05), ** (P <
0.01), *** (P < 0.001).

Response
Response Treatment Regression Equation R2
Variable

Chla Reference streams .02 + 0.005 (TP) 0.27***
Intact SMZ NS NS
Thinned SMZ -0.14 + 0.07 (SC) .36*

BOM Reference streams 2.6 0.47(SC) 0.24 (DO) 0.18(Turbidity) 0.67***
Intact SMZ 0.55 0.39(Flow) + 0.64 (Turbidity) 0.31*
Thinned SMZ -0.21 -.38 (Flow) 0.2 (Ammonia) 0.50***














Table 3-3. Average environmental conditions for winter sampling periods in reference (A,D), thinned SMZs (B1,C1), and intact SMZs
(B2,C2). Data are for pre-harvest (2001-2003) and post-harvest (2004-2008).
Total Total
NH4 o-phosphate NO2/N03 Total TotalSC DO Turbidity Temperature Leaffall
Year Flow (L/s) TSS (g/L) (g/L) (g/L) (g/L) Phosphorous Nitrogen pH (uS/) ( ) (NT) C) (g/m
(pg/IL) (|g/L) (|jg/L) p/L (y (uS/cm) (mg/L) (NTU) (C) (g/m2)
(pg/L) (pg/L)
A 2001-2002 0.998 0.015 2.48 2.73 1.08 8.22 238.00 5.53 42.28 4.47 1.78 16.13 34.29
2002-2003 2.520 0.001 6.28 1.75 0.00 3.69 278.28 4.73 30.60 7.34 0.19 12.15 12.29
2003-2004 1.041 0.017 11.97 1.85 0.00 13.26 345.87 5.03 35.95 4.51 1.18 16.08 19.26
2004-2005 1.759 0.003 2.88 2.49 2.34 4.90 233.30 4.87 24.90 7.62 1.23 12.00 21.26
2005-2006 1.472 0.013 6.20 1.78 0.00 16.94 343.30 5.35 26.85 6.87 1.10 13.63 30.19
2006-2007 2.579 0.008 3.93 3.01 0.00 9.61 291.87 5.11 33.68 8.99 0.63 13.05 24.55

D 2001-2002 0.019 0.004 4.54 45.46 9.42 77.00 212.46 7.23 84.03 5.25 4.03 15.68 38.25
2002-2003 2.735 0.004 0.00 27.24 7.85 51.25 285.97 5.88 94.85 7.85 2.95 12.73 16.23
2003-2004 3.068 0.008 7.65 23.74 4.41 51.75 237.73 6.85 70.90 6.82 4.03 15.90 22.18
2004-2005 3.386 0.003 1.68 18.86 3.00 39.00 232.05 6.61 74.98 9.39 2.98 11.73 26.06
2005-2006 5.361 0.016 6.59 12.43 9.40 30.25 218.54 7.12 60.93 8.79 4.51 13.05 29.76
2006-2007 3.900 0.001 4.85 25.69 2.38 27.36 203.76 7.09 82.80 9.88 2.61 12.05 25.84

B1 2001-2002 1.651 0.003 12.090 2.880 366.820 11.810 621.090 6.650 61.650 5.120 3.950 16.400 38.770
2002-2003 3.650 0.006 9.48 2.24 412.53 10.50 78.19 4.85 96.15 6.96 5.65 12.45 11.18
2003-2004 4.050 0.004 19.10 2.12 655.40 4.83 970.00 6.24 89.50 6.32 6.55 17.10 7.53
2004-2005 5.970 0.007 23.41 2.41 891.94 2.57 1165.21 6.15 72.00 8.65 5.18 14.15 8.30
2005-2006 5.410 0.005 31.80 1.90 1041.00 30.68 1256.39 6.61 71.40 8.06 4.55 14.55 9.02
2006-2007 10.370 0.002 17.88 2.27 346.90 6.43 535.03 6.26 87.95 8.40 4.19 13.05 8.75

B2 2001-2002 1.990 0.002 10.78 2.39 835.90 8.42 1058.00 6.50 80.80 4.71 3.40 16.70 51.13
2002-2003 2.650 0.003 1.89 2.56 824.67 4.69 1182.00 5.15 82.65 7.42 3.30 12.60 21.10
2003-2004 2.930 0.007 27.80 1.80 1161.00 6.84 1230.00 6.19 77.00 6.49 3.85 17.55 11.18
2004-2005 4.430 0.004 29.65 2.46 1480.00 4.78 1655.00 5.97 66.75 8.22 4.21 14.25 12.75
2005-2006 4.150 0.005 43.36 1.78 1523.00 5.05 1813.00 6.48 68.40 7.58 4.24 14.60 12.35
2006-2007 7.450 0.003 31.27 2.52 656.20 6.53 866.90 6.22 71.35 8.59 3.15 13.00 11.06
C1 2001-2002 0.088 0.001 6.89 5.61 1099.00 10.11 1344.00 7.80 101.55 8.13 4.15 13.70 39.97
2002-2003 3.730 0.001 0.00 4.28 1189.00 8.52 1580.00 5.80 106.30 9.17 3.15 12.30 14.15
2003-2004 5.280 0.005 13.05 4.97 900.80 15.77 1075.00 6.79 88.70 7.63 9.20 17.15 13.73
2004-2005 10.100 0.003 14.70 4.45 816.90 10.80 969.30 6.55 75.20 9.21 5.44 12.75 9.42
2005-2006 9.900 0.008 30.55 4.74 998.90 16.20 1290.00 6.90 78.90 8.19 8.83 14.25 15.57
2006-2007 9.830 0.001 16.58 6.20 818.20 7.94 1004.00 6.74 103.90 9.83 3.30 12.75 11.59


C2 2001-2002 1.630 0.003 14.18 3.89 1386.00 12.37 1541.00 7.45 84.90 6.87 5.15
2002-2003 3.290 0.002 14.94 2.56 1541.00 5.93 2062.00 5.95 89.95 8.52 3.05
2003-2004 6.190 0.005 16.92 4.26 1204.00 13.05 1413.00 6.57 75.65 7.22 7.40
2004-2005 7.450 0.006 26.48 2.82 1094.00 11.35 1267.00 6.32 68.10 8.97 5.93
2005-2006 6.760 0.013 48.33 3.42 1338.00 21.10 1653.00 6.78 70.90 7.70 8.08
2006-2007 7.610 0.002 16.75 2.40 1277.00 7.86 1410.00 6.46 91.50 8.71 4.62


15.90 24.20
13.40 16.10
17.25 10.55
13.15 21.17
14.95 19.70
13.20 17.30










Table 3-4. Indicator values for watersheds A and B based on taxonomic composition. Groups
are defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SMZ (3), and post-harvest intact SMZs (4).


Parachaetocladius
Alotanypus
Caecidiota
Corethrella
Crangonyx
Ptilostomis
Sciomyzidae
Stenochironomus
Ablabesmyia
Calopteryx
Cheumatopsyche
Cryptochironom us
Habrophlebiodes
Hemerodromia
Orthocladius
Paralauterborniella
Peltodytes
Sphaerium
Stenelmis
Tanytarsus
Thienemaniella
Anisocentropus
Hexatoma
Procladius


Group
1
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4


Indicator Value
37.5
44.3
39.5
27.8
38.6
43.7
44.7
39.8
44.2
36.6
26.4
41.8
35.5
25
30.3
42.3
30
44.8
49.6
34.5
30.3
32.4
34.2
37.1


p-value
0.007
0.000
0.012
0.040
0.000
0.001
0.005
0.008
0.004
0.012
0.042
0.008
0.020
0.045
0.039
0.005
0.016
0.004
0.001
0.025
0.040
0.020
0.016
0.019


- -- -- -










Table 3-5. Indicator values for watersheds C and D based on taxonomic composition. Groups
are defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SMZ (3), and post-harvest intact SMZs (4).


Parachaetocladius
Hexatoma
Leptophlebia
Corynoneura
Thienemaniella
Nippotipula
Pseudolimnophila
Bezzia
Alluaudomyia
Dixella
Psychoda
Sciomyzidae
Ophiogomphus
Cordulegaster
Amphinemura
Perlesta
Allocapnia
Anisocentropus
Helichus
Neoporus
Microvelia
Paracladopelma
Brillia
Cambaridae
Elimia
Cryptochironom us
Polypedilum
Stenochironomus
Tanytarsus
Tribelos
Hexagenia
Molanna
Triaenodes
Laevapex


Group
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
4
4
4
4
4
4
4
4
4


Indicator Value
31.2
31.6
35.7
34.2
44.3
39.5
34
36.4
35.4
48.9
50
37.5
54.9
42.6
36.7
42.5
38
37.1
41.8
36.1
46.7
41.1
34.8
45.6
38.4
33.5
30.4
42.1
33.6
36.2
34.6
24.2
27.6
39.8


p-value
0.023
0.034
0.019
0.049
0.003
0.002
0.002
0.001
0.038
0.001
0.001
0.010
0.000
0.005
0.027
0.006
0.018
0.028
0.009
0.035
0.002
0.004
0.006
0.001
0.005
0.022
0.039
0.008
0.026
0.019
0.033
0.031
0.043
0.005










Table 3-6. Indicator values for watersheds A and B based on biological traits. Groups are
defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SMZ (3), and post-harvest intact SMZs (4).

Trait Group Indicator Value p-value
df3 1 31.3 0.003
ar2 1 31.9 0.014
h3 1 38 0.000
trl 1 29.9 0.007
mh2 1 28.5 0.015
ds2 1 28.3 0.036
ht2 1 32.1 0.003
arl 2 26.6 0.005
tr5 2 29.4 0.007
sh2 2 26.2 0.008
mh4 2 29.7 0.002
dsl 2 29 0.004
s2 3 32.1 0.034
h4 3 28.8 0.030
mhl 3 30 0.040
mh3 3 32.2 0.014
v1 4 36.5 0.026
dfl 4 27 0.042
tr2 4 33.8 0.007










Table 3-7. Indicator values for watersheds C and D based on biological traits. Groups are
defined as pre-harvest all sites (1), post-harvest reference (2), post-harvest thinned
SMZ (3), and post-harvest intact SMZs (4).

Trait Group Indicator Value p-value
v2 1 27.1 0.012
ar2 1 29.9 0.013
h3 1 32.7 0.023
tr4 1 33.1 0.001
mh7 1 30.9 0.002
ds2 1 30.3 0.001
ht2 1 29.5 0.007
h5 2 44.7 0.003
mh5 2 32 0.003
rs3 2 33.3 0.009
tr3 3 29.9 0.010
mhl 3 28.9 0.023
mh6 4 30.3 0.022
ec2 4 26.3 0.047













li---- Fi* .L
A. F W,

SHanw Cia "
1 I Ihi- H- ..Y-t H ?I -
.
....--

II .



-,. '





.. --. ,














O Wet Season
* Dry Season


0.1



0.08

E
E 0.06



0.04



0.02



0




Figure 3-2.


Average chlorophyll a biomass (+SE) during the wet (May-September) and dry
season (October-April) from 2004-2008 in reference, thinned SMZs, and intact SMZ
streams after harvest.


Reference Thinned Intact














O Pre-harvest
* Post-harvest


T


Reference


Intact SMZ


Figure 3-3. C:N ratios of leaf fall from the riparian zone in reference and harvested watersheds
before (2001-2003) and after (2004-2007) harvest.


60


50
0

040
Z
3O
30


20


10


0 !---


Thinned SMZ















-2- Reference
-A-Thinned
-e- Intact SMZ


50.00



40.00



30.00

Z

20.00



10.00



0.00



Figure 3-4


SAverage ammonia (NH4) concentrations (+SE) in reference, thinned SMZs, and
intact SMZ streams. Harvest treatments were applied prior to the third sampling
period.


60.00


-


2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007
































2002 2003 2004 2005 2006 2007


SStream condition index (SCI) scores (+SE) for reference, thinned SMZs, and intact
SMZ streams. Samples below the red line indicate poor water quality, those above the
red line, fair water quality, and those above the blue line, good water quality.


10

0



Figure 3-5











1.6

-0- Intact SMZ
1.4 -A- Thinned SMZ
S-- Reference

1.2


5 1


S0.8


S0.6


0.4


0.2


0 -
2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007


Figure 3-6. Taxonomic stability (+SE) for reference, thinned SMZs, and intact SMZ streams.












0.35
-e- Intact
-A-Thinned SMZ
0.3 -- Reference


0.25


> 0.2


0.15_


0.1


0.05


0
2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007



Figure 3-7. Trait stability (+SE) for reference, thinned SMZs, and intact SMZ streams.









1.0 Harv



So A2
SA DO ** o3
S o *4
Flow TN
SNH4 Turb
A sc
0.0 A
A A U
A / pH

Co A A LF p
CL LF





-1.0- U










-2.0
-1.0 0.0 1.0
Axis 1



Figure 3-8. NMDS of taxonomic composition in watersheds A and B in pre-harvest (1) and in
post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).










1.5 Harv

*1
A2
o3
*4



0.5 A A
A A

Phosph "A A A DO o

LF *
x Flow
< r

Temp,
o NH4
-0.5 TN
Turb*





**

-1.5
-2.0 -1.0 0.0 1.0
Axis 1


Figure 3-9. NMDS of taxonomic composition in watersheds C and D in pre-harvest (1) and in
post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).





















A U

A A
A A



AA
A
.0


h5












dsl rl
tr
rs3 htl r *s1 ih2
mhl dl h6* '2*es*tri
S d2*sh2*.mh4ec2
tr2 mh3 h m.7.dfl 3 h2 f3 .h3
s2 es2 r3
t3 h ds3 shf2 ht2
e mh
r4 rs2
ecl
tr4


Axis 1


Tss


LF
DO
NH4
Flow
TN
Turb
SC


Axis 1


Figure 3-10. NMDS of biological traits in watersheds A and B in pre-harvest (1) and in post-

harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).





102


I I I I I































S 0 o00
OA
: .-


0*


Axis 1


h6 r3
tr. mh4
.v3
htl arlp slmh2 tr2 tr3
h .sh2 d
mh3* *ec2
mlh6
mh "6
d1
ti
**


hi


v2

r2
dfl mh7

ar3


ecl
sl mh5

tr4
rs2 *.shl
ar2
ht2
ht3 ds2 *
ds3 *s3 rs
s2 *vl


Axis 1


Figure 3-11. NMDS of biological traits in watersheds C and D in pre-harvest (1) and in post-

harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).















103


Harv

"1
A2
03
*4


10.











10-
.2 0 0







-1 0







-20


*

A A
A
U


Harv

.1
A2
*3
*4


r4

3


I I I I I I I









CHAPTER 4
EFFECTS OF PATCH TYPE, QUALITY, AND SIZE ON MACROINVERTEBRATE
COMMUNITY STRUCTURE

Introduction

Spatial heterogeneity in landscapes strongly affects community structure (Bond et. al

2000) and population dynamics (Kareiva 1990). In the simplest case, increasing either habitat

types or patches provides more potential niches, allowing increased species diversity and

abundance. However, certain habitat types may be better suited for a species or group of species,

resulting in preferential habitat selections. Physical characteristics, environmental conditions

(e.g., oxygen, temperature), food resources and predation risk are important factors determining

patch suitability, and spatial aspects of food webs are key to understanding community structure

and dynamics (Holt 1977, 1996).

Low gradient, headwater streams in the southeastern coastal plain are typically dominated

by sandy substrate, yet they also have patches of leaf packs, woody debris, and root mats. Two

important habitat patch types in logged streams are leaf packs and macrophyte beds, both of

which vary in quality and quantity over space and time. Thus, streambed heterogeneity results

from seasonal inputs of organic matter and the rearrangement of these patches in shifting

mosaics (Stout et al., 1985; Hildrew and Giller, 1994; Wallace et al., 1995).Leaf packs can peak

in autumn after leaf senescence, while macrophytes peak in the late spring and summer during

the growing season. However, both are present at some level throughout the year. Thus, patch

size and location will be highly variable and depend on changes in canopy cover and

allocthonous leaf input. Colonization of streambeds by macrophytes, coupled with decreased

allochthonous input in logged streams, can alter the number of patches available for stream biota.

Temporal and spatial changes in stream landscapes lead to changes in size, isolation and

structure of habitat patches. Leaf packs and macrophytes potentially differ in their temporal and









spatial dynamics. Depending on stream bed stability and flashiness of flow, the structure of leaf

packs can change greatly with time (Palmer 1996, Velasquez 2003). In logged streams, the rate

of leaf pack formation is often slow, resulting in increased patch isolation and fragmentation.

Leaf pack formation occurs primarily in autumn as leaves senesce and fall into the stream. They

then become smaller and are rearranged within the stream as invertebrates process leaves and

increased flow scours the channel bottom. Unlike leaf packs, rooted macrophytes are more

stable in streams and contribute to a less dynamic streambed landscape. Thus, macrophytes may

support superior competitors, while leaf packs may support more transient, inferior competitors.

Differences in patch quality and size drive habitat selection by stream invertebrates. Leaf

packs vary in suitability as habitat and food, with fast decomposing leaves acting more as a

resource, and slow decomposing leaves acting more as habitat (Dangles et al.2001). Essafi

(1994) found that invertebrate biomass did not decrease in leaf packs after leaves lost most of

their nutritional value, suggesting that leaf packs act as habitat and potential refugia in addition

to being a consumable resource. Leaf packs may also enter the hyporheic zone and provide

resources for subsurface biota (Strommer and Smock 1989). Although few invertebrates

consume macrophytes, high quality resources for invertebrates exist in macrophyte beds,

including decaying plants, root exudates, root associated bacteria, epilithic periphyton and

detritus (Sagova 2002, Tolonen 2003).

Previous studies of static stream landscapes suggest that small patches support higher

densities than large aggregated patches (Palmer 2000, Silver 2000). However, these studies

focused primarily on leaf packs and a small group of organisms (chironomids and copepods).

Silver et al.(2004b) observed that chironomid density was greater in both fragmented landscapes

and less stable habitats.









Given the current state of knowledge of patch dynamics in streams, the goal of the this

study was to understand the role of patch type, size, and quality in structuring invertebrate

communities and colonization dynamics. It was hypothesized that larger macrophyte patches

provide both more cover and a greater source of food (epiphyton/biofilm) and increase

invertebrate abundance and diversity. Invertebrate abundance and diversity should be lower in

large leaf packs because their interior will offer reduced water velocity and oxygen. This was

assessed using a combination of field observations and experimental manipulations of patches.

Materials and Methods

Field Sampling of Patches

Macrophytes and leaf packs were mapped three times over a year at 20 m intervals along

the length of the study reach (- 200 m) by establishing transects perpendicular to flow and

determining percent cover of leaf packs and macrophytes. Samples were obtained from

randomly selected patches of macrophytes (Ludwigia repens) and leaf packs four times between

September 2005 and June 2006. A net (250 rm mesh) was positioned downstream of the patch,

and three leaves were taken from each patch and placed in individual vials containing 100 ml of

deionized water for chlorophyll a analysis. Three additional leaves were preserved in phospho-

buffered formalin (1%) for bacteria counts. Leaf samples were kept on ice until returning to the

lab where they were stored at -200C until analyzed. The remainder of the patch was collected by

removing only its above-sediment portion and allowing it to drift into the net. The contents of

the net were placed in a ziplock bag, placed on ice, and returned to the laboratory for processing.

In the laboratory, patch samples were gently rinsed through nested sieves of Imm

(CPOM) and 0.250 [m (FPOM). Macroinvertebrates were sorted from the samples and

preserved in 70% ethanol. Each sample was then separated into terrestrially derived CPOM,

FPOM, and macrophytes. Patch size was determined by placing each sample in a 500ml glass









cylinder with water to determine the volume of the patch by water displaced. Each portion

(CPOM, FPOM, and macrophytes) was then dried at 600C for at least 48 hours and weighed to

compare dry weights to volume for a given area. FPOM samples were ashed at 550C for five

hours to determine organic content.

Since many invertebrates consume bacteria and periphyton, chlorophyll a, ash-free dry

weight (AFDW), and bacteria counts were used as indicators of patch quality. Chlorophyll a and

AFDW were analyzed as in Chapter 3. Leaves for chlorophyll and AFDW measurement were

vigorously shaken in 50 mL of deionized water for 30s, after which leaves were removed to

measure surface area. Water samples were filtered through 45 [im GFF filters, and bacteria on

the filters were stained with SYBR Green and counted under an epiflourescent microscope.

Leaves were photographed, and Scion Image (Scion Corp., Frederick, MD, U.S.A.) was used to

calculate total surface area.

Bacteria enumeration followed the protocol outlined in Buesing (2005). A 0.2 [im,

25mm aluminum oxide membrane filter (Whatman Anodisc) was placed on top of a wetted 0.45

[lm, 25 mm cellulose nitrate filter on a glass filter manifold. Leaves for bacteria counts were

thawed and sonicated for one minute at 80 W while on ice. Then, the sample was vortexed, and

a 100 pl aliquot was removed after 10s. The sample and one ml nanopure water was added to

the filter manifold to ensure mixing and a homogeneous slide mount and pressure applied using a

vacuum.

The Anodisc filter was removed and gently dried using a Kimwipe. Filters were placed

face-up on a 100ul drop of SYBR Green II fluorescent stain diluted 400 fold (Molecular Probes,

Eugene, Oregon, USA) on labelled petri dishes. Filters were stained in the dark for 15 minutes,

then dried and placed face-up on a glass slide. A 30-uL drop of antifade mounting solution (50%









glycerol, 0.1% p-phenylenediamine, 50% PBS: 120 mMNaC1, 10 mMNaH2PO4, pH 7.5) was

added, and a cover slip was placed on top. Slides were then counted or stored frozen at -200C for

up to six weeks.

An Epifluorescence microscope equipped with a high-pressure mercury lamp (HPO 100

W), with a Chroma filter set (no. 41001; excitation filter 480 nm, beam splitter 505 nm, emission

filter 530 nm) was used to count bacteria. Cell numbers were counted from at least 10 fields

until a total of 400 bacterial cells was reached (Kirchman 1993). Preliminary counts from 25

slides were used to determine a size class distribution with a calibrated micrometer and placed in

the following classes: cocci (< 0.5 jm, > 0.5 jim diameter), vibrio, filamentous, and rod (< 0.35

jlm, > 0.35 jm). In subsequent slides, at least 15 cells from each size class were measured.

Volumes (V) of individual cells were calculated under the assumption that cells are

cylindrical with hemispheric ends (Fry, 1988), which works for both rods and cocci. The total

biovolume (BV) of bacterial cells per g of leaf material was calculated as:

BV (Z b,)VAf
DM SfAcDMi

where bi is the biovolume of an individual bacteria cell, Vs the sample volume, Af the total

filtration area, Sf the volume of the subsample passed over the filter, A, the filtration area, in

which bacteria were counted, and DM1 the litter dry mass.

Bacterial dry mass or carbon was calculated from bacteria BV based on empirically determined

conversion factors. For pelagic freshwater bacteria, Loferer- Krol3bacher et al.(1998) established

the following relationship:

dmb = 435bv 0.86

where dmb is the dry mass and by the biovolume of a bacteria cell.









Field Experiment

The goal of the field experiment was to control for leaf species, patch size, and patch age

to examine initial macroinvertebrate colonization patterns. Leaf packs consisted of dominant tree

species shared among watersheds B and C; Liriodendron tulipifera, Quercus nigra, and Pinus

spp. Leaves were collected in August 2006 prior to abcission and air dried for seven days.

Macrophytes were collected from seeps along the stream, washed thoroughly in distilled water,

and examined for invertebrates and biofilm before use. The macrophytes and leaf species were

used to create patches of 1, 2, or 4 g. A separate set often macrophyte samples were dried at

60C to determine a wet to dry mass regression and create an equivalent to the leaf packs prior to

the beginning of the experiment.

The three size classes were crossed with two levels of stability and four species in a

randomized block design. Blocks were created in a 10-20 m stretch of stream and replicated

three times along at 70 m length of each reach in the intact and thinned SMZ treatments in

watersheds B and C. Leaf packs were created by loosely tying leaves together using nylon line.

Macrophyte patches were anchored in the sediment using mesh produce bags (10" Vexar bags,

Avis Bag Co.). Leaf packs and macrophytes were tethered to pvc pipe driven into the streambed.

Stable patches were left undisturbed for 15 days, while unstable patches were disturbed once on

day 7 by rinsing the patch through the water column for one minute. Patches were then collected

after 7 and 15 days to determine colonization patterns.

Velocity, oxygen, and canopy cover were measured at each patch as potential

determinants of patch quality. Canopy cover was measured by taking four measurements using a

densitometer. Velocity was measured using a Marsh McBirney Flowmate 2000 (Frederick,MD).

Oxygen samples were taken by first removing a 10ml water sample from the patch with a 10 ml









syringe. Then, dissolved oxygen was measured using the micro winkler technique (Peck and

Uglow, 1990). Samples were fixed within two hours and returned to the lab for processing.

Leaf packs were rinsed through a 250 [im mesh sieve, and invertebrates were sorted from

the sample and identified. CPOM and FPOM trapped in the patch were separated, dried at 60C

for 48 hours, and weighed. Additionally, subsamples were taken and ashed at 550C to correct

for inorganic accumulation on leaf litter.

Data Analysis

Field observations

Independent and dependent variables were transformed to meet assumptions of normality

and independence. Analysis of covariance (ANCOVA) was utilized to determine the

relationship between invertebrates and patch type using size as a covariate. Multiple regression

was used to relate invertebrate metrics to patch size, epiphyton biomass, and bacteria abundance

and biomass.

Experimental manipulation of patches

A three-way ANOVA was utilized to relate changes in macroinvertebrate metrics to

initial leaf mass, species, and disturbance. Rarefaction was used to compare taxon richness

across samples after standardizing for patch size. Linear regression was used to relate the

expected number of species to the patch size. Multiple regressions were used to examine the

influence of canopy cover, dissolved oxygen, trapped FPOM and CPOM, and velocity on

macroinvertebrates.

Results

Field Observations

The total biomass of epiphyton (chlorophyll a) was not related to patch type or size.

Values were lower during autumn/winter than in spring/summer (F3,122 = 4.2, P<0.01) (Fig. 4-1).









Differences in total bacterial abundance related to patch type were dependent on patch size

(F1,115 = 4.6, P<0.05). Overall, abundance increased with linearly with patch size, but the slope

was greater for leaf packs than macrophytes. Temporally the number of bacteria cells decreased

from fall to winter and increased from spring to summer (F3,119 = 5.6, P<0.01), but did not

depend on patch size (Fig. 4-2). Total bacterial biomass was higher in leaf packs than on

macrophytes (F1l,11 = 11.8, P<0.001), but was not influenced by patch size. Total biomass per

patch changed with date, but was related to the size of the patch (F3,114 = 4.0, P<0.01). In

general, biomass increased with patch size, but an outlier led to high biomass in a small

macrophyte patch. FPOM trapped within patches increased in both patch types from fall to

summer (F3,122 = 15.0, P<0.0001). FPOM changed with patch type, but was dependent on patch

size (Fl,111 = 25.8, P<0.0001). FPOM in leaf packs increased with patch size, but did not

change with patch size of macrophytes. Further, the volume of FPOM trapped in leaf packs was

significantly higher than that in macrophytes (29.4 vs. 21.2 cm3).

Patch quality parameters were weighted for patch size. Bacterial biomass/cm3 changed

with date (F3,116 = 10.2, P<0.0001), but depended on patch type (F3,116 = 3.7, P<0.02). Biomass

was greatest in November for both leaf packs and macrophytes, but was higher in leaf packs

(Fig. 4-3). Bacterial abundance/cm3 changed with date (F3,116 = 12.4, P<0.0001), but depended

on patch type (F3,116 = 10.0, P<0.0001). Abundance was lowest in April for both patch types

(Fig. 4-4). Chla/cm3 changed with date (F3,122 = 4.0, P<0.001) and patch type (F,122 = 6.4,

P<0.02) and was higher for macrophytes on all dates except November (Fig. 4-5).

Changes in taxon richness with date (F3,118 = 6.0, P<0.01) and patch type (Fl,11 = 6.7,

P<0.001) were dependent on patch size. Taxon richness increased with patch size for leaf packs,

but did not have any relationship to patch size for macrophytes. After adjusting taxon richness









based on taxa/cm3, there was a significant effect of patch type (F1,116 = 53.8, P<0.001), date

(F3,116 = 12.6, P<0.001), and their interaction (F3,116 = 19.2, P<0.001) on taxon richness. Taxon

richness was higher in Ludwigia and greatest in the winter sampling period (Fig. 4-6). Changes

in invertebrate abundance with date (F3,116 = 7.1, P<0.001) and patch type (F1,116 = 17.5,

P<0.001) were dependent on patch size. There was a positive relationship between patch size

and leaf packs, but no relationship between patch size and macrophytes. After adjusting

abundance based on individuals/cm3, patch type (F1,116 = 43.8, P<0.001), date (F3,116 = 10.8,

P<0.001), and their interaction (F3,116 = 13.3, P<0.001) significantly affected abundance. In

general, invertebrates were more abundant in Ludwigia, peaking during winter (Fig. 4-7).

Changes in the proportion of shredders did not depend on patch size, but were different

between patch types (Fi,122 = 8.3, P<0.01) and over time (F3,122 = 3.5, P<0.02). Shredders were

more common in leaf packs moreso in the winter than in the summer. Differences in filterers

with patch type depended on patch size (Fl,11 = 12.9, P<0.001). Filterers were positively related

to patch size in leaf packs, but did not display any relationship to patch size in macrophytes, and

they were more abundant in summer than fall and winter (F3,122 = 5.9, P<0.01) (Fig. 4-8).

Predators did not change significantly over time, but differences between patches depended on

patch size (Fl,11 = 10.1, P<0.001). Predators increased with patch size in leaf packs, but

decreased with size in macrophytes. However, predators were more abundant in macrophytes

than in leaf packs ( 25 vs. 20 percent of community composition). Collector-gatherers did not

change over time, but the effects of patch type differed by patch size (F3,118 = 2.7, P<0.05). They

increased with patch size in macrophytes, but decreased with size in leaf packs. Overall,

collector-gatherers comprised a larger proportion in leaf packs than in macrophytes (34 vs 23

percent).









Regressions. Invertebrate abundance had a positive relationship with both bacterial

biomass and FPOM for leaf packs, but was only related to FPOM for macrophytes. Taxon

richness was positively related to bacterial biomass and FPOM for leaf packs and FPOM for

macrophytes. The proportion of shredders was positively related to patch size and negatively to

bacterial abundance for leaf packs and did not relate to any parameter for macrophytes. Scrapers

were positively related to patch size, chlorophyll a, and bacterial abundance for macrophytes.

Filterers were positively related to bacterial abundance, biomass, and FPOM for leaf packs and

to FPOM and chlorophyll a for macrophytes. Collector-gatherers were related to chlorophyll a

and FPOM for macrophytes (Tables 4-1, 4-2).

Field Experiment

C:N ratios varied among leaf species with Pinus (40.29) having the highest and Ludwigia

(14.7) have the lowest ratio. Quercus and Liriodendron were similar with ratios of 30.5 and

26.6, respectively. Leaf mass decomposition over time was dependent on leaf species (F2,273

148.4, P<0.001), disturbance (F2,273 = 9.9, P<0.001), and mass (F2,273 = 205.5, P<0.001). Pinus

and Liriodendron lost two to three times more mass than Quercus patches (Fig. 4-9). The

percent of leaf mass loss increased with time, but did not differ between disturbance treatments.

Larger leaf packs lost more mass over time than smaller leaf packs, with 4-gram packs losing

five times more than 1-gram packs (Fig. 4-10). However, when corrected for percent loss over

time, mass was not significant. On average, leaves lost twenty five percent of their mass,

regardless of initial mass.

Changes in velocity due to disturbance depended on mass (F4,408 = 5.8, P<0.001) and leaf

species (F6,408 = 2.2, P<0.04). Average velocity ranged from 0.04 to 0.06 cm/s. In general

velocities were lower in Liriodendron and higher in larger leaf packs. CPOM trapped within

patches was related to leaf species (F3,372 = 50.8, P <0.001), disturbance (F2,372 = 4.7, P<0.01),









and mass (F2,372 = 5.9, P<0.01). More CPOM was trapped in the 4 g patches than the 1 and 2 g

patches (Fig. 4-11). The amount of CPOM trapped in patches ranged from 0.2 to 1.7 grams. The

most CPOM was trapped in Ludwigia and the least in Pinus (Fig. 4-12). Additionally, more

CPOM was trapped in patches that were collected after fifteen days and were not disturbed (Fig.

4-13). FPOM trapped within patches was related to leaf species (F3,406 = 40.9, P<0.0001),

disturbance (F2,406 = 5.7, P<0.01), and mass (F2,406 = 11.1, P<0.0001). More FPOM was trapped

over time and with increasing patch size (Fig. 4-14).The amount of FPOM ranged from 0.05 to

0.3 g and was greatest in Ludwigia and least in Pinus and Quercus (Fig. 4-15). Oxygen within

patches was not different between any treatment.

Invertebrate abundance changed significantly between leaf species (F3,402 = 5.3, P<0.01)

and initial leaf mass (F2,402 = 12.6, P<0.001). Abundance was lowest in Ludwigia with an

average of 15 individuals and highest in Pinus and Liriodendron with an average of 30

individuals (Fig. 4-16). Invertebrate abundance increased with increasing patch size, from 20 to

44 individuals (Fig. 4-17). However, there was no apparent evidence for a relationship between

patch size and expected species richness whe sample size was accounted for. Taxon richness

changed significantly between leaf species (F3,402 = 6.6, P<0.001) and initial leaf mass (F2,402

19.5, P<0.001). In general, the number oftaxa did not differ greatly, averaging between 3 and 5,

with Quercus patches having the least number of taxa (Fig. 4-18).

The proportion of predators did not differ between treatments. The proportion of scrapers

was dependent on initial leaf mass (F2,402 = 4.3, P<0.02) and was higher in the 4 g than 1 g

patches (Fig. 4-19). The proportion of shredders changed in response to mass (F2,402 = 3.1,

P<0.05), leaf type (F3,402 = 3.4, P<0.02), and disturbance (F2,402 = 5.6, P<0.01), however, the

effect of leaf type depended on disturbance treatment (F6,402 = 2.5, P<0.03). In general,









shredders became more common over time, more so in the undisturbed treatments, while more

abundant in the largest patches, they were not abundant overall and only ranged from 0-6 percent

of the community (Figs. 4-20,4-21). The proportion of filterers changed in response to mass

(F2,402 = 5.9, P < 0.01 and leaf type (F3,402 = 10.4, P<0.0001) and were twice as common in

Ludwigia than any other patch type and were more abundant in larger patches (Fig. 4-22,4-23).

Collector-gatherers were the dominant feeding group in all patches, ranging from 40-60 percent

of the community. Collector-gatherers differed between leaf species (F3,402 = 6.02, P<0.001) and

were least abundant in Ludwigia (Fig. 4-24).

Regressions

Invertebrate abundance was positively related to CPOM, velocity, and canopy cover and

negatively related to FPOM. Taxon richness had a positive relationship with velocity and

CPOM. The proportion of scrapers was negatively related to increased canopy cover and

positively related to velocity. Filterers were positively related to FPOM and oxygen within the

patch. Shredders were not predicted by any environmental variable. Collector-gatherers were

negatively related to FPOM and positively related to canopy cover (Table 4-3).

Discussion

Stream invertebrate communities are structured by a mosaic of habitats ranging from

macrophytes and substrate diversity to small-scale changes in flow patterns. Community

composition is related to the quantity, quality, and distribution of detritus on the streambed in

headwater streams (Arsuffi and Suberkropp, 1985; Murphy et al., 1998), and plays a significant

role in the distribution, species composition, and total biomass of benthic invertebrates

(Hearnden and Pearson, 1991; Reice 1974). Thus, patch size and quality are two key factors

affecting colonization patterns of patches. In the current study, invertebrate density and









community structure were determined by complex interactions among patch size, type, quality,

and abiotic variables.

Patch Complexity

Patches with greater structural complexity generally support more species and higher

abundances as potential niches increase (Dean and Connell, 1987; Douglas and

Lake, 1994; Downes et al., 1998, Downes et al., 2000). In the study streams, Ludwigia typically

fills the entire water column, providing habitat for benthic species, swimmers, and clingers,

while leaf packs rest on the surface of the streambed. Submerged macrophytes increase the

physical complexity of aquatic environments, providing habitat for colonisation by invertebrates

(Heck and Westone, 1977; Crowder and Cooper, 1982; Gregg and Rose, 1982; Tokeshi and

Pinder, 1985; Lodge, 1991; Newman, 1991). Additionally, macrophyte architecture has a

influences food supply through detritus trapping (Rooke, 1984) and growth of epiphytic algae

(Dudley, 1988), leading in some cases to distinct invertebrate communities on different

macrophytes (Minshall, 1984; Rooke, 1986). As a result, macrophytes in the current study

supported higher densities and taxon richness on a per volume basis than did leaf packs.

However, in the short-term experimental study, they supported the lowest invertebrate density.

Macrophyte leaves are not consumed by invertebrates, but the epilithon and biofilm matrix is in

most cases (Newman, 1991). Additionally, since macrophytes are growing within the stream,

they may exude less nutrients than decomposing allocthonous leaf litter. Thus, macrophytes may

need more time than terrestrially derived leaves both to attract invertebrates and be to

conditioned with suitable biofilm, as seen in the current study.

Structural complexity may also enhance resources available within habitat patches (Diehl

and Komijow, 1998). FPOM trapped within patches provided the basis for higher invertebrate

abundance and taxon richness in the observational study. Higher amounts of FPOM provide









more surface area for bacteria and fungi, thus providing more food for invertebrates.

Additionally, since FPOM is easily flushed from habitats during storm events, higher FPOM

may indicate greater stability of the patch, providing more reliable habitat for invertebrates.

Ludwigia patches trapped the most CPOM and FPOM in the short-term experimental study.

This ultimately increased diversity of niches available to invertebrates and improved suitability

for colonization. Since macrophytes are anchored in sediment, they may act like debris dams,

trapping and holding organic matter during storm events. Thus, macrophytes have the potential

to take over some of the function of woody debris typically absent in logged streams. Although

macrophytes became abundant following logging, inputs of pine needles will likely increase over

the next decade since the watershed was planted with a monoculture of pine. As expected, pine

patches created the least heterogeneity and trapped little if any organic matter. Many timber

operations in the southern U.S. utilize pine plantations, which could have a negative impact on

invertebrates by decreasing structural complexity and overall storage of organic matter.

Patch Stability

In addition to structural complexity, habitat stability plays a large role in determining the

composition of patch inhabitants. Although the southern coastal plain does not typically receive

high-energy flows such as those present in snow-melt, relatively large events may occur during

hurricanes and smaller events with storm events common during summer. Thus, more stable

habitats are likley to be more attractive to invertebrates. Stability provided by Ludwigia

enhanced colonization by filtering invertebrates. Additionally, sandy-bottomed streams in the

coastal plain do not provide relatively immobile substrates such as cobble and boulders present

in the piedmont. Thus, invertebrates depend on availability of organic substrate introduced from

the riparian zone or growing within the stream including woody debris, rootwads, macrophytes,

and leaf packs. However, leaf packs are ephemeral, rapidly decomposing, and are subject to









being scoured from the streambed during storms. In addition, Ludwigia patches provide multiple

food sources for filterers, such as Simuliidae, by allowing them access to the water column and

by trapping large amounts of organic matter. Thus, Ludwigia can sustain filterers even at low

flows, when only small amounts of FPOM and bacteria are present in the water column.

Hydrologic disturbance can create a mosaic of stable and unstable patches within

streams. Olsen et al.(2007) found that invertebrate densities were greatest in stable patches

following an experimental simulation of flooding in streams. However, this difference only

existed for 14 days following the disturbance. In the current study, a small scale disturbance had

little impact on colonization patterns of invertebrates. The expectation was that disturbed

samples would be more similar to the seven-day samples than the undisturbed fifteen-day

samples. The disturbed samples appeared to resemble the fifteen-day samples in most cases and

were even higher than the undisturbed in some cases. This may be linked to the size of the

disturbance and presence of source populations nearby. Colonization is a rapid process in

streams, and most areas recover in 10-30 days following localized disturbances (Mackay, 1992).

Melo and Froelich (2001) found that invertebrates recolonized overturned stones within 4 days,

and densities became higher than those on control stones within a month. Thus, 7 days between

sampling may have been too long to see any differences. Although not significant, total

abundance and mass-weighted abundance were higher in disturbed than in seven day or

undisturbed samples. This may be linked to higher amounts of FPOM trapped in disturbed

samples, and an increase in collector-gatherers. Additionally, small scale disturbances that leave

biofilm intact are less likely to have long lasting impacts on habitat occupancy (Miyake, 2003).

Patch Quality

The quality of leaves as food affects the performance (i.e. growth rates and densities) of

benthic macroinvertebrates (Cummins and Klug, 1979; Sweeney and Vannote, 1986) and is









determined by the leaf composition and attached biofilms (Lock et al., 1984; Hax and Golladay,

1993), which consist of autotrophic and heterotrophic components. In this study, patch quality

based on biofilm composition was influenced by temporal changes in environmental parameters.

Bacterial biomass was highest in autumn, while chlorophyll a was highest in spring. This

reflects changes in canopy cover typical in headwater streams since light is a primary factor

limiting primary production (Hill and Knight, 1988; Hepinstall and Fuller, 1994; Hill et al.,

1995) and consequently influences the development and biomass of biofilms (Ledger and

Hildrew, 1998). Higher bacterial biomass is likely linked to the greater surface area provided by

decaying organic matter derived from the riparian zone, as well as decaying algae and

macrophytes present in the spring and summer samples. Additionally, higher bacterial biomass

in autumn may fuel algal growth in spring. Several studies have indicated the existence of a link

between algae and bacteria (Rounick and Winterboum, 1983; Hepinstall and Fuller, 1994;

Ledger and Hildrew, 1998) whereby bacteria benefit from algal exudates for an energy source, or

as a substratum for colonisation (Rier and Stevenson, 2002).

Historically the primary energy source in headwater streams was thought to be

terrestrially-dervived leaf litter and the bacteria and fungi associated with it (e.g., Vannote et al.,

1980). However, more current research found sufficient algal growth even in streams with high

canopy cover (Mayer and Likens, 1987). Though epiphyton is typically associated with

macrophytes, the present study found similar chlorophyll a for leaf packs and macrophytes,

except during periods of maximum irradiance (e.g., spring). Thus, both habitats have the

potential to support diverse macroinvertebrate communities. However, bacterial biomass was

higher on leaf packs, suggesting these are a higher quality food source. This was not supported









by the data since abundance and taxon richness of invertebrates were higher in macrophyte

patches.

In the observational study, filterers were best predicted by chlorophyll a in macrophytes

and bacteria in leaf packs. This supports recent findings that many invertebrates exhibit

plasticity when selecting resources (Friberg and Jacobsen, 1994). In addition to organic matter

sloughing from epiphyton, the structure provided by algae will aid in development of a biofilm

matrix. Additionally, filterers were positively related to dissolved oxygen within the patch,

which was higher in macrophytes since they extend into the water column and release oxygen

during photosynthesis. Switching feeding behavior has also been observed in shredders, mixing

algal and detritus based carbon sources (Friberg and Jacobsen, 1994).

Patch quality is also linked to refractory compounds in leaves that may alter biofilm

structure, decomposition rates, and nutrient availability for colonizing species (Ostrofsky, 1993,

1997). This may be especially true for shredding invertebrates that depend on biofilm as well as

leaf properties (e.g., Lignin content). Habitat selection by shredders was apparent in the short-

term experiment in relation to leaf palatability. After seven days, shredders were more common

in Pinus and Liriodendron than in the less palatable Quercus and Ludwigia. However, shredders

became similar among all treatments after fifteen days and were similar between macrophytes

and leaf packs in the observational study. This indicates that although shredders initially select

more suitable habitat, accumulation of organic matter in other patches creates adequate habitat

for this group. Bastian (2007) found that shredders were distributed across a broad range of leaf

species in a stream, with no leaf species being preferentially colonized by shredders. However,

most studies find that shredder species exhibit clear leaf preferences (Anderson and Sedell, 1979;

Mackay and Kalff, 1973; Nolen and Pearson, 1993), and selectively feed on food resources of









different palatability or quality (Arsuffi and Suberkropp, 1985, Campbell and Fuchshuber, 1995).

Although shredders are implicated in breakdown of organic matter in streams, they usually

colonize leaf packs later than other feeding groups. Shredders usually select leaves at advanced

stages of conditioning (Arsuffi and Suberkropp 1984, 1985; Mackay and Kalff, 1973, Petersen

and Cummins, 1974) due to increased microbial biomass and fungal degradative enzymes and,

thus, increased leaf palatability (Suberkropp, 1998). Thus, Quercus leaves may not be colonized

as fast due to their refractory properties, but still may provide more than adequate habitat. In

addition, a case-making caddisfly, Anisocentropus, was commonly found in cases made from

Quercus. This is likely due to its resistance to breakdown, to provide long term protection.

Patch Size

Increased patch size potentially creates more niches, providing a diversity of resources

and refugia from predators. Although the amount of mass lost from patches increased with patch

size, breakdown rates were similar when comparing initial masses. Contrary to my hypothesis,

this indicates that conditions inside larger leaf packs do not necessarily become less suitable for

decomposition and provide equal opportunity for biofilm formation. In the observational study,

bacterial biomass increased with patch size for Ludwigia, but not for leaf packs. However,

invertebrates did not respond positively to this increased resource base and niche availability. In

the observational study, the expected species richness was not related to patch size. This

suggests a lack of differences in resources with larger patches.

Patch size was a determinant of feeding guild structure. Scrapers did not select habitat

based on leaf type and were most abundant in larger patches. Most scrapers are classified as

clingers and thus need habitat that will support their mass and provide a substantial food. Larger

patches should support more mass and protect this group from moderate flow events. In

addition, many grazing invertebrates quickly deplete their resources (McAuliffe, 1984), thus









emphasizing the need for great surface areas to support a significant community. In the

observational study, scrapers increased with patch size, bacterial abundance, and chlorophyll a,

but only in Ludwigia. Higher bacterial abundance may provide additional resources for scrapers,

since many invertebrates have flexible feeding habits. However, in the observational study, there

was no link between patch size and scraper abundance in leaf packs. Many of the larger leaf

patches in the observational study were multi-tiered, and much of the surface area was not

exposed to light, thus limiting primary productivity.

In the observational study, multiple confounding factors limited interpretation of

relationships between patch size and invertebrate communities. Leaf packs were diverse, multi

species assemblages in varying stages of decomposition. To control for this, the field experiment

used freshly abcissed leaves and only created single species patches. Liriodendron and Pinus

patches decomposed more rapidly than Quercus. Liriodendron leaves are soft and pliable with

lower C:N ratios than Quercus. However, pine needles had much higher C:N ratios, but

provided a larger exposed surface area for bacteria colonization. Nitrogen content, C:N ratio,

total phenolics, percentage lignin and lignin:N ratio explain much of the variability in leaf

processing rates (Taylor, Parkinson and Parsons, 1989; Ostrofsky, 1997).

Patch occupancy may be related to interactions between biotic and abiotic factors.

Collector gatherers are bottom-feeders in streams and tend to consume any type of small organic

particle. They are also the most abundant group in sandy-bottomed streams (Smock et. al, 1985).

However, this group was more abundant in leaf packs than in macrophytes, increasing with patch

size in macrophytes, but decreasing in leaf packs. An opposite relationship was found for

predatory invertebrates, suggesting predation on this group. This is supported by the higher

abundance of predators in macrophytes even though trapped organic matter was similar between









the patch types for the observational study. Although streams are thought to be primarily

structured by abiotic factors, biotic factors are likely to influence community structure

effectively at smaller scales (e.g., Peckarsky, 1983).

The proportion of shredders was negatively related to bacterial abundance for leaf packs.

This potentially suggests that competitive interactions may exist between these groups, since

both consume leaf organic carbon. This may explain the lack of a relationship between

shredders and bacteria in macrophytes. Interactions between shredders, organic matter

decomposition and microbes (bacteria and fungi) are complex. For example, fungi and bacteria

convert a portion of detrital organic matter into microbial biomass, transforming the detrital

substrate into a more nutritious food source for detritus feeders (Barlocher and Kendrick, 1975;

Suberkropp, 1992). At the same time, shredder fragmentation of the detrital matrix promotes

microbial activity, increasing available detrital surface for colonisation (Hargrave, 1970; Howe

and Suberkropp, 1994) and spreading microfungal spores (Rossi, 1985).

The results of this study support the expected response of invertebrates to changes in

habitat type and quality as logging reduces leaf packs and increases primary productivity.

Typically, headwater streams would lose shredders and gain more scrapers. However, in warm

temperate coastal plain systems, collector gatherers may be the dominant consumer of organic

matter. This may explain the decrease in collector-gatherers with the subsequent increase in

scrapers. In addition, scrapers were negatively related to canopy cover, while collector-gatherers

were positively related. This indicates that collectors may be the more natural feeding group in

occurring in undisturbed, sandy-bottomed streams. Since much of the substrate is highly mobile,

scouring of leaf packs may act as the initial decomposition mechanism, creating smaller particles

available for collectors, work usually done by shredders.










Table 4-1. Multiple regressions for leaf packs averaged over all time periods for the
observational study.
Dependent Variable Parameter Estimate SE t P
Invertebrate Abundance (F4,59=15.0, P < 0.0001, R2 = 0.58)
Size 0.28 0.23 0.05 0.96
Chlorophyll a -17.7 50.4 -0.35 0.72
Bacteria Abundance 0.08 0.14 0.57 0.57
Bacteria Biomass 0.33 0.1 3.2 0.003
FPOM 0.38 0.13 2.9 0.005
Taxon Richness (F4,59=7.7, P < 0.0001, R2 = 0.42)
Size 0.13 0.14 0.9 0.37
Chlorophyll a -26.8 30.4 -0.88 0.38
Bacteria Abundance 0.05 0.08 0.56 0.58
Bacteria Biomass 0.12 0.06 1.9 0.06
FPOM 0.17 0.08 2.2 0.03
Shredders (F4,59=2.0, P = 0.08, R2 = 0.16)
Size 0.86 0.35 2.5 0.02
Chlorophyll a -134.6 76.2 -1.77 0.08
Bacteria Abundance -0.52 0.21 -2.51 0.01
Bacteria Biomass -0.13 0.16 -0.8 0.13
FPOM -0.17 0.2 -0.87 0.39
Filterers (F4,59=8.9, P < 0.0001, R2 = 0.45)
Size -0.29 0.27 -1.1 0.28
Chlorophyll a 72.2 58.8 1.23 0.22
Bacteria Abundance 0.38 0.16 2.3 0.02
Bacteria Biomass 0.24 0.12 2 0.04
FPOM 0.46 0.15 3 0.005










Table 4-2. Multiple regressions for Ludwigia averaged over all time periods for the observational
study.

Dependent Variable Parameter Estimate SE t P
Invertebrate Abundance (F4,61=3.5, P = 0.008, R2 = 0.24)
Size 0.15 0.17 0.9 0.37
Chlorophyll a 20.6 13.9 1.6 0.12
Bacteria Abundance 0.12 0.15 0.17 0.44
Bacteria Biomass -0.04 0.13 -0.28 0.78
FPOM 0.28 0.1 2.8 0.007
Taxon Richness (F4,63=2.7, P = 0.03, R2 = 0.19)
Size 0.11 0.08 1.5 0.14
Chlorophyll a 9.7 5.8 1.7 0.1
Bacteria Abundance -0.02 0.07 -0.28 0.78
Bacteria Biomass -0.04 0.06 -0.67 0.51
FPOM 0.08 0.04 1.9 0.06
Scrapers (F4,63=2.6, P = 0.04, R2 = 0.20)
Size 0.62 0.25 2.5 0.01
Chlorophyll a -42.7 19.3 -2.2 0.03
Bacteria Abundance -0.56 0.22 -2.5 0.01
Bacteria Biomass 0.08 0.2 0.39 0.7
FPOM -0.21 0.15 -1.4 0.16
Filterers (F4,63=2.9, P = 0.02, R2 = 0.20)
Size -0.11 0.21 -0.52 0.61
Chlorophyll a 31.9 16.6 1.9 0.06
Bacteria Abundance 0.35 0.19 1.8 0.07
Bacteria Biomass -0.17 0.17 -0.99 0.33
FPOM 0.29 0.12 2.3 0.02
Collector-gatherers (F4,63=4.5, P = 0.002, R2 = 0.28)
Size 0.25 0.21 1.22 0.23
Chlorophyll a -46 15.9 -2.9 0.005
Bacteria Abundance -0.29 0.18 -1.57 0.11
Bacteria Biomass 0.25 0.16 1.55 0.13
FPOM -0.29 0.12 -2.4 0.02










Table 4-3. Multiple regressions for the field experiment averaged over all treatments for each
invertebrate metric.

Dependent Variable Parameter Estimate SE t P
Invertebrate Abundance (F5,255=15.0, P < 0.001, R2 = 0.23)
CPOM 0.45 0.15 3.6 0.0004
FPOM -0.99 0.5 -2 0.04
Velocity 5.9 1.52 3.9 0.0001
Canopy Cover 0.67 0.11 6.1 <0.0001
Oxygen -0.52 0.35 -1.5 0.14
Taxon Richness (F5,255=6.2, P < 0.0001, R2 = 0.11)
CPOM 0.48 0.19 2.5 0.01
FPOM -0.28 0.63 -0.45 0.65
Velocity 8.6 1.92 4.45 <0.0001
Canopy Cover 0.12 0.14 0.84 0.4
Oxygen -0.07 0.44 -0.15 0.88
Scrapers (F5,255=6.1, P < 0.0001, R2 = 0.11)
CPOM -0.03 0.24 -0.14 0.89
FPOM 0.29 0.78 0.37 0.71
Velocity 5.02 2.41 2.08 0.04
Canopy Cover -0.87 0.17 -5.05 <0.0001
Oxygen -0.25 0.55 -0.45 0.65
Filterers (F5,255=6.9, P < 0.0001, R2 = 0.12)
CPOM 0.32 0.19 1.65 0.1
FPOM 2.22 0.62 3.57 0.0004
Velocity -0.39 1.91 -0.21 0.84
Canopy Cover -0.09 0.14 -0.68 0.5
Oxygen 1 0.43 2.3 0.02
Collector-gatherers (F5,255=11.0, P < 0.0001, R2 = 0.18)
CPOM 0.01 0.1 0.12 0.9
FPOM -1.18 0.33 -3.58 0.0004
Velocity -0.55 1.02 -0.55 0.59
Canopy Cover 0.46 0.07 6.3 <0.0001
Oxygen -0.26 0.23 -1.12 0.26










0.012
-A- Leaf Packs
-- Ludwigia
0.01


0.008


0.006

0
0.004


0.002


0
November 2005 January 2006 April 2006 June 2006


Figure 4-1. Total biomass of chlorophyll a (mg) (+ SE) in each patch type.











80
-A- Leaf Packs
70 --- Ludwigia
Co
0
60
X

S50


40 -
40







0
"u20


0
I -


November 2005 January 2006 April 2006 June 2006


Figure 4-2. Total number of bacterial cells (1 X 106) ( SE) in each patch type.











0.7


0.6
C-
E

0 0.5
0)

S0.4


.2 0.3
CD



i \

0.1


0
November 2005 January 2006 April 2006


Figure 4-3. Bacterial biomass (pg C/cm3) ( SE) in each patch type.


June 2006










1

% 0.9

X 0.8

E 0.7

0 0.6

0 0.5

-0.4
S0.3

0.2
E -A- Leaf Packs
3 0.1 -- Ludwigia

0
November 2005 January 2006 April 2006 June 2006


Figure 4-4. Number of bacterial cells per cm3 (1 X 106) (+ SE) in each patch type.










0.0004
-A- Leaf Packs
0.00035 -B- Ludwigia

0.0003

E 0.00025

E 0.0002

E 0.00015

0.0001

0.00005

0
November January 2006 April 2006 June 2006
2005


Figure 4-5. Chlorophyll a biomass (mg/cm3) (+ SE) in each patch type.











4
-A- Leaf Packs
3.5 --- Ludwigia

3
E

02.5
U)
2

r1.5
0
x
1


0.5

0
November 2005 January 2006 April 2006 June 2006


Figure 4-6. Volume-weighted taxon richness (Taxa/cm3) ( SE) in each patch type.











14
-A- Leaf Packs
u 12 -- Ludwigia
U,

S10


-. 8

u,
S6


S4-
.0
,Q

,- 2


0
November 2005 January 2006 April 2006 June 2006


Figure 4-7. Volume weighted invertebrate density (Individuals/cm3) (+ SE) in each patch type.










0.5
-A- Leaf Packs
0.45 -- Ludwigia

0.4

0.35 -

0.3
LLI
0 0.25

o 0.2
o
0.15 -

0.1

0.05

0
November 2005 January 2006 April 2006 June 2006


Figure 4-8. Proportion of filtering invertebrates (+ SE) in each patch type.

















0.35

0.3

0.25

0.2

0.15

0.1

0.05


0 --


O Day 7


Pinus


Liriodendron


Quercus


Figure 4-9. Proportion of leaf mass decomposed ( SE) in relation to patch type and disturbance.












1.2



1



0.8


0)
S0.6
U)
U)

0.4



0.2



0 -----
1 2 4
Mass


Figure 4-10. Amount of leaf mass decomposed (g) (+ SE) in relation to initial patch mass.














5- 1

u) 0.8


o. 0.6


0 0.4
a-
0
0.2


0 -- -----
1 2 4
Mass

Figure 4-11. CPOM trapped in patches (+ SE) in relation to patch size.














1.6

1.4

u) 1.2
C
1

0.
0.8

0 0.6 T
a-
o
0.4

0.2

0 -- ---------------------- -
Pinus Liriodendron Ludwigia Quercus




Figure 4-12. Average amount of coarse particulate organic matter (g) (+ SE) trapped in each
patch type.

































Day 15 Disturbed


Day 15 Undisturbed


Figure 4-13. Average amount of coarse particulate organic matter (g) (+ SE) trapped in patches
by disturbance type.


1
-


u) 0.8
()
C--


C

S 0.4


0.2


0


Day 7


T i











0.2

0.18

0.16

S0.14

0 0.12

0.1 -

S0.08
0
O
a-
L 0.06

0.04

0.02

0 --- ------
Day 7 Day 15 Disturbed Day 15 Undisturbed


Figure 4-14. Average amount of fine particulate organic matter (g) ( SE) trapped in each patch
based on disturbance.












0.35


0.3


S 0.25


0.2


0.15

a-
LL 0.1


0.05


0 -
Pinus Liriodendron Ludwigia Quercus




Figure 4-15. Average amount of fine particulate organic matter (g) (+ SE) trapped in each patch
type.

































Pinus


Liriodendron


Ludwigia


Quercus


Figure 4-16. Average number of invertebrate individuals ( SE) in each patch type.













45

40 -

35
C
0 30
C
25 25

0 20

S15

S10

5

0
1 2 4
Mass


Figure 4-17. Average number of invertebrate individuals (+ SE) in each patch based on initial
patch mass.
































143

















6



5-



0 4- T






1-
0

ca
C
0
x
1-2



1



0 -- --------
1 2 4
Mass


Figure 4-18. Average number oftaxa (+ SE) in each patch in relation to initial patch mass.












0.3



0.25



0.2
L_



C 0.15
0

o
C.
L.
g 0.1
0.



0.05



0
0 ---------------------------

1 2 4
Mass


Figure 4-19. Proportion of scrapers (+ SE) in each patch based on initial patch mass.












0.03



0.025


Q,
V 0.02



0.015
O

0
0. 0.01

aC

0.005



0 --
1 2 4
Mass


Figure 4-20. Proportion of shredders (+ SE) in each patch based on initial patch mass.











0.07
O Day 7

0.06 Day 15 Disturbed

Day 15 Undisturbed
.2 0.05


0.04
c

*E 0.03
O
0
0.02


0.01


0
Pinus Liriodendron Ludwigia Quercus




Figure 4-21. Proportion of shredders ( SE) in each patch based on patch type and disturbance.












0.12



0.1



g 0.08


L.
0.06
0

o
Q.
g 0.04



0.02



0 ---------------------------

1 2 4
Mass


Figue 4-22. Proportion of filterers (+ SE) in each patch based on initial patch mass.











0.18

0.16

0.14

g 0.12

7 0.1
0o
0.08
0
0 0.06

0.04

0.02

0
Pinus Liriodendron Ludwigia Quercus




Figure 4-23. Proportion of filterers ( SE) in each patch type.











0.7


0.6


0.5


o 0.4


O
0 0.3

O
0

0.2
0
0.

CL 0.1



0
Pinus Liriodendron Ludwigia Quercus
Mass


Figure 4-24. Proportion of collector-gatherers ( SE) in each patch type.









CHAPTER 5
HABITAT SELECTION IN FRAGMENTED LANDSCAPES: COMPARING GENERALISTS
TO SPECIALISTS

Introduction

Dispersal of individuals relative to patch variability has important implications for

ecological processes, including population dispersal and redistribution, local population and

metapopulation dynamics, and intensity of species' interactions (Hanksi, 1998; Gilliam and

Fraser 2001). Habitat patch arrangement, amount, and perimeter:area ratio (e.g., edge) strongly

influence both community structure and interpatch dispersal both in terrestrial and aquatic

systems (Wiens, 1997; Pither and Taylor, 1998; Hanski, 1999; McIntyre and Wiens, 1999;

Jonsen and Taylor, 2000; Palmer, 2000). The importance of patches, and especially isolation

between patches, depends on dispersal ability of focal organism(s) (Kareiva andWennergren,

1995).

Since invertebrates respond to patches at a smaller scale than other groups, they are an

ideal model group for testing hypotheses related to habitat fragmentation (Bowne and Bowers,

2004). For instance, insects residing in patchy habitats display higher density when resources are

dispersed among many small patches as opposed to large, aggregated patches (Hanski, 1994;

Remer, 1998; Roitberg, 1997; Heard, 1998; Silver, 2004a). In this way, habitat connectivity

increases with increased habitat fragmentation (Tischendorf and Fahrig, 2000).

Both natural and anthropogenic forces leading to habitat loss and fragmentation have

been considered in debates over the relative importance of habitat amount versus arrangement in

determining community response to habitat fragmentation (Sih, 2000). Flather (2002) argued

that habitat amount is a more plausible explanation for population size, but arrangement becomes

important when total habitat cover declines to 30-50 %, emphasizing the need to study

processes over a range of total cover. Additionally, patches may be highly dynamic, changing in









shape and size over time (Pickett and Thompson, 1978) in response to disturbance and

succession.

Movement is a primary factor determining the effect of spatial heterogeneity on

ecological processes (Diffendorfer et al., 2000). Movement and dispersal provide escape from

competitors, predators and parasites. Risks associated with dispersal include increased mortality

due to predation and an inability to find suitable sites (Bilton et al., 2001). Interactions between

dispersal and landscape structure determine the ability of an organism to move through the

landscape (Merriam, 1984). Thus, the colonization rate of new patches by individuals is

influenced by emigration rate, mean dispersal distance relative to patch distance, mortality

incurred during dispersal, and mean number of potential dispersers (Johnst, 2002). The idea that

animal movement and dispersal occur as a result of behavioral choices made in response to

environmental heterogeneity across spatial and temporal scales emphasizes the importance of

linking behavioral and landscape ecology (Lima and Zollner, 1996).

Studies of movement across heterogenous landscapes are necessary to determine impacts

of habitat loss for management and conservation (Olden et al., 2004). Movement patterns in the

landscape are central to connectivity, patch and boundary dynamics, spread of disturbances,

source-sink and metapopulation dynamics (Ims, 1995). Dispersal is considered active when

attributed to behavioral decisions and passive when due to displacement. Biased flow in streams

emphasizes the importance of both passive and active dispersal. Movement of an individual

through a heterogeneous landscape is influenced by a number of abiotic (flow, temperature, light

levels) and biotic cues (food, predation risk). Movement between patches also depends on the

proportion of different habitat types, as well as spatial configuration of the landscape (Moilanen

and Hanski, 1998). Connectivity within a landscape depends on the spatial configuration of









patches and movement patterns of the organism. Thus, connectivity based on movement links

behavior and landscape structure (Goodwin and Fahrig, 2002).

Movement of invertebrates in streams is influenced by available habitat amount and type

(e.g., Palmer, 2000). In many cases, leaf packs and macrophytes share similar

macroinvertebrates, including Ephemeroptera, Chironomidae, Trichoptera, and Simuliidae

(Velasquez, 2003), making them useful for studying movement across different patch types.

However, they differ in the composition of other invertebrate fauna, suggesting that these patch

types are somewhat unique. Interpatch movement and ability to find patches of suitable quality

are key factors influencing species persistence. The ability of dispersing invertebrates to find

and settle in patches may be influenced by patch quality (Palmer, 1996) and physical

arrangement of patches on the stream bed (Silver, 2000).

The goal of this study was to determine implications of changing habitat availability and

type on invertebrate movement, focusing specifically on how patch type and amount affect

habitat selection. I hypothesized that reduction of available patches and increased isolation will

negatively affect the ability of habitat specialists to locate patches. Additionally, habitat

specialists should be more efficient at finding the next patch and will follow a relatively straight

path to it, while habitat generalists will choose a random, tortuous path.

Materials and Methods

Study Organisms

The habitat specialist, Anisocentropuspyraloides (Trichoptera: Calamoceratidae) is a

slow-moving detritivore that inhabits small streams flowing through deciduous forest throughout

the eastern U.S. (Wiggins, 1996). Larvae construct notched, oblong cases made of two leaves

sealed together with silk. Additionally, its diet consists primarily of organic matter and thus

depends on leaf packs for food and its case. This species is semivoltine and emerges in the spring









(Wiggins, 1996). Although dorso-ventrally flattened, the case likely creates drag while the

organism is crawling over the streambed.

The habitat generalist used in experiments was the snail, Elimia sp.(Gastropoda:

Pleuroceridae), which commonly occurs in all landscape units including macrophytes, leaf packs,

and the sandy matrix (personal observation, Chapter 4). This genus occurs throughout the

southern U.S. and is abundant in the study streams, with densities as high as 25 individuals/m2.

Elimia produces more than one generation per year and is parthenogenic, which contributes to its

abundance in the streams (Viera et al., 2006). Elimia is conical, limiting its drag as it moves

across the streambed.

Behavioral Observations

The effects of habitat type and amount on movement were examined using short-term

behavioral experiments within the stream. During the experiment, conditions were consistent with

average conditions throughout the stream. Over the seven day period, average water temperature

was 18.50 C, velocity was 0.13 cm/s, and canopy cover was 79 %. Leaf packs (Liriodendron

tulipifera) and macrophytes (Ludwigia repens) were collected as described in Chapter 4. Habitat

mosaics were created in a 5 m2 section of the channel in watershed C by adding leaf

packs:macrophytes at 1:0, 1:1, or 0:1 ratios, with total percent cover of 10, 30 and 50 percent of

the entire landscape (Fig. 1). Macrophytes and leaf packs were arranged randomly since effects

of patch configuration were not being addressed. Each leaf pack or macrophyte patch had a

surface area of 16 cm2. The sediment in the selected reach was raked to a depth of 0.75 m to

remove organic matter and invertebrates, then was smoothed to create a landscape completely

dominated by sand. A 3 X 3 grid composed of colored nylon was attached to pvc pipes at the

perimeter of the landscape and was placed 15 cm above the water as a reference point for









movement distances. A drift net was placed at the end of the landscape to trap emigrating

individuals.

Experimental organisms were collected from the stream each morning from the

streambed and naturally occurring leaf packs. Individuals were placed in separate flow-through

trays and allowed to acclimate to the stream reach for at least an hour. A video camera was set

up on a tripod to record movement of individuals. During each trial, individuals were placed at

the center of the landscape, facing downstream. Behavior was recorded for 30 minutes, with the

observer leaving the reach while trials were occurring. After 30 minutes, the length and width of

each individual was measured, removed from the landscape, and released downstream. On

average, Anisocentropus individuals were 4.2 cm long ( 0.2 SE) and 2 cm wide ( 0.1 SE),

while Elimia individuals were 4.3 cm long ( 0.1 SE) and 1.7 cm wide ( 0.1 SE). No individual

was used more than once, and trials were repeated for at least four individuals (more for Elimia

due to availability). After each trial, the streambed was gently scoured to remove any traces of

the individual path. Trials were run between 7 AM and 4 PM daily for a period of seven days

beginning 7 March, 2007. The grid was left in place each night, and pvc pipes were inserted into

the streambed as placeholders for the tripod.

Videos were digitized and manually analyzed on a computer screen with coordinates

(x,y) recorded every 10 s to determine movement parameters. For each path, total path length,

correlations between turning angles, mean cosine of turning angle, mean path length, and net

squared displacement were calculated to assess distance covered (Turchin et al. 1991). The

above parameters were used for correlated random walk models, which are useful for making

inter-specific comparisons (Kareiva and Shigesada 1983; Cain 1985; Crist et al.1992). Each path









was compared to the correlated random walk model of Nams and Bourgeois (2004) by

calculating Rdiff:

1 kR E(R 2)
Rdgff -
k E(R2)

where E(R2,) is the expected net squared displacement (Kareiva and Shigesada 1983), n is the

number of moves, and R2n is the mean net squared displacement. Positive values of Rdiff

indicate that the path is longer than predicted by correlated random walk models and negative

values indicate shorter paths.

An individual's overall rate of movement across a landscape is contingent upon its

tendency to move (or remain sedentary), movement velocity, and path tortuosity (Russell et

al.2003). Tortuosity of movement was assessed by calculating the fractal dimension (D) of each

movement path, whereby estimates near 1 indicate highly linear movement and near 2 suggest

approximate Brownian (plane-filling) movement (Hastings and Sugihara 1993). Fractal

dimensions were estimated with Fractal 4.0 software

(http://www.nsac.ns.ca/envsci/staff/vnams/Fractal.htm). The fractal mean method was used,

which is based on the traditional dividers method (Mandelbrot 1967, Sugihara and May 1990),

but corrects for estimation errors created when the last divider step does not fall exactly on the

end of the path (Nams and Bourgeois 2004). Fractal dimensions were estimated based on the

entire recorded movement path of each individual. Paths of four moves or less were not used in

the analyses because estimates of their fractal dimension sometimes fell below the theoretical

limit of 1.

To test whether the above movement behaviors differed among habitats, ANOVA was

used after normalizing the data. Where significant effects were observed, differences among









treatment-factor combinations were tested using post hoc Tukey's honest significant difference

(HSD) tests (c = 0.05).

Colonization

Habitat selection based on patch amount and type was examined in a short term

colonization study. Microlandscapes were created along an -75 m stretch of stream, separated

by at least 3 m. Landscapes were the same as those used in the short-term behavioral

experiment, but were half the size (45.7 cm W X 50.8 cm L), and were replicated three times in a

randomized block using each replicate as a block. Prior to creation of the landscape, the

streambed was raked to 0.5 m to remove any apparent organic matter or habitat and allowed to

settle for four hours. Drift nets were placed at the end of the landscape to trap emigrating

invertebrates. Macrophyte and leaf patches were anchored to the sediment in the appropriate

configuration (Fig. 1).

Invertebrates for the experiment were collected from the streambed and, leaf packs and

lengths of individuals were measured. Due to low abundance of Anisocentropus, only one

individual was used for each replicate, however, six individuals of Elimia were used. The shell

or case of the individual was blotted dry and marked with a drop of paint and the number of

landscape (from 1 to 27). Individuals were released at the center of the landscape after the paint

dried (- 5 minutes). After 24 hours, all patches were collected and placed in individually

labelled bags. Velocity was measured at the upstream and downstream end of the landscape with

a Flomate 2000 (Marsh McBirney). In addition, drift nets were collected and any marked

individuals in the matrix (sand) were collected. A surber sample was also taken from the

landscape to determine recolonization by other invertebrates.









Results


Movement

Anisocentropus

Mean step length did not differ for any of the microlandscapes, averaging 0.7 cm ( 0.3

SE) per step. Deviation from the correlated random walk between the leaf species depended on

amount of patch cover (F4,37 = 3.1, P = 0.03) (Fig. 2). Paths became more random (closer to the

CRW) with increased cover for single species landscapes, but were shorter than a CRW for

mixed landscapes. The probability of turning in the same direction differed by leaf type, but

depended on total amount of cover (F4,37 = 4.6, P = 0.004). This parameter increased with

increasing cover in Ludwigia dominated landscapes, but decreased in mixed landscapes (Fig. 3).

Correlation between adjacent angles differed by leaf type, but depended on total amount of cover

(F4,37 = 2.6, P = 0.04). In general, correlations between angles were negative, but became more

negative with increasing cover in mixed landscapes (Fig. 4). Net squared displacement differed

by leaf type, but depended on total amount of cover (F4,37 = 4.5, P = 0.004). Displacement

increased with increasing cover in Liriodendron dominated landscapes, but decreased in mixed

landscapes (Fig. 5). Mean D did not differ between leaf species or percent of habitat cover,

averaging 1.15 ( 0.02 SE).

Elimia

Changes in mean step length for leaf species depended on percent cover in the landscape

(F4,39 = 3.7, P = 0.01). Step length increased with increasing cover in Liriodendron landscapes

from 0.1 cm to 0.7 cm per step. It was higher in Ludwigia landscapes with 30 % cover,

increasing from 0.5 to 0.8 cm (Fig. 6). Deviation from CRW differed between leaf types (F2,38 =

4.4, P = 0.02) and total amount of cover (F2,38 = 4.8, P = 0.01). In general, paths were greater

than expected by CRW at 20 % cover, with the lowest values in Liriodendron (Fig. 7). The









mean cosine differed between the percent cover treatments, but depended on leaf type (F4,39 =

3.4, P = 0.01). Probability of turning in the same direction did not differ between treatments and

ranged from 0.25 to 0.45. Correlation between adjacent angles did not differ between treatments,

and ranged between 0.5 and -0.5. Net squared displacement did not differ between any of the

landscapes and ranged from 50 to 780 cm. Mean D did not differ between leaf species or percent

of habitat cover and averaged 1.03 ( 0.004 SE).

Colonization

Neither effects of patch type or amount significantly influenced the probability of Elimia

or Anisocentropus staying in the microlandscape. However, general trends existed, indicating

that the amount of cover affects the likelihood of these species remaining in the landscape. Both

invertebrate species were less likely to leave the landscape as the proportion of cover increased

in mixed habitats. The proportion of Elimia leaving the landscape decreased from 90 % to 40 %

with increasing cover. The proportion of Anisocentropus leaving the landscape decreased with

increasing cover in all patch types, and no individuals left the landscape in the mixed species

treatment with 30 % cover.

Discussion

Habitat fragmentation is typically viewed at a scale of kilometers; however, the scale at

which fragmentation alters local population dynamics likely lies at a much smaller scale,

particularly for invertebrates. This is one of a few studies to examine individual movement

patterns of aquatic invertebrates in response to patch structure (Olden 2004, Lancaster 2006;

Drew and Eggleston, 2006). In logged streams, the amount of habitat may be more important

than spatial configuration since reduced canopy cover limits overall leaf inputs. In the study

streams, invertebrate communities differed greatly between four adjacent streams, suggesting









effects of local filters on invertebrate communities. Thus, the quality of the riparian and

availability of instream habitat create a filter to limit presence of certain species.

Results from this study support the idea that instream habitat availability controls small

scale community composition. The habitat specialist, Anisocentropus, left landscapes without

preferred leaf litter habitat. In streams with little organic matter storage, this species may be

driven locally extirpated. Although it may be supported where riparian zones are left

undisturbed, this species prefers small streams and may be driven out of entire headwater

streams if they are logged along their length.

Logging limits the amount and quality of habitat available for aquatic invertebrates in

streams. This is accomplished by reducing leaf fall, as well as through an increase in peak flow

with increasing surface runoff (Beasley and Granillo, 1982; Williams et al., 1999; McBroom et

al., 2002; Grace et al., 2003). Thus, any leaf fall that does reach the stream is easily washed

downstream during storm events.

The results of this study suggest that increased habitat cover decreases emigration rates,

regardless of habitat configuration. Very few Anisocentropus individuals were able to colonize

patches successfully, but when successful, they remained there for the duration of the trial. This

suggests that, although small, patches were able to be used as refugia from flow and exposure.

Both Elimia and Anisocentropus were likely to remain in the microlandscapes with 30% cover.

Changes in landscape structure, such as reduction of the proportion of one or more patch

types or increased patch isolation, will alter the ability of organisms to disperse (Merriam 1984;

Fahrig and Merriam 1985). Species that can not disperse effectively as a result of a change in

structure will suffer reductions in regional population sizes (Fahrig and Merriam 1994). As a

result, relative abundances of Anisocentropus decreased in treatment watersheds following









harvest. In addition to decreased food availability with increasing isolation, availability of

refugia decreases. Landscapes in this study were in a particularly inhospitable matrix of sand,

with little heterogeneity. In addition, Anisocentropus individuals were commonly displaced

from the streambed in landscapes with low or no habitat available.

Habitat loss may also lead to more time being expended searching for suitable habitats,

potentially contributing to lowered survival rates and decreased fecundity. Correlation between

turning angles was always negative for Anisocentropus, leading to a wobbly path. It was a

clumsy crawler and appeared to have limited capacity for crawling over a sand dominated

streambed with little structure to cling to. Thus, it is likely this species is washed downstream

easily during storm events. However, this increased with increasing cover in mixed landscapes,

suggesting a search strategy.

Elimia took larger steps with increasing amount of cover in the microlandscape. This

may be related to the perceptual range of the organism, as it may not perceive patches as habitat

when they are farther apart as in the 10 percent cover treatment. This suggests that the scale of

the study may be larger than the scale of perceived habitat, but potentially defines this scale as

lying between the isolation found in the 10 and 30 percent cover treatments.

Perceptual range differs greatly among species (Zollner, 2000), regarding the ability of

the species to visualize a three dimensional landscape, and it ultimately determines the

individual's movement behavior, search strategy, and response to fragmentation (Lima and

Zollner, 1996; With and Crist, 1996). However, perceptual range may be dynamic even for

individuals of the same species and it changes with environmental conditions, such as flow

variability in streams. For example, downstream flow bias may increase perceptual distance to an

upstream patch, increasing isolation (Olden, 2004). However, in general, increased habitat









amount lengthens the time spent within the landscape and may provide protection from scouring

and predators.

Although habitat amount was a good predictor of emigration rates and movement rates,

habitat heterogeneity also played a role. Anisocentropus remained in landscapes longer when

both macrophytes and leaf packs were available, suggesting that habitat diversity leads to higher

abundances. Bronmark (1985) found that freshwater snails were more diverse in ponds with

more macrophyte species, reflecting the presence of different niches and refugia from predators.

In larger, agricultural landscapes, Jonsen and Fahrig (1997) found that more species and

individuals colonized landscapes with higher diversity. This suggests a scale-independent

relationship between the probability of colonization and diversity of patches in a landscape. The

latter increases the number of potential refuges and resources available in a landscape. However,

I did not expect this to act at a scale independent of resources. Anisocentropus was more likely

to remain within the microlandscape in the presence of Ludwigia. This suggests a preference for

this habitat, possibly due to increased three dimensional area and protection from flow provided

from Ludwigia.

In streams, even species considered specialists may display flexibility in feeding

preferences. Thus, both species considered to be generalists and specialists may be able to

supplement their diet with alternative food sources, enhancing the actual connectivity of the

landscape in contrast to the perceived connectivity (Dunning et al., 1992). Additionally,

Ludwigia traps organic matter faster than newly formed leaf packs (Chapter 4), creating a higher

quality resource. Thus, macrophytes may provide adequate resources for dispersing detritivores

living in patchy landscapes.









Upstream movement has been proposed as one part of the solution to the drift paradox,

whereby species need to recolonize upstream habitats to account for downstream drift.

Displacement along the longitudinal axis is of particular interest to stream ecologists, partly

because of its relevance to concepts such as Muller's colonisation cycle and the paradox of

upstream- downstream movement (e.g., Muller, 1982; Hershey et al., 1993; Anholt, 1995). In

essence, there needs to be a balance between downstream movement (both passive and active)

and upstream migration by larvae and adults to maintain position in suitable stream habitats (e.g.,

Elliott, 1971b; Soderstrom, 1987). In this study, most Elimia individuals (90 %) moved

upstream, regardless of landscape type, suggesting that this is a compensation mechanism for

potential disturbances such as floods. However, Anisocentropus did not exhibit a significant

displacement direction. Although this species spent much of its time attempting to move

upstream, the shape of its case made it susceptible to downstream drift.

Field studies of up- versus downstream movement of individually marked invertebrates

(i.e. at larger spatial and temporal scales than this study) provide contrasting results with regard

to directional movement. Among cased caddisflies, Jackson et al.(1999) recorded no directional

bias in net displacement at low discharge, but there was a downstream bias at higher discharges;

Erman (1986) reported some seasonal dependence but, generally, a net downstream

displacement. However, Hart and Resh (1980) reported no bias in net displacement direction, but

did not report displacement distance along the longitudinal axis. As in this study, upstream

displacement occurs commonly in snails (Schneider and Lyons, 1993; Huryn and Denny, 1997).

Although species capable of upstream flight, such as stoneflies, tend to move downstream

(Freilich, 1999).









Clearly, multiple factors can influence displacement at the stream scale (e.g., body shape,

temperature, discharge, life history stage and food availability), and generalizations are difficult.

Although discharge remained fairly unifrom during this study, there is strong evidence from

other studies suggesting that discharge is a primary determinant of movement rates and direction

(Olden, 2004; Lancaster, 2006). Thus, response to landscape structure may differ between

logged and unlogged streams.

Studies attempting to understand the role of patch structure and arrangement in streams

lag far behind those in terrestrial systems. However, it has become clear that both spatial

arrangement and habitat amount are determinants of community structure stemming from

changes in emigration and immigration rates (Palmer, 2000; Olden, 2004; Lancaster, 2006;

Olden, 2007). Additional studies are needed to determine if generalities exist in streams,

including long-term mark-recapture studies across life stages. Aquatic invertebrates are unique

in that they spend their larval period in the water and their adult stages on land. Thus, dispersal

studies will need to account for small scale movements in streams as well as the response of

adults to spatial structure in the terrestrial landscape. Clearcut watersheds may limit this

dispersal, creating streams that act as isolated islands. This is particularly important in

headwater streams since some species are dependent on specicific environmental conditions only

available in small, forested headwater systems (Lowe, 2002; Meyer et al., 2007).









SI I A
A


Figure 5-1. Microlandscape designs used in the behavioral and colonization experiments.
Liriodendron leaf packs (brown squares) and Ludwigia macrophyte patches at A) 10,
B) 20, and C) 30 percent cover. The same configuration was used for landscapes with
a single patch type.


A| B














O Ludwigia
0.2
Mixed
0.1 Liriodendron



S-0.1-

2 -0.2
-0.3



-0.5

-0.6

-0.7

-0.8
10 20 30
Percent Cover


Figure 5-2. Average deviation from a correlated random walk (+ SE) (CRW) (Rdiff) for
Anisocentropus.














T


O Ludwigia
* Mixed
* Liriodendron


10 20 30
Percent Cover


Figure 5-3. Average probability ( SE) of each turn being in the same direction for
Anisocentropus.


0.45


0.4
0.35
0.3
C
.2 0.25


0.15
0.1
0.05














0.1


0


-0.1


-0.5
1-


-0.3


-0.4


.1 -0.5

O Ludwigia
O -0.6 U Mixed
Liriodendron
-0.7
Percent Cover


Figure 5-4. Average correlation (+ SE) between turning angles for Anisocentropus.













2500
0 Ludwigia
MMixed
S2000 Liriodendron
2000



O 1500
.U)

0 1000



500 -
z

0
10 20 30
Percent Cover


Figure 5-5. Average net squared displacement (+ SE) of Anisocentropus in microlandscapes.














O Ludwigia
SMixed
* Liriodendron


- T


0 I
10 20
Percent Cover


Figure 5-6. Mean step length ( SE) in each landscape for Elimia.


1

E
0.8

C
()
-1 0.6
C.
a)
U)
c 0.4

0.2
0.2















O Ludwigia
3 E Mixed
U Liriodendron

2.5


0
E 2
L_
c-
o. 1.5





0.5



10 20 30

Percent Cover




Figure 5-7. Average deviation (+ SE) from a correlated random walk (Rdiff) for Elimia.









CHAPTER 6
CONCLUSIONS

Best management practices for forestry in the U.S. clearly depend on the geographic

region under review. For example, coastal plain streams in the southern U.S. are

characteristically low-gradient, sandy-bottomed systems with dynamically changing instream

habitat. In contrast, those managed for forestry in the western U.S. are typically high-gradient

montane streams with high habitat and substrate diversity and are susceptible to mass-wasting as

vegetation removal reduces bank stability. Although forestry practices in the Northwest can lead

to drastic reductions in water quality, evidence from the coastal plain indicates limited changes

in water quality and biotic diversity in streams impacted by logging, as long as stream

management zones are left intact.

Although there were few changes in biotic community structure following logging, this

does not discount use of aquatic invertebrates as indicators of water quality. Many biotic indices

weigh heavily upon the use of EPTs (Ephemeroptera, Plecoptera, and Trichoptera) in their

formation (e.g., Lenat, 1993). However, logging ultimately increases primary productivity in

streams, leading to higher densities of Baetid/Leptophlebiid ephemeropterans (Chapter 3; Stone

and Wallace, 1998). As a result, the FLSCI biotic index is inflated, suggesting an increase in

water quality with logging. One short-coming of local management organizations is the long-

term fascination with EPTs, sometimes leading to redundant use of this group by utilizing

metrics on the number of EPT taxa, % EPT, number of Trichoptera, and number of

Ephemeroptera, to name a few (e.g., Maxted et al., 2000).

As an alternative, use of biological traits has recently been advocated as a potential tool

for assessing aquatic ecosystems by academia and the federal government (Poff et al., 2006).

Biological traits are more informative indicators of ecosystem function than are changes in









abundance of individual species, and they are expected to change across a gradient of

anthropogenic and natural disturbances (Charvet et al., 2000; Dole'dec et al., 1999; Statzner et

al., 2001). Additionally, biological traits are regulated at a hierarchy of scales, with

environmental filters (e.g., climate and geology) creating a template for traits present in a

specific region (Townsend and Hildrew, 1994; Poff, 1997). Thus, a subset of traits is expected to

respond to disturbances within a certain region. In the logged streams, traits were consistent

with changes in the stream and were represented by species preferring algae and organic matter

in the water column, as well as those preferring to live in sandy habitat, reflecting reduction in

other habitat types (e.g., leaf litter).

The ability of the Florida Stream Condition Index to indicate the impacts of drought

effectively, but not forestry impacts, emphasizes the need to incorporate natural disturbances into

bioassessment programs. Most programs determine the condition of streams based on a single

sample. Even when multiple sampling time periods are included, they typically are 3-4 years

apart and occur in different locations than the first sample, since many large scale surveys are

probability based (Stoddard et al., 2005). Thus, predictive models need to be developed based

on current environmental conditions in the region as compared to historical conditions (e.g.,

amount of precipitation). The standardized precipitation index was a good indicator of changes

in water quality and thus could be incorporated into such a model.

Another confounding feature for predicting impacts of logging was related to habitat

availability and quality. Logged streams were colonized by the macrophyte, Ludwigia repens,

which was able to support higher densities and a more diverse invertebrate community. This was

accomplished through the stability provided by this habitat and its role in trapping organic matter

as compared to less stable leaf packs. Trapping of organic matter creates patches similar to









debris dams, and the addition of this habitat was preferred to landscapes with only leaf packs by

a specialist detritivore (Anisocentropuspyraloides). This situation may be unique to coastal plain

streams, where fine substrate is often entrained in storm events, creating a dynamically changing

landscape. This is in stark contrast to mountain streams with higher substrate diversity and

stability in the form of boulders and cobble.

Testing of any best management practice ultimately requires an understanding of

mechanisms behind changes in stream communities, as well as long-term monitoring data.

Results from this study provide information on the mechanisms leading to apparent improved

water quality in streams impacted by logging. Thus, additional effort should be placed on

developing assessments specific to coastal plain streams, since most are based upon expected

habitat diversity and channel structure found in Piedmont streams.









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BIOGRAPHICAL SKETCH

Marcus Griswold was born in Baltimore, Maryland, on September 30, 1978. He pursued a

B.S. in biology at the University of Maryland at College Park. His master's work took him to

the University of Florida to work on predator-prey dynamics of larval mosquitoes under the

direction of Phil Lounibos. His interest in aquatic ecology and background in Entomology led

him to Thomas Crisman to pursue a PhD in environmental engineering sciences, with a focus on

riparian zone management in aquatic ecosystems. During this time, his work was funded by the

U.S. EPA, Sigma Xi, and the Friends of the Osa. He has worked in a variety of stream systems

in the southeastern U.S. and Costa Rica, from primary tropical forests to degraded urban streams.

His goal is to utilize his knowledge of aquatic stressors to properly manage aquatic ecosystems,

balancing human needs and maintenance of ecosystem function and biodiversity.





PAGE 1

1 RIPARIAN ZONE MANAGEMENT IN COASTAL PLAIN STREAMS: MULTI-SCALE EFFECT S OF HABITAT FRAGMENTATION By MARCUS WAYNE GRISWOLD A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE RE QUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

PAGE 2

2 2008 Marcus Wayne Griswold

PAGE 3

3 To those who helped me balance my life. To m y wife Ann, for her adventurous spirit and her attempts to reduce my carbon footprint. To Leif fo r the changes he will inspire. To my mother for the gift of learning, teaching, compassion, and independence. To my family for their support and sense of home that will never fade.

PAGE 4

4 ACKNOWLEDGMENTS I would like to thank my advisor, T.L. Crisman, for his guidance and insight into my research as well as giving me numerous opportunities to expand my knowledge base. I benefited greatly from discussions with my committee B. Bolker, R. Holt, and W. Wise and their experience in a large breadth of disciplines. I am grateful to those who helped me find myself and my mentoring skills throughout this journe y. I thank those who let me pry my way into their research, just to discover something new and to those who reminded me that everyone has something to contribute. Included in this, I thank those who assisted with the fieldwork, and torturous days and nights of sorting: R. Sandidge, M. Dornberg, O. Stern, K. Alvarez, C. Cruz, L. Burhans, M. Diedrick, and M. Bell. I would like to thank Scott Terrell for his willingness to share data and Rebecca Winn for the initiation of the preharvest work.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........8 LIST OF FIGURES.........................................................................................................................9 ABSTRACT...................................................................................................................................12 CHAPTER 1 INTRODUCTION..................................................................................................................14 Overview of forestry practic es in southeastern U.S. ..............................................................14 Buffer Zones and Aquatic Ecosystems................................................................................... 15 Buffer Zones and Water Quality..................................................................................... 15 Current Status of Riparian Zone Management in the Southeastern U.S......................... 17 Habitat Fragmentation and Forestry Practices........................................................................18 2 IMPACTS OF CLIMATIC STABILITY ON THE STRUCTURAL AND FUNC TIONAL ASPECTS OF MACROIN VERTEBRATE COMMUNITIES AFTER SEVERE DROUGHT............................................................................................................. 20 Introduction................................................................................................................... ..........20 Materials and Methods...........................................................................................................22 Site Description...............................................................................................................22 Hydrologic and Environmental Variables....................................................................... 23 Invertebrate Sampling..................................................................................................... 24 Biological Traits.............................................................................................................. 25 Statistical Analysis.......................................................................................................... 26 Environmental variables........................................................................................... 26 Ordination: species co mposition and traits .............................................................. 27 Results.....................................................................................................................................28 Hydrologic and Climatic Patterns................................................................................... 28 Environmental Variables................................................................................................. 29 Benthic Macroinvertebrates............................................................................................. 30 Community succession.............................................................................................30 Community stability.................................................................................................31 Taxonomic Composition................................................................................................. 31 Wetland-Fed stream (WF)............................................................................................... 31 Seep-Fed stream (SF)...............................................................................................32 Biological Traits.............................................................................................................. 33 Wetland-Fed stream................................................................................................. 33 Seep-Fed stream.......................................................................................................34 Discussion...............................................................................................................................35

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6 Environmental Variation................................................................................................. 36 Temporal Variation and Successional Patterns in Taxonom ic Abundance..................... 38 Temporal Variation in Traits........................................................................................... 39 Drought Prediction..........................................................................................................41 3 TESTING BMP EFFECTIVENESS FOR SMALL COASTAL PLAIN STREAMS USING MACROINVER TEBRATES AS BIOINDICATORS .............................................56 Introduction................................................................................................................... ..........56 Materials and Methods...........................................................................................................59 Site Description...............................................................................................................59 Geology....................................................................................................................59 Vegetation................................................................................................................59 Climate..................................................................................................................... 60 Hydrology.................................................................................................................60 Experimental Harvest............................................................................................... 61 Physical and Biological Measurements........................................................................... 62 Physical measurements............................................................................................ 63 Energy sources.........................................................................................................63 Macroinvertebrates...................................................................................................64 Biological Traits....................................................................................................... 65 Data Analysis...................................................................................................................65 Energy sources.........................................................................................................65 Environmental variables........................................................................................... 66 Macroinvertebrates...................................................................................................66 Results.....................................................................................................................................67 Energy Source.................................................................................................................67 Environmental Variables................................................................................................. 68 Macroinvertebrates..........................................................................................................69 Stability.................................................................................................................... 69 Taxonomic composition........................................................................................... 69 Biological traits........................................................................................................ 72 Discussion...............................................................................................................................74 Energy Sources................................................................................................................74 Environmental Variables................................................................................................. 78 Macroinvertebrates..........................................................................................................80 Anthropogenic disturbance in the face of natural disturbances....................................... 82 4 EFFECTS OF PATCH TYPE, QUALI TY, AND SIZE ON MACROINVERTEBRATE COMMUNI TY STRUCTURE ............................................................................................104 Introduction................................................................................................................... ........104 Materials and Methods.........................................................................................................106 Field Sampling of Patches.............................................................................................106 Field Experiment...........................................................................................................109 Data Analysis.................................................................................................................110 Field obervations....................................................................................................110

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7 Experimental manipulation of patches................................................................... 110 Results...................................................................................................................................110 Field Observations......................................................................................................... 110 Field Experiment...........................................................................................................113 Regressions............................................................................................................. 115 Discussion.............................................................................................................................115 Patch Complexity.......................................................................................................... 116 Patch Stability................................................................................................................ 117 Patch Quality.................................................................................................................118 Patch Size..................................................................................................................... .121 5 HABITAT SELECTION IN FRAGMENTED LANDSCAPES: COMPARING GENE RALISTS TO SPECIALISTS ...................................................................................151 Introduction................................................................................................................... ........151 Materials and Methods.........................................................................................................153 Study Organisms...........................................................................................................153 Behavioral Observations............................................................................................... 154 Colonization..................................................................................................................157 Results...................................................................................................................................158 Movement......................................................................................................................158 Anisocentropus.......................................................................................................158 Elimia..................................................................................................................... 158 Colonization..................................................................................................................159 Discussion.............................................................................................................................159 6 CONCLUSIONS.................................................................................................................. 172 LIST OF REFERENCES.............................................................................................................175 BIOGRAPHICAL SKETCH.......................................................................................................206

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8 LIST OF TABLES Table page 2-1 Definition and codes for bi ological traits and m odalities................................................. 43 2-2 Mean annual values for environmental va riables for the wetla nd-fed (WF) and seepfed......................................................................................................................................44 3-1 Biological trait definitions and modalities........................................................................ 86 3-2 Results of multiple regressions for ch lorophy ll a biomass and benthic organic matter (BOM). Significance of R2 values is given by ( P < 0.05), ** ( P < 0.01), *** ( P < 0.001).................................................................................................................................87 3-3 Average environmental conditions for wi nter sampling periods in reference (A,D), thinned SMZs (B1,C1), and intact S MZs (B2,C2). Data are for pre-harvest (20012003) and post-harvest (2004-2008).................................................................................. 88 3-4 Indicator values for watersheds A and B based on taxonomic composition. Groups are defined as pre-h arvest all sites (1), post-harvest reference (2), post-harvest thinned SMZ (3), and post-h arvest intact SMZs (4).......................................................... 89 3-5 Indicator values for watersheds C and D based on taxonomic composition. Groups are defined as pre-h arvest all sites (1), post-harvest reference (2), post-harvest thinned SMZ (3), and post-h arvest intact SMZs (4).......................................................... 90 3-6 Indicator values for watersheds A and B based on biological traits. Groups are defined as pre-harvest all sites (1), post-h a rvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4)....................................................................... 91 3-7 Indicator values for watersheds C an d D based on biological traits. Groups are defined as pre-harvest all sites (1), post-h a rvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4)....................................................................... 92 4-1 Multiple regressions for leaf packs averaged over all time periods for the observational study. ......................................................................................................... 124 4-2 Multiple regressions for Ludwigia averaged over all tim e periods for the observational study.......................................................................................................... 125 4-3 Multiple regressions for the field experiment averaged over all treatments for each invertebrate m etric........................................................................................................... 126

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9 LIST OF FIGURES Figure page 2-1 Plot of Standardized Precipitation Inde x (SPI) values for southwestern Georgia, from 1956 to 2007......................................................................................................................45 2-2 Hydrograph based on mean daily discharge (m3/s) for each stream..................................46 2-3 Temporal variability of Bray-Curtis st ability values for environm ental variables in WF and SF ( SE).............................................................................................................. 47 2-4 Temporal changes in taxon ri chness and invertebrate abundance. .................................... 48 2-5 Changes in compositional stability (BrayCurtis distance) in WF and SF ( SE)............. 49 2-6 Linear regression of SPI valu es versus taxonom ic stability.............................................. 50 2-7 Changes in trait stability (Bray-Cu rtis distance) in W F and SF ( SE)............................. 51 2-8 NMDS ordinations of log10-abundance in site-year space an d taxon-space for W F. Time periods are indicated by different symbols. Ordination plots of taxa are based on weighted-averaging.......................................................................................................52 2-9 NMDS ordinations of log10-abundance in site-year space an d taxon-space for SF. Tim e periods are indicated by different symbols. Ordination plots of taxa are based on weighted-averaging.......................................................................................................53 2-10 NMDS ordinations of biological traits in site-y ear space and trait-space for WF. Time periods are indicated by different symbols. Ordination plots of taxa are based on weighted-averaging.......................................................................................................54 2-11 NMDS ordinations of biological traits in site-y ear space and trait-space for SF. Time periods are indicated by diffe rent symbols. Ordination pl ots of taxa are based on weighted-averaging............................................................................................................55 3-1 Topographic map and aerial photo of the four study watersheds (A-D). .......................... 93 3-2 Average chlorophyll a biomass (SE) during the wet (May-S eptember) and dry season (October-April) from 2004-2008 in refe rence, thinned SMZs, and intact SMZ streams afte r harvest.......................................................................................................... 94 3-3 C:N ratios of leaf fall from the riparian zone in reference and harvested watersheds before (2001-2003) and af ter (2004-2007) harvest. ........................................................... 95 3-4 Average ammonia (NH4) concentrations (SE) in reference, thinned SMZs, and intact SMZ streams. Harvest treatments were applied prior to the third sampling period.................................................................................................................................96

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10 3-5 Stream condition index (SCI) scores (SE ) for reference, thinned SMZs, and intact SMZ stream s. Samples below the red line indicate poor water quality, those above the red line, fair water quality, and those above the blue line, good water quality........... 97 3-6 Taxonomic stability (SE) for reference, thinned SMZs, and intact SMZ stream s.......... 98 3-7 Trait stability (SE) for reference, thinned SMZs, and intact SMZ stream s.....................99 3-8 NMDS of taxonomic composition in watersheds A and B in pre-harves t (1) and in post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)................ 100 3-9 NMDS of taxonomic composition in watersheds C and D in pre-harves t (1) and in post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4)................ 101 3-10 NMDS of biological traits in watershe ds A and B in pre-harvest (1) and in postharvest reference (2), thinned SMZs (3), and intact SMZ treatm ents (4)........................ 102 3-11 NMDS of biological traits in watershe ds C and D in pre-harvest (1) and in postharvest reference (2), thinned SMZs (3), and intact SMZ treatm ents (4)........................ 103 4-1 Total biomass of chlorophyll a (m g) ( SE) in each patch type...................................... 127 4-2 Total number of bacterial cells (1 X 106) ( SE) in each patch type............................... 128 4-3 Bacterial biomass (pg C/cm3) ( SE) in each patch type.................................................129 4-4 Number of bacterial cells per cm3 (1 X 106) ( SE) in each patch type.......................... 130 4-5 Chlorophyll a biomass (mg/cm3) ( SE) in each patch type............................................ 131 4-6 Volume-weighted taxon richness (Taxa/cm3) ( SE) in each patch type........................ 132 4-7 Volume weighted inverteb rate density (Individuals/cm3) ( SE) in each patch type...... 133 4-8 Proportion of filtering invertebrates ( SE) in each patch type....................................... 134 4-9 Proportion of leaf mass decomposed ( SE) in relation to patch type and disturbance. 135 4-10 Amount of leaf mass decomposed (g) ( SE) in relation to initial patch m ass............... 136 4-11 CPOM trapped in patches ( SE) in relation to patch size. ............................................. 137 4-12 Average amount of coarse particulate organic matter (g ) ( SE) trapped in each patch type.........................................................................................................................138 4-13 Average amount of coarse particulate orga nic matter (g) ( SE) tr apped in patches by disturbance type. .............................................................................................................. 139

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11 4-14 Average amount of fine particulate organi c m atter (g) ( SE) tra pped in each patch based on disturbance........................................................................................................140 4-15 Average amount of fine particulate organi c m atter (g) ( SE) tra pped in each patch type...................................................................................................................................141 4-16 Average number of invertebrate indi viduals ( S E) in each patch type......................... 142 4-17 Average number of invertebrate individua ls ( S E) in each patch based on initial patch mass..................................................................................................................... ...143 4-18 Average number of taxa ( SE) in each patch in relation to initial patch mass. ............. 144 4-19 Proportion of scrapers ( SE) in each patch based on initial p atch mass........................ 145 4-20 Proportion of shredders ( SE) in each patch based on initial patch mass...................... 146 4-21 Proportion of shredders ( SE) in each patch based on patch type and disturbance. ...... 147 4-22 Proportion of filterers ( SE) in each patch bas ed on initial patch mass......................... 148 4-23 Proportion of filterers ( SE) in each patch type............................................................. 149 4-24 Proportion of collector-gatherers ( S E) in each patch type............................................ 150 5-1 Microlandscape designs us ed in the behavioral and colonization experim ents. Liriodendron leaf packs (brown squares) and Ludwigia macrophyte patches at A) 10 B) 20, and C) 30 percent cover...................................................................................... 165 5-2 Average deviation from a correlated random walk ( SE) (CRW) (Rdiff) for Anisocentropus .................................................................................................................166 5-3 Average probability ( SE) of each turn being in the sam e direction for Anisocentropus .................................................................................................................167 5-4 Average correlation ( SE) between turning angles for Anisocentropus. .......................168 5-5 Average net squared displacement ( SE) of Anisocentropus in microlandscapes......... 169 5-6 Mean step length ( SE) in each landscape for Elimia ...................................................170 5-7 Average deviation ( SE) from a correlated random walk (Rdiff) for Elimia ................171

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12 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy RIPARIAN ZONE MANAGEMENT IN COASTAL PLAIN STREAMS: MULTI-SCALE EFFECT S OF HABITAT FRAGMENTATION By Marcus Wayne Griswold August 2008 Chair: Thomas Crisman Major: Environmental Engineering Sciences Riparian zones filter nutrients, sediment, and pro vide food and habitat for terrestrial and aquatic organisms. Georgias forestry practi ces were evaluated in coastal plain streams by manipulating harvest regimes in headwater stream s. Macroinvertebrate and their food sources were sampled before and after harvest. A drought occurring prior to the study degr aded stream s, depressing invertebrate abundance and diversity. A core set of speci es appeared immediately following drought, displaying short life cycles and resistance to desiccation, allowing for rapid recovery from disturbance. Communities shifted from small, sclero tized individuals abundant in drift, to those that were larger, soft-bodied, and rare in drift, indicating more favorable habitat. In response to harvest, communities shifted from detritivores to herbivores, following shifts in food availability from organic matter to algae and macrophytes. This was most apparent immediately following harvest and followed a trajecto ry of recovery over the next four years. Interestingly, multimetric indices of water qua lity based on macroinvertebrates suggested more favorable conditions in the most disturbed treatme nt. This relates to in creases in food quality, due to an increase in algae and macrophytes, and a decrease in C:N ratios in terrestrially derived

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13 leaves. However, invertebrates in the thinned SMZ were represented by species preferring to live in sand, highlighting the increased isolation of patches appare nt in these reaches. At the microhabitat scale, macrophyte patche s were m ore complex, stable, and trapped higher quantities of organic matter; attracting more diverse invertebrate communities than leaf packs. Shredders were more common in large l eaf packs and scrapers more common in large macrophytes. This reflected the higher biomass of chlorophyll a in macrophytes and bacteria in leaf packs. This was supported during a behavi oral study utilizing a ha bitat specialist and generalist where the availability of both m acrophytes and leaf packs was preferred by both groups and decreased emigration rates from landscap es. Increased diversity of habitats created by harvest potentially balanced the effects of habitat fragmentation and isolation. Evidence from this study indicates that pr operly m anaged riparian zones effectively maintain water quality in small coastal plain st reams. However, managers should consider the consequences of reducing habitat specialists a nd its potential effects on food-web structure.

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14 CHAPTER 1 INTRODUCTION Overview of forestry practices in southeastern U.S. Managed forests practices comprise a signifi cant land area within the U.S., thus their proper m anagement has broad scale consequenc es for biodiversity and ecosystem functions. Previous disregard for these ecosystems resulte d in loss of nearly 120 million hectares of forested land in the U.S. from 1630-2005, of which 40 million was lost in the southeastern U.S. (Alvarez, 2007). Currently, approximately 59 % of land in the southeastern U. S. is forested, with 98% managed for timber (Alvarez, 2007), repr esenting more than 10% of timberland in the U.S. In Georgia alone, there are 9.5 million hect ares of commercial forest land, comprising an area covering nearly 67% of the state (Georg ia Forestry Commission, 1999). Additionally, the Coastal Plain is extremely productiv e, with the fastest pine growth rates in the country, thus attracting forestry operations. (Demmon, 1951). Historically, logging has occurred along rive rs and stream s, in part to facilitate downstream transport of timber, with little regard for preserving stream habitat or biota. However, following enactment of the Clean Wate r Act in 1972, land managers recognized the importance of protecting water quality. In recent years, nonpoint-source (NPS) pollution has become one of the greatest threat s to U.S. water quality as point sources were eliminated or controlled (USEPA, 2003). Silvicul ture accounts for 5,900 km of impa ired rivers and streams in the U.S. and is ranked 9th of the 10 leading sour ces of nonpoint pollution of rivers and streams in the South (West, 2002). Currently, two percent of all assessed stream kilometers (7% of all impaired kilometers) are considered degraded through forestry activities (US EPA, 2000). In addition, 53 % of the freshwater supply, origin ates on forestlands (e.g., headwaters) (Alvarez,

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15 2007), and proper management strategies are necessary to protect loca l and downstream water quality. Buffer Zones and Aquatic Ecosystems Buffer Zones and Water Quality Riparian buffer zones (streamside management zones) are forested areas along stream s meant to protect biotic integrity and water quality. Riparian zone s act as important ecotones for aquatic systems, providing food for aquatic (e.g. organic matter and terrestrial insects) and terrestrial organisms (e.g., emerging aquatic adul ts) (Nakano et al., 1999), shading, temperature regulation, and woody debris; provid ing the basis for invertebrate community structure (Kiffney et al., 2003). Small headwater streams are closely linked to the riparian zone since they are relatively narrow and shaded by forest canopy (Cummins, 1974; Hynes, 1975; Vannote, 1980; Moore and Richardson, 2003). They account for 70-80 % of total watershed area in the U.S. and export organic matter (OM), sediment, prey items, and nutrients downstream (Meyer and Wallace, 2001; Kiffney et al., 2003). Logging and thinning of vegetation in the ripa rian zone reduce detrital input to stream s over time. The extent of this reduction is influenced by the remaining canopy cover in the riparian buffer zone. Decreased canopy cover le ads to increased light and temperature (e.g., Swift and Messer, 1971) in str eam channels, and may increase primary productivity, shifting production from heterotrophic to autotrophic pro cesses (Hartman and Scrivener,1990; Fuchs et al., 2003). In faster high gradient streams this process leads to dominance by algal communities, while in low-gradient, coastal plain streams it results in a mix of ma crophyte and algal growth (Noel et al., 1986; Kedzierski a nd Smock, 2001). This change typically results in increased density, biomass and diversity of macroinvertebrates and can sh ift macroinvertebrate dominance from shredders to grazers (Jackson et al., 2001; Kedzierski and Smock, 2001; Fuchs et al., 2003).

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16 Such a shift in foodweb structure potentially al ters ecosystem function (e.g., decomposition) and higher trophic levels, limiting food availability for detritivores. Watershed-level disturbances alter runoff regi mes and evapotranspiration rates. Logging potentially alters the hyd rologic regime, such th at increased surface runo ff contributes sediment and nutrients to the affected streams. The primary hydrological influence of harvesting and thinning is increased water yield due to decreased evapotranspiration that typically in harvest treatments is 69 to 210 mm/year (Beasley and Granillo, 1982; Williams et al., 1999; McBroom et al., 2002; Grace et al., 2003). This change in hydrology may ultimately homogenize microhabitats and exclude inverteb rates that prefer slow flow. Clearcut watersheds typically have large sedi m ent yields, potentially clogging fish gills and smothering invertebrate habitat. Gurtz and Wallace (1984) found that abundance of many invertebrate taxa in habitats susceptible to sediment deposition (i.e., pools and sandy reaches) declined in a stream draining a recently clear -cut watershed, whereas those taxa in less susceptible habitats (i.e. steep-gradient, boulde r outcrops) increased. Th is emphasizes the need for proper management of riparian zones in co astal plain streams as they are primarily low gradient systems dominated by extensive sandy reaches, with few outcroppings. In addition, creation of buffer zones decreases potential fo r sediment movement by promoting sheet flow rather than channelized flow across the landscape. Harvest related changes in nut rient export affect the abundan ce and diversity of aquatic invertebrates. Macroinvertebrat e abundance m ay initially increase as nutrients fuel algal growth, providing food to a typically resource-limited grazer population. However, Miltner and Rankin (1998) found a negative relationshi p between water quality indices based on macroinvertebrates and increased nutrient concentrations, especially in low order streams. Additionally, harvest-

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17 related increased nitrogen may accelerate leaf litter decompos ition, altering organic matter dynamics and potentially limiting resources available for detritivore populations (Bormann et al., 1974; Likens et al., 1978; Martin et al., 2000; Swank et al., 2001). However, these changes tend to be shortlived, with water che mical parameters recovering within one to two year s (Corbett et al., 1978; Martin and Pierce, 1980; Arthur et al., 1998). Vowell (2001) did not find any change in water chemistry in Florida when Best Management Practices (BMPs) were utilized nor did Adams (1995) in South Carolina. However, neither study connected long-term pre or post harvest data, nor did they selectively harvest within the buffer zone, an acceptable practice in Florida and Georgia (Georgia Forestry Commission, 1999). Current Status of Riparian Zone Man agement in the So utheastern U.S. Regulations for Stream Management Zone (S MZ) width vary am ong states, however, most rely on watershed slope as a predictor of sediment inputs foll owing harvest. Although Georgia recommends a buffer width for a perennial stream beginning at 12.2 meters (40 feet), with increases as slope of the adjacent watershed increases (Georgia Forestry Commission, 1999), current regulations allow for limited harvest within the SMZ. Such harvest, known as thinning or partial harvesting, may be conducted until either th ere is a minimum of 11.5 square meters of basal area per hectare (50 square feet of basal area per acre) or 50% canopy cover remaining. Aust and Blinn (2004) examined published research on the effects of forest practices on water quality in the southeastern U.S. for the previous 20 years. They concluded that forestry BMPs were effective for m inimizing potentially negative effects of forest practi ces on water quality, but needed to be refined to reflect site specific c onditions in the southeas t. Impacts of logging on stream biota have been well stud ied in high gradient streams in the northwest and the eastern Appalachians of the U.S., but little emphasis has been placed on small, low gradient streams in

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18 the southeastern part of the count ry. Furthermore, the effects of partial harvest within SMZs on water quality are not well documented. More research is ncessary to fill in gaps that currently exist regarding BMP effectiveness in the coastal plain and effects of partial harvesting within SMZs. Habitat Fragmentation and Forestry Practices Forestry practices potentially have advers e effects on communities by lim iting dispersal between watersheds, eliminating suitable envi ronmental conditions, and altering predator-prey dynamics. Even with current regulations for str eam water quality, clear cutting of a watershed down to the buffer zone commonly occurs. A lthough this can maintain local biodiversity, dispersal across this newly created, potentially hostile landscape may be difficult for small organisms such as invertebrates and amphibian s (Hughes et al., 1996; Fagan, 2002; Briers et al., 2004). Although distance between watersheds can serve as a template for determining population s tructure and species composition (e.g., Harding, 2003), locally influenced microhabitats may be the strongest drivers of co mmunity structure at th e reach and microhabitat scales. Indirect effects of loggi ng or riparian zone modification lead to changes in microhabitat structure in streams. This wa s clearly demonstrated in affore sted agricultural streams that displayed an 87 % reduction in the leaf litter storage compared to forested streams (Benstead and Pringle, 2004). Similarly, Noel et al.(1986) f ound that 50% of logged st reams were covered by macrophytes, while unlogged reference stream s had only 10% macrophyte cover. Thus, a gradient of tree removal from the riparian zone should change the physical and biotic structure of the stream in a predictable manner. In logged streams, leaf pack formation is ofte n slow, resulting in increased patch isolation and fragm entation. Rooted macrophytes, however become more abundant in logged streams

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19 and are more stable, contributing to a less dynamic streambed landscape. Thus, macrophytes may support more permanent coexisting species, wh ile leaf packs may support more transient, inferior competitors. Col onization of streambeds by macr ophytes, coupled with decreased allochthonous input to logged streams, may alter the av ailability patches for stream biota. Key gaps in the current literature lie primarily within their temporal and spatial scales. Most studies have lim ited data on pre-harvest co nditions in the watershed, especially true of studies in the southern coas tal plain (Smock et al., 2001). Water chemistry and biotic communities may vary significantly on a temporal scale, knowledge of which is required to determine whether changes following logging are re lated to natural or anthropogenically related disturbance. Many studies focus on changes in taxonomic structure of the biotic community. However, changes m ay be linked more to biological traits that are sensitive to changes in habitat structure (e.g., habitat templet sensu Southwood, 1978; Townsend and Hildrew, 1994). Studies also are limited to the reach scale, whereas or ganisms disturbed in the riparian zone may be affected at the microhabitat scale. Thus the objectives of this study were to: 1) Determine the impact of two logging regime s considered acceptable in the Georgia BMP m anual on stream communities through cha nges in water quality, taxonomic and trait composition, and the role of natural varia tion (e.g., drought) on th e recovery process (Chapters 2 and 3). 2) Link changes in habitat-scale, community com position to changes in pa tch availability at the m icrohabitat scale (Chapter 4). 3) Relate small scale patterns of dispersal for ins tream habitat fragme ntation in a habitat specialist and generalist invertebra te species (Chapter 5)

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20 CHAPTER 2 IMPACTS OF CLIMATIC STABILITY ON THE STRUCTURAL AND FUNC TIONAL ASPECTS OF MACROIN VERTEBRATE COMMUNITIES AFTER SEVERE DROUGHT Introduction Natural disturbances regulate community structure and ecosystem function, and thus play a crucial role in shaping aquatic and terrestrial commun ities (Sousa, 1984; Resh et al., 1988). Aquatic ecosystems are especially vulnerable to extreme climatic changes, such as drought, because these disturbances alter flow regimes, water chemistry, and ultimately, the biotic community (Wood and Petts, 1999). The long-term effects of drought on the economy, wildlife habitat, and re creation occur as ramp disturbances over periods of years ( sensu Lake, 2003), as opposed to the e ffects of flooding events, which subside after weeks or months. The frequency and predictability of droughts are generally low. However, when drought does occur, it can potentially act as a destabilizing agent for aquatic communities. The forecast for climat e change suggests increased frequency of extreme events, particularly drought, over the next century (Wetherald and Manabe, 2002; Kundzewicz et al., 2007). Increased intens ity and frequency of natural disturbances will ultimately affect ecosystem stability and influence organisms resistance and resilience to change. During extreme drought, streams typically form a series of disconnected pools and lose evidence of surficial flow over ti me, a response that can potentially reset the aquatic community. Furthermore, toxic accu mulation of nutrients and waste (Towns 1985, 1991; Closs and Lake 1995; Dahm et al., 2003), coupled with increased temperature (Matthews, 1998) and lowered dissolved oxygen (Stanley, 1997; Golladay and Battle, 2002), add stress to the remaining species pools. Species survival after

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21 drought depends on specific life history traits including resistance to desiccation and an ability to colonize habitats rapidly through drift and aeria l migration or oviposition (Williams, 1987, 1996; Boulton, 1989). Further colonization reflect s subsequent changes in water chemistry, habitat availability, and resource base following flow resumption. Biological traits are more informative i ndicators of ecosystem function than are changes in abundance of individual species, and they are expected to change across a gradient of anthropogenic and natural disturba nces (Charvet et al ., 2000; Doledec et al., 1999; Statzner, Hildrew and Resh, 2001). Howeve r, species loss decreas es the ability of ecosystems to resist disturba nces and leads to lowered stability (Hooper et al., 2005). Therefore, an integrative approach should ut ilize both species com position and biological traits to predict community responses to disturbances (Richards et al., 1997) Biological traits are regulated at a hierarchy of scales, with environmental filters (e.g., climate and geology) creating a template for traits that are present in a specific region (Townsend and Hildrew, 1994; Poff, 1997). Thus, a subset of tr aits is expected to respond to disturbances within a certain region. For example, species that are resilient to disturbance display a series of traits, including small size and multip le generations per year, that allow them to expand their population densitie s rapidly (Townsend and Hi ldrew, 1994). As functional redundancy is common among stream invertebrate s, biological traits can be compared across large regions to unde rstand the large-scale impact s of anthropogenic change (Statzner et al., 2004). This study utilized a six-y ear (2001-2007) dataset of m acroinvertebrates from headwater streams after an intense drought in the southeastern U.S. (1998 to 2002) to characterize inter-year succession al patterns following flow restoration relative to water

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22 quality and climatic parameters, biologi cal traits and taxonomic composition, and community stability. Biological traits were expected to respond similarly in the two streams because they are adjacent headwater st reams in the same basin and have access to the same species pool. Additionally, traits we re anticipated to respond primarily to local environmental variation (e.g., water quality pa rameters) as a reflec tion of large-scale environmental filters. However, changes in regional climatic data are expected to structure the overall successiona l pattern of the community. Materials and Methods Site Description The two study streams were located in southwestern Georgia (30' N / 84'W), approximately 16 km south of Bai nbridge in the Coastal Plain physiographic province. They lie within the Dry Creek wate rshed, which discharges to the Flint River approximately 22 km upstream of the Jim Woodruff Dam of Lake Seminole. Surface water flow in this basin is lowest from Se ptember to November and peaks during January to April due to higher rainfall and decreased evapotra nspiration (Couch et al ., 1996). Streams and rivers in the Coastal Plain receive substantial amounts of groundwater because they are typically deeply in cised into underlying aquifers (Couch et al ., 1996). These streams were first order (width ~ 1.25m), perennial, groundwater-influenced, low to medium gradient, with sand-dominated substrate (D50WF = 0.54mm, D50SF = 0.71mm). The wetland-fed stream (WF) has a broader, flatter valley floor with several lateral wetlands and drained a catchment of 26.2 ha with a gradient of 1.96%. The seepfed stream (SF) was more incised with a steeper, v-shaped valley, a 43.9 ha drainage basin and a 2.11% gradient (Summer et al., 2003). Both watersheds are forested with WF dominated by Nyssa biflora Liriodendron tulipifera Pinus taeda and Quercus alba, and

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23 SF dominated by Pinus glabra Fagus grandifolia Liriodendron tulipifera and Quercus nigra Hydrologic and Environmental Variables The climate of the region is character ized by warm, hum id summers, and mild winters. Average temperatures in January, the coldest month of the year, range from 2.8C to 16.3C. July is the hottest month, with average temperatures ranging from 21.5C to 33.5C (SERCC, 2004). Mean annua l precipitation is 1412 mm, with June having the highest mean rainfall (152.1 mm) and October the lowest (77.5 mm) (SERCC, 2004). Summer rains are usually short, with high intensity events giving way to low intensity frontal events from late fall to ear ly spring. Due to close proximity to the Gulf of Mexico, heavy rainfall associated with hurricanes and tropical storms is not unusual in late summer. Drought characteristics were based on regi onal precipitation data and flow data from both study streams. Flow data were obt ained from in-stream parshal flumes and ISCO (Teledyne Isco, Lincoln, NE, USA) sa mplers (Summer et al., 2003) beginning in 2001. A standardized precipitation index (SP I) (McKee et al., 1995) was calculated to assess the frequency and duration of droughts in the region based on monthly precipitation averages for southwest Georgia (National Climatic Data Center, 2007). This index is preferable over the Palmer drought severi ty index because it is easier to interpret, more realistic over the long-term, and does not depend on a normal distribution of precipitation (Guttman, 1999). SPI values less th an one indicate a water deficit, and those above one an excess. SPI values were calculated based on 3-, 12, and 48-month running averages to determine the presence of shor t-term, intermediate, and long-term droughts,

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24 respectively. For example th e three-month index for Nove mber 2002 is the average of August, September, and October 2002. Water temperature was measured from October 2001 through February 2007 with an Onset HOBO temperatu re logger (Pocasset, MA), programmed to record temperature every 15 minutes. Water chemistry and meteorological measurements have been collected by other investig ators as part of the Dry Creek Study, and these data were available for use in this study. Monthly in-situ measurements for dissolved oxygen, specific conductance, temperature, pH, and tu rbidity were made at eight sites (two per stream) with portable meters. Grab samples were taken from a midstream location and analyzed for inorganic nitr ogen, inorganic phosphorus, and ammonium. Specific details of data collection and sample analysis are in Jones et al.(2003). Va lues were ln (X+1) transformed prior to anal ysis to normalize data. Invertebrate Sampling Benthic macroinvertebrates were collected from four sample reaches (two per stream, separated by ~ 50 meters) with a 500m-mesh D-frame net (0.3 m wide) in December and February for six consec utive years beginning December 2001, which marked return of flowing water in both streams. Twenty samples (~ 0.5 m) were taken from each reach for a total of ~ 3.1 m2 area sampled from all available habitats and were combined into a single sample. Samples were preserved in 95% ethanol and identified to genus using regional and national keys(Pescador et al., 1995; Ep ler, 1995;1996; Merritt and Cummins, 1996; Pescador et al., 2000; Gelhaus, 2002; Richardson, 2003). Chironomid larvae were quantitatively subs ampled, mounted and identified following Epler (1995) and Merritt and Cummins (1996).

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25 Biological Traits Nine biological traits were selected to characterize body m orphology (i.e., size, body shape, body armoring), life history (i.e., voltinism, resistance to desiccation), mobility (i.e., occurrence in drift), and ecology (i.e., rheophily, habits, feeding preferences) (Table 1). These were anticip ated to vary in re sponse to changes in precipitation and display low statistical and phylogenetic dependence (Poff et al., 2006). Some desired traits were omitted due to the lack of available information (e.g., fecundity), particularly within the chironomi d genera. The nine biol ogical traits were divided into 30 modalities ranging from two to six levels per trait. Trait information was collected from the literature (e.g., Viera et al., 2006), as well as through communication with taxonomic experts. Trait information was coded at the generic le vel, except for some Diptera and non-insect taxa, whic h were coded at the family or order level, respectively. Where information on a particular trait coul d not be obtained for a taxon (in <5 % of cases), zero scores were entered for each cat egory so it did not influence overall results (Chevenet, Doledec and Chessel, 1994). Individual taxa were th en scored for the extent to which they displayed the categories of thes e traits using a fu zzy coding procedure (Chevenet et al., 1994). Fuzzy coding allows taxa to exhibit trait categories to different degrees (Chevenet et al., 1994) to take acc ount of intraspecific variations in trait expression (Charvet et al., 2000). The scoring range of 0 to 3 was adopted, with 0 being no affinity to a trait category and 3 being high affinity. Traits were rescaled as proportions (sum = 1), such that for each trai t modality, values ranged from 0 (no affinity among individuals for the modality) to 1 (all individuals had exclusive affinity for the modality) and modalities summed to 1 for each trait. To describe the functional composition of communities in terms of dens ity of individuals, the proportion of each

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26 category per trait was multiplied by the invertebrate abundances. This resulted in a traitby-site array that contained the density of i ndividuals for each trait category for each site; density was transformed (ln(x+1)) to approxima te a normal distribution for the statistical analyses. Statistical Analysis Environmental variab les Environmental variables were analyzed over tim e with repeated measures ANOVA (SAS Institute, 2002). When differences we re significant, post-hoc analysis was conducted using Tukeys test and Bonferroni corrections. Additionally, environmental stability was assessed by cal culating Bray-Curtis distan ces (Bray and Curtis, 1957) between adjacent years. Bray-Cur tis distances are a measure of dissimilarity with values ranging from 0 to 1. Zero denotes identical samples; thus, higher values denote lower compositional stability. This measure is computed as: hj ij hjij ihaa aa D || whereihD is the distance between samples i and h. Stability Compositional stability of invertebrate co mm unities was examined separately for the two streams between pairs of successive years. Stabil ity was measured by calculating Bray-Curtis distances between adjacent ye ars based on abundance data and biological traits. ANOVA was used to examine between year differences in compositional and traits stability scores for the streams. The relati onship between Bray-Curtis values and flow and SPI values were regressed to assess the impact of hydrologic scale on community and trait stability.

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27 Ordination: species composition and traits. Nonmetric multidimensional scaling (N MDS; Kruskal, 1964) was used to explore temporal patte rns in species composition and bi ological traits. NMDS is an ordination method based on ranked distances between samples, and it is highly suitable for ecological data that typically contain numerous zero values. First, a distance matrix was constructed using Sorensen's metric s. To reduce the chance of local optima (Legendre and Legendre, 1998; McCune, Grace and Urban, 2002), an initial ordination with 1000 runs was conducted, and the ordinatio n with the lowest stress value was used as the starting configuration for NMDS. Stress is the square root of the ratio of the squared differences between a monotoni c transformation of the calculated dissimilarities/distances and the plotted dist ances and the sum of the plotted distances squared. The number of dimensions retained was evaluated after inspecting the stress (goodness of fit) of solutions with dimensions 1 through 6, with values close to 0 being a good fit of the data. Significance was assess ed by conducting Monte Carlo tests using 999 runs of randomized data in the final ordination. A P-value was calculated as a function of the number randomized runs that re sulted in a stress less th an or equal to the observed stress (McCune and Mefford, 1999). Ordi nations were performed separately for each stream because preliminary analysis indi cated that differences between sites masked any temporal effects. Ordinations were performed on species abundances and abundanceweighted biological tr aits individually. A multi-response permutation procedure (MRPP; McCune and Grace 2002) was used to test f or significant differences in taxonomic composition and biological trait structure over time at each stream. MRPP is a nonparametric method that examines the

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28 null hypothesis of no difference between two or more a priori defined groups. The test statistic A describes the degree of within -group homogeneity compared with that expected by chance. MRPP was based on ln (x+1) transformed abundance data and the Bray-Curtis coefficient. Indi cator species analysis (IndVal; Dufrene and Legendre 1997) was used to identify significant indicato r species discriminating among the time periods for the species composition and biological trait data. IndVal is ba sed on a comparison of relative abundance and relative frequencies of taxa in different a priori groups. Good indicator taxa are those occu ring at all sites in a given group and never in any other groups (Dufrene and Legendre, 1997). The indi cator value ranges from zero to 100 and is maximized when all individuals occur within a single group of sites. The significance of the indicator values for each taxon was tested by Monte Carlo tests with 1000 permutations. All ordinations, MRPP, and indi cator species analyses were performed in PC-Ord ver. 5 (McCune and Mefford, 1999). Results Hydrologic and Climatic Patterns SPI values ranged from .54 to 4.29 duri ng the 50 year period from 1956 to 2006 in southwest Georgia (Fig. 1). Values grea ter than 2 are classified as extremely wet and values below as extremely dry (Guttman, 1999). Mean values for the 3-, 12-, and 48-month SPI during the 1998 drought were .25 (SD = .06), .29 (SD = 1.42), and 0.55 (SD = .86) respectively. Th e drought prior to the study period (1998 2002) was the worst of the past 50 years and the third worst of the past 100 years, exceeded only by droughts from 1930 to 1935 and 1938 to 1944 (Barber and Stamey, 2000). The 1998-2002 drought had serious impacts on streams and rivers in the region,

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29 with the number of zero-flow days reachi ng 2050 year recurrence levels and the Flint River displaying record low daily flows (Barber and Stamey, 2000). The current study (late 2001 to 2007) occu rred during a peri od of average precipitation, with slightly above-average SPI values for m onths 3 and 12 (i.e., 0.13, SD = .02 and 0.14, SD = 1.00, respec tively) and a slightly be low-average SPI value for month 48 (i.e., .33, SD = .22). Additionally, hydrographs recorded flow throughout most of the sampling period (Fig. 2), and th e number of zero-flow days progressively decreased over time in both streams, indica ting a period of stream recovery. However, SPI values in 2006 indicate a return to a drought period, an observation supported by occurrence of a substantial drought in Georgia in 2007. Environmental Variables Although highly variable, environmental stability was rela tively high throughout the study, w ith Bray-Curtis values ra nging from 0.03 to 0.15 (Fig. 3). Most environmental parameters fluctuated over time regardless of changes in precipitation or discharge (Table 2), however, some parame ters changed significantly with time. Ammonia remained low throughout most of th e study, but doubled in the third year in both streams (F5,41 = 2.3, P = 0.05). Values for pH were variable, but were highest immediately following drought, decreasing thereafter (F5,41 = 4.7, P < 0.01). Additionally, WF remained more acidic than SF throughout the study. Orthophosphate decreased over time (F5,41 = 5.4, P = 0.02), but increased again in the 2006 sampling period. In general, conductivity decreased following flow resumption (F5,41 = 2.3, P = 0.05) but increased again during th e 2006 sampling period. Temperature decreased by four degrees over the study period (F5,41 = 5.1, P < 0.001), ranging from

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30 12C to 16 C. Leaf fall peaked in the fi rst year following the drought, but was reduced by 50% the following year (F5,41 = 2.6, P = 0.04). Benthic Macroinvertebrates Community succession Although the two streams differed extensively in term s of successional patterns following drought, a number of species responded similarly at both s ites. A core set of taxa were present throughout the six-y ear sampling period at both sites including Ceratopogonidae (Bezzia ), Chironomidae (Parametriocnemus, Polypedilum Tanytarsus Tribelos, Zavrelimyia ), Decapoda (Cambaridae), Tabanidae ( Chrysops ), and Tipulidae ( Pilaria ). Similarities in the second year included Chironomidae ( Cantopelopia Orthocladiinae) and Ptychopteridae ( Bittacomorpha ), while those in the fourth and fifth year of sampling included Trichoptera ( Lepidostoma ), Hemiptera ( Microvelia ), and Odonata ( Boyeria ). The sixth year was the first year that no additional taxa were found (Appendices 1 and 2). Taxon richness increased significantly over time (F4,30 = 122.73, P < 0.001), primarily during the initial three years of th e study (Fig. 2-4A), but was consistently lower in WF (F1,30 = 56.65, P < 0.001). However, taxon richness saturated with the same number of taxa occurring from the fourth to the sixth year. Te mporal progression of abundance was more humped shaped, decreasing after the fourth year. Invertebrate abundance increased similarly in both streams through time (F4,30 = 8.68, P < 0.001)(Fig. 4B), but WF consistently had signifi cantly fewer individuals than SF (F1,30 = 19.94, P < 0.001).

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31 Community stability Bray-Curtis values for taxonomic com position decreased progressiv ely from 2001 to 2006, with increased stability over time at both sites. Ho wever, Bray-Curtis values decreased during the 2006 to 2007 peri od, indicating a change in community structure to an earlier period (Fig. 2-5). Communities were more stable in wetter than drier periods, as indicated by the negative re lationship between Bray-Curtis values and SPI values (Fig. 2-6). For SF, stability was si gnificantly related to both local and regional hydrologic and climatic indicators, however, stronger relationships existed with flow (R2 = 0.33, P <0.001) and the 48-month SPI (R2 = 0.5, P < 0.001). Only long-term 48-month SPI values were related to stability in WF with a similar negative relationship between SPI values and stability. Biological traits were relatively stable over tim e, and low Bray-Curtis values suggested that traits were more stable than taxonomic composition (Fig. 2-7), while those for WF were only significantly correlated with the intermediate 12-month SPI (R2 = 0.2, P = 0.02). Biological traits for SF were not significantly correlated with local hydrologic or regional climatic variables. Taxonomic Composition Wetland-Fed stream (WF) NMDS ordination (stress = 10.8, P = 0.001) explained 88.4% of the variance in the dataset, with 22%, 36%, and 31% explai ned by Axis 1, 2, and 3 respectively. Overall, the ordination indicated tem poral separati on of species composition (Fig. 2-8) and was supported by significant diffe rences between all time periods (MRPP, A = 0.5, P < 0.001). Axis 1 was primarily represented by local variables including pH (r = .5), dissolved oxygen (r = .5), and turbidity (r = .4). The genera Calopteryx (r = .6), Chironomus

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32 (r = 0.6), Chrysops (r = 0.6), Eukiefferiella (r = 0.7), Lepidostoma (r = 0.6), and Pycnopsyche (r = 0.7) were most strongly correlated with Axis 1. Axis 2 was most related toboth local and large-scale va riables including pH (r = .4) dissolved oxygen (r = 0.4), and the 12-month (r = 0.4) and 48-month SPI (r = 0.7). The genera Agabus (r = 0.7), Boyeria (r = 0.66), Conchepelopia (r = 0.6), Erioptera (r = 0.8), Microtendipes (r = 0.7), and Orthocladius/Cricotopus (r = 0.7) were most strongly related to Axis 2. Axis 3 was correlated with dissolved oxygen (r = .5), and 48-month SPI (r = .5). The genera Caecidiota (r = .6), Microvelia (r = .8), and Smitia (r = .7) were strongly correlated with Axis 3. No significant indicator sp ecies were found in the W F stream for the first three years following drought. Taxonomic indicators of temporal change (P < 0.05) included genera indicative of the fourth year such as Corethrella Stenochironomus Polypedilum Pseudolimnophila Cordulegaster Lepidostoma and Scirtidae. Those having a maximum indicator value for the fifth year we re primarily predators and included Cryptochironomus Alotanypus, Clinotanypus, Bezzia Alluadomyia and Laevapex Those in the last year of the study included Larsia and Erioptera Seep-Fed stream (SF) NMDS ordination (stress = 12.9, P = 0.001) explained 90.2% of the variance in the SF dataset, with 77% and 13% explained by Axes 1 and 2, respectively. Overall, the ordination indicated separation of species com position with time (Fig.9) and was supported by significant diffe rences between all time periods (MRPP, A = 0.5, P< 0.0001). Axis 1 was primarily repres ented by o-phosphate (r = .6), NO2/NO3 (r = .4), dissolved oxygen (r = 0.8), flow (r = 0.6), 3month (r = 0.4) and 48-month (r = 0.7) SPI.

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33 The genera Alluaudomyia (r = 0.6), Bezzia (r = 0.7), Corynoneura (r = 0.7), Stempellinella (r = 0.6), Thienemaniella (r = 0.8), and Zavriella (r = .8) were most strongly correlated with Axis 1. Axis 2 was most related to pH (r = 0.7), dissolved oxygen (r = .5), and leaffall (r = 0.5). The genera Neoporus (r = .7), Parachaetocladius (r = .6), Sphaerium (r = .6), and Pycnopsyche (r = .5) were most strongly related to Axis 2. Significant indicator species for the second year included Allocapnia Helichus Parachaetocladius, and Stenelmis. The third year was m ostly represented by shredders and scrapers including Anisocentropus Cordulegaster Eurylophella Habrophlebiodes Ophiogomphus Pseudolimnophila and Stempellinella The indicators in the fourth year included Baetidae, Psychoda Scirtidae, Tribelos and Zavrelimyia The fifth year was represented by Caenis Calopteryx Diplectrona, Microvelia Nippotipula Rheotanytarsus, and Stenonema The last year of the study was represented by Corynoneura. Biological Traits Wetland-Fed stream NMDS ordination (stress = 11.5, P = 0.001) explained 87.2% of the variance in the dataset, with 53%, 10%, and 25% explained by Axes 1, 2, and 3 respectively. Tem poral changes were supported by overall si gnificant differences between time periods (MRPP, A = 0.3, P < 0.0001) (Fig. 10). However, pairwi se comparisons indicated weak changes in traits over time. Axis 1 was prim arily represented by specific conductance (r = .4) and 12-month SPI (r = 0.5) and thus related to intermediate temporal changes. Soft bodied (ar1, r=0.9), fast flow preferring (r3, r = 0.6), sprawlers (h4, r = 0.6) with bluff and tubular shapes (sh2, r = 0.8) were positiv ely correlated with Axis 1. Sclerotized (ar2,

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34 r = .9), slow flow preferring (r2, r = .6), streamlined traits (sh1, r = .8) were negatively correlated with Axis 1. Axis 2 was negatively correlated with pH (r = .4). Burrowers (h2, r = 0.8) were strongly correlated with Axis 2. Axis 3 was most related to local, short-term variables including t ss (r = .6), dissolved oxygen (r = 0.5), temperature (r = .5), and 3-month SPI (r = 0.4) Collector-gatherers (tr1, r = 0.8) with several generations per year (v3, r = 0.6) were positively related to Axis 3. Those with one generation a year (v2, r = .7), hard shells or cases (a r3, r = .7), and a predatory lifestyle (tr5, r = .8) were ne gatively related to Axis 3 Analysis of indicator species showed that early colonizers had sclerotized, tubular or bluff bodies and are abundant in drift. Late r years were characterized by species that cling to the substra te, rarely drift, and are hard shelled or made a case. Seep-Fed stream NMDS ordination (stress = 7.9, P = 0.001) explained 97% of the variance in the dataset, with 80% and 17% explained by Axes 1 a nd 2, respectively. Overall, the ordination indicated separation of species com positi on with time (Fig. 11) and was supported by significant effects of time on tr ait composition (MRPP, A = 0.4, P < 0.0001). Axis 1 was most related to leaf fall (r = 0.5) and the 48-month SPI (r = 0.4). Small (s1, r = 0.8) softbodied (ar1, r = 0.9) bluff or tubular (sh2, r = 0.8) individual s that gather food (tr1, r = 0.8), with more than one generation per year (v1, r = 0.8), abundant in drift (df1, r = 0.8), and sprawled (h4, r = 0.6) or climbed (h6, r = 0.6) over the substrate were positively related to Axis 1. Shredders (tr4, r = .7) and scrapers/herbivores (tr3, r = -0.7) uncommon in drift (df1, .8) with medium (s2, r = .6) to large (s3, r = .5) streamlined (sh1, r = .8) and with sclerotized (ar2, r = .8 ) or shelled (ar3, r = .8)

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35 bodies and less than one generation per year ( v1, r = .8) were negativ ely related to Axis 1. Axis 2 was correlated with NO3/NO2 (r = 0.4). Small individuals (s1, r = 0.5) lacking resistance to desiccation ( d2, r = 0.8) with more than one generation per year (v3, r = 0.5), are common in drift (df2, r = 0.7), prefer fast flowing wa ter (r3, r = 0.7) and cling to substrates (h1, r = 0.8) were positively related to Axis 2. Medium-sized (s2, r = .7) individuals rare in drift (df1, r = .6) resi stant to desiccation (d1, r = .8) with one generation per year (v2, r = .5) that pref er slow flowing water (r2, r = .5), are predators (tr5, r = .6), and burrow into th e substrate (h2, r = .8) were negatively related to Axis 2. Indicator traits in the first two years incl uded scrapers/herbivores with hard shells or cases that clim b on substrate. Those in th e third year included genera with less than one generation per year and not resistant to desiccation. Th e last two years following the drought were represented by predators and skat ers preferring fast flowing water. Discussion Few studies have attempted to dissect the functional and structural responses of aquatic communities to a severe, un predicta ble drought event (Boulton and Lake, 1992; Wood and Petts, 1999; Wright et al., 2001; Churchel and Batzer, 2007). Studies on the impacts of short-term wet and dry season cycl es have provided insi ght into predictable climatic variation, primarily in Mediterranean and arid climates (Gasith and Resh, 1999; Acuna et al., 2005; Beche, McElravy and Res h, 2006; Bonada et al., 2006). In this study, regional precipitation indices (SPI) were good predictors of temporal changes in both taxonomic composition and biological trait stru cture in perennial st reams. Communities became more stable over time and were significan tly more stable in wet, rather than dry, years. Temporal changes in community co mposition and trait structure resulted in a

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36 rapidly stabilizing community w ithin the first three to four years after drought, producing highly stable and persistent communities in the fourth and fifth years. Stability was maintained throughout the o ccurrence of a large discharge event 4 months before collection of the fifth-year sam ples (Fig. 2). Recolonization after flood events is rapid, limiting effects to shortterm changes in abundance and community composition (Townsend, Doledec and Scarsb rook, 1997). Beche, McElravy and Resh (2006) also found that invertebrate communities and trait characteristics were more stable in wet, rather than dry, season communities and postulated that droughts have more severe long-term consequences than flooding for invertebrate communities. Traits changed less with time than taxonom ic composition and were more stable. This may be a product of the high functional redundancy existing among aquatic invertebrates (Poff, 1997; Lamouroux, Doledec and Gayraud, 2004). For example, although climatic variation can change species presence, multiple species share similar traits, allowing taxa to survive during changi ng conditions. The role of local and regional abiotic filters are discussed below in relation to temporal changes in structural (e.g., taxonomic) and functional (e.g., traits) aspects of invertebrate commun ities as a result of a disturbance imposed by a long-term drought. Environmental Variation Environmental stability was relatively high but highly variable throughout the study, with Bray-Curtis values ranging from 0.03 to 0.15 (Fig. 3). However, local water chemistry variables did not follow changes in precipitation or flow. This may be linked to high connectivity to the floodplain and oxyge nation of the hyporheic zone; these interactions are typically lost during severe drying even ts (Boulton, 2003; Lake, 2003)

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37 Droughts act on local stream variables by concentrating nutrients and organic m atter, and potentially increasing temperatur e (Closs and Lake, 1995; Stanley, Fisher and Grimm, 1997; Matthews, 1998; Golladay a nd Battle, 2002; Dahm, 2003). A decrease in o-phosphate following drought reflected flushing of stored nutrients during increased flow periods (Dahm, 2003). Ammonia peaked in the third year in both streams, reflecting increased microbial activity and organic ma tter. Massive amounts of organic matter are typically stored in the stream channel a nd floodplain during drought. Initial flushes from early flow events may not have been enough to carry organic matter from the floodplain into the stream, however, a large flow event in the spring prior to the third sampling period likely made a large amount of organi c matter available. Baldwin (2005) also suggested that peaks in ammonia following dr ying events might have originated from dead bacterial cells. As in other studies, a coupled decrease in water temperature and increase in discharge led to higher overall dissolved oxygen values (Stanley, Fisher and Grimm, 1997; Matthews, 1998; Golladay a nd Battle, 2002). Conductivity also decreased with time, reflecting diluti on of concentrated ions typically found during drought (Stanley, Fisher and Grimm, 1997; Caruso, 2002; Line et al., 2006) and may have been linked to greater contribution of groundw ater versus surface flow found during dry periods (Rider and Beli sh, 1999; Caruso, 2002). Limited precipitation and water availability in th e riparian zone altered local landscape dynamics. Leaf fall within the ripa rian zone decreased following the drought, indicating a recovery period from the drought as trees often drop their leaves during periods of moisture deficit (Escudero a nd del Arco, 1987). Although this may provide more resources for invertebrate s, leaf quality may be lower and thus limit decomposition.

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38 Temporal Variation and Successional Patterns in Taxonomic Abundance Broad-scale measures of macroinvertabrate communities were responsive to tem poral changes in environmental conditi ons. Overall abundance was more responsive to short-term environmental variation than we re taxa richness or st ability. Taxa richness was lowest immediately following drought, peaking in the 2004 sampling period. Changes in taxa richness have been linked to disturbance history in relation to short-term and long-term droughts (Beche, 2006). As fl ow regimes recover, more favorable conditions exist including in creased habitat availability and heterogeneity, higher dissolved oxygen levels, a nd dilution of nutrients. A set of nine core taxa existed in both stream s immediately following drought forming a regional species pool adapted to extreme conditions. Most either have multiple generations per year or a de siccation resistant stage. Cr ayfish typically respond to drought by creating deeper burrows, which may al so provide other species a refuge from receding water levels (Boulton, 1989). The chironomid genus, Polypedilum makes cocoons to resist periods of drying (Hinton, 1960). The presence of coleopteran adults and hemipterans in WF immediately followi ng drought reflect their ability to survive outside of the stream and ra pidly colonize via aerial disp ersal (Ortega et al., 1991; Wissinger, 1997). Changes in taxonomic composition were link ed to both localand large-scale environmental variables. Dissolved oxygen and pH were most linked to changes in taxonomic conditions for local variables, while long-term 12and 48-month precipitation most influenced overall changes in taxonomic composition in WF. Low pH values in WF excluded entire taxonomic groups, including Ep hemeroptera and Plecoptera. Dissolved oxygen is often posited to be a controlling variable for invertebrate communities in

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39 streams and is closely related to water quality. The relationshi p of this variable with longterm SPI values indicates the advantage of incorporating regional climatic data into bioassessment protocols. Temporal Variation in Traits Traits were more related to local abiotic variables than to flow or long-term precipitation indices. Initially, traits may be filtered by large-scale factors, including climate and geology (Poff, 1997); thus at the smaller scale of two adjacent watersheds, traits may vary locally. Across small, physiographically homoge neous regions (e.g., watersheds, ecoregions), sites are likely to be located within a single regional species pool (Zobel, 1997). Thus, as predicted by the habitat templet model (Southwood, 1977; 1988; Townsend and Hildrew 1994), local charac teristics at the r each scale directly influence biological traits. Traits responded predictably to changes in local environm ental conditions. As pH increased and nutrients decreased, species le ss likely to drift became more common in the stream reaches. Initial availability of nitrogen and phosphorous allowed for early colonization of scrapers (e.g., Boulton, 1991) as algal sources within the stream accumulated on available substrate. However, this effect was not apparent in WF, reflecting the lower productivity of grazers typically associated with colored, acidic streams (Rosemond et al., 1992). Additionally, shredders became more common in the second and third year, as previously e xposed patches of organic matter became submerged. In addition, species typically cl assified as detritivores (e.g., nemourid stoneflies) may consume algal biomass, assuming the role of scrapers, especially in streams with lower pH (Ledger and Hildrew, 2005). In a comparison of rivers affected by drought in Italy, Fenoglio et al.(2007) docum ented an increase in collectors and a

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40 decrease in shredders and scrapers w ith increased drought duration, suggesting a predictable cyclic change in feeding habits with drought. After a major disturbance, body size is hypot hesized to increase as communities stabilize. According ly, medium-sized species became more common as the community stabilized, while smaller species were more common during the less-stable time periods. Small body size is often related to shorter-life cycles, and might therefore serve as a resilience trait. However, small body size may al so allow for exploitation of refugia such as the hyporheic zone during droughts or fl oods (Townsend, 1989), serving as a potential source of colonizers (DoleOlivier, Marmonier and Beff y, 1997). Thus, small body size may also be useful for resisting impact s of disturbance (e.g., Townsend, Doledec and Scarsbrook, 1997). Organisms with longer life cycles require m ore stable habitat and water chemistry. Adaptations to high variability were less common by the third year of sampling, when species commonly had unior semivoltine life cycles and lacked adaptations for resisting desiccation. Additi onally, hardening of the exoskeleton reduces mortality during periods of drying and floods. Sclerotized and hard-shelled organisms were more common during the first two years after drought, while traits favoring softbodied organisms became more common with time. Although there was a general trend toward species lacking resistan ce to desiccation, many species in the streams appeared to be adapted to some level of drying through a desiccation-resistant or diapause stage. Although many traits responded predic tably to the drought, stream lined individuals were more comm on immediately following drought, reflecting the abundance of adult dytiscid beetles and amphipods as early colonizers. Dytis cid beetles colonize

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41 across large areas via aerial dispersal, while amphipods may persist in refugia by aestivating in moist sediments or disperse through underground rout es (Wiggins et al., 1980; Harris and Roosa, 2002). In small coastal pl ain streams, discharge is lower than in many montane headwater streams, thus streamlined bodies may not be necessary to resist flow forces. However, within four years, sp ecies preferring fast flow, such as clingers, became more abundant, suggesting that behavi oral rather morphologi cal adaptations to flow may be a distinguishing tra it of coastal plain streams. Drought Prediction A major hurdle that is often encountere d when as sessing impacts of extreme, unpredictable events on aquatic ecosystems is the availability of data prior to the disturbance (Lake, 2000; Lake, 2003). Alt hough long-term datasets (>10 years) are increasingly common in ecology, many geographi cal regions lack such data. Long-term datasets allow for the prediction of drought vi a precipitation indices, changes in stability and trait composition. The SPI ut ilized in this study indica ted a trend toward a major drought prior to the o ccurrence of such an event (Fig. 1). However, the 24-month SPI may bemost relevant since most invertebrate li fe cycles require months to years. Values fell toward 2001 levels in 2006, and a dryi ng period was evident after the last sampling period. This observation is further supported by the occu rrence of a severe drought in the same region during 2007 (U.S. Drought Monitor, http://www.drought.unl.edu/dm/archive.html). Thus, use of long-term regional precipitation data, which is more widely av ailable than discharge and ecological data, may provide a unique opportunity to study pr eand post-recovery aspects of extreme events.

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42 Stability of species composition d ecreased in both stream s in 2006, reflecting the oncoming drought. This change was more striking in WF than SF, likely because SF is buffered by groundwater inputs, while WF is dependent on surface water inputs from a wetland headwater. Traits were relatively stable ove r the study period, but decreased in the wetland-fed stream fro m 2005. Additionally, predators and species common in drift became more abundant in 20062007. Predators are linked to disturbance and become more common in distur bed or degraded streams as resources for other guilds are patchy (Rawer-J ost et al., 2000). This suggests return to a disturbed condition where organisms have the ability to emigrate if envi ronmental conditions become suboptimal. Biological traits have been advocated as good indicators of disturbance in aquatic ecosystem s (i.e. Doledec, Statzner and Bour nard, 1999). One associated issue is whether they predict changes in disturbance regime more effectively than taxonomic structure or they are a complementary aspect that shoul d be examined in disturbance ecology and biomonitoring programs (Doledec and Statzner, 2008). The results are unclear, as studies across biomes suggest they are more, less or equally as informative than taxonomic structure (Stevens et al., 2003; Finn and Poff, 200 5; Heino, 2007, Hoeinghaus, Winemiller and Birnbaum, 2007). Although less apparent than changes in taxonomic structure, stability of biologi cal traits in this study indi cated a disturbance during the drought period and the potential for another disturbance during the 2006 sampling period. Thus, traits may be useful indicators of disturbance that can be compared across watersheds. One caveat to this is that func tional traits are thought to be relatively insensitive to natural variation (Charvet et al., 2000; Statzner et al., 2001; 2005). The

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43 current study focused primarily on natural vari ation in climatic conditions and indicated changes in trait composition as a result of this variation. T hus, additional effort should be devoted to distinguishing the effects of na tural and anthropogenic disturbances when devising biological monitoring programs. Table 2-1. Definition and codes for biological traits and modalities. Trait Code Modality Trait Code Modality Voltinism v1 Semivoltine Habit h1 Clingers v2 Univoltine h2 Burrowers v3 Multivoltine h3 Swimmer Drying Resistance d1 Absent h4 Sprawler d2 Present h5 Skater Drift df1 Rare h6 Climber df2 Common Trophic tr1 Gatherer df3 Abundant tr2 Filterer Armoring ar1 Soft tr3 Scraper/Herbivore ar2 Sclerotized tr4 Shredder ar3 Case/Shell tr5 Predator Maximum Size s1 Small (<9mm) Shape sh1 Streamlined s2 Medium (9-16mm) sh2 Not Streamlined s3 Large (>16mm) (Bluff, Tubular) Rheophily r1 Standing r2 Slow r3 Fast

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44Table 2-2. Mean annual values for environmental variable s for the wetland-fed (WF) and seep-fed (SF) streams Year Flow (L/s) TSS (g/L) NH4 (g/L) ophosphate (g/L) NO2/NO3 (g/L) Total Phosphorous (g/L) Total Nitrogen (g/L) pH SC (uS/cm) DO (mg/L) Turbidity (NTU) Temperature ( C) Leaffall (g/m2) WF 20012002 0.99 0.015 2.48 2.73 1.08 8.22 238.00 5.53 42.28 4.47 1.78 16.13 34.29 20022003 2.52 0.001 6.28 1.75 0.00 3.69 278.28 4.73 30.60 7.34 0.19 12.15 12.29 20032004 1.04 0.017 11.97 1.85 0.00 13.26 345.87 5.03 35.95 4.51 1.18 16.08 19.26 20042005 1.76 0.003 2.88 2.49 2.34 4.90 233.30 4.87 24.90 7.62 1.23 12.00 21.26 20052006 1.47 0.013 6.20 1.78 0.00 16.94 343.30 5.35 26.85 6.87 1.10 13.63 30.19 20062007 2.58 0.008 3.93 3.01 0.00 9.61 291.87 5.11 33.68 8.99 0.63 13.05 24.55 SF 20012002 0.02 0.004 4.54 45.46 9.42 77.00 212.46 7.23 84.03 5.25 4.03 15.68 38.25 20022003 2.74 0.004 0.00 27.24 7.85 51.25 285.97 5.88 94.85 7.85 2.95 12.73 16.23 20032004 3.07 0.008 7.65 23.74 4.41 51.75 237.73 6.85 70.90 6.82 4.03 15.90 22.18 20042005 3.39 0.003 1.68 18.86 3.00 39.00 232.05 6.61 74.98 9.39 2.98 11.73 26.06 20052006 5.36 0.016 6.59 12.43 9.40 30.25 218.54 7.12 60.93 8.79 4.51 13.05 29.76 20062007 3.90 0.001 4.85 25.69 2.38 27.36 203.76 7.09 82.80 9.88 2.61 12.05 25.84

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45 -3 -2 -1 0 1 2 3 4 51956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(a) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(b) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(c) -3 -2 -1 0 1 2 3 4 51956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(a) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(b) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(c) C B A -3 -2 -1 0 1 2 3 4 51956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(a) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(b) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(c) -3 -2 -1 0 1 2 3 4 51956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(a) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(b) -3 -2 -1 0 1 2 31956 1958 1960 1963 1965 1968 1970 1972 1975 1977 1980 1982 1985 1987 1989 1992 1994 1997 1999 2001 2004 2006SPI(c) C B A Figure 2-1. Plot of Standardized Precipitation Index (SPI) values for southwestern Georgia, from 1956 to 2007. A) 3-month, B) 12-mont h, and C) 48-month. Values above 2 indicate an extremely wet year, while valu es below indicate an extremely dry year.

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46 (a) A (a) A (b) B (b) B Figure 2-2. Hydrograph based on m ean daily discharge (m3/s) for each stream. A) stream with wetland headwater (WF) and B) stream with seep headwater (SF).

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47 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.1601-0202-0303-0404-0505-0606-07Bray-Curtis Distance WF SF Figure 2-3. Temporal variability of Bray-Curtis stability values f or environmental variables in WF and SF ( SE).

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48 0 10 20 30 40 50 60 200120022003200420052006Total Taxa WF SFA 0 200 400 600 800 1000 1200 1400 1600 1800 200120022003200420052006Abundance WF SFB Figure 2-4. Temporal changes in taxon richness and invertebrate abundance. A) taxon richness and B) abundance values (per ~ 3.1m2) (SE) for individual years.

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49 0 0.1 0.2 0.3 0.4 0.5 0.6 0.701-0202-0303-0404-0505-0606-07Bray-Curtis Distance WF SF Figure 2-5. Changes in compositional stability (B ray-Curtis distan ce) in WF and SF ( SE).

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50 R2 = 0.11 R2 = 0.14 R2 = 0.490 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 -2.5-2-1.5-1-0.500.511.52SPIBray-Curtis Values 48-month SPI 12-month SPI 3-month SPI Linear (3-month SPI) Linear (12-month SPI) Linear (48-month SPI) R2 = 0.18 R2 = 0.21 R2 = 0.510 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 -2.5-2-1.5-1-0.500.511.52SPIBray-Curtis Values 48-month SPI 12-month SPI 3-month SPI Linear (3-month SPI) Linear (12-month SPI) Linear (48-month SPI)A B R2 = 0.11 R2 = 0.14 R2 = 0.490 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 -2.5-2-1.5-1-0.500.511.52SPIBray-Curtis Values 48-month SPI 12-month SPI 3-month SPI Linear (3-month SPI) Linear (12-month SPI) Linear (48-month SPI) R2 = 0.18 R2 = 0.21 R2 = 0.510 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 -2.5-2-1.5-1-0.500.511.52SPIBray-Curtis Values 48-month SPI 12-month SPI 3-month SPI Linear (3-month SPI) Linear (12-month SPI) Linear (48-month SPI)A B Figure 2-6. Linear regression of SPI values versus taxonom ic stability. A) Wetland-Fed (WF) and B) Seep-Fed streams.

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51 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.1601-0202-0303-0404-0505-0606-07Bray-Curtis Distance WF SF Figure 2-7. Changes in trait stab ility (Bray-Curtis distan ce) in WF and SF ( SE).

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52 Figure 2-8. NMDS ordinations of log10-abundance in site-year spa ce and taxon-space for W F. Time periods are indicated by different symbol s. Ordination plots of taxa are based on weighted-averaging.

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53 Figure 2-9. NMDS ordinations of log10-abundance in site-year spa ce and taxon-space for SF. Tim e periods are indicated by different symbol s. Ordination plots of taxa are based on weighted-averaging.

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54 Figure 2-10. NMDS ordinations of biological traits in s ite-y ear space and trait-space for WF. Time periods are indicated by different symbol s. Ordination plots of taxa are based on weighted-averaging.

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55 Figure 2-11. NMDS ordinations of biological traits in s ite-y ear space and trait-space for SF. Time periods are indicated by different symbol s. Ordination plots of taxa are based on weighted-averaging.

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56 CHAPTER 3 TESTING BMP EFFECTIVENESS FOR SMALL COASTAL PLAIN STREAMS USING MACROINVER TEBRATES AS BIOINDICATORS Introduction Headwater streams are tightly coupled w ith the surrounding riparian landscape. Thus, changes in the structure of the riparian zon e can a ffect water quality of larger streams and rivers, since they are heavily influenced by headwater streams that feed them (Meyer and Wallace, 2001). Headwater stream s make up a majority of channel length within stream networks and serve importa nt ecological and bi ological functions by delivering water, sediment, organic material prey items, and nutrients to downstream reaches (Sidle et al., 2000; Gomi et al., 2001; Meyer and Wallace, 2001; Wipfli and Gregovich, 2002). As the importance of ecosyst em services, such as water quality and biodiversity, becomes more widely recognize d, the need to protect aquatic resources increases. Thus, proper management of te rrestrial landscapes must take into account needs of aquatic organisms and communities. Numerous studies have found significant im pacts of logging on physical and chemical aspects of streams, including redu ced large woody debris in streams (Golladay, Webster and Benfield, 1987), increased se diment input (Beschta, 1978), discharge (Hartman and Scrivener, 1990), nutrient inpu ts (Likens et al., 1969; McClurkin et al., 1985), and decreased shading re sulting in higher water temperature (Swift and Messer, 1971; Webster and Waide, 1982). Elevated light temperature and nutrient concentration can increase algal biomass within the stream shifting the base of the food web from allochthonous to autochthonous sources (L ikens et al., 1970; Wallace and Gurtz, 1986; Bilby and Bisson, 1992). The extent and impact of these effects are influenced by

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57 geology, soils and vegetation of the catchment, the extent to which the riparian buffer strip remains after logging, stream discharg e, and channel gradient and morphology. Changes in abiotic characteristics of a stream following logging can affect the structure and function of th e stream community, includi ng periphyton (Lowe, Golladay and Webster, 1986), fish (Garman and Moring, 1993) and macroinvertebrates. Logging activities can disrupt stream invertebrate communities, but the magnitude and trajectory of effects vary. Increased light penetrat ion and warmer temperatures from canopy removal, and nutrient enrichment in runo ff from ground disturbance, increase aquatic invertebrate density and/or biomass in streams (Newbold et al., 1980; Murphy et al., 1981; Hawkins et al., 1982; Wallace and Gurt z, 1986; Campbell and Doeg, 1989; Brown et al., 1997). Fine sediment loading, particul arly in watersheds w ith steep slopes, can reduce invertebrate populations following logging (Growns and Davis 1994, Waters 1995, Wood and Armitage 1997), clogging trach eal gills, and burying food sources. In many cases, invertebrate communities shift from shredders to grazers (algae consumer) or detritivores (collector-gatherer) (Haefner and Wallace 1981; Gurtz and Wallace, 1984; Webster et al., 1992). Although Stone and Wallace (1998) found shifts in dom inance of taxa, there was no loss of taxa in logged versus unlogged si tes. They posited that measures of taxon richness may be useful for indicating presence of pollutants, but not for more discrete disturbances. Long-term impacts of clea r cutting were documented decades later, stemming from recovery of riparian vege tation and canopy cover (Growns and Davis, 1991; Stout et al., 1993; St one and Wallace 1998).

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58 Although there are exceptions (e.g., Wallace and Gurtz, 1986), most studies exam ining effects of riparian zone manageme nt on streams last only a few years, with only a year of pre-harvest data, limiting th e predictive power of post-harvest data. Perhaps the assumption is that management activities are only important if they supercede natural variati on in environmental conditi ons. However, catastrophic disturbances such as hurricanes and drought s potentially alter impacts of human induced disturbances. Thus, it is important to incor porate natural disturban ces into studies of anthropogenic disturbances in aquatic ecosystem s to generate more ge neral predictions of disturbance (Ward, 1998). The impacts of forest management activ ities on aquatic ecosy stem s have been well studied in the Northwest and Mid-Atlan tic U.S., where there are steep slopes and high-gradient streams, but little effort has been placed on st reams in the Southeast coastal plain (Stone and Wallace 1998; Kedzierski and Smock, 2001). These low-gradient streams have shallow slopes and finer sediment (sand and silt) than montane streams and thus are likely to respond differently to logging. Even fewer studies have investigated the impact of logging within buffer zones (e.g, Kr eutzweiser et al., 2005) even though this is an acceptable practice throughout the South east (e.g., Georgia Forestry Commission, 1999). Additionally, it appears that no study has utilized biologica l traits, other than feeding guilds, to understand impacts of forest ry practices. The goal of this study was to test the effectiveness of Georgias best mana gement practices for forestry along streams. This was assessed through multiple years of pre and post-harvest sampling of macroinvertebrates, water quality parameters, and invertebrate food sources.

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59 Materials and Methods Site Description Four study watersheds were located with in International Papers Southlands experim ental forest in sout hwestern Georgia within th e Dry Creek watershed, which discharges to the Flint River. The first order headwater st reams were labeled from A to D (Fig. 3-1) since they did not have official nomenclature. Watersheds A and B were shallow, floodplain influenced, wetland-fed streams, while C and D were incised, seepfed streams. Geology The watersheds were located on the Pelham escarpment between the Tifton upland and Dougherty plain. Soils of the study sites were dominated by Ultisols. Riparian soils were com prised of Chiefland and Esto series, which feature well drained fine sands over clay loams. The lower slopes comprised Eu stis series soils, which were loamy sands over sandy loams and classified as somewhat excessively well drained. Upland soils were Wagram, Norfolk, Lakeland, Orangeburg, and Lucy series, which are generally well drained loamy sands over sandy clay loams, with the exception of the Lakeland Unit, which has a sandy texture throughout and is ch aracterized as exce ssively well drained (USDA, 1939). This transitional area has bluffs and deep ravines that create cool microclimates supporting rare plant species with northern affi nities (Wharton, 1978). Vegetation Species composition of the vegetation was similar among watersheds. The upland consisted of m ature, planted pine, and the riparian areas were mixed pine and hardwoods.

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60 Species dominating the overstory in riparian areas were: Nyssa biflora Liriodendron tulipifera Pinus glabra, Magnolia virginiana Fagus grandifolia Liquidambar styraciflua Quercus nigra and Quercus michauxii. Magnolia grandiflora was most common in watersheds C and D (Internati onal Paper unpublished data). The upland of each watershed was dominated by Pinus taeda which was established at varying times by hand planting. The midstory of all wa tersheds was generally composed of Carpinus caroliniana Ostrya virginiana, Acer rubrum Acer barbatum and Oxydendrum arboretum Magnolia pyramidata occurred in riparian areas and midslopes of watersheds C and D. Climate The climate of the region is character ized by warm, hum id summers and mild winters with average annual precipita tion of 1412 mm (SERCC, 2007). Temperatures range from an average maximum of 33.5C to a minimum of 2.8 C. June has the highest mean rainfall (152.1 mm) and October the lowest (77.5 mm) (SERCC, 2007). Summer rains are usually short, high intensity events giving way to low intensity frontal events from late fall to early spring. Due to proxi mity to the Gulf of Mexico, spin-off from hurricanes and tropical storms in late summer is not unusual. Drought conditions occurred during 1998-2002 and resulted in an accumulated rain fall deficit of 711-1270 mm in parts of southwestern Georgia (see Chapter 2). Hydrology Surface water flow in the Apalachicola-Chat tah oochee-Flint river basin is lowest from September to November and peaks duri ng January to April due to higher rainfall and decreased evapotranspiration (Couch et al ., 1996). Streams and rivers in the Coastal Plain receive substantial groundwater because they are typically deeply incised into

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61 underlying aquifers (Couch et al., 1996). The study streams are first order, groundwaterinfluenced, low to medium gradient, and have sand-dominated substrate. In-stream habitat includes coarse woody debris, undercut banks, leaf packs, and fine roots. Fiberglass parshall flumes (Tracom Inc., A tlanta, GA) were placed at the downstream end of each reach. The four study watersheds average 39 ha, with average annual discharge of 1.5 L/s prior to harvest (Summer et al., 2003; Summer unpublished data). Experimental Harvest The statistical design was BACI (Before After Control Im pact) using a paired watershed design, with two treatment and two re ference first-order watersheds varying in area from 24 to 44 ha. Watershed pairs were determined based on landscape morphology and vegetative community, and treatment waters heds were randomly selected within each pair. Watersheds A and B formed the first pair with Watershed B selected for treatment. Watersheds C and D formed the second pair, with Watershed C selected for treatment. Each watershed was divided into an upstr eam and downstream reach, separated by at least 50 m. The reference watersheds did not receive silviculture treatm e nts during the study period. The remaining two watersheds were clea rcut after 27 months of baseline data collection (June 2001 to September 2003). Post harvest data collec tion continued until February 2007. In treatment watersheds, the SMZ in the upstream reach was left intact (intact SMZ), while 50% basal area was re moved in the downstream portion (thinned SMZ). SMZ widths were determined acco rding to minimum recommendations in Georgia BMP manual(Georgia Forestry Commission, 1999). Slopes less than 20% received a 40 foot (12m) buffer and while those greater than 20% received a 70 foot (21m) buffer.

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62 Physical and Biological Measurements Eight 50m sample reaches, two per watershed, were established 30.8 m upstream of hydrology flumes. Three transects w ere established perpendicular to the thalweg within each reach at 15, 30, and 45m to serve as in-stream data collection points for physical measurements including channel cross-sections, canopy cover, and percent cover of in-stream habitat. A survey of habitat unit and channel characteristics was conducted longitudinally within established macroinverteb rate sample reaches once before harvest (December 2001) and once after (October 2004). A 50 m fiberglass tape was placed in the thalweg of the stream along which boundaries between habitat unit types (riffle, run, glide, pool, backwater pool step, and undercut bank) were determined and physical characteristics recorded. A backwater pool was defined as being slower and deeper than a glide but lacking characteristics of a pool, such as scouring, deposition, and presence of a deep section followed by a shallow tail downstreeam (i.e. measurable residual pool depth). For each unit type, le ngth, wetted width, and maximum water depth were recorded. For steps and pools, a step height and residual pool depth were taken. The length and diameter of channel obstructions (e.g., wood, roots) were recorded when the object was primarily responsible for pool formation. The number of functional (e.g., ability to change stream morphology) and nonfunctional wood pieces greater than 10 cm in diameter was recorded, and texture of the streambed (e.g., sand, silty-sand) was visually assessed. Habitat data were converted into percent cover, to define m ajor habitat types to be sampled for macroinvertebrates. Canopy photos were taken at each transect once before and once after harvest with a digital camera fitted with a 180 hemispherical fisheye lens to calculate % canopy cover.

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63 Physical measurements Water temperature was measured from October 2001 through February 2007 with an Onset HOBO temperatu re logger (Pocasset, MA), programmed to record temperature at 15 minute interv als. Stream flow, water chem istry, and meteorological measurements were collected by other investigators and technicians as part of the D ry Creek Study, and these data were available for use in this study. Stream stage and discharge were recorded every 15 minutes by Isco Model 4320 Bubbler Flow Meters at six sites: one in the stream at the ou tlet of watersheds A, B, C, D, and one in the upstream portion of watersheds B and C (Sum mer, 2003). Monthly in-situ measurements for dissolved oxygen, specific conductance, temper ature, pH, and turbidity were made at the downstream portion of each reach with porta ble m eters. Grab samples of water were also taken and analyzed for inorganic ni trogen, inorganic phosphorus, and ammonium (Jones et al., 2003). Energy sources Sixteen leaf litter tr ap s (surface area 0.26 m2 each) were positioned within the riparian area: streambank (6), 10 m from the st ream (6), and 20 m from the stream (4). Following harvest, leaf litter traps 20 m fr om the stream were beyond the SMZ, while the 10 m samples were within but near the edge of the SMZ. Leaf litter was collected monthly and dried at 60C for 48 hours a nd sorted into pine, hardwood, small woody debris, and mast. A subsample of leaf litter from riparian zone samples was used for nutrient analysis. Three samples were comb ined from each reach on a quarterly basis (May, September, December, and February) and ground to a fine powder. A 3-5 mg subsample was then analyzed for C:N ratios using a Carlo-Erba CNS analyzer.

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64 Within each stream reach, ten randomly se lected location s were sampled monthly following harvest for periphyton, benthic orga nic matter (BOM), and macrophytes from 2003-2007. At each sampling point, a 0.25 m2 sampling quadrat was randomly tossed onto the streambed. Periphyton and BOM samp les were collected by inserting petri dishes (17.34 cm2) into the streambed (Tett et al., 1978). Chlorophyll a was analyzed spectrophotometrically (Sartory and Grobbek aar, 1984) to estimate periphyton biomass. The contents of addistional petri dishes were dried at 60C for at least 48 hours, weighed, burned at 550C for five hours, and reweighed for as h-free dry weight determination after cooling. Macrophytes were sampled by removing all vegetation above the sediment surface that existed within a 0.25 m2 quadrat. These were then ri nsed and dried at 60C. BOM was square root transformed, and chlo rophyll a was log-transformed prior to statistical analysis. Macroinvertebrates Benthic macroinvertebrates were collected within established sample reaches with a 500-m-mesh D-frame net (0.3 m wide) using a multi-habitat sampling procedure (Barbour et al., 1999) during December and Fe bruary from 2001 to 2007. Within each reach, 20 sampling sweeps (~3.1 m2) were made through all ha bitat types including sand, woody debris, fine roots, and leaf packs. Samp les were placed in 1 L bottles, preserved in 95 % Ethanol and returned to the lab for pr ocessing. Macrophytes were included after 2003 because they became a significant habitat type in the treatment watersheds. All samples were processed by washing organic de bris (leaves and woody debris) with water onto a 500-m-mesh sieve. Larval Chironomid ae were subsampled (randomly selected 100 individuals) and mounted in CMC moun ting media for both voucher specimens and identification to genus. Macroi nvertebrates were enumerated and identified to genus or

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65 species using local and regional keys (Pes cador et al., 1995; Ep ler, 1995;1996; Merritt and Cummins, 1996; Pescador et al., 2000; Gelhaus, 2002; Richardson, 2003). Biological Traits Fourteen biological traits were select ed to characterize body morphology (size, body shape, body arm oring, respiration), life hist ory (voltinism, resistance to desiccation, eggs cemented to substrate, and development and hatch times), mobility (occurrence in drift), and ecology (rheophily, behavior, feeding preference s, microhabitat preference) (Table 3-1) to delineate responses to change s in disturbance regime (Poff et al., 2006). Some desired traits were omitted due to the lack of available information (e.g., fecundity), particularly for chironomid genera. The fourteen biological traits were divided into 49 modalities ranging from two to seven levels per trait. Trait information was collected from literature (Viera et al., 2006), as well as through communication with taxonomic experts in the United States. Traits were coded and analyzed as in Chapter 2. Data Analysis Energy sources Changes in leaf fall C:N ratios, perip hyton, and BOM with tim e and treatment were analyzed with repeated measures ANOVA (SAS Institute, 2002). Seasonal impacts of harvest on periphyton biomass were a ssessed by grouping time periods into by wet or dry seasons. The wet season was defined as May September, while the dry season was October April. Multiple regressions were utilized to relate changes in BOM and chlorophyll a in relation to environmental variables for each treatment. To reduce impacts of multicollinearity on the regressi on model, Pearsons correlations were calculated for each pair of environmental va riable, and values greater than 0.6 were removed. This resulted in pH and orthophosphate being removed from the dataset.

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66 Environmental variables Environmental variables were analyzed over tim e with repeated measures ANOVA (SAS Institute, 2002). Since macroinvert ebrate samples were taken during the winter/spring period, only environmental data from this period were analyzed. When differences were significant, post-hoc anal ysis was conducted usi ng Tukeys test and Bonferroni corrections. Additi onally, environmental stability was assessed by calculating Bray-Curtis distances (Bray and Curtis, 1957) between adjacent years. These measure dissimilarity with values ranging from 0 to 1. Zero denotes identical samples; thus, higher values denote lower stability and unity implies complete turnover. Macroinvertebrates The Florida Stream Condition Index (SC I) com bines metrics that respond to changes in human induced disturbance to yiel d a score reflecting wa ter quality (Florida Depatment of Environmetal Protection, 2004). Higher values indicate better water quality. SCI values were analyzed by time a nd treatment effects using repeated measures ANOVA (SAS Institute, 2002). Stability of invertebrate communities Compositional stability of invertebrate communities was examined for streams between pairs of success ive years (e.g., 1 vs 2, 2 vs 3, etc.). Stability was measured by calculating Bray-Curtis distances between ad jacent years based on abundance data and biological traits. ANOVA then was used to examine between year differences in compositional and biological trait stability scores for the streams. Ordination: species co mposition and traits Nonmetric multidimensional scaling (NMDS; Kruskal, 1964) was used to explore temporal patterns in species composition and biological traits as in Chapter 2. Since the

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67 experiment was designed as a paired waters hed study (A paired with B and C with D), ordinations were performed on the pairs se parately. For comparing treatments, preharvest samples were grouped together and co mpared with post-harvest reference and treatment reaches. Ordinations were pe rformed on species a bundances and abundance weighted biological tr aits individually. A multi-response permutation procedure (MRPP; McCune and Grace, 20 02) was used to test for significant differences in taxonomic composition and biological trait structure over time at each stream. Indicator species analys is (IndVal; Dufrene and Legendre 1997) was used to identify signifi cant indicator species discriminating among the time periods for the species composition and biological trait da ta. All ordinations, MRPP, and indicator species analyses were performed in PC-Ord ver. 5 (McCune and Mefford, 1999). Results Energy Source Benthic algal biomass estimated from ch lorophyll a differed significantly between trea tments (F2, 2834 = 102.4, P < 0.001) and seasons (F1,2834 = 40.8, P < 0.001) was twice as high in the selective harves t treatment as in the reference and intact treatments during the dry season (0.04 vs. 0.08 mg/m2). In the wet season, ch lorophyll a was 50% greater in the selective treatment compared to re ference and intact treatments (Fig. 3-2). Chlorophyll a was best predicted by phosphorous in the reference streams, conductivity in the thinned SMZs, and was not predicted by any variable in the intact SMZ streams. (Table 3-2). BOM differed significantly between treatments (F1, 1992 = 66.5, P < 0.001), increasing along a gradient fr om selective (12.5 0.5 g/m2) to intact (17.4 0.7 g/m2) to

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68 reference (22.8 0.6 g/m2) treatments. Significant re gressions were found for all treatments, but were explained by different predictors. BOM was best predicted by conductivity, oxygen, and turbidity in reference streams, by flow and ammonia in thinned SMZs, and by flow and turbidity in intact SMZs (Table 3-2). C:N ratios in leaf fall were generally high, ranging from 40 to 70. Values were similar in the reference streams between pr e and post harvest samples, but decreased significantly after harvest in the intact (F1, 36 = 12.8, P < 0.01) and thinned (F1, 36 = 4.2, P < 0.05) SMZs (Fig. 3-3). Environmental Variables Ammonia (F2,82 = 31.8, P < 0.001), total nitrogen (F2,82 = 55.8, P < 0.001), and total phosphorous (F2,82 = 3.2, P < 0.05) varied significantly with harvest, but not over time. Ammonia peaked three years following ha rvest, with levels 9 times higher than the reference streams in the intact SMZ treatme nt and 6 times higher in the thinned SMZ treatment (Fig. 3-4). Total nitrogen also peaked in the third year following harvest, with values increasing by twenty percent in th e harvested watersheds. Total phosphorous peaked in the third year in the harvested wa tersheds, but was always lower than in the reference watersheds (Table 3-3). Dissolved oxygen levels increased over time (F4,82 = 13.9, P < 0.001) and ranged from values of 5 9 mg/L, but were not affected by harvest. Temperature changed significantly over time (F4,82 = 11.2, P < 0.001), ranging from 13-18 C. Although changes relative to harvest were not significant, winter temperatures were 1-2 C higher in treatment streams following harvest. Flow increased over the course of the study (F4,82 = 5.7, P < 0.001) as precipitation increased, more so in harveste d watersheds than reference watersheds (F2,82

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69 = 15.5, P < 0.001) after harvest. Flow ranged from 0.5 to 3.5 L/s in reference streams but reached levels of 7.5 and 10 L/s in intact SMZ and thinned SMZ treatments, respectively. Turbidity varied significantly over the course of the study (F4,82 = 2.6, P < 0.05), but did not have any discernible tem poral pattern. However, values increased significantly following harvest (F2,82 = 22.1, P < 0.001), doubling in intact SMZs and tripling in thinned SMZs compared with the reference in th e first year following harvest (Table 3-3). Macroinvertebrates SCI values became more positive over time and with more extensive harvest, indicating b etter water quality. These increases were most notable in selective harvest, followed by intact SMZs and reference sites (Fig. 3-5). Stability Taxonomic stability increased significan tly over tim e in all treatments (F5,88 = 6.7, P < 0.001) as Bray-Curtis values decreased (Fi g. 3-6). Trends in tr ait stability did not change significantly with site or treatment over the course of the study. However, higher Bray-Curtis values in the inta ct SMZ indicate higher spec ies turnover (Fig. 3-7). Taxonomic composition Watersheds A (Reference) and B (Harvested). NMDS ordination (stress = 11.8, P = 0.001) explained 89 % of the variance in the dataset, with 38 %, 11 %, and 40 % explained by Axes 1, 2, and 3 respectively. Ov er all, the ordination indicated a distinct separation of community composition based on harvest levels (Fig. 3-8) and was supported by significant differe nces between reference and harvest samples (MRPP, A = 0.3, P< 0.001). However, post-harvest samples from thinned and intact SMZs were not different. Axis 1 was primarily represented by total nitrogen (r = 0.8), ammonia (r = 0.5), conductivity (r = 0.8), pH (r = 0.5) flow (r = 0.6), and turbidity (r = 0.8). The genera

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70 Alotanypus (r = .6), Nippotipula (r = 0.5), Crangonyx (r = -0.8), Habrophlebiodes (r = 0.6), Helichus (r = 0.6), Stenelmis (r = 0.7), and Sphaerium (r = 0.6) were most strongly correlated with Axis 1. Axis 2 was most related to dissolved oxygen (r = 0.5), Nanocladius (r = 0.6), Parametriocnemus (r = 0.6), Bezzia (r = 0.6), and Erioptera (r = 0.5). Axis 3 was correlated with dissolved oxyge n (r = 0.6), flow (r = 0.5), leaf fall (r = 0.5), Cryptochironomous (r = 0.7), Polypedilum (r = 0.5), Conchepelopia (r = 0.6), Alluaudomyia (r = 0.6), Simulium (r = 0.6), Sphaerium (r = 0.8), and Tanytarsus (r = 0.7). For watersheds A and B, drought impacts se parated along axis 3 of the NMDS, with positive values leading to a recovery from disturbance. Harvest effects separated along Axis 1, with positive values indicating the harvest induced disturbance. Only one chironomid species, Parachaetocladius was a significant species for pre-harvest sam ples. By contrast, seven spec ies were significant indicators for reference streams after harvest. These were primarily predators or those consuming organic matter and included Alotanypus, Caecidiota Corethrella Crangonyx Ptilostomis, Sciomyzidae and Stenochironomus Thirteen species were indicators for the thinned SMZ treatment. They occupied a range of trophic habits and included Ablabesmyia Calopteryx Cheumatopsyche, Cryptochironomous, Habrophlebiodes, Hemerodromia Orthocladius Paralauterborniella Peltodytes, Sphaerium Stenelmis Tanytarsus and Theinemaniella Indicator species reflective of the intact SMZ treatment were primarily predators and shredders including, Anisocentropus, Procladius, and Hexatoma (Table 3-4). Watersheds C (Harvested) and D (Reference). NMDS ordination (stress = 12.9, P = 0.001) explained 88 % of variance in the dataset, with 39 %, 31 % and 18 % explained by Axes 1, 2, and 3, respectively. Ov erall, the ordination indicated separation

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71 of the invertebrate communities by harvest regime (Fig. 3-9) and was supported by significant differences between reference and harvest sites, but not between thinned and intacts SMZs. Axis 1 was primarily represented by ammonia (r = 0.5), total phosphorous (r = .5), dissolved oxygen (r = 0.6), flow (r = 0.7), and leaf fall (r = -0.4). Polypedilum (r = 0.5), Tanytarsus (r = 0.5), Tribelos (r = 0.8), Simulium (r = 0.5), Habrophlebiodes (r = 0.6), and Diplectrona (r = 0.5) were most strongly corr elated with Axis 1. Axis 2 was most related to ammonia (r = -0.5), total n itrogen (r = .5), and tu rbidity (r = -0.6). Nippotipula (r = 0.6), Pseudolimnophila (r = 0.7), Bezzia (r = 0.8), Chrysops (r = 0.6), Stenelmis (r = 0.6), and Helichus (r = 0.7) were most strongly related to Axis 2. Axis 3 was most related to to tal nitrogen (r = 0.6). Stempellinella (r = -0.6), Tanytarsus (r = 0.6), Corynoneura (r = -0.6), Thienemaniella (r = -0.7), Stenelmiss (r = 0.6), and Helichus (r = 0.7) were most strongly related to Axis 3. For watersheds C and D, Axis 1 of the NMDS appears related to both disturbances, with drought samples having lower values than reference, which had lower valu es than harvest samples. Significant indicator taxa for the pre-ha rves t samples were primarily predators and collector-gathers, including Parachaetocladius, Hexatoma, and Leptophlebia Eighteen taxa were significant indicators for the reference streams after the harvest occurred, primarily consisting of predators a nd shredders. Four taxa were indicators for the thinned SMZ treatment. All were prim arily scrapers and collector gatherers and included Decapoda (Cambaridae), Brillia Elimia and Paracladopelma The indicator taxa reflective of the intact SMZ treatment were predators, scrapers, filterers, gatherers, and shredders, including, Cryptochironomous, Polypedilum Stenochironomous Tanytarsus Tribelos, Molanna, Triaenodes Laevapex and Hexagenia (Table 3-5).

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72 Biological traits Watersheds A (Reference) and B (Harvested). NMDS ordination (stress = 14.3, P = 0.001) explained 91.1% of the variance in the dataset, with 66 % and 25 % explained by Axis 1 and 2 respectively. Overall, the or dination indicated sepa ration of comm unity composition with harvest regime (Fig.3-10) and was supported by significant differences between reference and harvest sites, but not between thinned and intact harvest treatments (MRPP, A = 0.2, P< 0.01). Axis 1 was primarily represented by ammonia (r = -0.4), total nitrogen (r = -0.5), dissolved oxygen (r = -0.6 ), and flow (r = -0.4). Traits positively associated with Axis 1 included bu rrowers (h2, r = 0.7) and collector-gatherers (tr1, r = 0.8), with sclerotized bodies (ar2, 0.7) and slow-hatch ing eggs (ht2, r = 0.8), that are abundant in drift (df3, r = 0.6) and live in gravel (mh3, r = -0.7) and woody debris (mh6, r = 0.7). Those negatively associated w ith Axis 1 included medium-sized (s2, r = 0.7) sprawlers (h4, r = -0.6), filte rers (tr2, r = -0.7), and herb ivores (tr3, r = -0.6), with less than one generation per year (v1, r = 0.6) and fast-hatching (h t1, r = -0.7) cemented eggs (ec1, r = -0.6) living in sand (mh1, r = -0.7) or rocks (mh2, r = -0.7). Axis 2 was most related to total nitrogen (r = -0.4) and turbidity (-0.5). Traits positively associated with Axis 2 included small (s 1, r = 0.7), soft-bodied (ar 1, r = 0.7) individuals with cutaneous respiration (rs1, r = 0.7), and rapid development rates (ds1, r = 0.7). Those negatively associated with axis 2 included la rge (s3, r = -0.6) shredders (tr4, r = -0.6) with tracheal gills (rs2, r = -0.8), slow development (ds2, r = -0.6) less than one generation per year (v1, r = -0.6), an d cemented eggs (ec1, r = 0.6). Traits indicative of pre-harvest samples included sclerotized (ar2) collectorgatherers (tr1) and swimm ers (h3) common in drift (df3), with long hatching (ht2) and development (ds2) times. Those indicative of the reference streams in the post-harvest

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73 period included bluff (sh2), soft-bodied (ar1 ) predators (tr5) with short development times (ds1) living in plant matter (mh4). Species in the thinned SMZ treatment were medium-sized (s2) sprawlers (h4), living in sand (mh1) and gravel (mh3) substrate. Species in the intact SMZ treatment included fi lterers (tr2) with semi-voltine life cycles (v1) that are rare in drif t (df1) (Table 3-6). Watersheds C (Harvested) and D (Reference). NMDS ordination (stress = 11.1, P = 0.001) explained 95.1% of variance in the dataset, with 81 % and 15 % explained by Axes 1 and 2, respectively. Overall, ordination did not indicate separation of comm unity composition by harvest (Fig.3-11) although MRPP did indicate signifi cant differences between reference and harvest samples. Axis 1 did not strongly relate to any environmental variables. Shredders (tr4, r = 0.7) and swimmers (h3, r = 0.7) with tracheal gills (rs2, r = 0.8), cemented eggs (ec1, r = 0.8), long development (ds2, r = 0.8) and hatch times (ht2, r = 0.8) in fast turbulent water (r4, r = 0.7) with streamlined (sh1, r = 0.8), sclerotized (ar2, r = 0.9) bodies univoltine life cycles (v2, r = 0.5), living in detritus (mh5, r = 0.7) were positively related to Axis 1. Collector-gatherers (tr1, r = -0.6) and sprawlers (h4, r = -0.6) with cutaneous resp iration (rs1, r = -0.9) bluff bodies (sh2, r = 0.8) multivoltine life cycles (v3, r = -0.6), short development (ds1, r = -0.9) and hatch times (ht1, r = -0.9), abundant in drift (df3, r = -0.7), small (s1, r = -0.7), soft-bodies (ar1, r = -0.8) were negatively related to Axis 1. Axis 2 did not relate to any environmental variable. Large-bodied (s3, r = 0.8) individuals were positivel y related to axis 2. Small bodied (s1, r = -0.7), burrowers (h2, r = -0.7) not common in drift (d f1, r = -0.8) were negatively associated with axis 2.

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74 Traits indicative of pre-harvest sample s included individuals with m id-length hatching (ht2) and development times (ds2), semivoltinism (v2), sclerotized bodies (ar2), swimmers (h3) and shredders (t r4), residing in silt substrate (mh7). Species in reference streams during the post-harvest period included predators (tr5) respir ing via spiracles or plastrons living in detritus (mh5). Species in the thinned SMZ treatment included herbivores (tr3) preferring sandy substrate (mh1). Species in the intact SMZ treatment included individuals without cemented eggs living in woody debris (Table 3-7). Discussion The need for properly managed watersheds has becom e clear as estuaries and deltas become inundated with sediment, nutrien ts, and chemical pollutants (Justic et al., 1993; Long et al., 1994). Proper management of small streams will contribute significantly to reductions in the downstream tr ansport of these materials since headwater streams account for ~ 80 % of all stream mile s (Gomi et al., 2002). Historically, logging has been the most prominent land use in h eadwater streams, highlighting the importance of protecting these systems during this practi ce. In this study, the impacts of logging in Georgias coastal plain had small, but si gnificant impacts on aquatic communities and their food sources. Although strong bottom-up eff ects occurred in the disturbed streams; in general best management practices eff ectively protected the streams during clearcut harvest. Energy Sources Terrestrially derived organic matter is the prim ary resource in many headwater streams (e.g., Vannote et al., 1980). In the sout heastern U.S., this food base is available throughout the year due to the long grow ing season and may be less limiting in undisturbed streams than in temperate zones (Roberts, 2002). In this study, leaf fall

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75 quantity and quality was altered by harvest as well as natural disturbances. A severe drought prior to the study led to a sharp decline in riparian le af fall in all streams, likely due to physiological responses of vegetati on to changes in precipitation regimes. Following harvest, a decline in leaf fall oc curred in the harves ted watersheds, while reference sites continued to accumulate litt er. Thus, the decrease in habitat and food availability was accentuated in response to both the pulse and press disturbances. Additionally, lower C:N ratios in rapidly grow ing herbaceous litter in the thinned SMZs may have given invertebrates access to higher quality food. The decrease in leaf fall was directly related to less storage of BOM in harvested watersheds. As expected, a decrease in canopy in the logged sites decreased organic m atter inputs and availability, and increased algal and macrophyt e biomass. Studies have found logged sites to have significantly lower leaf biomass than reference streams when no buffer strip was established (Golladay et al ., 1989; Stout et al., 1993). However, this study shows a clear loss in orga nic matter storage even with the retention of a protected buffer zone. Although leaf fall from riparian vegetation is closely related to BOM, the contributing area may depend on watershed characteristics. Lateral inputs into the stream (Fisher and Likens, 1973) emphasize the impor tance of maintaining a wide buffer zone. Additionally, leaves are carried into the stream with surface runoff. Thus, the extent of the buffer zone may influence organic matter, altering food and habitat availability for aquatic organisms. Although less BOM storage is linked to changes in canopy cover, factors affecting decom position rates may play a role in BOM loss. In many streams microorganisms and invertebrates are primar ily responsible for decomposition (Petersen

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76 et al., 1989), but this proce ss is additionally linked to ab iotic conditions. Less BOM was stored in the sediment with increases in flow, ammonia, conductivity, and dissolved oxygen. However, these changes were related to factors unique to harvest treatments. In reference streams, a negative relationsh ips with BOM and conductivity, dissolved oxygen, and turbidity suggest an interaction between abiotic a nd biotic factors affecting loss. As dissolved oxygen levels increase d, higher decomposition rates may have been responsible for decreases in BOM. This was likely related to an increase in microbial biofilm and invertebrate abundance and dive rsity typically found at higher dissolved oxygen levels (Allan, 1995). D ecreases in conductivity were linked to flushing of the streams as flow was restored following the drought. Additionally, drying of the streambed releases SO4 2as reduced sulfur is oxidize d, leading to an increase in conductivity (Bayley et al., 1986; Devito, 1999). This increase reduces the solubility of carbon, thus decreasing decomposition rates (Cla rk et al., 1005) and potentially reducing invertebrate abundance. In the harvested watersheds, the stro ng negative relationshi p found between BOM and flow, suggests the loss of BOM is c ontrolled prim arily by physical factors. Movement of organic matter and sediment occurs during most storm events in sandybottomed, coastal plain streams and is more pronounced in the clearcut streams due to increased runoff and peak flow (Golladay et al., 1987). Ultimately, this leads to trapping of litter in discrete, spatially variable habitats such as debris dams (Palmer et al., 1996). Although flow was an important predictor of BOM storage, ammonia and turbidity also played a role. In the streams with an in tact SMZ, BOM increased as the water became more turbid. Reaches draining the intact SMZ retained silt from upstream sections,

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77 leading to habitat smothering, clogging biofilm and gills of macroinvertebrates (Allan, 1995). In the thinned SMZ, stored BOM decr eased with increasing levels of ammonia, reflecting the contribution of b acteria to leaf litter decomposition. Thus, discrete changes in the physical structure of th e stream due to harvest potentially limit ecosystem function and food resources. Although forested headwater streams obtain most of their energy from allochthonous sources, periphyt on is expected to become the dominant food and habitat source as canopy cover is eliminated. In our study, streams with intact buffer zones did not differ from reference streams, however, streams in thinned reaches had periphyton biomass nearly double that of reference str eams. Murphy et al.(1986) reported that clearcut streams averaged 130% greater peri phyton biomass than buffered and old growth streams. Additionally, Brosofske et al.(1997) show ed that logging practices that affect the width of riparian reserves al ong streams also alter the amount of light reaching the stream surface. However, other factors may interact w ith photosynthetically active radiation to determ ine standing stock of periphyton. In a study examining the impacts of selective harvest in Canada, periphyton biomass in creased both as light levels and water temperature increased and buffer width na rrowed (Kiffney et al.2003). Additionally, foodweb structure (Wootton and Power, 1993; Hillet al., 1995) and nutrients (Hillebrand, 2002) can also be important in controlling al gal accrual. In the reference streams, chlorophyll a increased with in creasing total phosphorous. In general, small headwater streams are nutrient limited (phosphorous a nd nitrogen) (Elwood et al., 1981) and thus periphyton responds rapidly to any increase in the water column. Additionally, Hart and

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78 Robinson (1990) found strong bot tom-up effect of phosphorous addition in streams linking increased scraper abundance with hi gher periphyton biomass, emphasizing the importance of nutrients in changing community structure. However, none of the measured variables had a strong relationship with periphyton in th e harvested streams, indicating increases in light may be the primary factor contributing to periphyton biomass in harvested streams. Although few variables explained changes in periphyton due to harvest, discharge levels in these stream s were linked to the the type of primary production established in these streams. Low flow in low-gradient compared to montane streams may allow for growth of macrophytes as well as macroa lga. Colonization by the macrophyte, Ludwigia repens in the harvested streams increased attach ment surfaces available for algal cells. Kedzierski and Smock (2001) found an increase in the macrophyte Sparganium and the algal species Chara in response to logging in coastal plain streams in Virginia, which they linked to increased macroinvertebrate a bundance and biomass. They found that this macrophyte served as an ideal attachment site for filterers (e.g., Simulidae and Rheotanytarsus), thus increasing microhabitat dive rsity in logged reaches. Long-term availability of periphyton and macrophytes may influence invertebrate community structure years after logging, since overstor y canopy cover will take years to decades to limit light penetration (Fuchs et al., 2003). Environmental Variables Water temperature frequently increases in logg ed areas and has complex effects on life cycles of stream bi ota (Hogg andWilliams, 1996). For example, it influences the rate at which eggs develop and juvenile fi sh and invertebrates grow, which, in turn, determines voltinism, rates of growth, and productivity (Allan, 1995; O'Hop et al., 1984;

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79 Wallace and Gurtz 1986). Both winter and summ er temperatures were 1-2 C higher in treatment than reference streams following harv est, indicating long-term effects on biota. While temperatures peaked at 18 C duri ng winter sampling periods, temperatures exceeding 26C were common in the treatment wa tersheds in the late summer, potentially excluding cool-water adapted invertebrates a nd fish. However, this did not result in lower dissolved oxygen concentrations in the treatment watersheds, in part due to the increased growth of macrophytes present th roughout the water column. Additionally, since a 1-2C is the predicted increase in temperature resulting from climate change (Kundzewicz et al., 2007), the longterm effects of this temperature change may be useful for predicting changes in temp erature on aquatic biota. Buffer zones along streams are expected to retain nutrients (Polyakov et al., 2005), allowing them to be taken up by vegeta tion and assimilated in to the terrestrial ecosystem. However, ammonia levels tripled or quadrupled following harvest, increasing from 10-15 g/L to 30-50 g/L. The U.S. EPA standard for ammonia is 27 g/L (USEPA, 1999), the threshold fo r potential toxicity for aqua tic biota. Surprisingly, concentrations were higher in the intact SMZ than in the thinned SMZ. In the intact SMZ, runoff may still reach the streams, but is more likely retained with fine particles and organic matter, contributing to bacterial produc tion. Additionally, retention of silt in these streams likely reduced benthic oxygen, leading to more ammonia. Ammonia adsorbs to silt-clay fractions in stre ams (Silva and Williams, 2001) and may increase retention in these reaches. Additionally, a prescribed burn in the watersheds may have also contributed ammonia to the streams (Knoepp and Swank 1993). However, in the thinned

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80 SMZs there appeared to be a balance between substrate flushing a nd inputs from runoff so that benthic silt levels were reduced. Macroinvertebrates Both taxonomic and trait composition are expe cted to change in respons e to large scale disturbances. The taxonomic similarity within streams increased over time regardless of treatment. This was linked to recovery of the invertebrate community following a long term drought (Griswold et al., 2008). Biological traits were stable over the course of the study; however, there were trends related to harvest. Statzner et al.(2004) also found that traits were relatively stable ove r large temporal and spatial scales in Europe. This stability may be linke d to the finite number of traits that are available within a region based on climat e and geologic features. However, strong changes in environmental conditions are likely to alter stability of trait composition. Winter flow values continued to escalate in the harvested watersheds over the final two years, nearly doubling the flow rate compared to the reference watersheds. A decrease in trait stability during this period in the treatment watersheds suggests that disturbed sites may be less resistant to change. However, the extension of the study over a longer period would be necessary to determine if this is the case. Harvest led to a shift in dominant species associated with chan ges in the food base and environm ental conditions. The species re sponding to harvest in watersheds B and C were different taxonomically, but shared simila r ecological roles. For example, species responding to harvest consumed benthic peri phyton or organic matter present within the water column. In watershed B this included sphaeriid clams, elmid beetles, and mayflies, while in watershed C blackflies ( Simulium ), Tanytarsus midges, and mayflies ( Habrophlebiodes ) increased in abundance. This shif t to from detritus to algae and fine

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81 matter is common in streams impacted by fo rest activities (e.g., Noel et al., 1986). Differences in species composition between the harvested watersheds are likely linked to habitat stability and flow regime. The greatest structural and functional changes occurred in the thinned SMZs, resulting in the lowest B OM and canopy cove r, and the highest periphyton biomass. Species in the thinned SMZs preferred to live in sand and were larger than in the other stream reaches. This preference for sand reflec ts the regular scouring and lack of organic matter in the thinned treatments. Additio nally, larger body sizes and abundance of herbivores are likely related to greater availa bility of periphyton in these treatments. Most studies link herbivore abundance to increased periphyton biomass as a result of logging (Gurtz and Wallace 1984). The intact SMZ was dominated by filterers (e.g., Simulium ), like ly linked to enhanced transport of organic matter from the clearcut section of this watershed. Blackflies require faster flow and a stable source of attachment, conditions provided by larger substrate particle size and abundant macrophytes present in watershed C. The sphaeriid clams present in watershed B prefer slow flow and burrow in the fine sediment. Fine particulates may enter the stream thr ough bank erosion, or lateral inputs from runoff and resuspension providing additional food (Anderson and Sedell, 1979). Harvested watersheds typically export significantly more particulate organic matter than undisturbed reference watersheds (Webster et al., 1990). Additionally, species living in woody debris were an important component in this treatment. Windthrow resulting from the 2004 hurricanes provided organic matter to this system that may have been flushed out in the thinned treatment.

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82 Invertebrates in the refere nce stream s shared traits indicative of an undisturbed forested headwater coastal plain stream. In general, species were soft-bodied and bluff, indicating lower flow and less scouring. When left undisturbed, streams in this region have riparian zones that limit high peak flows during storm events in these streams. For example, soft-bodied tipulid larvae have limite d ability to resist sc ouring and are easily washed downstream. Thus, species with th is trait are adapted to low-gradient, undisturbed streams. Additionally, species in the reference streams were more likely to prefer living in plant material derived from the riparian zone and thus are closely linked to the riparian zone. Thus, biological tra its were accurate predictors of functional changes occurring in watersheds fo llowing a logging disturbance. The utility of using biologi cal traits and fuzzy coding f or linking trophic habits to disturbance lies in the catholic food pr eferences of many inve rtebrates. Species historically thought to be shredde rs supplement their diet with algae, especially when this food source becomes dominant (Zah et al., 2001 ). This flexibility in food choice may limit the ability of bioassessment protocols to detect disturbance. However, many species rely heavily on a primary food source, and li ttle is known of their reproductive capacity when faced with a less preferred food choi ce. Additionally, traits are stable over interannual periods, allowing for more flex ible sampling protocols (Snook and Milner, 2002). Thus, analysis of trophic habitat, combined with fuzzy coding, which allows species to be assigned to multiple groups, will ultimately enhance the robustness of sampling programs. Anthropogenic disturbance in the face of natural disturbances Water quality indices derived from ec ological and taxonomic information on aquatic invertebrates should be responsive to a gradient of disturbances within and

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83 between streams. For instance, many water quality indices were initially derived to understand downstream effects of points source s such as sewage (Kolkwitz and Marsson, 1909). However, the challenge to create indi ces that respond to nonpoint sources as well as multiple stressors has brought this approach to the extent of its limits. In these indices, lower values reflect poor wa ter quality (e.g., pollution tolera nt organisms), while high values indicate good water quality (e.g., po llution sensitive species). However, the Florida SCI was not responsive to the harvest treatments, suggesting the harvest streams had better water quality than the reference streams two years after the harvest. The SCI was highly responsive to natural disturban ces, and values increased from poor water quality to excellent water quality as streams responded to restoration of flow and precipitation following the 1998-2002 drought.. A strong relationship existed between SCI scores and both flow and dissolved oxygen, the prim ary factors responsible for recovery of invertebrate communities following drought (Chapter 2). Harvest created a diverse range of microhabitats (e.g., light and temperature patche s), likely providing more niches for other species. Additionally, discharge was greater in the selective harvest treatment, which may have buffered these streams from any drying ove r the course of the study. Lastly, as periphyton levels increased in the selective harvest treatm ent, increased Ephemeroptera abundance drove the SCI scores higher since this group tends to be a good indicator of water quality. The SCI has not been able to differen tiate between reference and disturbed stream s in other cases. Vowell (2001) did not find evidence that the SCI was able to discriminate between reference and logged sites in Florida. In a survey of 167 headwater

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84 streams in Oregon, Herlihy et al.(2005) also found that environmental variation was a stronger driver of changes in taxonomic composition than logging history. Further support exists for the short-tem impact of harvest on streams. Kreutzweiser et al.(2005) only found an initial peak in scrapers and filterers immediately following harvest in watersheds with selective ha rvest. They also found that taxonomic structure differed among headwater streams with si milar characteristics within the same basin, providing further support for the use of biological trai ts in bioassessment. Given the predicted increase in natural disturbances, the valu e of these indices becomes questionable for detecting anthropogenic disturba nces. However, they have been used successfully for detecting large disturbances such as urba nization and agricultural practices. Describing and understanding va riability in stream system s is difficult because processes and patterns vary at different spat ial and temporal scales (Wiens et al., 1986; Roth et al., 1996; Allan and Lammert, 1999). Assemblages can vary at small spatial scales, yet appear stable, or at least resilient, at larger scales (Rahel, 1990). This phenomenon has been referred to as the shifting mosaic, steady-stat e model (Clark, 1991; Moloney and Levin, 1996). The study streams were exposed to two press disturbances and at least one pulse disturbance over a de cade. The former included a drought lasting from 1998-2002, logging in 2003, and a hurricane in 2004. The enhanced discharge resulting from the storms did not influence taxonomic composition or trait structure. However, the impacts of harvest and drought, discussed here and in Chapter 2, indicate that natural variab ility needs to be taken into account when attempting to link changes in land use to changes in structural and f unctional aspects of aquatic ecosystems.

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85 Changes in forestry management practic es over the past couple decades have driven the need to understand im pacts of logging along streams on water quality and biodiversity. The assumption cannot be made that simply leaving a few trees along the stream will protect it from land use within the watershed. Thus, more state management programs have incorporated watershed slope into the equation for determining buffer width (e.g., Georgia Forestry Commission, 1999). This study found evidence for longterm impacts of properly managed SMZs on a quatic biodiversity and basal resources. However, these effects were most pronounced in the first year following harvest. Thus, models examining the impacts of SMZ manageme nt must incorporate direct and indirect effects of forestry activities.

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86 Table 3-1. Biological trait definitions and modalities. Trait CodeModality Trait CodeModality Life History Ecology Voltinism v1SemivoltineHabith1Clingers v2Univoltine h2Burrowers v3Multivoltine h3Swimmer Drying Resistance d1Absent h4Sprawler d2Present h5Skater Eggs cemented to substrateec1Yes h6Climber ec2No Trophictr1Gatherer Development Time ds1< 6 weeks tr2Filterer ds2< 1 year tr3Scraper/Herbivore ds3> 1 year tr4Shredder Egg Hatch Time ht1< 1 week tr5Predator ht2< 1 monthRheophilyr1Standing ht3> 1 month r2Slow Mobility r3Fast Laminar Drift df1Rare r4Fast Turbulent df2Common Microhabitatmh1Sand df3Abundant mh2Rock Morphology mh3Gravel Armoring ar1Soft mh4Macrophyte/Algae ar2Sclerotized mh5Detritus ar3Case/Shell mh6Woody debris Maximum Size s1Small (<9mm) mh7Silt s2Medium (9-16mm) s3Large (>16mm) Shape sh1Streamlined sh2Not Streamlined (Bluff, Tubular) Respiration rs1Cutaneous rs2Tracheal Gills rs3Spirales/Plastron

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87 Table 3-2. Results of multiple regressions for chlorophyll a biomass and benthic organic m atter (BOM). Significance of R2 values is given by ( P < 0.05), ** ( P < 0.01), *** ( P < 0.001). Response Variable TreatmentRegression Equation R2ChlaReference streams .02 + 0.005 ( TP ) 0.27*** Intact SMZNSNS Thinned SMZ -0.14 + 0.07 ( SC ) .36* BOMReference streams 2.6 0.47( SC ) 0.24 ( DO ) 0.18(Turbidit y ) 0.67*** Intact SMZ 0.55 0.39( Flow ) + 0.64 ( Turbidit y ) 0.31* Thinned SMZ -0.21 .38 ( Flow ) 0.2 ( A mmonia ) 0.50***

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88 Table 3-3. Average environmental conditions for winter sampling pe riods in referen ce (A,D), thin ned SMZs (B1,C1), and intact SMZs (B2,C2). Data are for pre-harvest (2001-2003) and post-ha rvest (2004-2008). YearFlow (L/s)TSS (g/L) NH4 (g/L) o-phosphate (g/L) NO2/NO3 (g/L) Total Phosphorous (g/L) Total Nitrogen (g/L) pH SC (uS/cm) DO (mg/L) Turbidity (NTU) Temperature ( C) Leaffall (g/m2) A2001-20020.9980.0152.482.731.088.22238.005.5342.284.471.7816.1334.29 2002-20032.5200.0016.281.750.003.69278.284.7330.607.340.1912.1512.29 2003-20041.0410.01711.971.850.0013.26345.875.0335.954.511.1816.0819.26 2004-20051.7590.0032.882.492.344.90233.304.8724.907.621.2312.0021.26 2005-20061.4720.0136.201.780.0016.94343.305.3526.856.871.1013.6330.19 2006-20072.5790.0083.933.010.009.61291.875.1133.688.990.6313.0524.55 D2001-20020.0190.0044.5445.469.4277.00212.467.2384.035.254.0315.6838.25 2002-20032.7350.0040.0027.247.8551.25285.975.8894.857.852.9512.7316.23 2003-20043.0680.0087.6523.744.4151.75237.736.8570.906.824.0315.9022.18 2004-20053.3860.0031.6818.863.0039.00232.056.6174.989.392.9811.7326.06 2005-20065.3610.0166.5912.439.4030.25218.547.1260.938.794.5113.0529.76 2006-20073.9000.0014.8525.692.3827.36203.767.0982.809.882.6112.0525.84 B12001-20021.6510.00312.0902.880366.82011.810621.0906.65061.6505.1203.95016.40038.770 2002-20033.6500.0069.482.24412.5310.5078.194.8596.156.965.6512.4511.18 2003-20044.0500.00419.102.12655.404.83970.006.2489.506.326.5517.107.53 2004-20055.9700.00723.412.41891.942.571165.216.1572.008.655.1814.158.30 2005-20065.4100.00531.801.901041.0030.681256.396.6171.408.064.5514.559.02 2006-200710.3700.00217.882.27346.906.43535.036.2687.958.404.1913.058.75 B22001-20021.9900.00210.782.39835.908.421058.006.5080.804.713.4016.7051.13 2002-20032.6500.0031.892.56824.674.691182.005.1582.657.423.3012.6021.10 2003-20042.9300.00727.801.801161.006.841230.006.1977.006.493.8517.5511.18 2004-20054.4300.00429.652.461480.004.781655.005.9766.758.224.2114.2512.75 2005-20064.1500.00543.361.781523.005.051813.006.4868.407.584.2414.6012.35 2006-20077.4500.00331.272.52656.206.53866.906.2271.358.593.1513.0011.06 C12001-20020.0880.0016.895.611099.0010.111344.007.80101.558.134.1513.7039.97 2002-20033.7300.0010.004.281189.008.521580.005.80106.309.173.1512.3014.15 2003-20045.2800.00513.054.97900.8015.771075.006.7988.707.639.2017.1513.73 2004-200510.1000.00314.704.45816.9010.80969.306.5575.209.215.4412.759.42 2005-20069.9000.00830.554.74998.9016.201290.006.9078.908.198.8314.2515.57 2006-20079.8300.00116.586.20818.207.941004.006.74103.909.833.3012.7511.59 C22001-20021.6300.00314.183.891386.0012.371541.007.4584.906.875.1515.9024.20 2002-20033.2900.00214.942.561541.005.932062.005.9589.958.523.0513.4016.10 2003-20046.1900.00516.924.261204.0013.051413.006.5775.657.227.4017.2510.55 2004-20057.4500.00626.482.821094.0011.351267.006.3268.108.975.9313.1521.17 2005-20066.7600.01348.333.421338.0021.101653.006.7870.907.708.0814.9519.70 2006-20077.6100.00216.752.401277.007.861410.006.4691.508.714.6213.2017.30

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89 Table 3-4. Indicator values for watersheds A an d B based on taxonomic composition. Groups are defined as pre-harvest all sites (1), pos t-harvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4). GroupIndicator Valuep-value Parachaetocladius 137.50.007 Alotanypus 244.30.000 Caecidiota 239.50.012 Corethrella 227.80.040 Crangonyx 238.60.000 Ptilostomis 2 43.70.001 Sciomyzidae 2 44.70.005 Stenochironomus 2 39.80.008 Ablabesmyia 3 44.20.004 Calopteryx 3 36.60.012 Cheumatopsyche 3 26.40.042 Cryptochironomus 3 41.80.008 Habrophlebiodes 3 35.50.020 Hemerodromia 3 250.045 Orthocladius 3 30.30.039 Paralauterborniella 3 42.30.005 Peltodytes 3 300.016 Sphaerium 3 44.80.004 Stenelmis 3 49.60.001 Tanytarsus 3 34.50.025 Thienemaniella 3 30.30.040 Anisocentropus 4 32.40.020 Hexatoma 4 34.20.016 Procladius 4 37.10.019

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90 Table 3-5. Indicator values for watersheds C an d D based on taxonomic composition. Groups are defined as pre-harvest all sites (1), pos t-harvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4). GroupIndicator Valuep-value Parachaetocladius 131.20.023 Hexatoma 131.60.034 Leptophlebia 135.70.019 Corynoneura 234.20.049 Thienemaniella 244.30.003 Nippotipula 2 39.50.002 Pseudolimnophila 2 340.002 Bezzia 2 36.40.001 Alluaudomyia 2 35.40.038 Dixella 2 48.90.001 Psychoda 2 500.001 Sciomyzidae 2 37.50.010 Ophiogomphus 2 54.90.000 Cordulegaster 2 42.60.005 Amphinemura 2 36.70.027 Perlesta 2 42.50.006 Allocapnia 2 380.018 Anisocentropus 2 37.10.028 Helichus 2 41.80.009 Neoporus 2 36.10.035 Microvelia 2 46.70.002 Paracladopelma 3 41.10.004 Brillia 3 34.80.006 Cambaridae3 45.60.001 Elimia 3 38.40.005 Cryptochironomus 4 33.50.022 Polypedilum 4 30.40.039 Stenochironomus 4 42.10.008 Tanytarsus 4 33.60.026 Tribelos 4 36.20.019 Hexagenia 4 34.60.033 Molanna 4 24.20.031 Triaenodes 4 27.60.043 Laevapex 4 39.80.005

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91 Table 3-6. Indicator values for watersheds A and B based on biological traits. Groups are defined as pre-harvest all sites (1), post-h a rvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4). TraitGroupIndicator Valuep-value df3131.30.003 ar2131.90.014 h31380.000 tr1129.90.007 mh2128.50.015 ds2128.30.036 ht2132.10.003 ar1226.60.005 tr5229.40.007 sh2226.20.008 mh4229.70.002 ds12290.004 s2332.10.034 h4328.80.030 mh13300.040 mh3332.20.014 v1436.50.026 df14270.042 tr2433.80.007

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92 Table 3-7. Indicator values for watersheds C and D based on biological traits. Groups are defined as pre-harvest all sites (1), post-h a rvest reference (2), post-harvest thinned SMZ (3), and post-harvest intact SMZs (4). TraitGroupIndicator Valuep-value v2127.10.012 ar2129.90.013 h3 1 32.70.023 tr4 1 33.10.001 mh7 1 30.90.002 ds2 1 30.30.001 ht2 1 29.50.007 h5 2 44.70.003 mh5 2 320.003 rs3 2 33.30.009 tr3 3 29.90.010 mh1 3 28.90.023 mh6 4 30.30.022 ec2 4 26.30.047

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93 Figure 3-1. Topographic map a nd aerial photo of the four study watersheds (A-D).

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94 0 0.02 0.04 0.06 0.08 0.1 0.12 ReferenceThinnedIntactChla (mg/m2) Wet Season Dry Season Figure 3-2. Average chlorophyll a biomass ( SE) during the wet (May-S eptember) and dry season (October-April) from 2004-2008 in refe rence, thinned SMZs, and intact SMZ streams after harvest.

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95 0 10 20 30 40 50 60 70 80Reference Thinned SMZ Intact SMZC:N Ratio Pre-harvest Post-harvest Figure 3-3. C:N ratios of leaf fall from the ripari an zone in reference and harvested watersheds before (2001-2003) and af ter (2004-2007) harvest.

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96 0.00 10.00 20.00 30.00 40.00 50.00 60.002001-20022002-20032003-20042004-20052005-20062006-2007NH4 (ug/L) Reference Thinned Intact SMZ Figure 3-4. Average ammonia (NH4) concentrations (SE) in reference, thinned SMZs, and intact SMZ streams. Harvest treatments were applied prior to the third sampling period.

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97 0 10 20 30 40 50 60 70 80Stream Condition Index (SCI) Reference Thinned SMZ Intact SMZ 2002 2003 2004 2005 2006 2007 Figure 3-5. Stream condition inde x (SCI) scores (SE) for re fere nce, thinned SMZs, and intact SMZ streams. Samples below the red line i ndicate poor water quality, those above the red line, fair water quality, and those a bove the blue line, good water quality.

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98 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 2001-20022002-20032003-20042004-20052005-20062006-2007Bray-Curtis Values Intact SMZ Thinned SMZ Reference Figure 3-6. Taxonomic stability (SE) for refere nce, thinned SMZs, and intact SMZ stream s.

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99 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 2001-20022002-20032003-20042004-20052005-20062006-2007Bray-Curtis Values Intact Thinned SMZ Reference Figure 3-7. Trait stability (SE) for referen ce, thinned SMZs, and intact SMZ stream s.

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100 NH4 TN pH SC DO Turb Flow LF -1.0 -2.0 0.01.0 -1.0 0.0 1.0Axis 1Axis 3 Harv 1 2 3 4 Figure 3-8. NMDS of taxonomic composition in watersheds A and B in pre-harves t (1) and in post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).

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101 NH4 Phosph TN DO Turb Temp Flow LF -2.0 -1.5 -1.00.01.0 -0.5 0.5 1.5Axis 1Axis 2 Harv 1 2 3 4 Figure 3-9. NMDS of taxonomic composition in watersheds C and D in pre-harves t (1) and in post-harvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).

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102 -2 -2.0 024 -1.0 0.0 1.0Axis 1Axis 2 Harv 1 2 3 4 v1 v2 v3 d1 d2 df1 df2 df3 ar1 ar2 ar3 s1 s2 s3 r1 r2 r3 r4 h1 h2 h3 h4 h5 h6 tr1 tr2 tr3 tr4 tr5 sh1 sh2 mh1 mh2 mh3 mh4 mh5 mh6 mh7 rs1 rs2 rs3 es1 es2 ec1 ec2 ds1 ds2 ds3 ht1 ht2 ht3 -0.3 -0.3 -0.10.10.3 -0.1 0.1 0.3Axis 1Axis 2 Harv 1 2 3 4 Tss NH4 TN SC DO Turb Flow LF -2 -2.0 024 -1.0 0.0 1.0Axis 1Axis 2 Harv 1 2 3 4 Figure 3-10. NMDS of biological tr aits in watersheds A and B in pre-harvest (1) and in postharvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).

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103 -3 -2.0 -11 -1.0 0.0 1.0 2.0Axis 1Axis 2 Harv 1 2 3 4. v1 v2 v3 d1 d2 df1 df2 df3 ar1 ar2 ar3 s1 s2 s3 r1 r2 r3 r4 h1 h2 h3 h4 h5 h6 tr1 tr2 tr3 tr4 tr5 sh1 sh2 mh1 mh2 mh3 mh4 mh5 mh6 mh7 rs1 rs2 rs3 es1 es2 ec1 ec2 ds1 ds2 ds3 ht1 ht2 ht3 -0.3 -0.15 -0.10.10.3 -0.05 0.05 0.15Axis 1Axis 2 Harv 1 2 3 4 Figure 3-11. NMDS of biological tr aits in watersheds C and D in pre-harvest (1) and in postharvest reference (2), thinned SMZs (3), and intact SMZ treatments (4).

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104 CHAPTER 4 EFFECTS OF PATCH TYPE, QUALITY, AND SIZE ON MACROINVERTEBRATE COMMUNI TY STRUCTURE Introduction Spatial heterogeneity in landscapes strongl y affects comm unity structure (Bond et. al 2000) and population dynamics (Kar eiva 1990). In the simplest case, increasing either habitat types or patches provides more potential niches, allowing in creased species diversity and abundance. However, certain habitat types may be better suited for a species or group of species, resulting in preferential habitat selections. Physical characteristics, environmental conditions (e.g., oxygen, temperature), food resources and predation risk are important factors determining patch suitability, and spa tial aspects of food webs are key to understanding community structure and dynamics (Holt 1977, 1996). Low gradient, headwater streams in the southeastern coastal plain are typically dominated by sandy substrate, yet they also have patches of leaf packs, woody debris and root m ats. Two important habitat patch types in logged streams are leaf packs and macrophyte beds, both of which vary in quality and quantity over space an d time. Thus, streambed heterogeneity results from seasonal inputs of organic matter and the rearrangement of thes e patches in shifting mosaics (Stout et al., 1985; Hildrew and Giller, 1994; Wallace et al., 1995).Leaf packs can peak in autumn after leaf senescence, while macrophytes peak in the late spring and summer during the growing season. However, both are present at some level throughout the year. Thus, patch size and location will be highly variable and depend on changes in canopy cover and allocthonous leaf input. Coloni zation of streambeds by macrophyt es, coupled with decreased allochthonous input in logged streams, can alter the number of patches available for stream biota. Temporal and spatial changes in stream landscap es lead to changes in size, isolation and structure of habitat patches. Leaf packs and m acrophytes potentially differ in their temporal and

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105 spatial dynamics. Depending on stream bed stability and flashiness of flow, the structure of leaf packs can change greatly with time (Palmer 1996, Velasquez 2003). In logged streams, the rate of leaf pack formation is often slow, resulting in increased patch isolation and fragmentation. Leaf pack formation occurs primarily in autumn as leaves senesce and fall into the stream. They then become smaller and are rearranged within the stream as invertebrates process leaves and increased flow scours the channel bottom. Un like leaf packs, rooted macrophytes are more stable in streams and contribute to a less dyna mic streambed landscape. Thus, macrophytes may support superior competitors, while leaf packs may support more transient, inferior competitors. Differences in patch quality and size drive hab ita t selection by stream invertebrates. Leaf packs vary in suitability as ha bitat and food, with fast decomp osing leaves acting more as a resource, and slow decomposing leaves acting more as habitat (Dangles et al.2001). Essafi (1994) found that invertebrate biomass did not decrease in leaf p acks after leaves lost most of their nutritional value, suggesting that leaf packs act as habitat and potential refugia in addition to being a consumable resource. Leaf packs may also enter the hyporheic zone and provide resources for subsurface biota (Strommer and Smock 1989). Although few invertebrates consume macrophytes, high quality resources fo r invertebrates exist in macrophyte beds, including decaying plants, root exudates, root associated bacteria, epilithic periphyton and detritus (Sagova 2002, Tolonen 2003). Previous studies of static stream landscap es suggest that sm all patches support higher densities than large aggregated patches (P almer 2000, Silver 2000). However, these studies focused primarily on leaf packs and a small gr oup of organisms (chironomids and copepods). Silver et al.(2004b) observed that chironomid density was greater in both fragmented landscapes and less stable habitats.

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106 Given the current state of knowledge of patch dynam ics in streams, the goal of the this study was to understand the role of patch type, size, and quality in structuring invertebrate communities and colonization dynamics. It wa s hypothesized that larger macrophyte patches provide both more cover a nd a greater source of food (e piphyton/biofilm) and increase invertebrate abundance and diversity. Invertebrate abundance and diversity should be lower in large leaf packs because their interior will offer reduced water velocity and oxygen. This was assessed using a combination of field observation s and experimental manipulations of patches. Materials and Methods Field Sampling of Patches Macrophytes and leaf packs were mapped three tim es over a year at 20 m intervals along the length of the study reach (~ 200 m) by establishing transect s perpendicular to flow and determining percent cover of leaf packs and macrophytes. Samples were obtained from randomly selected patches of macrophytes ( Ludwigia repens) and leaf packs four times between September 2005 and June 2006. A net (250 m mesh) was positioned downstream of the patch, and three leaves were taken from each patch a nd placed in individual vi als containing 100 ml of deionized water for chlorophyll a analysis. Three additional l eaves were preserved in phosphobuffered formalin (1%) for bacteria counts. Leaf samples were kept on ice until returning to the lab where they were stored at -20C until analyz ed. The remainder of the patch was collected by removing only its above-sediment portion and allowing it to drift into the ne t. The contents of the net were placed in a ziplock bag, placed on ice, and returned to the laboratory for processing. In the laboratory, patch samples were gently rinsed through nested sieves of 1mm (CPOM) and 0.250 m (FPOM). Macroinvertebr ates were sorted from the samples and preserved in 70% ethanol. Each sample was th en separated into terre strially derived CPOM, FPOM, and macrophytes. Patch size was determin ed by placing each sample in a 500ml glass

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107 cylinder with water to determine the volume of the patch by water displaced. Each portion (CPOM, FPOM, and macrophytes) was then dried at 60C for at least 48 hours and weighed to compare dry weights to volume for a given area. FPOM samples were ashed at 550C for five hours to determine organic content. Since many invertebrates consume bacteria and periphyton, chlorophyll a, ash-free dry weight (AFDW ), and bacteria counts were used as indicators of patch quality. Chlorophyll a and AFDW were analyzed as in Chapter 3. Leaves for chlorophyll and AFDW measurement were vigorously shaken in 50 mL of deionized water for 30s, after which leaves were removed to measure surface area. Water samples were filt ered through 45 m GFF filters, and bacteria on the filters were stained with SYBR Green and counted under an epiflourescent microscope. Leaves were photographed, and Scion Image (Scion Corp., Frederick, MD, U.S.A.) was used to calculate total surface area. Bacteria enumeration followed the protocol outlined in Buesing (2005). A 0.2 m, 25mm aluminum oxide membrane filter (Whatm an Anodisc) was placed on top of a wetted 0.45 m, 25 mm cellulose nitrate filter on a glass filter manifold. Leav es for bacteria counts were thawed and sonicated for one minute at 80 W while on ice. Then, the sample was vortexed, and a 100 l aliquot was removed after 10s. The sample and one ml nanopure water was added to the filter manifold to ensure mixing and a homog eneous slide mount and pressure applied using a vacuum. The Anodisc filter was removed and gently dr ied using a Kimwipe. Filters were placed face-up on a 100ul drop of SYBR Green II fluorescent stain diluted 400 fold (Molecular Probes, Eugene, Oregon, USA) on labelled petri dishes. Filters were stained in the dark for 15 minutes, then dried and placed face-up on a glass slide. A 30-uL drop of antifade mounting solution (50%

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108 glycerol, 0.1% p-phenylenediamine, 50% PBS: 120 mM NaCl, 10 mM NaH2PO4, pH 7.5) was added, and a cover slip was placed on top. Slides we re then counted or stored frozen at -20C for up to six weeks. An Epifluorescence microscope equipped with a high-pressure mercury lamp (HPO 100 W), with a Chroma filter set ( no. 41001; excitation filter 480 nm, beam splitter 505 nm, emission filter 530 nm) was used to count bacteria. Cell numbers were counted from at least 10 fields until a total of 400 bacterial cel ls was reached (Kirchman 1993). Preliminary counts from ~ 25 slides were used to determine a size class distri bution with a calibrated micrometer and placed in the following classes: cocci (< 0.5 m, > 0.5 m diameter), vibrio, filamentous, and rod (< 0.35 m, > 0.35 m). In subsequent slides, at least 15 cells from each size class were measured. Volumes (V) of individual ce lls wer e calculated under the assumption that cells are cylindrical with hemispheric e nds (Fry, 1988), which works for both rods and cocci. The total biovolume (BV) of bacterial cells per g of leaf material was calculated as: lcf fsi iDMAS AVb DM BV )( where bi is the biovolume of an individual bacteria cell, Vs the sample volume, Af the total filtration area, Sf the volume of the subsample passed over the filter, Ac the filtration area, in which bacteria were counted, and DMl the litter dry mass. Bacterial dry mass or carbon was calculated from bacteria BV based on empirically determ ined conversion factors. For pelagic freshwater bacter ia, LofererKrbacher et al.(1998) established the following relationship: bv dmb435 0.86 where dmb is the dry mass and bv the biovolume of a bacteria cell.

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109 Field Experiment The goal of the field experiment was to contro l for leaf species, patch size, and patch age to exam ine initial macroinvertebrate colonization patterns. Leaf packs cons isted of dominant tree species shared among watersheds B and C; Liriodendron tulipifera Quercus nigra and Pinus spp. Leaves were collected in August 2006 prior to abcission and air dried for seven days. Macrophytes were collected from seeps along the st ream, washed thoroughly in distilled water, and examined for invertebrates and biofilm before use. The macrophytes and leaf species were used to create patches of 1, 2, or 4 g. A separa te set of ten macrophyte samples were dried at 60C to determine a wet to dry mass regression and cr eate an equivalent to the leaf packs prior to the beginning of the experiment. The three size classes were crossed with two lev els of stab ility and four species in a randomized block design. Blocks were created in a 10-20 m stretch of stream and replicated three times along at 70 m length of each reach in the intact and thinned SMZ treatements in watersheds B and C. Leaf packs were created by loosely tying leaves toge ther using nylon line. Macrophyte patches were anchored in the sedime nt using mesh produce bags (10 Vexar bags, Avis Bag Co.). Leaf packs and macrophytes were teth ered to pvc pipe driven into the streambed. Stable patches were left undisturbed for 15 days, while unstable patches were disturbed once on day 7 by rinsing the patch through the water column for one minute. Patches were then collected after 7 and 15 days to determine colonization patterns. Velocity, oxygen, and canopy cover were m easured at each patch as potential determ inants of patch quality. Canopy cover was measured by taking four measurements using a densitometer. Velocity was measured using a Marsh McBirney Flowmate 2000 (Frederick,MD). Oxygen samples were taken by firs t removing a 10ml water sample from the patch with a 10 ml

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110 syringe. Then, dissolved oxygen was measured using the micro winkler technique (Peck and Uglow, 1990). Samples were fixed within two h ours and returned to the lab for processing. Leaf packs were rinsed through a 250 m mesh sieve, and inve rtebrates were sorted from the sample and identified. CPOM and FPOM trappe d in the patch were se parated, dried at 60C for 48 hours, and weighed. Additionally, subsamples were taken and ashed at 550C to correct for inorganic accumulation on leaf litter. Data Analysis Field obervations Independent and dependent variables were transformed to meet assumptions of normality and independence. Analysis of covarian ce (ANC OVA) was utilized to determine the relationship between invertebrates and patch type using size as a covariate. Multiple regression was used to relate invertebrate metrics to pa tch size, epiphyton biomass, and bacteria abundance and biomass. Experimental manipulation of patches A three-way ANOVA was utilized to relate changes in macroinvertebrate metrics to initial leaf mass, species, a nd disturbance. Rarefaction wa s used to com pare taxon richness across samples after standardizing for patch size. Linear regression wa s used to relate the expected number of species to the patch size. Multiple regressions were used to examine the influence of canopy cover, dissolved oxygen, trapped FPOM and CPOM, and velocity on macroinvertebrates. Results Field Observations The total biomass of epiphyton (chlorophyll a) was not related to patch type or size. Values were lower during autumn/w inter than in spring/summer (F3,122 = 4.2, P<0.01) (Fig. 4-1).

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111 Differences in total bacterial abundance relate d to patch type were dependent on patch size (F1,115 = 4.6, P<0.05). Overall, abundance increased w ith linearly with patch size, but the slope was greater for leaf packs than macrophytes. Temporally the number of b acteria cells decreased from fall to winter and incr eased from spring to summer (F3,119 = 5.6, P<0.01), but did not depend on patch size (Fig. 4-2). Total bacterial biomass was higher in leaf packs than on macrophytes (F1,118 = 11.8, P<0.001), but was not influenced by patch size. Total biomass per patch changed with date, but was related to the size of the patch (F3,114 = 4.0, P<0.01). In general, biomass increased with patch size, bu t an outlier led to high biomass in a small macrophyte patch. FPOM trapped within patches increased in both patch types from fall to summer (F3,122 = 15.0, P<0.0001). FPOM changed with patc h type, but was dependent on patch size (F1,1118 = 25.8, P<0.0001). FPOM in leaf packs incr eased with patch size, but did not change with patch size of macrophytes. Further, the volume of FPOM trapped in leaf packs was significantly higher than that in macrophytes (29.4 vs. 21.2 cm3). Patch quality parameters were weighted for patch size. Bacterial biom ass/cm3 changed with date (F3,116 = 10.2, P<0.0001), but depended on patch type (F3,116 = 3.7, P<0.02). Biomass was greatest in November for both leaf packs and macrophytes, but was higher in leaf packs (Fig. 4-3). Bacterial abundance/cm3 changed with date (F3,116 = 12.4, P<0.0001), but depended on patch type (F3,116 = 10.0, P<0.0001). Abundance was lowest in April for both patch types (Fig. 4-4). Chla/cm3 changed with date (F3,122 = 4.0, P<0.001) and patch type (F1,122 = 6.4, P<0.02) and was higher for macrophytes on a ll dates except November (Fig. 4-5). Changes in taxon richness with date (F3,118 = 6.0, P<0.01) and patch type (F1,118 = 6.7, P<0.001) were dependent on patch size. Taxon richne ss increased with patch size for leaf packs, but did not have any relationship to patch size for macrophytes. After ad justing taxon richness

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112 based on taxa/cm3, there was a significant e ffect of patch type (F1,116 = 53.8, P<0.001) date (F3,116 = 12.6, P<0.001) and their interaction (F3,116 = 19.2, P<0.001) on taxon richness. Taxon richness was higher in Ludwigia and greatest in the winter samp ling period (Fig. 4-6). Changes in invertebrate abundance with date (F3,116 = 7.1, P<0.001) and patch type (F1,116 = 17.5, P<0.001) were dependent on patch size. There was a positive relationship between patch size and leaf packs, but no relationship between patch size and macrophytes. After adjusting abundance based on individuals/cm3, patch type (F1,116 = 43.8, P<0.001) date (F3,116 = 10.8, P<0.001) and their interaction (F3,116 = 13.3, P<0.001) significantly affected abundance. In general, invertebrates were more abundant in Ludwigia peaking during winter (Fig. 4-7). Changes in the proportion of shredders did not depend on patch size, but were different between patch types (F1,122 = 8.3, P<0.01) and over time (F3,122 = 3.5, P<0.02). Shredders were more common in leaf packs moreso in the winter than in the summer. Differences in filterers with patch type depended on patch size (F1,118 = 12.9, P<0.001). Filterers were positively related to patch size in leaf packs, but did not display any relationship to patch size in macrophytes, and they were more abundant in summer than fall and winter (F3,122 = 5.9, P<0.01) (Fig. 4-8). Predators did not change significantly over time but differences betw een patches depended on patch size (F1,118 = 10.1, P<0.001). Predators increased w ith patch size in leaf packs, but decreased with size in macrophytes. However, predators were more abundant in macrophytes than in leaf packs ( 25 vs. 20 percent of comm unity composition). Collector-gatherers did not change over time, but the effects of patch type differed by patch size (F3,118 = 2.7, P<0.05). They increased with patch size in macrophytes, but de creased with size in l eaf packs. Overall, collector-gatherers comprised a larger proportion in leaf packs than in macrophytes (34 vs 23 percent).

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113 Regressions. Invertebrate abundance had a positive relationship with both bacterial biom ass and FPOM for leaf packs, but was only related to FPOM for macrophytes. Taxon richness was positively related to bacterial biomass and FPOM for leaf packs and FPOM for macrophytes. The proportion of shredders was positiv ely related to patch size and negatively to bacterial abundance for leaf packs and did not relate to any para meter for macrophytes. Scrapers were positively related to patch size, chlor ophyll a and bacterial a bundance for macrophytes. Filterers were positively related to bacterial a bundance, biomass, and FPOM for leaf packs and to FPOM and chlorophyll a for macrophytes. Colle ctor-gatherers were related to chlorophyll a and FPOM for macrophytes (Tables 4-1, 4-2). Field Experiment C:N ratios varied among leaf species with Pinus (40.29) having the highest and Ludwigia (14.7) have the lowest ratio. Quercus and Liriodendron were sim ilar with ratios of 30.5 and 26.6, respectively. Leaf mass decomposition ov er time was dependent on leaf species (F2,273 = 148.4, P<0.001), disturbance (F2,273 = 9.9, P<0.001), and mass (F2,273 = 205.5, P<0.001). Pinus and Liriodendron lost two to three times more mass than Quercus patches (Fig. 4-9). The percent of leaf mass loss increased with time, but did not differ between disturbance treatments. Larger leaf packs lost more mass over time than smaller leaf packs, with 4-gram packs losing five times more than 1-gram packs (Fig. 4-10) However, when corrected for percent loss over time, mass was not significant. On average, leav es lost twenty five percent of their mass, regardless of initial mass. Changes in velocity due to disturbance depended on mass (F4,408 = 5.8, P<0.001) and leaf species (F6,408 = 2.2, P<0.04). Average velocity ranged from 0.04 to 0.06 cm/s. In general velocities were lower in Liriodendron and higher in larger leaf pa cks. CPOM trapped within patches was related to leaf species (F3,372 = 50.8, P <0.001), disturbance (F2,372 = 4.7, P<0.01),

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114 and mass (F2,372 = 5.9, P<0.01). More CPOM was trapped in the 4 g patches than the 1 and 2 g patches (Fig. 4-11). The amount of CPOM tra pped in patches ranged from 0.2 to 1.7 grams. The most CPOM was trapped in Ludwigia and the least in Pinus (Fig. 4-12). Additionally, more CPOM was trapped in patches that were collected after fifteen da ys and were not disturbed (Fig. 4-13). FPOM trapped within patche s was related to leaf species (F3,406 = 40.9, P<0.0001), disturbance (F2,406 = 5.7, P<0.01), and mass (F2,406 = 11.1, P<0.0001). More FPOM was trapped over time and with increasing patch size (Fi g. 4-14).The amount of FPOM ranged from 0.05 to 0.3 g and was greatest in Ludwigia and least in Pinus and Quercus (Fig. 4-15). Oxygen within patches was not different be tween any treatment. Invertebrate abundance changed sign ificantly between leaf species (F3,402 = 5.3, P<0.01) and initial leaf mass (F2,402 = 12.6, P<0.001). Abundance was lowest in Ludwigia with an average of 15 individuals and highest in Pinus and Liriodendron with an average of 30 individuals (Fig. 4-16). Inverteb rate abundance increased with increasing patch size, from 20 to 44 individuals (Fig. 4-17). However, there was no apparent evidence for a relationship between patch size and expected species richness whe sample size was accounted for. Taxon richness changed significantly between leaf species (F3,402 = 6.6, P<0.001) and in itial leaf mass (F2,402 = 19.5, P<0.001). In general, the number of taxa di d not differ greatly, averaging between 3 and 5, with Quercus patches having the least numbe r of taxa (Fig. 4-18). The proportion of predators did not differ betw een treatm ents. The proportion of scrapers was dependent on initial leaf mass (F2,402 = 4.3, P<0.02) and was higher in the 4 g than 1 g patches (Fig. 4-19). The proportion of shredders changed in response to mass (F2,402 = 3.1, P<0.05), leaf type (F3,402 = 3.4, P<0.02), and disturbance (F2,402 = 5.6, P<0.01), however, the effect of leaf type depend ed on disturbance treatment (F6,402 = 2.5, P<0.03). In general,

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115 shredders became more common over time, more so in the undisturbed treatments, while more abundant in the largest patches, they were not abundant overall and only ranged from 0-6 percent of the community (Figs. 4-20,4-21). The proportion of filterers changed in response to mass (F2,402 = 5.9, P < 0.01 and leaf type (F3,402 = 10.4, P<0.0001) and were twice as common in Ludwigia than any other patch type and were more abundant in larger patc hes (Fig. 4-22,4-23). Collector-gatherers were the dominant feeding group in all patches, ranging from 40-60 percent of the community. Collector-gathere rs differed between leaf species (F3,402 = 6.02, P<0.001) and were least abundant in Ludwigia (Fig. 4-24). Regressions Invertebrate abundance was positively relate d to CPOM, velocity, and can opy cover and negatively related to FPOM. Taxon richness ha d a positive relationship with velocity and CPOM. The proportion of scrapers was negativ ely related to increased canopy cover and positively related to velocity. Filterers were positiv ely related to FPOM and oxygen within the patch. Shredders were not predicted by any environmental variable. Collector-gatherers were negatively related to FPOM and positively related to canopy cover (Table 4-3). Discussion Stream invertebrate communities are structur ed b y a mosaic of habitats ranging from macrophytes and substrate diversity to small-s cale changes in flow patterns. Community composition is related to the quantity, quality, and dist ribution of detritus on the streambed in headwater streams (Arsuffi and Suberkropp, 1985; Murphy et al., 1998), and plays a significant role in the distribution, species composition, and total biomass of benthic invertebrates (Hearnden and Pearson, 1991; Reice 1974). Thus, patch size and quality are two key factors affecting colonization patterns of patches. In the current study, invertebrate density and

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116 community structure were determined by complex interactions among patch size, type, quality, and abiotic variables. Patch Complexity Patches with greater structural complexity generally support more species and higher abundances as potential niches increase (Dean and Connell, 1987; Douglas and Lake, 1994; Downes et al., 1998, Downes et al., 2000). In the study stream s, Ludwigia typically fills the entire water column, providing habitat for benthic species, swimmers, and clingers, while leaf packs rest on the surface of the st reambed. Submerged macrophytes increase the physical complexity of aquatic environments, pr oviding habitat for colonisation by invertebrates (Heck and Westone, 1977; Crowder and Cooper, 1982; Gregg and Rose, 1982; Tokeshi and Pinder, 1985; Lodge, 1991; Newman, 1991). A dditionally, macrophyte architecture has a influences food supply through detritus trappi ng (Rooke, 1984) and growth of epiphytic algae (Dudley, 1988), leading in some cases to di stinct invertebrate communities on different macrophytes (Minshall, 1984; Rooke, 1986). As a result, macrophytes in the current study supported higher densities and taxon richness on a per volume basis than did leaf packs. However, in the short-term experimental study, they supported the lowest invertebrate density. Macrophyte leaves are not consumed by invertebrate s, but the epilithon and biofilm matrix is in most cases (Newman, 1991). Additionally, sinc e macrophytes are growin g within the stream, they may exude less nutrients than decomposing allocthonous leaf litter. Thus, macrophytes may need more time than terrestrially derived leav es both to attract invertebrates and be to conditioned with suitable biofilm, as seen in the current study. Structural complexity may also enhance resour ces available within habitat patches (Diehl and Kornijow, 1998). FPOM trapped within patche s provided the basis for higher invertebrate abundance and taxon richness in the observationa l study. Higher am ounts of FPOM provide

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117 more surface area for bacteria and fungi, thus providing more food for invertebrates. Additionally, since FPOM is easily flushed from habitats during stor m events, higher FPOM may indicate greater stability of the patch, providing more reliabl e habitat for invertebrates. Ludwigia patches trapped the most CPOM and FPOM in the short-term experimental study. This ultimately increased diversity of niches av ailable to invertebrates and improved suitability for colonization. Since macrophytes are anchored in sediment, they may act like debris dams, trapping and holding organic matter during storm events. Thus, m acrophytes have the potential to take over some of the func tion of woody debris typically abse nt in logged streams. Although macrophytes became abundant following logging, inputs of pine needles will likely increase over the next decade since the waters hed was planted with a monoculture of pine. As expected, pine patches created the least heterogeneity and trap ped little if any organi c matter. Many timber operations in the southern U.S. utilize pine pl antations, which could have a negative impact on invertebrates by decreasing structural complexity and overall storage of organic matter. Patch Stability In addition to structural complexity, habitat st ability p lays a large role in determining the composition of patch inhabitants. Although the sout hern coastal plain does not typically receive high-energy flows such as those present in snow-m elt, relatively large events may occur during hurricanes and smaller events with storm even ts common during summer. Thus, more stable habitats are likley to be more attractive to invertebrates. Stability provided by Ludwigia enhanced colonization by filtering invertebrate s. Additionally, sandy-bottomed streams in the coastal plain do not provide relatively immobile substrates such as cobble and boulders present in the piedmont. Thus, invertebrates depend on ava ilability of organic subs trate introduced from the riparian zone or growing within the st ream including woody debris, rootwads, macrophytes, and leaf packs. However, leaf packs are ephe meral, rapidly decomposing, and are subject to

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118 being scoured from the streambed during storms. In addition, Ludwigia patches provide multiple food sources for filterers, such as Simuliidae, by allowing them access to the water column and by trapping large amounts of organic matter. Thus, Ludwigia can sustain filterers even at low flows, when only small amounts of FPOM and bact eria are present in the water column. Hydrologic disturbance can create a mosaic of stable and unstable patches within stream s. Olsen et al.(2007) found that invertebra te densities were greate st in stable patches following an experimental simulation of flooding in streams. However, this difference only existed for 14 days following the disturbance. In the current study, a small scale disturbance had little impact on colonization patt erns of invertebrates. The ex pectation was that disturbed samples would be more similar to the sevenday samples than the undisturbed fifteen-day samples. The disturbed samples appeared to rese mble the fifteen-day samples in most cases and were even higher than the undisturbed in some cases. This may be linked to the size of the disturbance and presence of source populations nearby. Coloni zation is a rapid process in streams, and most areas recover in 10-30 days following localized disturbances (Mackay, 1992). Melo and Froelich (2001) found that invertebrates recolonized ove rturned stones within 4 days, and densities became higher than those on control stones within a month. Thus, 7 days between sampling may have been too long to see any differences. Although not significant, total abundance and mass-weighted abundance were hi gher in disturbed than in seven day or undisturbed samples. This may be linked to higher amounts of FPOM trapped in disturbed samples, and an increase in collector-gatherers. Additionally, small scale di sturbances that leave biofilm intact are less likely to have long la sting impacts on habitat occupancy (Miyake, 2003). Patch Quality The quality of leaves as food affects the perform ance (i.e. gr owth rates and densities) of benthic macroinvertebrates (Cummins and Klug, 1979; Sweeney and Vannote, 1986) and is

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119 determined by the leaf composition and attached biofilms (Lock et al., 1984; Hax and Golladay, 1993), which consist of autotrophic and heterotr ophic components. In this study, patch quality based on biofilm composition was in fluenced by temporal changes in environmental parameters. Bacterial biomass was highest in autumn, while chlorophyll a was highest in spring. This reflects changes in canopy cover typical in head water streams since light is a primary factor limiting primary production (Hill and Knight, 1988; Hepinstall and Fuller, 1994; Hill et al., 1995) and consequently influences the develo pment and biomass of biofilms (Ledger and Hildrew, 1998). Higher bacterial biomass is likel y linked to the greater surface area provided by decaying organic matter derived from the riparian zone, as well as decaying algae and macrophytes present in the spring and summer samp les. Additionally, higher bacterial biomass in autumn may fuel algal growth in spring. Severa l studies have indicated the existence of a link between algae and bacteria (Rounick and Wi nterbourn, 1983; Hepinstall and Fuller, 1994; Ledger and Hildrew, 1998) whereby bacteria benefit from algal exudates for an energy source, or as a substratum for colonisation (Rier and Stevenson, 2002). Historically the primary energy source in headw ater streams was thought to be terrestrially-dervived leaf litter a nd the bacteria and fungi associ ated with it (e.g., Vannote et al., 1980). However, more current research found suffic ient algal growth even in streams with high canopy cover (Mayer and Likens, 1987). Though epiphyton is typically associated with macrophytes, the present study found similar ch lorophyll a for leaf packs and macrophytes, except during periods of maximum irradiance (e .g., spring). Thus, both habitats have the potential to support diverse macroinvertebrate communities. However, bacterial biomass was higher on leaf packs, suggesting these are a high er quality food source. This was not supported

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120 by the data since abundance and taxon richness of invertebrates were higher in macrophyte patches. In the observational study, filterers were be st p redicted by chlorophyll a in macrophytes and bacteria in leaf packs. This supports recent findings that many invertebrates exhibit plasticity when selecting resources (Friberg a nd Jacobsen, 1994). In addition to organic matter sloughing from epiphyton, the struct ure provided by algae will aid in development of a biofilm matrix. Additionally, filterers were positively related to dissolved oxygen within the patch, which was higher in macrophytes since they ex tend into the water co lumn and release oxygen during photosynthesis. Switching feed ing behavior has also been observed in shredders, mixing algal and detritus based carbon sour ces (Friberg and Jacobsen, 1994). Patch quality is also linked to refractory com pounds in leaves that may alter biofilm structure, decomposition rates, and nutrient availability for colonizing species (Ostrofsky, 1993, 1997). This may be especially true for shredding invertebrates that depend on biofilm as well as leaf properties (e.g., Lignin conten t). Habitat selection by shredde rs was apparent in the shortterm experiment in relation to leaf palatabilit y. After seven days, shredders were more common in Pinus and Liriodendron than in the less palatable Quercus and Ludwigia However, shredders became similar among all treatments after fifteen days and were similar between macrophytes and leaf packs in the observational study. This in dicates that although shre dders initially select more suitable habitat, accumulation of organic matter in other patches creates adequate habitat for this group. Bastian (2007) f ound that shredders were distributed across a broad range of leaf species in a stream, with no leaf species being preferentially colonized by shredders. However, most studies find that shredder species exhibit clear leaf preferences (Anderson and Sedell, 1979; Mackay and Kalff, 1973; Nolen and Pearson, 1993), and selectively feed on food resources of

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121 different palatability or quality (Arsuffi a nd Suberkropp, 1985, Campbell and Fuchshuber, 1995). Although shredders are implicated in breakdown of organic matter in streams, they usually colonize leaf packs later than other feeding groups Shredders usually select leaves at advanced stages of conditioning (Arsuffi and Suberkr opp 1984, 1985; Mackay and Kalff, 1973, Petersen and Cummins, 1974) due to increased microbial biomass and fungal de gradative enzymes and, thus, increased leaf palatabi lity (Suberkropp, 1998). Thus, Quercus leaves may not be colonized as fast due to their refractory properties, but st ill may provide more than adequate habitat. In addition, a case-making caddisfly, Anisocentropus, was commonly found in cases made from Quercus This is likely due to its resistance to br eakdown, to provide long term protection. Patch Size Increased patch size potentially creates more niches, providing a diversity of resources and refugia from predators. Although the amount of mass lost from patches increased with patch size, breakdown rates were similar when compari ng initial masses. Contrary to my hypothesis, this indicates that conditions inside larger leaf packs do not necessarily become less suitable for decomposition and provide equal opportunity for biofilm formation. In the observational study, bacterial biomass increased with patch size for Ludwigia but not for leaf packs. However, invertebrates did not respond positivel y to this increased re source base and niche availability. In the observational study, the expected species richness was not re lated to patch size. This suggests a lack of differences in resources with larg er patches. Patch size was a determinant of feeding guild st ructure. Scrapers did not select habitat based on leaf type and were m ost abundant in larg er patches. Most scra pers are classified as clingers and thus need habitat that will support their mass and provide a substantial food. Larger patches should support more mass and protect th is group from moderate flow events. In addition, many grazing invertebrates quickly deplete their resour ces (McAuliffe, 1984), thus

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122 emphasizing the need for great surface areas to support a significant community. In the observational study, scrapers increased with patc h size, bacterial abundan ce, and chlorophyll a, but only in Ludwigi a. Higher bacterial abundance may provide additional resources for scrapers, since many invertebrates have flexible feeding ha bits. However, in the observational study, there was no link between patch size and sc raper abundance in leaf packs. Many of the larger leaf patches in the observational study were multi-ti ered, and much of the surface area was not exposed to light, thus lim iting primary productivity. In the observational study, multiple conf ounding factors lim ited interpretation of relationships between patch size and invertebrate communities. Leaf packs were diverse, multi species assemblages in varying stages of decompos ition. To control for this, the field experiment used freshly abcissed leaves and only created single species patches. Liriodendron and Pinus patches decomposed more rapidly than Quercus Liriodendron leaves are soft and pliable with lower C:N ratios than Quercus. However, pine needles ha d much higher C:N ratios, but provided a larger exposed surface area for bact eria colonization. Nitrogen content, C:N ratio, total phenolics, percentage lignin and lignin:N ra tio explain much of the variability in leaf processing rates (Taylor, Parkins on and Parsons, 1989; Ostrofsky, 1997). Patch occupancy may be related to interactio ns between biotic a nd abiotic factors. Collecto r gatherers are bottom-feeders in streams and tend to consume any type of small organic particle. They are also the most abundant group in sandy-bottomed streams (Smock et. al, 1985). However, this group was more abundant in leaf packs than in macrophytes, increasing with patch size in macrophytes, but decreasing in leaf p acks. An opposite relationship was found for predatory invertebrates, sugges ting predation on this group. This is supported by the higher abundance of predators in macrophytes even thou gh trapped organic matter was similar between

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123 the patch types for the observational study. Although streams are thought to be primarily structured by abiotic factors, biotic factors are likely to influence community structure effectively at smaller scales (e.g., Peckarsky, 1983). The proportion of shredders was negatively relate d to bacterial abundan ce for leaf packs. This potentially suggests that com petitive interactions may exist between these groups, since both consume leaf organic carbon. This may ex plain the lack of a relationship between shredders and bacteria in macrophytes. Inte ractions between shredders, organic matter decomposition and microbes (bacteria and fungi) are complex. For example, fungi and bacteria convert a portion of detrital organic matter into microbial bi omass, transforming the detrital substrate into a more nutritious food source fo r detritus feeders (Barlocher and Kendrick, 1975; Suberkropp, 1992). At the same time, shredder fr agmentation of the detrital matrix promotes microbial activity, increasing av ailable detrital surface for colo nisation (Hargrave, 1970; Howe and Suberkropp, 1994) and spreading microfungal spores (Rossi, 1985). The results of this study s upport the expected response of invertebrates to changes in habitat type and quality as l ogging reduces leaf packs and in creases primary productivity. Typically, headwater stream s would lose shredders and gain more scrapers. However, in warm temperate coastal plain systems, collector gath erers may be the dominant consumer of organic matter. This may explain the decrease in collec tor-gatherers with the subsequent increase in scrapers. In addition, scrapers were negatively related to canopy cover, while collector-gatherers were positively related. This indi cates that collectors may be the more natural feeding group in occuring in undisturbed, sandy-botto med streams. Since much of the substrate is highly mobile, scouring of leaf packs may act as the initial d ecomposition mechanism, creating smaller particles available for collectors, work usually done by shredders.

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124 Table 4-1. Multiple regressions for leaf packs averaged over all time periods for the observational study. Dependent VariableParameterEstimate SEt P Size0.280.230.050.96 Chlorophyll a-17.750.4-0.350.72 Bacteria Abundance0.080.140.570.57 Bacteria Biomass0.330.13.2 0.003 FPOM0.380.132.9 0.005 Size0.130.140.90.37 Chlorophyll a-26.830.4-0.880.38 Bacteria Abundance0.050.080.560.58 Bacteria Biomass0.120.061.90.06 FPOM0.170.082.2 0.03 Size0.860.352.5 0.02 Chlorophyll a-134.676.2-1.770.08 Bacteria Abundance-0.520.21-2.51 0.01 Bacteria Biomass-0.130.16-0.80.13 FPOM-0.170.2-0.870.39 Size-0.290.27-1.10.28 Chlorophyll a72.258.81.230.22 Bacteria Abundance0.380.162.3 0.02 Bacteria Biomass0.240.122 0.04 FPOM0.460.153 0.005 Invertebrate Abundance (F4,59=15.0, P < 0.0001, R2 = 0.58) Taxon Richness (F4,59=7.7, P < 0.0001, R2 = 0.42) Shredders (F4,59=2.0, P = 0.08, R2 = 0.16) Filterers (F4,59=8.9, P < 0.0001, R2 = 0.45)

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125 Table 4-2. Multiple regressions for Ludwigia av eraged over all time peri ods for the observational study. Dependent VariableParameter Estimate SEt P Size 0.150.170.90.37 Chlorophyll a 20.613.91.60.12 Bacteria Abundance0.120.150.170.44 Bacteria Biomass-0.040.13-0.280.78 FPOM 0.280.12.8 0.007 Size 0.110.081.50.14 Chlorophyll a 9.75.81.70.1 Bacteria Abundance-0.020.07-0.280.78 Bacteria Biomass-0.040.06-0.670.51 FPOM 0.080.041.90.06 Size 0.620.252.5 0.01 Chlorophyll a -42.719.3-2.2 0.03 Bacteria Abundance-0.560.22-2.5 0.01 Bacteria Biomass0.080.20.390.7 FPOM -0.210.15-1.40.16 Size -0.110.21-0.520.61 Chlorophyll a 31.916.61.90.06 Bacteria Abundance0.350.191.80.07 Bacteria Biomass-0.170.17-0.990.33 FPOM 0.290.122.3 0.02 Size 0.250.211.220.23 Chlorophyll a -4615.9-2.9 0.005 Bacteria Abundance-0.290.18-1.570.11 Bacteria Biomass0.250.161.550.13 FPOM -0.290.12-2.4 0.02 Filterers (F4,63=2.9, P = 0.02, R2 = 0.20) Collector-gatherers (F4,63=4.5, P = 0.002, R2 = 0.28) Invertebrate Abundance (F4,61=3.5, P = 0.008, R2 = 0.24) Taxon Richness (F4,63=2.7, P = 0.03, R2 = 0.19) Scrapers (F4,63=2.6, P = 0.04, R2 = 0.20)

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126 Table 4-3. Multiple regressions for the field expe rim ent averaged over all treatments for each invertebrate metric. Dependent VariableParameterEstimate SEt P CPOM0.450.153.6 0.0004 FPOM-0.990.5-2 0.04 Velocity5.91.523.9 0.0001 Canopy Cover0.670.116.1 <0.0001 Oxygen-0.520.35-1.50.14 CPOM0.480.192.5 0.01 FPOM-0.280.63-0.450.65 Velocity8.61.924.45 <0.0001 Canopy Cover0.120.140.840.4 Oxygen-0.070.44-0.150.88 CPOM-0.030.24-0.140.89 FPOM0.290.780.370.71 Velocity5.022.412.08 0.04 Canopy Cover-0.870.17-5.05 <0.0001 Oxygen-0.250.55-0.450.65 CPOM0.320.191.650.1 FPOM2.220.623.57 0.0004 Velocity-0.391.91-0.210.84 Canopy Cover-0.090.14-0.680.5 Oxygen10.432.3 0.02 CPOM0.010.10.120.9 FPOM-1.180.33-3.58 0.0004 Velocity-0.551.02-0.550.59 Canopy Cover0.460.076.3 <0.0001 Oxygen-0.260.23-1.120.26 Filterers (F5,255=6.9, P < 0.0001, R2 = 0.12) Collector-gatherers (F5,255=11.0, P < 0.0001, R2 = 0.18) Invertebrate Abundance (F5,255=15.0, P < 0.001, R2 = 0.23) Taxon Richness (F5,255=6.2, P < 0.0001, R2 = 0.11) Scrapers (F5,255=6.1, P < 0.0001, R2 = 0.11)

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127 0 0.002 0.004 0.006 0.008 0.01 0.012 November 2005January 2006April 2006June 2006Chla (mg) Leaf Packs Ludwigia Figure 4-1. Total biomass of chlorophyll a (m g) ( SE) in each patch type.

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128 0 10 20 30 40 50 60 70 80 November 2005January 2006April 2006June 2006Total Bacteria Cells (1 X 106) Leaf Packs Ludwigia Figure 4-2. Total number of bacterial cells (1 X 106) ( SE) in each patch type.

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129 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 November 2005January 2006April 2006June 2006Bacterial Biomass (pg C/cm3) Leaf Packs Ludwigia Figure 4-3. Bacterial biomass (pg C/cm3) ( SE) in each patch type.

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130 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 November 2005January 2006April 2006June 2006Number Bacterial Cells/cm3 (1 X 106) Leaf Packs Ludwigia Figure 4-4. Number of bacte rial cells per cm3 (1 X 106) ( SE) in each patch type.

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131 0 0.00005 0.0001 0.00015 0.0002 0.00025 0.0003 0.00035 0.0004 November 2005 January 2006April 2006June 2006Chl a (mg/cm3) Leaf Packs Ludwigia Figure 4-5. Chlorophyll a biomass (mg/cm3) ( SE) in each patch type.

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132 0 0.5 1 1.5 2 2.5 3 3.5 4 November 2005January 2006April 2006June 2006Taxon Richness/cm3 Leaf Packs Ludwigia Figure 4-6. Volume-weighted taxon richness (Taxa/cm3) ( SE) in each patch type.

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133 0 2 4 6 8 10 12 14 November 2005January 2006April 2006June 2006Invertebrate Density (Individuals/cm3) Leaf Packs Ludwigia Figure 4-7. Volume weighted inve rtebrate density (Individuals/cm3) ( SE) in each patch type.

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134 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 November 2005January 2006April 2006June 2006Proportion Filterers Leaf Packs Ludwigia Figure 4-8. Proportion of filtering invert eb rates ( SE) in each patch type.

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135 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45Pinus Liriodendron QuercusProportion Leaf Mass Loss Day 7 Day 15 Disturbed Day 15 Undisturbed Figure 4-9. Proportion of leaf mass decomposed ( SE) in relation to patch type and disturbance.

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136 0 0.2 0.4 0.6 0.8 1 1.2124MassMass Lost (g) Figure 4-10. Amount of leaf mass decomposed (g ) ( SE) in relation to initial patch mass.

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137 0 0.2 0.4 0.6 0.8 1 1.2124MassCPOM in patches (g) Figure 4-11. CPOM trapped in patches ( SE) in relation to patch size.

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138 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8PinusLiriodendronLudwigiaQuercusCPOM in patches (g) Figure 4-12. Average amount of co arse particulate organic m atter (g) ( SE) trapped in each patch type.

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139 0 0.2 0.4 0.6 0.8 1 1.2Day 7 Day 15 DisturbedDay 15 UndisturbedCPOM in patches (g) Figure 4-13. Average amount of co arse particulate organic m atter (g) ( SE) trapped in patches by disturbance type.

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140 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2Day 7 Day 15 DisturbedDay 15 UndisturbedFPOM in patch (g) Figure 4-14. Average amount of fine particulate or ganic m atter (g) ( SE) trapped in each patch based on disturbance.

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141 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35PinusLiriodendronLudwigiaQuercusFPOM in patch (g) Figure 4-15. Average amount of fine particulate or ganic m atter (g) ( SE) trapped in each patch type.

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142 0 5 10 15 20 25 30 35 40 45PinusLiriodendronLudwigiaQuercusInvertebrate Abundance Figure 4-16. Average number of invertebrate in dividuals ( SE) in each patch type.

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143 0 5 10 15 20 25 30 35 40 45124MassInvertebrate Abundance Figure 4-17. Average number of invertebrate in dividuals ( SE) in each patch bas ed on initial patch mass.

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144 0 1 2 3 4 5 6124MassTaxon Richness Figure 4-18. Average number of taxa ( SE) in each patch in relation to initial pa tch mass.

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145 0 0.05 0.1 0.15 0.2 0.25 0.3124MassProportion Scrapers Figure 4-19. Proportion of scra pers ( SE) in each patch based on initial patch m ass.

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146 0 0.005 0.01 0.015 0.02 0.025 0.03124MassProportion Shredders Figure 4-20. Proportion of shredders ( SE) in each patch based on initial patch m ass.

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147 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07PinusLiriodendronLudwigiaQuercusProportion Shredders Day 7 Day 15 Disturbed Day 15 Undisturbed Figure 4-21. Proportion of shredders ( SE) in each patch based on patch type and disturbance.

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148 0 0.02 0.04 0.06 0.08 0.1 0.12124MassProportion Filterers Figue 4-22. Proportion of filterers ( SE) in each patch bas ed on initial patch mass.

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149 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18PinusLiriodendronLudwigiaQuercusProportion Filterers Figure 4-23. Proportion of filterers ( SE) in each patch type.

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150 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7PinusLiriodendronLudwigiaQuercusMassProportion Collector-Gatherers Figure 4-24. Proportion of collector-gat herers ( SE) in each patch typ e.

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151 CHAPTER 5 HABITAT SELECTION IN FRAGMENTED LANDSCAPES: COMPARING GENERALISTS TO SPECIALISTS Introduction Dispersal of individuals rela tive to patch variability has im portant implications for ecological processes, including population disp ersal and redistribution, local population and metapopulation dynamics, and intensity of species interactions (Hanks i, 1998; Gilliam and Fraser 2001). Habitat patch arrangement, amount and perimeter:area ra tio (e.g., edge) strongly influence both community structure and interpatch dispersal both in terrestrial and aquatic systems (Wiens, 1997; Pither and Taylor, 1998; Hanski, 1999; McIntyre and Wiens, 1999; Jonsen and Taylor, 2000; Palmer, 2000). The impor tance of patches, and especially isolation between patches, depends on dispersal ability of focal organism(s) (Kareiva andWennergren, 1995). Since invertebrates respond to patches at a sm aller scale than other groups, they are an ideal m odel group for testing hypotheses related to habitat fragmentati on (Bowne and Bowers, 2004). For instance, insects residing in patchy hab itats display higher dens ity when resources are dispersed among many small patches as opposed to large, aggregated patches (Hanski, 1994; Remer, 1998; Roitberg, 1997; Heard, 1998; Silver, 2004a). In this way, habitat connectivity increases with increased habitat fragme ntation (Tischendorf and Fahrig, 2000). Both natural and anthropogenic forces leadi ng to habitat loss and fragm entation have been considered in debates over the relative import ance of habitat amount versus arrangement in determining community response to habitat frag mentation (Sih, 2000). Flather (2002) argued that habitat amount is a more plausible explanation for population size, but arrangement becomes important when total habitat cover declines to ~ 30-50 %, emphasizing the need to study processes over a range of total cover. Additionally, patches may be highly dynamic, changing in

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152 shape and size over time (Pickett and Thomps on, 1978) in response to disturbance and succession. Movement is a primary factor determini ng the effect of spatial heterogeneity on ecological processes (Diffendorfer et al., 2000). Movem ent and dispersal provide escape from competitors, predators and parasites. Risks associ ated with dispersal include increased mortality due to predation and an inability to find suitable sites (Bilton et al., 2001). Interactions between dispersal and landscape structure determine the ab ility of an organism to move through the landscape (Merriam, 1984). Thus, the colonizat ion rate of new patches by individuals is influenced by emigration rate, mean dispersal distance relative to patch distance, mortality incurred during dispersal, and mean number of po tential dispersers (Johnst, 2002). The idea that animal movement and dispersal occur as a result of behavioral choices made in response to environmental heterogeneity across spatial and temporal scales emphasizes the importance of linking behavioral and landscape ecology (Lima and Zollner, 1996). Studies of movement across heterogenous lands capes are necessary to determ ine impacts of habitat loss for management and conservation (O lden et al., 2004). Movement patterns in the landscape are central to connect ivity, patch and boundary dynamics, spread of disturbances, source-sink and metapopulation dynamics (Ims, 1995) Dispersal is cons idered active when attributed to behavioral decisions and passive wh en due to displacement. Biased flow in streams emphasizes the importance of both passive and ac tive dispersal. Movement of an individual through a heterogeneous landscape is influenced by a number of abiotic (flow, temperature, light levels) and biotic cues (food, predation risk). Movement between patches also depends on the proportion of different habitat type s, as well as spatial configur ation of the landscape (Moilanen and Hanski, 1998). Connectivity within a landsc ape depends on the spatial configuration of

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153 patches and movement patterns of the organism. Thus, connec tivity based on movement links behavior and landscape structure (Goodwin and Fahrig, 2002). Movement of invertebrates in streams is in fluenced by available ha bitat amount and type (e.g., Palm er, 2000). In many cases, leaf packs and macrophytes share similar macroinvertebrates, including Ephemeroptera, Chironomidae, Trichoptera, and Simuliidae (Velasquez, 2003), making them useful for studying movement across different patch types. However, they differ in the composition of other invertebrate fauna, sugge sting that these patch types are somewhat unique. Interpatch movement and ability to find patches of suitable quality are key factors influencing species persistence. The ability of dispersing invertebrates to find and settle in patches may be influenced by patch quality (Palmer, 1996) and physical arrangement of patches on the stream bed (Silver, 2000). The goal of this study was to de termine implications of changing habitat availability and type on invertebrate movement, focusing specifically on how patch type and amount affect habitat selection. I hypothesized that reduction of available patc hes and increased isolation will negatively affect the ability of ha bitat specialists to locate patches. Additionally habitat specialists should be more efficient at finding th e next patch and will follow a relatively straight path to it, while habitat generalis ts will choose a random, tortuous path. Materials and Methods Study Organisms The habitat specialist, A nisocentropus pyraloides (Trichoptera: Calamoceratidae) is a slow-moving detritivore that inhabits small st reams flowing through deciduous forest throughout the eastern U.S. (Wiggins, 1996). Larvae constr uct notched, oblong cases made of two leaves sealed together with silk. A dditionally, its diet consists prim arily of organic matter and thus depends on leaf packs for food and its case. This species is semivoltine and emerges in the spring

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154 (Wiggins, 1996). Although dorso-ventrally flat tened, the case likely creates drag while the organism is crawling over the streambed. The habitat generalist used in experim ents was the snail, Elimia sp.(Gastropoda: Pleuroceridae), which commonly o ccurs in all landscape units in cluding macrophytes, leaf packs, and the sandy matrix (persona l observation, Chapter 4). This genus occurs throughout the southern U.S. and is abundant in the study streams, with dens ities as high as 25 individuals/m2. Elimia produces more than one generation per year and is parthenogenic, wh ich contributes to its abundance in the streams (Viera et al., 2006). Elimia is conical, limiting its drag as it moves across the streambed. Behavioral Observations The effects of habitat type and amount on m ovement were examined using short-term behavioral exeriments within the stream. During the experiment, conditions were consistent with average conditions thoughout the stream. Over the seven day pe riod, average water temperature was 18.5 C, velocity was 0.13 cm/s, and canopy cover was 79 %. Leaf packs ( Liriodendron tulipifera ) and macrophytes (Ludwigia repens ) were collected as described in Chapter 4. Habitat mosaics were created in a 5 m2 section of the channel in watershed C by adding leaf packs:macrophytes at 1:0, 1:1, or 0:1 ratios, with total percent cover of 10, 30 and 50 percent of the entire landscape (Fig. 1). Macrophytes and leaf packs were arranged randomly since effects of patch configuration were not being addressed. Each leaf pack or macrophyte patch had a surface area of 16 cm2. The sediment in the selected r each was raked to a depth of 0.75 m to remove organic matter and invertebrates, then was smoothed to create a landscape completely dominated by sand. A 3 X 3 grid composed of co lored nylon was attached to pvc pipes at the perimeter of the landscape and was placed 15 cm above the water as a reference point for

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155 movement distances. A drift net was placed at the end of the landscape to trap emigrating individuals. Experimental organisms were collected from the stream each morning from the streambed and naturally occuring leaf packs. Individuals were placed in separate flow-through trays and allowed to acclimate to the stream reach for at least an hour. A video camera was set up on a tripod to record movement of individuals. During each trial, individuals were placed at the center of the landscape, facing downstream. Behavior was recorded for 30 minutes, with the observer leaving the reach while trials were occu ring. After 30 minutes, th e length and width of each individual was measured, removed from the landscape, and released downstream. On average, Anisocentropus individuals were 4.2 cm long ( 0.2 SE) and 2 cm wide ( 0.1 SE), while Elimia individuals were 4.3 cm long ( 0.1 SE) a nd 1.7 cm wide ( 0.1 SE). No individual was used more than once, and trials were repe ated for at least four individuals (more for Elimia due to availability). After each trial, the streambed was gently scoured to remove any traces of the individual path. Trials were run between 7 AM and 4 PM daily for a period of seven days beginning 7 March, 2007. The grid was left in place each night, and pvc pipes were inserted into the streambed as placeholders for the tripod. Videos were digitized and manually analyzed on a com puter screen with coordinates (x,y) recorded every 10 s to determine movement parameters. For each path, total path length, correlations between turning angles, mean cosine of turning angle, mean path length, and net squared displacement were calculated to assess distance covered (Turchin et al.1991). The above parameters were used for correlated ra ndom walk models, which are useful for making inter-specific comparisons (Kareiva and Shigesad a 1983; Cain 1985; Crist et al.1992). Each path

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156 was compared to the correlated random wa lk model of Nams and Bourgeois (2004) by calculating Rdiff: k n n n n diffRE RER k R1 2 2 2)( )( 1 where E(R2 n) is the expected net squared displa cement (Kareiva and Shigesada 1983), n is the number of moves, and R2 n is the mean net squared displacement. Positive values of Rdiff indicate that the path is l onger than predicted by correlated random walk models and negative values indicate shorter paths. An individuals overall rate of movement across a landscape is contingent upon its tendency to move (or rem ain sedentary), moveme nt velocity, and path tortuosity (Russell et al.2003). Tortuosity of movement was assessed by calculating the fractal dimension (D) of each movement path, whereby estimates near 1 indica te highly linear movement and near 2 suggest approximate Brownian (plane-filling) moveme nt (Hastings and Sugihara 1993). Fractal dimensions were estimated with Fractal 4.0 software (http://www.nsac.ns.ca/envsci/staff/vnams/Fractal.htm). The fractal mean method was used, which is based on the traditional dividers method (Mandelbrot 1967, Sugihara and May 1990), but corrects for estimation errors created when th e last divider step does not fall exactly on the end of the path (Nams and Bourgeois 2004). Frac tal dimensions were estimated based on the entire recorded movement path of each individual. Paths of four moves or less were not used in the analyses because estimates of their fracta l dimension sometimes fell below the theoretical limit of 1. To test whether the above movement be haviors differed am o ng habitats, ANOVA was used after normalizing the data. Where signif icant effects were observed, differences among

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157 treatmentfactor combinations were tested us ing post hoc Tukeys honest significant difference (HSD) tests ( = 0.05). Colonization Habitat selection based on patch amount a nd type was exam ined in a short term colonization study. Microlandscapes were created along an ~75 m stretch of stream, separated by at least 3 m. Landscapes were the same as those used in the short-term behavioral experiment, but were half the size (45.7 cm W X 50.8 cm L), and were replicated three times in a randomized block using each replicate as a bloc k. Prior to creation of the landscape, the streambed was raked to 0.5 m to remove any apparent organic matter or habitat and allowed to settle for four hours. Drift nets were placed at the end of the landscape to trap emigrating invertebrates. Macrophyte and l eaf patches were anchored to th e sediment in the appropriate configuration (Fig. 1). Invertebrates for the experiment were collect ed f rom the streambed and, leaf packs and lengths of individuals were meas ured. Due to low abundance of Anisocentropus, only one individual was used for each rep licate, however, six individuals of Elimia were used. The shell or case of the individual was bl otted dry and marked with a dr op of paint and the number of landscape (from 1 to 27). Individu als were released at the center of the landscape after the paint dried (~ 5 minutes). After 24 hours, all patche s were collected and placed in individually labelled bags. Velocity was measured at the upstream and downstream end of the landscape with a Flomate 2000 (Marsh McBirney). In addition, drift nets were collected and any marked individuals in the matrix (sa nd) were collected. A surber sa mple was also taken from the landscape to determine recolonizat ion by other inve rtebrates.

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158 Results Movement Anisocentropus Mean step length did not diffe r for any of the m icrolandscapes, averaging 0.7 cm ( 0.3 SE) per step. Deviation from the correlated ra ndom walk between the leaf species depended on amount of patch cover (F4,37 = 3.1, P = 0.03) (Fig. 2). Paths became more random (closer to the CRW) with increased cover for single species landscapes, but were shorter than a CRW for mixed landscapes. The probability of turning in the same direction differed by leaf type, but depended on total amount of cover (F4,37 = 4.6, P = 0.004). This parameter increased with increasing cover in Ludwigia dominated landscapes, but decreased in mixed landscapes (Fig. 3). Correlation between adjacent angles differed by leaf type, but depended on total amount of cover (F4,37 = 2.6, P = 0.04). In general, correlations betw een angles were negative, but became more negative with increasing cover in mixed landscape s (Fig. 4). Net square d displacement differed by leaf type, but depended on total amount of cover (F4,37 = 4.5, P = 0.004). Displacement increased with increasing cover in Liriodendron dominated landscapes, but decreased in mixed landscapes (Fig. 5). Mean D did not differ between leaf species or percent of habitat cover, averaging 1.15 ( 0.02 SE). Elimia Changes in mean step length for leaf species depended on percent c over in the landscape (F4,39 = 3.7, P = 0.01). Step length incr eased with increasing cover in Liriodendron landscapes from 0.1 cm to 0.7 cm per step. It was higher in Ludwigia landscapes with 30 % cover, increasing from 0.5 to 0.8 cm (Fig. 6). Deviati on from CRW differed between leaf types (F2,38 = 4.4, P = 0.02) and total amount of cover (F2,38 = 4.8, P = 0.01). In general, paths were greater than expected by CRW at 20 % cove r, with the lowest values in Liriodendron (Fig. 7). The

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159 mean cosine differed between the percent cove r treatments, but depended on leaf type (F4,39 = 3.4, P = 0.01). Probability of turning in the same direction did not differ between treatments and ranged from 0.25 to 0.45. Correlation between adjacen t angles did not differ between treatments, and ranged between 0.5 and -0.5. Net squared di splacement did not differ between any of the landscapes and ranged from 50 to 780 cm. Mean D did not differ between leaf species or percent of habitat cover and averaged 1.03 ( 0.004 SE). Colonization Neither effects of patch type or amount si gnificantly influenced the probability of Elimia or Anisocentropus stay ing in the microlandscape. Howe ver, general trends existed, indicating that the amount of cover affects the likelihood of these species remaining in the landscape. Both invertebrate species were less li kely to leave the landscape as the proportion of cover increased in mixed habitats. The proportion of Elimia leaving the landscape decreased from 90 % to 40 % with increasing cover. The proportion of Anisocentropus leaving the landscap e decreased with increasing cover in all patch types, and no indivi duals left the landscape in the mixed species treatment with 30 % cover. Discussion Habitat fragmentation is typically viewed at a sc ale of kilometers; however, the scale at which fragmentation alters loca l population dynamics likely lies at a much smaller scale, particularly for invertebrates. This is one of a few studies to examine individual movement patterns of aquatic invertebrate s in response to patch struct ure (Olden 2004, Lancaster 2006; Drew and Eggleston, 2006). In logged streams, the amount of habitat may be more important than spatial configurat ion since reduced canopy cover limits overall leaf inputs. In the study streams, invertebrate communities differed greatly between four adjacent streams, suggesting

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160 effects of local filters on invertebrate commun ities. Thus, the quality of the riparian and availability of instream habitat create a filte r to limit presence of certain species. Results from this study support the idea that in stream habitat availability controls small scale community composition. The habitat specialist, Anisocentropus, left landscapes without preferred leaf litter habitat. In streams with lit tle organic matter storage, this species may be driven locally extirpated. Although it may be supported where ripa rian zones are left undisturbed, this species prefers small streams and may be driven out of entire headwater streams if they are logged along their length. Logging limits the amount and quality of hab itat available for aquatic invertebrates in stream s. This is accomplished by reducing leaf fall, as well as through an increase in peak flow with increasing surface runoff (Beasley and Gr anillo, 1982; Williams et al., 1999; McBroom et al., 2002; Grace et al., 2003). Thus, any leaf fall that does reach the stream is easily washed downstream during storm events. The results of this study sugge st that increased habitat cove r decreases em igration rates, regardless of habitat configuration. Very few Anisocentropus individuals were able to colonize patches successfully, but when successful, they remained there for the duration of the trial. This suggests that, although small, patches were able to be used as refugia from flow and exposure. Both Elimia and Anisocentropus were likely to remain in the microlandscapes with 30% cover. Changes in landscape structure, such as reduc tion of the proportion of one or m ore patch types or increased patch isolati on, will alter the ability of organisms to disperse (Merriam 1984; Fahrig and Merriam 1985). Species that can not disperse effectivel y as a result of a change in structure will suffer reductions in regional population sizes (Fah rig and Merriam 1994). As a result, relative abundances of Anisocentropus decreased in treatment watersheds following

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161 harvest. In addition to decrea sed food availability with increa sing isolation, availability of refugia decreases. Landscapes in this study were in a particularly inhos pitable matrix of sand, with little heteroge neity. In addition, Anisocentropus individuals were commonly displaced from the streambed in landscapes with low or no habitat available. Habitat loss may also lead to more time bei ng expended searching for suitable habitats, potentially contributing to lowe red survival rates and decrease d fecundity. Correlation between turning angles was always negative for Anisocentropus leading to a wobbly path. It was a clum sy crawler and appeared to have limite d capacity for crawling over a sand dominated streambed with little structure to cling to. Thus, it is likely this species is washed downstream easily during storm events. However, this incr eased with increasing cover in mixed landscapes, suggesting a search strategy. Elimia took larger steps with increasing am ount of cover in the microlandscape. This may be related to the perceptual range of the or ganism, as it may not perceive patches as habitat when they are farther apart as in the 10 percent c over treatment. This sugg ests that the scale of the study may be larger than the scale of perceive d habitat, but potentially defines this scale as lying between the isolation found in the 10 and 30 percent cover treatments. Perceptual range differs greatly among species (Zollner, 2000), regarding the ability of the spec ies to visualize a three dimensional landscape, and it ultimately determines the individuals movement behavi or, search strategy, and respons e to fragmentation (Lima and Zollner, 1996; With and Crist, 1996). However, perceptual range may be dynamic even for individuals of the same species and it changes with environm ental conditions, such as flow variability in streams. For example, downstream flow bias may increase perceptual distance to an upstream patch, increasing isolati on (Olden, 2004). However, in general, increased habitat

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162 amount lengthens the time spent within the la ndscape and may provide protection from scouring and predators. Although habitat amount was a good predictor of em igration rates and movement rates, habitat heterogeneity also played a role. Anisocentropus remained in landscapes longer when both macrophytes and leaf packs were available, s uggesting that habitat di versity leads to higher abundances. Bronmark (1985) found that freshwater snails were more diverse in ponds with more macrophyte species, reflecting the presence of different niches and refugia from predators. In larger, agricultural landscap es, Jonsen and Fahrig (1997) found that more species and individuals colonized landscapes with higher diversity. This suggests a scale-independent relationship between the probability of colonization and diversity of patches in a landscape. The latter increases the number of pot ential refuges and resources avai lable in a landscape. However, I did not expect this to act at a scale independent of resources. Anisocentropus was more likely to remain within the microlandscape in the presence of Ludwigia This suggests a preference for this habitat, possibly due to in creased three dimensional area a nd protection from flow provided from Ludwigia In streams, even species considered specia lists may display flexibility in feeding preferences. Thus, both species considered to be generalists and specia lists may be able to supplement their diet with alternative food sources, enhancing the actual connectivity of the landscape in contrast to the perceived c onnectivity (Dunning et al., 1992). Additionally, Ludwigia traps organic matter faster than newly form ed leaf packs (Chapter 4), creating a higher quality resource. Thus, macrophytes may provide adequate resoures for dispersing detritivores living in patchy landscapes.

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163 Upstream movement has been proposed as one part of the solution to the drift paradox, whereby species need to recolon ize upstream habitats to account for downstream drift. Displacement along the longitudinal ax is is of particular interest to stream ecologists, partly because of its relevance to concepts such as Mullers colonisation cycle and the paradox of upstream downstream movement (e.g., Muller, 1982; Hershey et al., 1993; Anholt, 1995). In essence, there needs to be a balance between downstream movement ( both passive and active) and upstream migration by larvae a nd adults to maintain position in suitable stream habitats (e.g., Elliott, 1971b; Soderstrom, 1987). In this study, most Elimia individuals (90 %) moved upstream, regardless of landscape type, suggesti ng that this is a compensation mechanism for potential disturbances su ch as floods. However, Anisocentropus did not exhibit a significant displacement direction. Although this species spent much of its time attempting to move upstream, the shape of its case made it susceptible to downstream drift. Field studies of upversus downstream moveme nt of individually m arked invertebrates (i.e. at larger spatial and temporal scales than this study) provide contras ting results with regard to directional movement. Among cased caddisflies Jackson et al.(1999) recorded no directional bias in net displacement at low discharge, but th ere was a downstream bias at higher discharges; Erman (1986) reported some seasonal depe ndence but, generally, a net downstream displacement. However, Hart and Resh (1980) re ported no bias in net displacement direction, but did not report displacement distance along the longitudinal ax is. As in this study, upstream displacement occurs commonly in snails (Schneider and Ly ons, 1993; Huryn and Denny, 1997). Although species capable of upstr eam flight, such as stoneflie s, tend to move downstream (Freilich, 1999).

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164 Clearly, multiple factors can influence displ acement at the s tream scale (e.g., body shape, temperature, discharge, life hist ory stage and food availability), a nd generalizations are difficult. Although discharge remained fairly unifrom during this study, there is strong evidence from other studies suggesting th at discharge is a primary determinan t of movement rates and direction (Olden, 2004; Lancaster, 2006). Thus, respons e to landscape structur e may differ between logged and unlogged streams. Studies attempting to understa nd the role of patch structur e an d arrangement in streams lag far behind those in terrestrial systems. Ho wever, it has become clear that both spatial arrangement and habitat amount are determinan ts of community structure stemming from changes in emigration and immigration rate s (Palmer, 2000; Olden, 2004; Lancaster, 2006; Olden, 2007). Additional studies are needed to de termine if generalities exist in streams, including long-term mark-recaptur e studies across life stages. A quatic invertebrates are unique in that they spend their larval period in the wate r and their adult stages on land. Thus, dispersal studies will need to account for small scale move ments in streams as well as the response of adults to spatial structure in the terrestrial landscape. Clearcut watersheds may limit this dispersal, creating streams that act as isolated islands. This is particularly important in headwater streams since some species are depend ent on specicific environmental conditions only available in small, forested headwater sy stems (Lowe, 2002; Meyer et al., 2007).

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165 A B C A B C Figure 5-1. Microlandscape desi gns used in the behavioral an d colonization experim ents. Liriodendron leaf packs (brown squares) and Ludwigia macrophyte patches at A) 10 B) 20, and C) 30 percent cover. The same c onfiguration was used for landscapes with a single patch type.

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166 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 102030Percent CoverDeviation from CRW Ludwigia Mixed Liriodendron Figure 5-2. Average deviation from a correl ated random walk ( SE) (CRW) (Rdiff) for Anisocentropus

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167 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 102030Percent CoverProbability of Turning in Same Direction Ludwigia Mixed Liriodendron Figure 5-3. Average probability ( SE) of each turn being in the sam e direction for Anisocentropus

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168 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 102030Percent CoverCorrelation between Turning Angles Ludwigia Mixed Liriodendron Figure 5-4. Average correlation ( S E) between turning angles for Anisocentropus.

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169 0 500 1000 1500 2000 2500 102030Percent CoverNet Squared Displacement (cm) Ludwigia Mixed Liriodendron Figure 5-5. Average net squa red disp lacement ( SE) of Anisocentropus in microlandscapes.

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170 0 0.2 0.4 0.6 0.8 1 1.2 102030Percent CoverMean Step Length (cm) Ludwigia Mixed Liriodendron Figure 5-6. Mean step length ( SE) in each land scape for Elimia

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171 0 0.5 1 1.5 2 2.5 3 3.5 102030Percent CoverDeviation from CRW Ludwigia Mixed Liriodendron Figure 5-7. Average deviation ( SE) fr om a correlated random walk (Rdiff) for Elimia

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172 CHAPTER 6 CONCLUSIONS Best management practices for forestry in the U. S. clearly de pend on the geographic region under review. For example, coastal plain streams in the southern U.S. are characteristically low-gradient, sandy-bottome d systems with dynamically changing instream habitat. In contrast, those managed for forestry in the western U.S. ar e typically high-gradient montane streams with high habitat and substrate diversity and are susceptible to mass-wasting as vegetation removal reduces bank stability. Although forestry practices in the Northwest can lead to drastic reductions in water quality, evidence fr om the coastal plain indicates limited changes in water quality and biotic diversity in st reams impacted by logging, as long as stream management zones are left intact. Although there were few changes in biotic community structure following logging, this does not discount use of aquatic invertebrates as indicators of water qualit y. Many biotic indices weigh heavily upon the use of EPTs (Ephem eropt era, Plecoptera, and Trichoptera) in their formation (e.g., Lenat, 1993). However, loggi ng ultimately increases pr imary productivity in streams, leading to higher densities of Baetid/Leptophlebiid ephemeropter ans (Chapter 3; Stone and Wallace, 1998). As a result, the FLSCI biotic index is inflated, suggesting an increase in water quality with logging. One short-coming of local management organizations is the longterm fascination with EPTs, sometimes leadi ng to redundant use of this group by utilizing metrics on the number of EPT taxa, % EPT, number of Trichoptera, and number of Ephemeroptera, to name a few (e.g., Maxted et al., 2000). As an alternative, use of biol ogical traits h as recently been advocated as a potential tool for assessing aquatic ecosystems by academia and the federal government (Poff et al., 2006). Biological traits are more informative indicato rs of ecosystem functi on than are changes in

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173 abundance of individual species, and they are expected to change across a gradient of anthropogenic and natural disturbances (Charvet et al., 2000; Doledec et al., 1999; Statzner et al., 2001). Additionally, biological traits are re gulated at a hierarchy of scales, with environmental filters (e.g., clim ate and geology) creating a templa te for traits present in a specific region (Townsend and Hildrew, 1994; Poff, 1997) Thus, a subset of traits is expected to respond to disturbances within a certain region. In the logged streams, traits were consistent with changes in the stream and were represen ted by species preferring algae and organic matter in the water column, as well as those preferring to live in sandy habitat, reflecting reduction in other habitat types (e.g., leaf litter). The ability of the Florida Stream Condition Index to indicate the im pacts of drought effectively, but not forestry impacts, emphasizes th e need to incorporate natural disturbances into bioassessment programs. Most programs determin e the condition of streams based on a single sample. Even when multiple sampling time periods are included, they typically are 3-4 years apart and occur in different locations than the first sample, since many large scale surveys are probability based (Stoddard et al., 2005). Thus, predictive models need to be developed based on current environmental conditions in the region as compared to historical conditions (e.g., amount of precipitation). The standardized pr ecipitation index was a good indicator of changes in water quality and thus could be incorporated into such a model. Another confounding feature for predicting impacts of logging was related to habitat availability and quality. Logged stre am s were colonized by the macrophyte, Ludwigia repens, which was able to support higher densities and a more diverse invertebrate community. This was accomplished through the stability provided by this ha bitat and its role in trapping organic matter as compared to less stable leaf packs. Trapping of organic matter creates patches similar to

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174 debris dams, and the addition of this habitat was preferred to la ndscapes with only leaf packs by a specialist detritivore ( Anisocentropus pyraloides ). This situation may be unique to coastal plain streams, where fine substrate is often entrained in storm events, creating a dynamically changing landscape. This is in stark c ontrast to mountain streams with higher substrate diversity and stability in the form of boulders and cobble. Testing of any best management practice ultim ately requires an understanding of mechanisms behind changes in stream communiti es, as well as long-term monitoring data. Results from this study provide information on the mechanisms leading to apparent improved water quality in streams impacted by logging. Thus, additional effo rt should be placed on developing assessments specific to coastal plain streams, since most are based upon expected habitat diversity and cha nnel structure found in Piedmont streams.

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175 LIST OF REFERENCES Adams, T.O., D.D. Hook, and M.A. Floyd. 1995. Eff ectiveness m onitoring of silvicultural best management practices in South Carolina. S outh Journal of Applie d Forestry 19: 170-176. Acua, V., I. Muoz, A. Giorgi, M. Omella, F. Sabater, and S. Sabater. 2005. Drought and postdrought recovery cy cles in an intermittent Mediterranean stream: structural and functional aspects. Journal of the North Ameri can Benthological Society 24: 919-933. Allan, J.D. 1995. Stream Ecology: Structure and F unction of Running W aters. Dordrecht, Neth.: Kluwer. 388pp. Allan, J. D. and M. Lammert. 1999. Assessing biotic integrity of stream s: Effects of scale in measuring the influence of land use/cover and ha bitat structure on fish and macroinvertebrates Environmental Management 23: 257-270. Anderson, N.H. and J. R. Sedell. 1979. Detritus processing by m acroinvertebrates in stream ecosystems. Annual Review of Entomology 24: 351-377. Anholt, B.R. 1995. Density dependence resolv es the stream drift paradox. Ecology 76: 2235 2239. Arthur, M. A., G.B. Coltharp, and D.L. Brown. 1998. Effects of best m anagement practices on forest streamwater quality in eastern Kentuc ky. Journal of the American Water Resources Association 34: 481. Alverez, M. 2007. The State of Americas Forests. Society of Am erican Foresters, Bethesda, MD. 76 pp. Arsuffi, T.L. and K. Suberkropp. 1985. Selectiv e feeding by stream ca ddisfly (Trichoptera) detritivores on leaves with fungalcolonized patches. Oikos 45: 50-58. Aust, W.R. and C.R. Blinn. 2004. Forestry best m anagement practices for timber harvesting and site preparation in the eastern United States : An overview of water quality and productivity research during the past 20 years (1982). Wa ter, air, and soil po llution: Focus 4: 5-36. Baldwin D.S., G.N. Rees, A.M. Mitchell, and G. W atson. 2005. Spatial and temporal variability of nitrogen dynamics in an upland stream before and after a drought. Marine and Freshwater Research 56: 457-464. Barber N.L. and T.C. Stamey. 2000. Droughts in Georgia. USGS Open File Report no. 380. Barbour, M.T., J. Gerritsen, B.D. Snyder, and J.B. Stribling. 1999. Rapid bioassessm ent protocols for use in streams a nd wade able rivers: Periphyton, benthic macroinvertebrates and fish, 2nd ed. U.S. EPA, Office of Wa ter. Washington, D.C. EPA 841-B-99-002.

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BIOGRAPHICAL SKETCH Marcus Griswold was born in Baltimore, Maryland, on September 30, 1978. He pursued a B.S. in biology at the Univers ity of Maryland at College Park. His m asters work took him to the University of Florida to work on predato r-prey dynamics of larval mosquitoes under the direction of Phil Lounibos. His interest in aquatic ecology and background in Entomology led him to Thomas Crisman to pursue a PhD in envi ronmental engineering sciences, with a focus on riparian zone management in aquatic ecosystems. During this time, his work was funded by the U.S. EPA, Sigma Xi, and the Friends of the Osa. He has worked in a variety of stream systems in the southeastern U.S. and Costa Rica, from prim ary tropical forests to degraded urban streams. His goal is to utilize his knowledge of aquatic stressors to properly manage aquatic ecosystems, balancing human needs and maintenance of ecosystem function and biodiversity.