THE INFLUENCE OF COARSE WOODY DEBRIS, DISTURBANCE, AND
RESTORATION ON BIOLOGICAL COMMUNITIES IN SANDY COASTAL PLAIN
STREAMS
by
Richard Morgan Mitchell
A dissertation submitted to the Graduate Faculty of
Auburn University
in partial fulfillment of the
requirements for the Degree of
Doctor of Philosophy
Auburn, Alabama
December 18, 2009
Keywords: crayfish, coarse woody debris, benthic macroinvertebrates, catchment
disturbance
Copyright 2009 by Richard Morgan Mitchell
Approved by
Jack W. Feminella, Chair, Professor, Department of Biological Sciences
Arthur C. Benke, Adjunct Professor, Department of Biological Sciences
Micky D. Eubanks, Associate Professor, Department of Entomology and Plant
Pathology
ii
Abstract
The influence of instream habitat on benthic macroinvertebrates was assessed
from multiple descriptive and experimental studies within the Fort Benning Military
Installation (FBMI), Georgia and the Tuskegee National Forest, Alabama, USA.
Instream habitat, in the form of coarse woody debris (CWD), plays an important role in
stabilizing sandy bottom streams in the Coastal Plains of the Southeastern United
States.
Chapter 2 describes the results of an instream restoration experiment conducted
in 8 streams at FBMI to assess the influence of CWD additions on instream habitat and
benthic macroinvertebrate assemblages. Macroinvertebrates were sampled before and
after CWD additions in each stream to allow pre- and post-restoration comparisons of
assemblages. Results revealed that streams receiving CWD additions dampened the
influence of hydrologic disturbance on structural and functional measures of the
macroinvertebrate assemblages, whereas non-restored streams showed a general
decrease in those same measures.
Chapter 3 describes the results of a multi-stream survey at FBMI designed to
examined the influence of catchment disturbance on instream habitat availability and its
putative effects on freshwater crayfish populations. Results showed that catchment
disturbance was negatively correlated to instream CWD and BPOM habitat and, in turn,
iii
that crayfish density and biomass were strongly related to CWD. These data suggested
that catchment disturbance influences crayfish by influence instream habitat availability.
Chapter 4 describes a field experiment designed to quantify the influence of
crayfish on benthic food webs in sandy coastal plains streams. The experiment was
conducted in a forested section of Choctafaula creek, Macon County, Alabama, with the
Tuskegee National Forest. The experimental was an in-situ enclosure-exclosure
complete randomized block design. Results showed that crayfish had limited influence
on leaf litter (i.e., basal resource), however, they did have a significant influence on
other benthic macroinvertebrates. It appears that this influence was due to direct
predation, as determined by stable isotope analysis, which showed a trophic position
similar to other predators from the study.
Chapter 5 of this dissertation assessed crayfish production and diet from 3 sandy
bottom streams at FBMI. The purpose was to equate differences in production and diet
to differences in CWD abundance. Results showed crayfish productivity was greatest in
the stream with the highest CWD abundance, with the lowest productivity occurring in
the stream with the lowest CWD abundance. These results suggest that habitat may
plan a substantial role on crayfish productivity, and changes to habitat abundance may
negatively impact crayfish. Additionally, results showed that crayfish diets were
significantly different among streams, with crayfish from the low CWD stream containing
a high amount of inorganic matter, suggesting diets are of poor quality compared to
crayfish from streams with intermediate to high CWD.
iv
Acknowledgments
The author would like to thank his committee members Drs. Jack W. Feminella,
Micky D. Eubanks, and Arthur C. Benke for their guidance and support during his
graduation studies. He would also like to thank Dr. Dennis R. DeVries who served as
the outside reader and offered useful comments on earlier drafts of the dissertation.
The author would also like to thanks the following peers who provided field help and
alternative perspectives on research findings: Dr Kelly Maloney, Dr. Brian Helms, Dr.
Ken Fritz, Stephanie Miller, Dr. Abbie Tomba, and Dr. Michael Gangloff, Mollie
Newman. He would also like to thank the following technicians who helped in the field:
Talitha Thompson, Adriene Burnette, Courtney Ford, and Matthew Feminella. The
author would like to thank his mother Christine, brother David, and sister-in-law Kim for
their loving support during his work on his dissertation. He would also like to thank
Sandy Nichols for her loving support and understanding during the course of his
dissertation. Drs. Patrick J. Mulholland, Brian J. Roberts, and Jeffery N. Houser
provided field assistance and helpful suggestions for study design, and Hugh West
provided logistical support at Fort Benning. This research was supported by contracts
from the U.S. Department of Defense?s Strategic Environmental Research and
Development Program (SERDP) to Oak Ridge National Laboratory (ORNL). ORNL is
managed by the University of Tennessee-Battelle LLC for the U.S. Department of
Energy under contract DE-AC05-00OR22725.
v
Table of Contents
Abstract..........................................................................................................................ii
Acknowledgments .........................................................................................................iv
List of Tables.................................................................................................................ix
List of Figures................................................................................................................xi
Chapter 1 Introduction .................................................................................................. 1
1.1 Reference ................................................................................................... 5
Chapter 2 Influence of Hydrologic Variation and Instream Habitat Restoration on Sandy
Southeastern Plains Streams of Western Georgia, USA ........................... 11
2.1 Summary.................................................................................................... 11
2.2 Introduction................................................................................................. 12
2.3 Methods...................................................................................................... 14
2.3.1 Study Site.......................................................................................... 14
2.3.2 Experimental Design ......................................................................... 15
2.3.3 Benthic Microhabitat and Organic Matter Sampling .......................... 16
2.3.4 Benthic Macroinvertebrate Sampling................................................. 18
2.3.5 Data Analysis .................................................................................... 19
2.4 Results ....................................................................................................... 21
2.4.1 Extent of CWD Additions ................................................................... 21
2.4.2 Precipitation and Discharge............................................................... 22
2.4.3 CWD, %BPOM, and Streambed Variability ....................................... 22
vi
2.4.4 Benthic Macroinvertebrates............................................................... 23
2.5 Discussion .................................................................................................. 25
2.5.1 Influence of Hydrologic Variation on CWD......................................... 25
2.5.2 Hydrologic and CWD Addition Influence on Instream Habitat
and BPOM ........................................................................................ 27
2.5.3 Influence of CWD Additions on Dampening Hydrologic Variation ...... 29
2.6 Conclusion.................................................................................................. 30
2.7 References ................................................................................................. 32
Chapter 3 Multi-scale Controls on Populations of the Crayfish Procambarus versutus
(Cambaridae) in Sandy Streams of Western Georgia, USA ...................... 64
3.1 Summary.................................................................................................... 64
3.2 Introduction................................................................................................. 65
3.3 Methods...................................................................................................... 68
3.3.1 Study Site.......................................................................................... 68
3.3.2 Study Sites and Landscape-scale Measures..................................... 69
3.3.3 Instream Habitat Measures ............................................................... 70
3.3.4 Crayfish Sampling ............................................................................. 71
3.3.5 Statistical Analysis............................................................................. 72
3.4 Results ....................................................................................................... 73
3.4.1 Instream Habitat Conditions .............................................................. 73
3.4.2 Landscape-scale Relationships with Instream Habitat....................... 74
3.4.3 Instream Habitat Relationships with Crayfish Measures.................... 74
3.4.4 Disturbance relationship with crayfish population measures ............. 76
3.5 Discussion .................................................................................................. 76
vii
3.5.1 Influence of Disturbance on Instream Habitat.................................... 76
3.5.2 Influence of Instream Habitat on Crayfish.......................................... 78
3.5.3 Relationship between Catchment Disturbance and Crayfish.............. 80
3.6 Literature Cited........................................................................................... 83
Chapter 4 Influence of the Crayfish Procambarus versutus on leaf breakdown and
benthic macroinvertebrates in a sandy-bottom stream ............................ 112
4.1 Summary.................................................................................................. 112
4.2 Introduction............................................................................................... 113
4.3 Methods.................................................................................................... 116
4.3.1 Study Site........................................................................................ 116
4.3.2 Study Species ................................................................................. 116
4.3.3 Experimental Design ....................................................................... 117
4.3.4 Crayfish Trophic Position and Food Web Analysis.......................... 118
4.3.5 Predictions and Analysis ................................................................. 120
4.4 Results .................................................................................................... 121
4.4.1 Field Experiment............................................................................. 121
4.4.2 Food Web Analysis......................................................................... 123
4.5 Discussion ................................................................................................ 124
4.5.1 Influence on Leaf Litter Breakdown ................................................. 124
4.5.2 Crayfish Influence on Macroinvertebrate Assemblages................... 126
4.5.3 Crayfish Trophic Relationships in Leaf Litter Food Webs ................ 129
4.6 Literature Cited......................................................................................... 131
Chapter 5 Contrasting Diet and Production of the Crayfish Procambarus versutus from
Three Coastal Plain Streams in Western Georgia, USA ......................... 145
viii
5.1 Summary............................................................................................ 145
5.2 Introduction......................................................................................... 146
5.3 Methods............................................................................................. 148
5.3.1 Study Streams.......................................................................... 148
5.3.2 Study Animal ............................................................................ 149
5.3.3 Coarse Woody Debris and Benthic Particulate Organic Matter
Sampling .................................................................................. 150
5.3.4 Crayfish Sampling .................................................................... 151
5.3.5 Crayfish Density, Biomass, and Production.............................. 151
5.3.6 Crayfish Diet and Trophic Position ........................................... 152
5.4 Results ............................................................................................. 155
5.4.1 CWD and BPOM ..................................................................... 155
5.4.2 Crayfish Density, Biomass, Size, and Production.................... 156
5.4.3 Crayfish Diet and Trophic Position .......................................... 157
5.5 Discussion ........................................................................................ 159
5.5.1 Importance of CWD and its Influence on Basal Resources ..... 159
5.5.2 Crayfish Density, Biomass, and Production............................. 161
5.5.3 Crayfish Diet and Trophic Position .......................................... 163
5.6 Literature Cited................................................................................. 168
ix
List of Tables
2.1 Locations and characteristics of study streams..................................................... 43
2.2 Summary of instream physical variables for restored and unrestored streams,
measured by season............................................................................................ 45
2.3 F-values (p-values in parentheses) of repeated measures ANOVA (F
1,30
) on
compositional macroinvertebrate measures. TRT = restored or control streams,
Period = pre- and post-restoration. Bold highlights values significant at
p = 0.05 ................................................................................................................. 46
3.1 Study stream locations, with catchment and disturbance characteristics. UTM =
Universal Transverse Mercator, %BGRD = percentage of catchment as bare ground
on slopes > 5% and % of unpaved roads in catchment. Catchments were listed
in order of increasing landscape disturbance ....................................................... 92
3.2 Mean (+1SE) instream habitat-scale variables. CWD = coarse woody debris relative
abundance. %BPOM = benthic particulate organic matter. Catchments were listed
in order of increasing landscape disturbance (Table 1)......................................... 94
3.3 Pearson?s correlation coefficients summarizing relationships between landscape
variables with instream habitat variables, by season. Bold correlation coefficients
were significant at ?=0.05. Disturbance intensity = %BGRD (percent of bare ground
on slopes >5% and unpaved roads within catchment). ND= no data (CWD was
measured in spring only). CWD = coarse woody debris relative abundance.
%BPOM = benthic particulate organic matter ....................................................... 96
3.4 F-values (p-values in parentheses) of repeated measures ANOVA (F
1,30
) on
compositional macroinvertebrate measures. TRT = restored or control streams,
Period = pre- and post-restoration. Bold highlights values significant at
p = 0.05 ................................................................................................................ 98
3.5 ANOVA summary showing differences for crayfish population variables among
streams and between microhabitats. Habitat represents pools vs. runs. Mean size
= mean crayfish size (as carapace length). DF = degrees of freedom. Values are
F-statistics (p-value) ........................................................................................... 100
x
3.6 ANOVA summary showing differences for crayfish population variables among
streams and between microhabitats. Habitat represents pools vs. runs. Mean size
= mean crayfish size (as carapace length). DF = degrees of freedom. Values are
F-statistics (p-value) ........................................................................................... 102
5.1 Watershed and physicochemical characteristics for streams where Procambarus
versutus were collected. Average stream slope (%) is from a 100-m stream reach
where crayfish were collected. Mean temperature (?C) is the mean annual
temperature of each stream during the period crayfish were collected (Mean ?1SE).
DO (dissolved oxygen, mg/L), pH, and Ca
+
(mg/L) were taken from the downstream-
most point of study sites. Velocity (m/s), Depth (m), and Wetted stream width (m)
are reach averages from collection sites (Mean ?1SE). Discharge (m
3
/s) was taken
from the downstream most point of study sites ................................................... 176
5.2 Calculation of Procambarus versutus production by the size-frequency method, from
Sally branch tributary (SBT), Fort Benning Military Reservation, Georgia........... 177
5.3 Calculation of Procambarus versutus production by the size-frequency method, from
Kings Mill creek (KMC), Fort Benning Military Reservation, Georgia .................. 179
5.4 Calculation of Procambarus versutus production by the size-frequency method, from
Bonham creek tributary (BCT), Fort Benning Military Reservation, Georgia ....... 181
5.5 Calculation of production attributed to each food type and amount consumed by
Procambarus versutus, from Sally Branch tributary (SBT), Fort Benning Military
Reservation, Georgia (annual production = 566.80 mg/m
2
/yr) ............................ 183
5.6 Calculation of production attributed to each food type and amount consumed by
Procambarus versutus, from King?s Mill creek (KMC), Fort Benning Military
Reservation, Georgia (annual production = 1311.14 mg/m
2
/yr) .......................... 185
5.7 Calculation of production attributed to each food type and amount consumed by
Procambarus versutus, from Bonham creek tributary (BCT), Fort Benning Military
Reservation, Georgia (annual production = 1870.83 mg/m
2
/yr) .......................... 187
xi
List of Figures
2.1 Relative abundance of in-stream coarse woody debris (CWD, as % of total
streambed cover), before (pre-restoration, spring 2003) and after debris dam
additions (fall 2003 and fall 2004 CWD additions) for the 4 restored streams.
Restored streams received debris dam additions in Oct-Nov 2003 and supplemental
debris dams (SB3 and LPK) in Nov 2004 .............................................................. 48
2.2 Precipitation data from Columbus, Georgia, for the period 1949?2006. Pre-
restoration sampling occurred in 2001, 2002, and 2003, whereas post-restoration
period occurred in 2004, 2005, and early 2006. Note that much of the post-
restoration sampling occurred in years that were among the wettest on record (late
2003, 2004, and 2005). A = annual precipitation, B = summer precipitation ........ 50
2.3 Comparison of mean (+1 SE) baseflow discharge in restored (in compartments SB3,
SB2, KM1, LPK) (A) and unrestored streams (compartments BC1, BC2, SB3, HB)
(B) before (2001- 2003) and after restoration (2004, 2005, 2006). Vertical dashed
line on A shows approximate time of debris dam additions (Oct-Nov 2003). Note that
much of the post-restoration sampling (2004, 2005) occurred during conditions of
substantially higher discharge than pre-restoration sampling (n = 24) .................. 52
2.4 Mean (+1 SE) summer depth in restored and unrestored stream during the pre- and
post-restoration periods. * = p < 0.05 ................................................................... 54
2.5 Average relative abundance and functional feeding groups of the benthic
macroinvertebrate assemblage that showed a significant Period effect during the
summer. A = biomass (restored, F = 14.47, p = 0.001; unrestored, F = 9.68, p =
0.006), B = density (restored, F = 12.40, p = 0.002; unrestored, F = 13.73, p =
0.002), C = species richness (restored, F = 5.37, p = 0.032; unrestored, F = 15.26, p
= 0.001), D = %Filterers (restored, F = 4.20, p = 0.053, unrestored, F = 7.68, p =
0.013) Error bars are standard error. * = p < 0.05 ............................................... 56
xii
2.6 Average relative abundance and functional feeding groups of the benthic
macroinvertebrate assemblage that showed a significant Treatment?Period effect.
A = winter EPT density (restored, F = 10.27, p = 0.017; unrestored, F = 0.17, p =
0.685), B = winter %EPT (restored, F = 19.33, p < 0.0001; unrestored, F = 1.39, p =
0.225), C = spring %Filterers (restored, F = 1.58, p = 0.225; unrestored, F = 4.25, p
= 0.050), D = spring %Collectors (restored, F = 1.18, p = 0.292, unrestored, F =
6.98, p = 0.017), E = summer %Scrapers (restored, F = 0.59, p = 0.45; unrestored,
F = 7.11, p = 0.016), F = summer Chironomidae richness (restored, F = 1.08, p =
0.312; unrestored, F = 12.03, p = 0.003). Error bars are standard error.
* = p < 0.05............................................................................................................ 58
2.7 Nonmetric multidimensional scaling (NMS) ordination results. Symbols represent
stream/year-specific macroinvertebrate scores. A (summer: Circles: 2001, inverted
triangle: 2002, square: 2004, diamond: 2005, triangle: 2006). B (winter: Circles:
2002, inverted triangle: 2003, square: 2004, diamond: 2005, triangle: 2006). R
2
values represent the proportion of variation in the macroinvertebrate assemblage
similarity accounted for by each axis. Arrows on axes indicate direction of
relationships between hydrologic and habitat variables and NMS scores (see text for
values). Axis scores are raw values, stress level = 13.01 (summer) and 13.65
(winter), for the 3-dimension solution, with a final instability of 0.00001 after 151
iterations for summer, and 0.00001 after 67 iterations for winter .......................... 60
2.8 Average vector length comparison between restored and unrestored streams, with
vector length calculated for each stream between the first year of pre-restoration
sampling (2001: summer, A; 2002: winter, B) and each subsequent year of
sampling. Differences between restored and unrestored streams are designated by
different letters using Tukey?s pair-wise comparisons and treatments with the same
letter were not significantly different. Error bars are standard deviations ........... 62
3.1 The amount of streambed variability as express as coefficient of variance of depth
in runs and pools plotted against the catchment disturbance intensity for the 8 study
streams across 3 seasons (top panel = spring, middle panel = summer, bottom
panel = winter).................................................................................................... 104
3.2 Comparison of mean (+1SE) crayfish (Procambarus versutus) density, biomass,
carapace length and % female between run and pool microhabitats across three
seasons (spring, summer, winter). * p < 0.05..................................................... 106
3.3 Mean density of crayfish (Procambarus versutus, as number per m
2
) in runs plotted
against catchment disturbance intensity for the 8 study streams for spring (A),
summer (B), and winter (C) ............................................................................... 108
3.4 Mean biomass of crayfish (Procambarus versutus) plotted against catchment
disturbance intensity for the 8 study streams across season. A = pools and runs, B
= pools, and C = runs......................................................................................... 110
xiii
4.1 The effects of crayfish (Procambarus versutus) on leaf litter break in field
experiments (Mean ? 1 SE). Differences between treatments are designated by
different letters using Tukey?s pair-wise comparisons and treatments with the same
letter were not significantly different. Treatments were crayfish exclusion (E), 1
crayfish enclosure (1C), 3 crayfish enclosure (3C), open cage (CC), and no cage
(NC) .................................................................................................................... 137
4.2 The effect of crayfish (Procambarus versutus) on macroinvertebrate assemblages in
field experiments. Mean (?1 SE) macroinvertebrate density (A), mean (?1 SE)
macroinvertebrate biomass (B), mean (?1 SE) log10-transformed Stenonema sp.
Density (C), mean (?1 SE) log10-transformed predacious Plecoptera density (D),
mean (?1 SE) Cheumatopsyche sp. density (E), mean (?1 SE) non-Tanypodinae
Chironomidae density (F), mean (?1 SE) Tipula sp. (G). Differences among
treatments are shown by different letters using Tukey?s pair-wise comparisons and
treatments with the same letter were not significantly different. Treatments were
crayfish exclusion (E), 1 crayfish enclosure (1C), 3 crayfish enclosure (3C), open
cage (CC), and no cage (NC) ............................................................................. 139
4.3 The effect of crayfish (Procambarus versutus) on Tipula sp. size in field experiments
(Mean ? 1 SE). Differences between treatments are designated by different letters
using Tukey?s pair-wise comparisons and treatments with the same letter were not
significantly different. Treatments were crayfish exclusion (E), 1 crayfish enclosure
(1C), 3 crayfish enclosure (3C), open cage (CC), and no cage (NC) ................. 141
4.4 Stable isotope cross-plots of the Choctafaula creek benthic food web. All ?
15
N and
?
13
C values are average values (? 1 SE) from 3 to 5 samples per taxonomic group,
except crayfish (Procambarus versutus), which was composed of 30 individuals 143
5.1 Locations of study watersheds within Fort Benning Military Reservation, GA. The
dotted line within the western portion of the reservation designates the
Chattahoochee River. BCT (Bonham Creek Tributary) is the high-CWD stream,
KMC (King?s Mill Creek) is the intermediate-CWD stream, and SBT (Sally Branch
Tributary) is the low-CWD stream ...................................................................... 189
5.2 Mean (? 1 SE) percentage of stream bottom covered by coarse woody debris for
the 3 study streams. Differences between study streams are designated by
different letters using Tukey?s pair-wise comparisons and treatments with the same
letter were not significantly different ................................................................... 191
xiv
5.3 Mean (? 1 SE) percentage of benthic particulate organic matter from sediment core
samples. A and B are samples from the mid-channel and near-bank, respectively
during the spring. C and D are samples from the mid-channel and near-bank,
respectively during the summer. E and F are samples from the mid-channel and
near-bank, respectively during the winter. Differences among streams are shown
by different letters, such that treatment means with the same letter were not
significantly different .......................................................................................... 193
5.4 Mean (? 1SE) monthly density (A), biomass (B), and individual size as carapace
length (C) of the crayfish Procambarus versutus for the 3 study streams ......... 195
5.5 Monthly size frequency distribution of the crayfish Procambarus versutus for the 3
study streams. Width of each bar represents percentage of total individuals within
each size class .................................................................................................. 197
5.6 Mean (? 1SE) annual density and biomass, and annual production of the crayfish
Procambarus versutus for the 3 study streams. Differences between streams for
annual density and biomass are shown by different letters, such that treatment
means with the same letter were not significantly different ................................. 199
5.7 Mean (? 1SE) percent gut-content for each of the four gut-content categories. A is
BCT (Bonham Creek Tributary), B is KMC (King?s Mill Creek), and C is SBT (Sally
Branch Tributary) ................................................................................................ 201
5.8 Mean transformed percent organic gut-content for crayfish (Procambarus versutus)
in each of the 3 study streams. A is from spring 2006 and B is from fall 2006.
Differences between study streams are designated by different letters using Tukey?s
pair-wise comparisons and treatments with the same letter were not significantly
different ............................................................................................................... 203
5.9 Mean (? 1SE) crayfish (Procambarus versutus)
15
N values for fall 2005 and 2006
(A) and mean (? 1SE) crayfish trophic position for fall 2005 and 2006 (B). Within
year differences between study streams are designated by different letters using
Tukey?s pair-wise comparisons and treatments with the same letter were not
significantly different ............................................................................................ 205
1
1. INTRODUCTION
Stream ecosystems are influenced by a wide variety of environmental factors,
ranging from anthropogenic disturbance in the uplands to instream habitat availability in
the channel. It has been well documented that a streams catchment are tightly
connected with stream communities through influence of hydrologic and chemical
conditions (Hynes 1975, Junk et al. 1989). Similarly, instream habitat is greatly affected
by the surrounding catchment, both with upland and riparian (lateral) regions of the
catchment (Harmon et al. 1986, Lenat and Crawford 1994, Wallace et al. 1996, Paul
and Meyer 2001, Maloney et al. 2005). Catchment disturbance is an important factor
affecting stream communities, often through its influence on instream habitat (Resh et
al. 1988, Palmer et al. 1996, Maloney et al. 2008). My dissertation research is
separated into 4 primary chapters, with the first data chapter (Chapter 2) describing the
influence of hydrologic regime on the efficacy of instream coarse woody debris (CWD)
restoration and its influence benthic macroinvertebrates. Chapter 3 focuses on the
influence of upland disturbance on both instream habitat and crayfish populations, and
how upland disturbance influences crayfish populations indirectly by altering habitat
availability. Chapter 4 describes an in situ experiment quantifying the effect of crayfish
density on a basal food resource (i.e. leaf litter) and litter-associated benthic
macroinvertebrates. The final chapter (5) describes the influence of contrasting CWD
abundance on crayfish density, biomass, productivity, and trophic position in the stream
food web.
2
Temporal changes in flow regimes in streams have been shown to greatly
influence stream communities and their habitats. Hydrologic impacts can occur from
high natural variation (e.g. drought, snow melt), or anthropogenic changes within
catchments that alter intensity and duration of instream flow (Resh et al. 1988, Poff and
Ward 1989, Paul and Meyer 2001, Rose and Peters 2001, Maloney et al. 2006). These
changes can have a strong influence on CWD by decreasing its availability through
burial or displacement downstream during flooding events (Shields et al. 2003, Maloney
et al. 2005). Restoration efforts to improve instream habitat through the addition of
CWD has received only recent attention (Shields et al. 2003, Entrekin et al. 2009, Lester
and Wright 2009). These efforts attempted to restore woody habitat for stream
invertebrates and vertebrates as well as increase streambed stability. However, most of
these studies focused only on the influence of CWD additions, and did not consider the
influence of the hydrologic regime on CWD restoration efforts. Chapter 2 describes an
experimental approach designed to assess the efficacy of CWD restoration during
strongly contrasting hydrologic conditions on benthic macroinvertebrate assemblages in
sandy coastal plains streams of Western Georgia, USA. During the study, the
hydrologic regime showed a substantial change between pre- and post-restoration
periods, which likely influenced the efficacy of the restoration effort. The main
objectives were to 1) assess if artificial CWD additions altered the benthic
macroinvertebrate community assemblage over a 3 y post-restoration period, and 2)
characterize differences in macroinvertebrate assemblage response between restored
and unrestored streams during extreme wet years with increased hydrologic
disturbance.
3
Land use changes resulting in increased sedimentation of streams through forest
practices and soil disturbance can subsequently alter instream habitat and thus impact
biotic communities (Lenat et al. 1981, Karr 1991, Wang et al. 2001, Maloney and
Feminella 2006, Burcher et al. 2007). Much research has focused on the degradation
of faunal composition and diversity associated with sedimentation (Cordone and Kelly
1961, Lenat et al. 1981, Wood and Armitage 1997, Angradi 1999). Sedimentation from
upland disturbance can impact benthic macroinvertebrate assemblages by altering
behavior (i.e., increasing downstream displacement [drift]) or causing mortality directly
by burial (Newcombe and MacDonald 1991, Waters 1995), or indirectly by loss of
habitat (Maloney and Feminella 2006). However, there has been considerable work on
the general benthic macroinvertebrate assemblage, but comparatively little on the
influence of sedimentation on stream crayfish populations. The influence of upland
disturbance, through sedimentation, on crayfish could have a substantial influence on
stream ecosystems because of their important ecological role in streams (Momot et al.
1978, Huryn and Wallace 1987). The objectives of Chapter 3 were to 1) relate
landscape-level land use, specifically catchment scale-disturbance, and instream
habitat, 2) investigate the relationships between instream habitat conditions and crayfish
population measures, and 3) relate crayfish population measures to catchment-scale
disturbance.
The ecological role of crayfish in aquatic ecosystems has long been well known
(Momot et al. 1978, Momot 1995). Crayfish have been shown to influence
macroinvertebrate assemblages and basal resources (e.g. leaf litter, algae; Creed 1994,
Parkyn et al. 1997), sometimes through ecosystem engineering (Creed and Reed
4
2004), which involves creating or modifying habitats and influencing resource availability
for other species (Jones et al. 1994, 1997, Usio and Townsend 2004, Helms and Creed
2005). However, most studies have been done in streams of either high gradient or
high latitude, and much of this research has been focused on large, long-lived species.
Chapter 4?s objectives were to 1) assess the influence of a small, short-lived crayfish
species on its basal resource (leaf detritus) and benthic macroinvertebrate prey
colonizing leaf litter, and 2) describe crayfish trophic position to assess its potential
effect on the benthic food web.
Freshwater crayfish depend on a wide variety of habitats (e.g., gravel, boulders,
vegetation, and coarse woody debris) as refuge from predation by fishes and terrestrial
vertebrates (Stein 1977). Research has demonstrated the link between habitat
availability and crayfish abundance, but few studies have assessed the importance of
habitat availability on regulation of intrinsic factors of crayfish populations, including
growth and production (Stein 1977, Contreras-Balderas and Lozano-Vilano 1996,
Mitchell and Smock 1996). In addition, most stream research on crayfish has been
conducted in systems with primary gravel and/or cobble substrate (Momot 1995,
Whitledge and Rabeni 1997, Evans-White et al. 2003); no studies have been conducted
in low-gradient sandy streams. Biota in these systems rely heavily on CWD for
available stable habitat, but it is unknown if CWD provides a comparable level of
variation in suitable habitat and refuges against predation as structurally diverse upland
streams containing gravel-cobble substrates (Huryn and Wallace 1987, Mitchell and
Smock 1991). The objective of Chapter 5 was to assess the effect of CWD abundance
on crayfish density, biomass and production. In addition, Chapter 5 describes the
5
influence of variation in CWD and benthic particulate organic matter abundance on
crayfish diet and trophic position in the food web.
6
1.1 LITERATURE CITED
Angradi, T. R. 1999. Fine sediment and macroinvertebrate assemblages in Appalachian
streams: a field experiment with biomonitoring applications. Journal of the North
American Benthological Society 18:49-66.
Burcher, C. L., H. M. Valett, and E. F. Benfield. 2007. The land-cover cascade:
relationships coupling land and water. Ecology 88:228-242.
Contreras-Balderas, S. and M. de Lourdes Lozano-Vilano. 1996. Extinction of most
Sandia and Potosi valleys (Nuevo Leon, Mexico) endemic pupfishes, crayfishes
and snails. Ichthyological Explorations of Freshwaters 7:33-40.
Cordone, A. J. and D. W. Kelly. 1961. The influence of inorganic sediment on the
aquatic life of streams. California Fish and Game 47:189-228.
Creed, R. P. and J. M. Reed. 2004. Ecosystem engineering by crayfish in a
headwater stream community. Journal of the North American
Benthological Society 23:224-236.
Entrekin, S. A., J. L. Tank, E. J. Rosi-Marshall, T. J. Hoellein, and G. A. Lamberti. 2009.
Response of secondary production by macroinvertebrates to large wood addition
in three Michigan streams. Freshwater Biology 54:1741-1758.
Evans-White, M. A., W. K. Dodds, and M. R. Whiles. 2003. Ecosystem significance of
crayfishes and stonerollers in a prairie stream: functional differences between co-
occurring omnivores. Journal of the North American Benthological Society
22:423-441.
7
Helms, B. S. and R. P. Creed. 2005. The effects of 2 coexisting crayfish on an
Appalachian river community. Journal of the North American Benthological
Society 24:113-122.
Huryn, A. D. and J. B. Wallace. 1987. Production and litter processing by crayfish in an
Appalachian mountain stream. Freshwater Biology 18:277-286.
Hynes, H. B. N. 1975. The stream and its valley. Verhandlugen der Internationalen
Vereingigung f?r theoetische und angewandte Limnologie 19:1-15.
Jones, C. G., J. H. Lawton, and M. Shachak. 1994. Organisms as ecosystem
engineers. Oikos 69:373-386
Jones, C. G., J. H. Lawton, and N. Shachak. 1997. Positive and negative effects of
organisms as physical ecosystem engineers. Ecology 78:1946-1957
Junk, W. J., P. B. Bayley, and R. E. Sparks. 1989. The flood pulse concept in river-
floodplain systems. Pages 110-127 in D. P. Lodge (editor). Proceedings of the
International large River Symposium. Canadian Special Publications in Fisheries
and Aquatic Sciences.
Karr, J. R. 1991. Biological integrity: a long-neglected aspect of water resource
management. Ecological Applications 1:66-84.
Lenat, D. R., D. L. Penrose, K. W. Eagleson. 1981. Variable effects of sediment
addition on stream benthos. Hydrobiologia 79:187-194.
Lester, R. E. and W. Wright. 2009. Reintroducing wood to streams in agricultural
landscapes: changes in velocity profile, stage and erosion rates. River Research
and Applications 25:376-392.
8
Maloney, K. O. and J. W. Feminella. 2006. Evaluation of single- and multi-metric
benthic macroinvertebrate indicators of catchment disturbance over time at the
Fort Benning Military Installation, Georgia, USA. Ecological Indicators 6:469-484.
Maloney, K. O., J. W. Feminella, R. M. Mitchell, S. A. Miller, P. J. Mulholland, and J. N.
Houser. 2008. Landuse legacies and small streams: identifying relationships
between historical land use and contemporary stream conditions. Journal of the
North American Benthological Society 27:280-294.
Maloney, K. O., P. J. Mulholland, and J. W. Feminella. 2005. Influence of catchment-
scale military land use on stream physical and organic matter variables in small
Southeastern Plains catchments (USA). Environmental Management 35:677-
691.
Mitchell, D. J. and L. A. Smock. 1991. Distribution, life history and production of
crayfish in James River, Virginia. American Midland Naturalist 126:353-363.
Momot, W. T., H. Gowing, and P. D. Jones. 1978. The dynamics of crayfish and their
role in aquatic ecosystems. American Midland Naturalist 99:10-35.
Momot, W. T. 1995. Redefining the role of crayfish in aquatic ecosystems.
Reviews in Fisheries Science 3:33-63.
Newcombe, C.P., MacDonald, D.D., 1991. Effects of suspended sediments on
aquatic ecosystems. N. Am. J. Fish. Manage. 11:72?82.
Paul, M. J. and J. L. Meyer. 2001. Streams in the urban landscape. Annual Review of
Ecology and Systematics 32:333-365.
9
Poff, N. L. and J. V. Ward. 1989. Implications of streamflow variability and predictability
for lotic community structure: a regional analysis of streamflow patterns.
Canadian Journal of Fisheries and Aquatic Sciences 46:1805-1818.
Resh, V. H., A. V. Brown, A. P. Covich, M. E. Gurtz, H. W. Li, G. W. Minshall, S. R.
Reice, A. L. Sheldon, J. B. Wallace. 1988. The role of disturbance in stream
ecology. Journal of the North American Benthological Society 7:433-455.
Rose, S., and N. E. Peters. 2001. Effects of urbanization on stream flow in the Atlanta
area (Georgia, USA): a comparative hydrological approach. Hydrological
Processes 15:1441-1457.
Shields, F. D., S. S. Knight, N. Morin, and J. Blank. 2003. Response of fishes and
aquatic habitats to sand-bed stream restoration using large woody debris.
Hydrobiologia 494:251-257.
Stein, R. A. 1977. Selective predation, optimal foraging, and the predator-prey
interaction between fish and crayfish. Ecology 58:1237-1253.
Usio, N. and C. R. Townsend. 2004. Roles of crayfish: consequences of predation and
bioturbation for stream invertebrates. Ecology 85:807-822.
Wallace, J. B., J. W. Grubaugh, and M. R. Whiles. 1996. Influence of coarse woody
debris on stream habitat and invertebrate biodiversity. Pages 119-129 in J. W.
McMinn and D. A. Crossley (editors), Biodiversity and coarse woody debris in
southern forests (Proceedings of the workshop on coarse woody debris in
southern forest: effects on biodiversity). USDA Forest Service, Southern
Research Station, Asheville, North Carolina.
10
Wang, L., J. Lynons, P. Kanehl, and R. Bannerman. 2001. Impacts of urbanization on
stream habitat and fish across multiple spatial scales. Environmental
Management 28:255-266.
Waters, T. F. 1995. Sediment in waters: sources, biological effects, and control.
American Fisheries Society, Bethesda, Maryland.
Whitledge, G. W. and C. F. Rabeni. 1997. Energy sources and ecological role of
crayfish in an Ozark stream: insights from stable isotopes and gut analysis.
Canadian Journal of Fisheries and Aquatic Sciences 54:2555-2563.
Wood, P. J. and P. D. Armitage. 1997. Biological effects of fine sediment in the lotic
environment. Environmental Management 21:203-217.
11
2. INFLUENCE OF HYDROLOGIC VARIATION AND INSTREAM HABITAT
RESTORATION ON SANDY SOUTHEASTERN PLAINS STREAMS OF WESTERN
GEORGIA, USA
2.1 SUMMARY
Hydrologic variation (i.e., floods and droughts) has been shown to greatly
influence stream communities, but few studies have assessed varying hydrologic
regimes on instream restoration efforts. In small coastal plains streams disturbance
from uplands can increase sediment intrusion and reduce abundance of instream
coarse woody debris (CWD), in turn reducing habitat availability for benthic
macroinvertebrates. This impact can be exacerbated in wet years and thus may limit
the effectiveness of restoration efforts. We quantified macroinvertebrates and their
habitats in 8 streams for 2 y before and 3 y after artificial addition of CWD (4 restored, 4
unrestored), to assess efficacy of CWD additions as a restoration tool to increase bed
stability and increase macroinvertebrate habitat, at the Fort Benning Military Installation,
GA. CWD additions had an extremely limited effect on increasing most
macroinvertebrate measures. For example, relative to pre-restoration levels, density
and % of EPT taxa increased in restored streams during winter, and did not change in
unrestored streams; however, these and most other metrics did not differ between
restored and unrestored streams in other seasons. We suspect that restoration efficacy
was reduced in most streams because of extreme hydrologic conditions during the
12
post-restoration period the effect of high discharge on burial of CWD additions in these
unstable stream beds. While few positive increases were observed in relation to CWD
additions, some changes in metrics in unrestored streams compared to restored
streams during the post-restoration period. Nonmetric multidimensional scaling
ordinations showed shifts in the overall assemblage structure in both restored and
unrestored streams in some seasons, with shifts being greater in unrestored streams
than restored streams. These data suggest that the CWD additions had a dampening
effect on high hydrologic disturbance during the post-restoration period, and that long-
term monitoring of instream restoration efforts may be necessary to assess the overall
effectiveness of such efforts in streams exposed to highly variable hydrologic
conditions.
2.2 INTRODUCTION
The hydrologic regime is a ?master variable? exerting a strong governing force on
physical, chemical, and biological attributes in streams. Therefore, alterations to these
regimes, either by catchment-scale disturbance by humans or natural flooding events
can have large ecosystem-level effects (Resh et al. 1988, Poff and Ward 1989, Paul
and Meyer 2001, Rose and Peters 2001, Maloney et al. 2006). For example, increased
runoff from catchment disturbance increases transport of suspended sediments and
solute concentrations, which, in turn, influences stream communities (Paul and Meyer
2001, Swank et al. 2001, Maloney et al. 2006). Additionally, floods can directly affect
stream communities by altering instream flow conditions, such as near-bed turbulence
regimes, or increase scouring of stream substrates (Carling 1992, Bennison and Davis
13
1992). Often the above factors act synergistically, and when they occur together,
stream community impacts may be even greater.
Instream coarse woody debris (CWD) additions often are used in stream
restoration projects to restore instream habitat. Interest in CWD additions as a
restoration tool stems from its importance in organic matter storage and stable habitat
structure in streams (Bilby and Likens 1985, Harmon et al. 1986, Benke and Wallace
1990, Wallace et al. 1995). It has been suggested that re-establishment of CWD levels
in streams may help to restore them to a desired pre-disturbance condition more quickly
then that of natural processes (Grippel and White 2000, Hrodeny and Sutton 2008).
Much CWD restoration work has been conducted as 1- or 2-y experiments
(Smock et al. 1989, Wallace et al. 1995, Hrodey et al. 2008), yielding little information
on long-term success or the influence of varying hydrologic regimes on restoration
efforts. Tracking restoration efforts over longer time periods allows for the bracketing of
a reasonable amount of hydrologic variation that may influence the restoration efficacy.
The purpose of our study was to assess the influence of highly variable hydrologic
conditions (i.e., as extreme wet years and high discharge) on the efficacy of instream
habitat restoration in low-gradient sandy-bottom streams, in the form of artificial CWD
additions. Specifically, we examined 1) if artificial CWD additions altered the benthic
macroinvertebrate assemblages and their habitats in restored (vs. unrestored) strems
over a 3-y post-restoration period, and 2) the degree to which high hydrological variation
in the post-restoration period influence the effectiveness of CWD additions on benthic
assemblages and habitats in the restored streams.
14
2.3 METHODS
2.3.1 Study site
The study was conducted at the Fort Benning Military Installation (FBMI), in west-
central Georgia, USA. FBMI occurs in the Southeastern Plains Level-III ecoregion
(Ormernik 1987), with a humid and mild climate and year-round precipitation (mean =
105 cm/y), encompassing an area of 735 km
2
. The predominant land use is associated
with military training and includes dismounted infantry, tracked vehicle maneuvers (i.e.,
tanks), heavy weapons usage, and airborne training drop zones (USAIC 2001, Dale et
al. 2002). In addition to land use associated with military training activities, forestry
practices at FBMI includes selective timber harvesting and controlled burning. Much of
the forestry practices are related to restoration of longleaf pine (Pinus palustris) forest
and red-cockaded woodpecker (Picoides borealis) populations (Noss 1989, Dale et al.
2002). Upland vegetation in catchments consists of longleaf pine (Pinus palustris) and
loblolly pine (P. taeda), with some hickories (Carya spp.), flowering dogwood (Cornus
florida), and oaks (Quercus spp.), whereas the riparian vegetation was dominated by
mesic hardwoods, sweetbay magnolia (Magnolia virginiana), water oak (Q. nigra),
white oak (Q. alba), yellow poplar (Liriodendron tulipifera), red maple (Acer rubrum),
black gum (Nyssa sylvatica), and sweet gum (Liquidambar styraciflua) (Cavalcanti
2004). The study streams have received much attention from previous research,
focused mostly on effects of landscape-scale disturbance on instream water quality,
benthic community, and ecosystem responses (Houser et al. 2005, 2006, Maloney et al.
2005, 2006, Bhat et al. 2006, Maloney and Feminella 2006). Briefly, these studies have
shown a strong linkage between upland disturbance and instream environmental
15
conditions, including decreased CWD abundance (Houser et al. 2005, Maloney et al.
2006, Maloney and Feminella 2006). Collectively, previous research work has
suggested that loss of instream CWD from disturbance may have a significant impact
on instream habitat conditions and associated biota, and that the study streams are
good candidates for quantifying the influence of in stream restoration (as CWD
additions) on benthic communities.
2.3.2 Experimental design
Streams in 8 catchments were selected (Table 2.1); study streams were small
(1
st
or 2
nd
order) and usually low gradient, with primarily sand, silt, and clay substrates in
the active channel. Additionally streams had high riparian shading typical of other small
Southeastern Plains streams (Felley 1992). Study streams showed a wide baseline
range of CWD abundance, from ~3 to 12% of areal coverage of stream bottom and
mean stream gradient from 0.83 to 5.1% (Table 2.1). CWD data was converted to
planar area (m
2
of CWD per m
2
of stream bed) by multiplying the CWD diameter by
length and then dividing by the area of stream bottom sampled for each transect, and
then converted to % areal coverage of stream bottom (Maloney et al. 2005).
The study was divided into 2 phases. Phase I (pre-restoration) involved
quantifying baseline biotic and abiotic conditions from 8 streams (BC1, BC2, HB, SB2,
SB3, SB4, KM1, LPK) spanning a range of upland catchment disturbance level from
undisturbed to moderately to highly disturbed, as indicated by the % of the catchment
occurring as bare ground and road cover (Table 2.1; Maloney et al. 2005). Phase II
(post-restoration) involved a 2-y study of the above 8 streams in which 4 catchments
16
(SB2, SB3, LPK, KM1) received instream CWD additions (restored streams) and
streams in the 4 remaining catchments (BC1, BC2, HB, SB4) were used as controls
(unrestored streams). Selected riparian trees were felled (N. sylvatica in KM1, SB2,
SB3, and Q. alba in LPK) and cut into 1-2 m long sections (~10 cm diam) in August
2003, and left on the ground until deployment in the stream. CWD additions involved
deploying 10 to 15 woody debris dams (~10 m apart) over a 100- to150-m reach in
November 2003. Individual debris dams consisted of 3 logs placed in a Z-shaped
pattern anchored into the streambed by rebar (Roberts et al. 2006). These
configurations were done to allow water flow around debris dams during baseflow rather
than impounding sections upstream of debris dams. Debris dams traditionally consist of
small and large CWD, so we focused on adding larger piece of wood that would
accumulate natural smaller wood pieces over time.
During the 1st year of phase-II we observed that much of the CWD additions
became buried in 2 of the 4 treatments streams (SB3 and LPK). Thus, we augmented
initial CWD addition in these 2 streams in November 2004 to help compensate for these
losses. Augmentations consisted adding 10 new debris dams in SB3 and LPK in
between debris dams deployed in 2003, such that debris dams occurred every 5 m in
these 2 streams.
2.3.3 Benthic microhabitat and organic matter sampling
Stream discharge (velocity-area method, Gore 1996) was estimated seasonally
to assess differences in hydrologic conditions over the study. To assess the influence of
CWD additions on reach-scale streambed stability, we established cross-stream
17
transects (4?5 per stream) and measured streambed height at fixed sampling points
along each transect. Transects were established ~15 m apart throughout the study
reach (see Ray and Megahan 1979, Ziser 1985 for method). Stability was quantified
seasonally both 1 y prior to restoration and 3 y after restoration (November 2002
through September 2006). Using this method, small changes in mean bed height over
time reflected a stable bed (i.e., low rates of sediment accretion or scour) whereas large
changes reflected an unstable bed. A suite of instream physicochemical parameters
was sampled seasonally (winter, spring, summer), including 3 current velocity
measurements (Marsh-McBirney Flowmeter, Model 2000) at 3 set locations and mean
stream channel width and depth (5 measurements per cross-stream transect), to assess
the influence of CWD additions on microhabitat conditions.
Natural CWD abundance (woody debris > 2.5 cm in diameter) and benthic
particulate organic matter (%BPOM, particles < 2.5 cm in diameter) was quantified
during pre- and post-restoration in each stream, to assess effects of instream CWD
addition on organic matter retention. CWD was quantified annually, as surface of
woody per surface area of stream bed, during spring 2002, 2003, and 2005 along 15
cross-stream transects (~5 m apart) (Maloney et al. 2005), whereas %BPOM was
assessed seasonally by taking 6 core (2.5 cm diam) samples from the upper 10 cm of
substrate at the same location as current velocity (n = 18 %BPOM
samples/stream/date), collected randomly from the center of the channel (n = 3) and the
outer 1/3 of the channel (n = 3). In the laboratory, %BPOM from core samples was
quantified as ash-free dry mass (AFDM), where samples were dried at 80?C to a
18
constant mass (48?72 h), desiccated and weighed, combusted at 550?C in a muffle
furnace for 3h, and then desiccated and re-weighed for AFDM (Minshall 1996).
2.3.4 Benthic macroinvertebrate sampling
Benthic macroinvertebrates were sampled seasonally (winter, spring, summer) in
treatment and control streams both in the pre- and post-restoration period using a
combination of 1) quantitative Hester-Dendy (HD) artificial substrate multiplate samplers
(Rinella and Feminella 2005), and 2) semiquantitative multi-habitat net samples
(Maloney and Feminella 2006). Twelve HDs were used per stream (total area = 1.12
m
2
) on each sampling date in 4 run microhabitats (3 HDs per run), which were
incubated for 6 to 8 wk to allow macroinvertebrate colonization. We used HDs to
simulate wood surfaces, and previous research has shown that HDs are a good
surrogate for sampling wood habitats in coastal plains streams (Rinella and Feminella
2005). Multi-habitat sampling was conducted using a kick-net (250 ?m mesh) with
samples collected from general benthic macroinvertebrate habitats (e.g., runs, debris
dams, and root wads). We standardized kick-nets to a known area (~1 m
2
) and time (~1
min) to increase sampling precision, and also to supplement HD samples to better
characterize richness and % composition (Maloney and Feminella 2005). Benthic
samples were field-preserved with 95% ethanol, returned to the laboratory. There,
samples were sieved (125 ?m mesh) to remove leaf fragments and small sticks, and the
remaining materials sorted for 30 min to remove all large macroinvertebrates (>2mm
length); the residue was then poured through graded sieves (2 mm - 125 ?m mesh) to
remove all large debris. The entire residue material was sorted for HD samples,
19
whereas we subsampled kick-net residual material (removing at least 200 organisms
per subsample, see Vinson and Hawkins 1996) from the elutriate. Macroinvertebrates
were identified to the lowest possible taxonomic level, usually genus, using keys in
Merritt and Cummins (1996), Wiggins (1996) and Epler (2001).
For each stream we estimated macroinvertebrate density, biomass, Shannon
diversity (H?), and species richness for the entire macroinvertebrate assemblage.
Biomass was determined by measuring length of animals (nearest mm) and converted
length into AFDM using length-mass equations in Benke et al. (1999). Additional
macroinvertebrate compositional measures, included Ephemeroptera, Trichoptera, and
Plecoptera (EPT) density, Chironomidae richness (Chiro richness), and % of the
assemblage as chironomids (%Chiro) and EPT (%EPT). Previous research has
suggested that proportions of macroinvertebrate functional feeding groups, such as
shredders and scrapers, are greatly influenced by CWD abundance (Wallace et al.
1995). Thus, we also included %Shredders, %Scrapers, %Collectors, %Filterers, and
%Predators in our analysis of assemblage composition.
2.3.5 Data analysis
Benthic macroinvertebrate response variables were analyzed by season because
previous research in the study streams showed high seasonality in assemblages
(Maloney and Feminella 2006). A repeated-measures ANOVA was used to detect the
main effects of treatment (restored vs. unrestored streams), period (before vs. after
CWD additions), and a treatment-period interaction on macroinvertebrate measures
using SAS PROC MIXED (8.0, SAS Institute, 2000 Cary, North Carolina). In this
20
analysis, treatment and period represented fixed effects and stream was the repeated
factor. A significant period effect indicated a difference between pre- and post-
restoration, whereas a significant treatment effect indicated response variable differed
between treatments. However, both main effects do not discern whether the difference
was related to CWD additions or natural differences; rather, a significant treatment-
period interaction indicated that CWD additions affected macroinvertebrate measures
differently between treatments before and after additions, which was the main contrast
of interest. To test the influence of CWD additions we ran a 1-way ANOVA on
macroinvertebrate measures that showed significant treatment and period effects.
Additionally, we examined the potential effects of hydrologic variation (with precipitation
as a surrogate measure for discharge) on macroinvertebrate measures. This procedure
was done by performing a 1-way ANOVA on macroinvertebrate measures showing
significant period effects. One-way ANOVA was used to determine the effect of CWD
additions on habitat and %BPOM for individual streams. To satisfy conditions of
normality, count data were square-root transformed, percentage data were arcsine-
square-root transformed, and biomass and density were log-transformed (Zar 1999).
An ? level of 0.05 was used for all significance testing.
We also used nonmetric multidimensional scaling (NMS, McCune and Grace,
2002) to examine yearly macroinvertebrate assemblage similarity by season within and
among restored and unrestored streams. NMS is an indirect gradient analysis
technique that uses pairwise dissimilarity (Bray-Curtis distance) matrices to estimate
stream position in species space (Jongman et al. 1995). Relative abundance of benthic
macroinvertebrate data was used for the NMS analysis. Rare taxa were removed to
21
reduce their influence on ordinations (< 10% of samples) (Cao and Larsen 2001) prior to
ordinations, using PC-ORD (MjM Software Design, Gleneden Beach, Oregon). NMS
ordination scores were then regressed against independent instream habitat variables
to determine which variables were related to macroinvertebrate assemblages in
restored and unrestored streams. Additionally, to examine temporal shifts in
assemblages attributable to restorations and/or constrasting hydrological regimes we
compared mean vector length of faunal shifts in 2-dimensional space between the first
year of the study (2001, Summer and Winter; 2002, Spring) and each successive year,
by season. We used Pythagorean?s theorem to calculate the mean Euclidean distance
each assemblage shifted over the study. Finally, we compared among mean vector
length of restored vs. unrestored streams using 1-way ANOVA and, if appropriate,
Tukey?s post-hoc test to determine where differences among means occurred.
2.4 RESULTS
2.4.1 Extent of CWD additions
CWD additions during 2003 increased the areal coverage of instream CWD from
3.79 to 6.90% LPK (82% increase), 3.70 to 8.89% in SB3 (140%), 7.30 to 11.62% in
SB2 (59%), and 8.60 to 12.09% in KM1 (40%; Fig. 2.1). Augmentation of CWD during
2004 increased areal coverage of submerged CWD from 3.79 to 10.21% in LPK (169%
increase) and 3.70 to 13.46% in SB3 (264%; Fig. 2.1).
22
2.4.2 Precipitation and Discharge
Precipitation and stream discharge differed greatly over the 5-y study, ranging
from below-average to average rainfall leading up to the restoration (1999-2002) to
higher than average rainfall post-restoration (2003-2005; Fig. 2.2A). This contrast
between periods was greatest during summer with 2003, 2004 and 2005 being the 5
th
,
4
th
, and 2
nd
wettest summers over a 56-y period of record, respectively (Fig. 2.2B). No
sampling occurred during summer 2003, so the increase in summer rainfall in 2003 (cf.
1999-2002; Fig. 2.2B) did not influence macroinvertebrate sampling during the pre-
restoration period. This large difference in precipitation over the study was evident in
high variation discharge between the pre- and post-restoration periods: mean summer
discharge was significantly higher in the post- (vs. pre-) restoration period in all streams
(Table 2.2, Fig. 2.3). Similar to discharge, mean summer depth showed significant
increases in both restored and unrestored streams in the post-restoration period (Table
2.2, Fig. 2.4).
2.4.3 CWD, %BPOM and Streambed Variability
Burial of the debris dams was substantial in the first 2 y following restoration,
ranging from ~30% in KM1 to 75% in SB3. The source of sediment in SB2, SB3, LPK
likely resulted from a combination of instream and upland sediments.
Overall, %BPOM did not consistently change in either restored or unrestored
streams, and little difference occurred between the pre- and post-restoration period.
%BPOM showed no increase during winter or spring for either restored or unrestored
streams, with increased %BPOM occurring in restored streams only during summer,
23
and only in 2 of 4 restored streams (SB2: F = 9.09, p < 0.0001; KM1: F = 8.43, p <
0.0001). %BPOM significantly decreased in only 2 unrestored streams between pre-
vs. post-restoration (BC2 in winter: F = 7.69, p < 0.0001; HB in spring: F = 3.39, p =
0.029).
CWD additions appeared to have some effect on mean streambed height
following restoration, as bed height either increased (SB2, SB3; F = 9.90, p = 0.009, F =
26.16, p < 0.0001, respectively) or decreased (LPK; F = 62.71, p < 0.0001) during the
post-restoration (vs. pre-restoration) period. Only 1 unrestored stream (SB4, F = 5.50, p
= 0.037) showed a significant difference (increase) between pre- and post-restoration.
CWD additions appeared to promote accretion in 2 of the 4 restored streams (SB3,
SB2) after restoration, which also was evident by the high degree of debris dam burial
observed in the first year of post-restoration.
2.4.4 Benthic macroinvertebrates
Increases in precipitation and associated discharge appeared to have their
greatest influence on benthic assemblages in summer, the season with the highest
number of significant period effects. Macroinvertebrate metrics showing the greatest
response to period effects were total biomass, density, richness, and %Filterers (Table
2.3), all of which were lower in both restored and unrestored streams during the post-
(vs. pre-) restoration period (Fig. 2.5).
Several macroinvertebrate metrics showed treatment differences between
restored and unrestored streams, when comparing before and after restoration. % EPT
and EPT density both increased in restored streams during winter, and were significant
24
for both Period effects and Treatment-Period interactions (Table 3). EPT density
significantly increased (by ~3 fold) from pre-restoration levels in restored streams
whereas unrestored streams did not change (Fig. 2.6A), as did % EPT (Fig. 2.6B). EPT
density and % EPT, % Filterers and % Collectors in spring also showed a significant
Treatment-Period interaction (Table 3). However, unlike the EPT and % Collectors
metrics, % Filterers decreased in unrestored streams but not in restored streams (Fig.
2.6C). Last, % Scrapers and Chironomidae richness in summer showed a Treatment-
Period interaction (Tables 2.3) and, similar to the functional feeding group metrics in
spring, % Scrapers and Chironomidae richness significantly decreased in unrestored
streams but not in restored streams (Figs. 2.6E and F, respectively).
NMS showed a strong relationship between altered hydrologic conditions and
benthic macroinvertebrate assemblages during summer and winter over the study. For
summer assemblages, NMS axes 1 and 3 accounted for most of the macroinvertebrate
assemblage variation (R
2
= 0.35 and 0.25, respectively; Fig. 2.7A). When axes 1 and 3
were regressed against instream hydrologic and habitat variables, axis 1 was best
explained by discharge (R
2
adj
= 0.27, p = 0.001), and axis 3 by depth (R
2
adj
= 0.30, p <
0.0001). For winter assemblages, axes 1 and 3 accounted for most of the variation (R
2
= 0.32 and 0.26, respectively; Fig. 2.7B). When axes 1 and 3 were regressed against
instream hydrologic and habitat variables, axis 1 was best explained by discharge and
depth (R
2
adj
= 0.25, p = 0.002), and axis 3 was best explained by depth and current
velocity (R
2
adj
= 0.13, p = 0.042). For spring assemblages, NMS showed no strong
relationships between changing hydrology and benthic assemblages.
25
The degree of shifts in assemblages in the post-restoration period from 2001 (1
st
pre-restoration mean vector length) was higher in unrestored streams than restored
streams during summer 2005 (F = 13.10, p = 0.011) and 2006 (F = 6.78, p = 0.040)
(Fig. 2.8A). In contrast, winter mean vector length did not differ from 2002 assemblages
in 2005, but did significantly differ in 2006 (F =9.89, p = 0.02) (Fig. 2.8B). Spring
assemblages in restored or unrestored streams did not significantly shift during the
study (p > 0.05).
2.5 DISCUSSION
2.5.1 Influence of hydrologic variation on CWD additions
High variable hydrologic regimes may affect instream restoration efforts by
increasing sediment inputs and destabilizing instream habitat under varying flow
conditions, thus potentially reducing restoration efficacy. Stream and river restoration
projects often do little to assess effectiveness of a given project during post-restoration
(NRC 1992, Bernhardt et al. 2005); however, by tracking restoration efforts over a
longer time period researchers are more likely to gauge overall success of a given
project in association with greater variation in hydrologic regimes. The purpose of most
restoration projects is to restore the natural range of ecosystem composition, structure,
or dynamics (Falk 1990, Allen et al. 2002), but if a project is not monitored long enough
to bracket a reasonable magnitude of variation in hydrologic conditions then they may
not be able to judge the true outcome of the restoration. Varying hydrology likely will
influence instream habitat, such as coarse woody debris (CWD), by displacing it down
26
stream or by burial (Shields et al. 2003), and efforts to restore such habitats need to be
monitored over a long term to assess success.
CWD is an important structural and functional component of sandy bottom
streams in the Southeastern US (Benke and Wallace 1990, Benke et al. 2001). Thus,
CWD additions within impaired CWD-poor streams have been considered a viable
restoration method in prior research (Grippel and White 2000, Webb and Erskine 2003,
Lester et al. 2007). However, our results suggest that the efficacy of CWD additions on
benthic macroinvertebrates and habitat can be highly variable both temporally and
spatially, whose influence may depend on environmental conditions, particularly during
hydrologically extreme periods.
Changes to the hydrologic regime appear to have greatly influenced the
macroinvertebrate assemblage, especially during the summer. Macroinvertebrate
density and biomass was significantly decreased in both restored and control streams,
which is counter to that observed by others (Smock et al. 1989, Smock et al. 1992,
Wallace et al. 1995). Much research over the last 20 y has demonstrated the
importance of flow regime on macroinvertebrate assemblages (Resh et al. 1988, Poff
and Ward 1989), often manifested by substantial changes in near-bed hydrology
(Bennison and Davis 1992, Townsend et al. 1997, Nelson and Lieberman 2002). Our
results showing a strong Period effect for density and biomass suggests a plausible link
to changes in hydrologic regime in these streams over the study. Others have found
that increased discharge in the form of floods can negatively affect macroinvertebrate
density and biomass, as well as overall taxa richness (Suren and Jowett, 2006).
Dramatic decreases in density and biomass as well as the shift in macroinvertebrate
27
assemblages in general would explain why the influence of CWD additions in restored
streams was so limited in our experiment.
2.5.2 Hydrologic and CWD addition influence on instream habitat and BPOM
Several studies have shown that following CWD additions, overall or relative
(microhabitat) stream depth and volume increase in relation to CWD structures (Wallace
et al. 1995, Shields et al. 2003). Wallace et al. (1995) found that the deposition area
was associated with an increase in organic matter retention, which, in turn, increased
basal resource (detritus) abundance for benthic macroinvertebrates. Our results did not
show this pattern as depths in both restored and unrestored streams were higher in the
post vs. pre-restoration period during the summer baseflow period. Rather, increases in
depth in all streams likely resulted because of increased precipitation and discharge
during the post- (vs. pre-) restoration period. In related work from the study streams,
Roberts et al. (2007) reported a decrease in reach-scale velocity in restored streams
within 1 mo after CWD additions; in contrast, our findings indicated that this difference
was not sustained over the longer term, because of possibly changing discharge
conditions during the post-restoration period. % BPOM showed no difference between
pre- and post-restoration, and likewise there was no difference between restored or
unrestored streams. This may have resulted from BPOM being buried at greater depths
then our sampling was done, were taken at, suggesting which would suggest our
method was inadequate to sample BPOM. Additionally, our BPOM values represent a
reach-level %BPOMmeasure as our samples were not specifically taken at either
28
natural or artificial debris dams. Thus, it is unclear from our data if CWD additions had
a substantial influence of %BPOM.
Instream CWD has been widely associated with increased inorganic and organic
matter (Baillie and Davies 2002), and CWD additions have reportedly increased
abundance of sediment and particulate matter retention (Wallace et al. 1995, Laitung et
al. 2002, Pretty and Dobson 2004), both indicating the importance of CWD in stabilizing
stream beds and entraining organic matter. Our results on bed instability did not
support this pattern. One reason for the lack of an effect of CWD additions on bed
stability was the high degree of burial occurring after CWD additions in 3 of the 4
restored streams (LPK, SB2, SB3). In 2 of these streams where CWD was augmented
in 2004 (LPK, SB3) most of these additional logs also became buried by May 2006
sampling (personal observations). Like streambed stability, no differences were
observed in %BPOM between restored or unrestored streams. Previous research in the
study streams found that upland disturbance had a substantial influence on instream
CWD abundance (Maloney et al. 2005). Previous research of the 4 streams that had a
significant bed height change in the current study showed that they occur in highly
disturbed watersheds (Maloney and Feminella 2005), and this fact along with changing
hydrologic conditions between pre- and post-restoration periods may have contributed
to these differences. For CWD additions to have a positive influence on streambed
stability, increasing %BPOM, and reducing CWD burial under the highly variable
hydrologic conditions observed during the study, upstream sediment both in-channel
and from disturbed upland sources will likely have to be reduced. Additionally, a
relatively small restored reach in larger sediment-disturbed stream appears to have little
29
positive effect, especially during wet year. A greater restoration effort throughout the
reach may help alleviate the influence of hydrologic variability and reduce sediment
movement throughout the channel, even in highly disturbed watersheds.
2.5.3 Influence of CWD additions on dampening hydrologic variation
Similar to abiotic factors, most benthic macroinvertebrate metrics showed
equivocal response to CWD additions. The transient influence on fishes of CWD
additions has been reported elsewhere (Shields et al. 2003) and suggests that the sole
use of CWD in restoration practices only may temporarily offset stream impairment.
Shields et al. (2003) reported that CWD additions failed because of high discharge
events and within 2 y after restoration, with ~ 30% of additions losing wood to
downstream displacement. In our study, CWD habitat loss did not occur because of
downstream displacement but rather from burial. Winter was the only season in which a
positive increase in benthic macroinvertebrate metrics was observed in the restored
streams compared to unrestored streams, and this pattern was limited to EPT density
and %EPT. Similar increases did not occur in other seasons and may have become
dampened from increased precipitation and discharge during the post-restoration
period. Even though most metrics did not show an increase in the restored relative to
the unrestored streams, many metrics showed a decrease in unrestored relative to
restored streams.
NMS showed a strong shift in assemblage structure in both restored and
unrestored streams in relation to changing discharge and increasing stream depth;
however, restored streams showed a comparatively smaller shift from pre-restoration
30
conditions compared to the unrestored streams; this result suggested that CWD
additions buffered impacts of the altered hydrologic regime. In this context, efficacy of
CWD additions in the restored streams was dampened by the high degree of inorganic
sediment, but the presence of CWD additions in restored streams, even in a largely
buried state, appeared to enhance recovery of benthic macroinvertebrate assemblages.
Longer-term studies in these streams are being done to quantify the degree of benthic
recovery from hydrologic disturbance and assemblage enhancement to levels
consistently exceeding pre-restoration conditions.
2.6 CONCLUSION
A successful restoration project must not only ameliorate impairment in the short
term, but also exhibit long-term and self-sustaining effects (Palmer and Allen 2006).
Our results suggest that debris dam additions to streams channels, while somewhat
effective over the short term, may not be a solution for restoring stream conditions,
especially in sand-bottomed channels. Additionally, our results suggest the importance
of understanding the influence of background environmental variability, such as strongly
contrasting hydrology before, during, and after restoration projects. In addition to the
influence of current conditions, an understanding land use legacies in watersheds
where restoration efforts will be implemented may help guide the restoration process.
Previous work in the current watersheds has shown a significant influence of legacy
effects on instream conditions of both biotic and abiotic factors (Maloney et al. 2008). A
more productive and self-sustained restoration practice for small headwater streams
may be the r-vegetation of riparian zones and ephemeral drains as well as increase the
31
restoration reach within the stream channel itself. This broader approach to restoration
may decrease the movement of new sediment into the perennial channel by both
stabilizing upland soils and instream channel conditions, thus reducing the influence of
hydrology on benthic communities.
32
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43
Table 2.1. Locations and characteristics of study streams. All values measured in
this table from Maloney et al. (2005) and Maloney and Feminella (2006).
44
Stream Stream
code
UTM Military land
use
Drainage
area (km
2
)
Mean stream
slope (%)
Disturbance
intensity
(% catchment)
Pre-restoration
CWD
(% areal
coverage)
Restored
Little Pine Knot LPK 0719223N Heavy 0.33 5.10 11.26 3.79
Tributary
3585421E Machinery
Sally Branch SB3 0716673N Infantry/ 0.72 1.00 10.49 3.70
Tributary
3584684E Ranger
Sally Branch SB2 0716808N Heavy 1.23 2.31 8.12 7.30
Tributary
3584787E Machinery
Kings Mill Creek KM1 0720701N, Infantry/ 3.69 0.83 4.63 8.60
3600036E Ranger
Control
Sally Branch SB4 0716005N, Heavy 1.00 1.33 13.65 3.11
Tributary 3584889E Machinery
Bonham BC1 0710893N, Infantry/ 2.10 1.67 10.46 12.62
Tributary 3588286E Ranger
Bonham BC2 0710627N, Infantry/ 0.75 2.67 3.15 8.92
Tributary 3588976E Ranger
Hollis Branch HB 0717848N Infantry/ 2.15 2.00 6.62 6.34
3583123E Ranger
45
Table 2.2. Summary of instream physical variables for restored and unrestored streams, by season.
Variable Seasonal mean One-way ANOVA
Summer Winter Spring Summer Winter Spring
Pre- Post- Pre- Post- Pre- Post- F p F p F p
Velocity (m/s)
Restored 0.117 0.210 0.129 0.128 0.125 0.157 *** *** ***
Unrestored 0.074 0.105 0.114 0.114 0.098 0.113 *** *** ***
Depth (m)
Restored 0.063 0.111 0.125 0.139 0.086 0.115 10.36, 0.005 *** ***
Unrestored 0.083 0.139 0.135 0.169 0.109 0.164 5.67, 0.028 *** ***
Width (m)
Restored 1.275 1.217 1.535 1.058 1.399 1.028 *** *** ***
Unrestored 1.072 1.218 1.743 0.964 1.290 1.080 *** 6.30, 0.022 ***
Discharge
(m
3
/s)
Restored 0.005 0.129 0.010 0.204 0.011 0.215 8.16, 0.010 10.65, 0.004 10.29, 0.005
Unrestored 0.012 0.088 0.011 0.164 0.006 0.128 16.42, 0.001 26.40, <0.0001 8.27, 0.01
46
Table 2.3. F-values (p-values in parentheses) of repeated measures ANOVA (F
1,30
) on
compositional macroinvertebrate measures. TRT = restored or control streams, Period
= pre- and post-restoration. Boldface indicates values significant at p = 0.05.
47
Metric Season Treatment Period Treatment*Period
Winter
Biomass 2.52 (0.124) 0.38 (0.544) 1.43 (0.242)
Density 18.02 (0.0002) 0.49 (0.488) 0.95 (0.123)
H? 0.98 (0.330) 7.84 (0.009) 1.10 (0.302)
Taxa richness 0.87 (0.359) 0.00 (0.975) 1.52 (0.228)
EPT Density 4.67 (0.039) 4.16 (0.051) 5.47 (0.023)
% EPT 1.38 (0.249) 28.66 (<0.0001) 9.15 (0.005)
% Chiro 0.01 (0.921) 0.00 (0.990) 0.27 (0.645)
Chiro richness 0.57 (0.455) 1.67 (0.206) 1.99 (0.169)
% Predators 3.79 (0.061) 2.31 (0.139) 0.74 (0.395)
% Shredders 0.67 (0.418) 13.41( 0.001) 0.21 (0.648)
% Collectors 0.84 (0.367) 6.65 (0.015) 0.34 (0.565)
% Filterers 0.40 (0.530) 16.65 (0.0003) 0.20 (0.658)
% Scrapers 0.77 (0.389) 0.01 (0.916) 0.08 (0.780)
% Clingers 2.33 (0.138) 1.60 (0.216) 0.22 (0.640)
Spring
Biomass 3.26 (0.081) 10.80 (0.003) 2.37 (0.135)
Density 3.65 (0.066) 3.69 (0.065) 1.93 (0.175)
H? 3.08 (0.090) 1.52 (0.228) 0.62 (0.438)
Taxa richness 1.65 (0.209) 12.23 (0.002) 0.04 (0.847)
EPT Density 1.14 (0.294) 1.98 (0.170) 1.13 (0.297)
% EPT 1.95 (0.174) 0.73 (0.399) 0.95 (0.339)
% Chiro 1.11 (0.300) 4.90 (0.034) 2.15 (0.153)
Chiro richness 0.09 (0.767) 12.77 (0.001) 0.04 (0.840)
% Predators 0.07 (0.800) 0.06 (0.810) 1.62 (0.213)
% Shredders 2.37 (0.134) 10.97 (0.002) 1.21 (0.281)
% Collectors 3.15 (0.071) 0.90 (0.352) 13.55 (0.001)
% Filterers 0.05 (0.825) 0.08 (0.775) 7.63 (0.010)
% Scrapers 0.05 (0.819) 37.71 (<0.0001) 0.44 (0.514)
% Clingers 0.64 (0.430) 7.29 (0.011) 0.35 (0.560)
Summer
Biomass 0.97 (0.332) 25.70 (<0.0001) 0.07 (0.794)
Density 0.29 (0.596) 5.37 (0.028) 0.00 (0.968)
H? 0.63 (0.434) 2.18 (0.151) 0.34 (0.566)
Taxa richness 2.01 (0.166) 23.34 (<0.0001) 2.13 (0.155)
EPT Density 0.29 (0.596) 5.37 (0.028) 0.00 (0.968)
% EPT 1.19 (0.284) 5.50 (0.026) 0.24 (0.626)
% Chiro 1.55 (0.223) 0.01 (0.923) 6.17 (0.019)
Chiro richness 0.23 (0.636) 7.95 (0.008) 1.51 (0.229)
% Predators 0.40 (0.530) 0.48 (0.494) 1.10 (0.302)
% Shredders 0.58 (0.452) 5.82 (0.004) 0.01 (0.999)
% Collectors 0.65 (0.428) 3.91 (0.058) 0.01 (0.930)
% Filterers 1.30 (0.264) 15.10 (0.001) 0.27 (0.607)
% Scrapers 0.18 (0.677) 12.30 (0.001) 5.98 (0.021)
% Clingers 7.33 (0.011) 0.22 (0.640) 0.23 (0.632)
48
Figure 2.1. Relative abundance of in-stream coarse woody debris (CWD, as % of total
streambed cover), before (pre-restoration, spring 2003) and after debris dam additions
(fall 2003 and fall 2004 CWD additions) for the 4 restored streams. Restored streams
received debris dam additions in Oct-Nov 2003 and supplemental debris dams (SB3
and LPK) in Nov 2004.
49
BC1 BC2 SB4 HB SB2 KM1 LPK SB3
% CWD of Stream Bottom
0
2
4
6
8
10
12
14
16
Pre-restoration CWD abundance
Fall 2003 CWD additions
Fall 2004 CWD additions
Unrestored Restored
50
Figure 2.2. Precipitation data from Columbus, Georgia, for the period 1949?2006. Pre-
restoration sampling occurred in 2001, 2002, and 2003, whereas post-restoration period
occurred in 2004, 2005, and early 2006. Note that much of the post-restoration
sampling occurred in years that were among the wettest on record (late 2003, 2004,
and 2005). A = annual precipitation, B = summer precipitation.
51
1
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4
Increasing Annual Rainfall (cm)
0
20
40
60
80
100
120
140
160
180
200
1999
2000
2001
2006
2002
2004
2003
2005
A
Year (1949-2006)
1
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Increasing Summer Rainfall (cm)
0
10
20
30
40
50
60
70
80
1999
2000
2001
2004
2002
2003
2005
2006
B
52
Figure 2.3. Comparison of mean (+1 SE) baseflow discharge in restored (in
compartments SB3, SB2, KM1, LPK) (A) and unrestored streams (compartments BC1,
BC2, SB3, HB) (B) before (2001- 2003) and after restoration (2004, 2005, 2006).
Vertical dashed line on A shows approximate time of debris dam additions (Oct-Nov
2003). Note that much of the post-restoration sampling (2004, 2005) occurred during
conditions of substantially higher discharge than pre-restoration sampling (n = 24).
53
Disch
arge (
m
3
/sec.)
0.00
0.05
0.10
0.15
0.20
0.25
Year
2001-2003 2004 2005 2006
0.00
0.05
0.10
0.15
0.20
0.25
A
B
p<0.0001
p<0.0001
54
Figure 2.4. Mean (+1 SE) summer depth in restored and unrestored stream during the
pre- and post-restoration periods. * = p < 0.05.
55
SB2 SB3 KM1 LPK BC1 BC2 SB4 HB
Av
er
ag
e Dep
t
h
(m)
0.00
0.05
0.10
0.15
0.20
0.25
Pre-restoration
Post-restoration
*
*
*
*
*
*
Restored Unrestored
56
Figure 2.5. Average relative abundance and functional feeding groups of the benthic
macroinvertebrate assemblage that showed a significant Period effect during the
summer. A = biomass (restored, F = 14.47, p = 0.001; unrestored, F = 9.68, p = 0.006),
B = density (restored, F = 12.40, p = 0.002; unrestored, F = 13.73, p = 0.002), C =
species richness (restored, F = 5.37, p = 0.032; unrestored, F = 15.26, p = 0.001), D =
%Filterers (restored, F = 4.20, p = 0.053, unrestored, F = 7.68, p = 0.013) Error bars
are standard error. * = p < 0.05.
57
Biomass
(
m
g/
m
2
)
0
50
100
150
200
250
Pre-restoration
Post-restoration
Density
(no.
/m
2
)
0
500
1000
1500
2000
Restored Control
S
p
ec
i
e
s Ri
ch
n
e
s
s
0
10
20
30
40
50
60
Restored Control
%
Filter
ers
0
10
20
30
40
*
*
*
*
*
*
*
*
A
B
C
D
58
Figure 2.6. Mean (+1 SE) relative abundance and functional feeding groups of the
benthic macroinvertebrate assemblage that showed a significant Treatment?Period
effect. A = winter EPT density (restored, F = 10.27, p = 0.017; unrestored, F = 0.17, p =
0.685), B = winter %EPT (restored, F = 19.33, p < 0.0001; unrestored, F = 1.39, p =
0.225), C = spring %Filterers (restored, F = 1.58, p = 0.225; unrestored, F = 4.25, p =
0.050), D = spring %Collectors (restored, F = 1.18, p = 0.292, unrestored, F = 6.98, p =
0.017), E = summer %Scrapers (restored, F = 0.59, p = 0.45; unrestored, F = 7.11, p =
0.016), F = summer Chironomidae richness (restored, F = 1.08, p = 0.312; unrestored,
F = 12.03, p = 0.003). * = p < 0.05.
59
EPT
d
e
ns
i
ty (n
o.
/m2
)
0
50
100
150
200
250
Pre-restoration
Post-restoration
% EPT
0
5
10
15
20
25
%
F
il
t
erers
0
5
10
15
20
25
30
% C
o
llec
tors
0
10
20
30
40
50
Restored Control
% Scra
pers
0
2
4
6
8
Restored Control
Chi
r
ono
mida
e rich
ness
0
5
10
15
20
25
*
A B
C
D
E
F
*
*
*
*
*
60
Figure 2.7. Nonmetric multidimensional scaling (NMS) ordination results. Symbols
represent stream/year-specific macroinvertebrate scores. A.--- (summer: Circles: 2001,
inverted triangle: 2002, square: 2004, diamond: 2005, triangle: 2006). B.--- (winter:
Circles: 2002, inverted triangle: 2003, square: 2004, diamond: 2005, triangle: 2006). R
2
values represent the proportion of variation in the macroinvertebrate assemblage
similarity accounted for by each axis. Arrows on axes indicate direction of relationships
between hydrologic and habitat variables and NMS scores (see text for values). Axis
scores are raw values, stress level = 13.01 (summer) and 13.65 (winter), for the three-
dimension solution, with a final instability of 0.00001 after 151 iterations for summer,
and a final instability of 0.00001 after 67 iterations for winter.
61
Axis 1 (R
2
= 0.35)
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
Axis
3
(
R
2
=
0.2
5
)
-1.0
-0.5
0.0
0.5
1.0
1.5
2001
2002
2004
2005
2006
Discharge
De
pth
A
Axis 3 (
R
2
= 0.26)
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0 2002
2003
2004
2005
2006
Axis 1 (R
2
= 0.32)
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
Discharge, Depth
Depth
,
Fl
ow
B
62
Figure 2.8. Mean (+1 SD) vector length comparison between restored and unrestored
streams, with vector length calculated for each stream between the 1st year of pre-
restoration sampling (2001: summer, A; 2002: winter, B) and each subsequent year of
sampling. Differences between restored and unrestored streams are designated by
different letters using Tukey?s pairwise comparisons and treatments with the same letter
were not significantly different.
63
2002 2004 2005 2006
Mean v
ector length w
i
th 2001
0.0
0.5
1.0
1.5
2.0
2.5
Unrestored
Restored
a
a
a
a
a
b
a
b
2003 2004 2005 2006
M
ean v
ector length w
i
th
2002
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
a
a
a
a
a
a
a
b
A
B
64
3. MULTI-SCALE CONTROLS ON POPULATIONS OF THE CRAYFISH
PROCAMBARUS VERSUTUS (CAMBARIDAE) IN SANDY STREAMS OF WESTERN
GEORGIA, USA
3.1 SUMMARY
Landscape disturbance can structure benthic populations principally by altering
instream habitat conditions. We evaluated the effects of disturbance on populations of
the crayfish Procambarus versutus, from small sandy-bottom streams in western
Georgia, USA, through the direct influence of catchment disturbance on instream
habitat. We quantified crayfish and habitat variables from 8 streams across a gradient
of catchment disturbance. Catchment disturbance (as indicated by % of bare ground in
the catchment) was negatively correlated with several measures of instream habitat
quality, including relative abundance of coarse woody debris (CWD) and percent
benthic particulate organic matter (%BPOM) during spring and summer, and mean
stream depth. In turn, crayfish density was positively related to CWD and %BPOM
across most seasons, whereas crayfish biomass was correlated with CWD, %BPOM,
and discharge and depth. Catchment disturbance was a good predictor of crayfish
population density and biomass, and appeared to have a greater effect on individuals in
runs compared to pools. Pools showed little difference across streams in relation to
catchment disturbance; however, crayfish density and biomass decreased across
streams in relation to increasing catchment disturbance. These results suggest that
65
catchment level disturbance influences instream habitat which, in turn, directly influence
crayfish populations.
3.2 INTRODUCTION
Disturbance is an important driver of the structure of many stream communities
through its direct and indirect effects on instream habitat (Resh et al. 1988, Palmer et al.
1996). Dissimilar disturbance episodes affect communities differently, and these events
have been categorized into pulse, press, and ramp disturbance types (Lake 2000).
Pulse disturbances are intense short-term events, such as floods, which typically have a
distinct time frame. Press disturbances differs from pulse disturbances mainly in the
duration of the event, with press events (e.g., dams or channelization) arising quickly
like pulses, but continue influencing the system for a longer time frame. Finally, Ramp
disturbances arise over a longer time period, such as a drought or the incremental
spread of an exotic species, which have a pervasive influence on the system. Ramp
disturbances are similar to press disturbances in having long-term effects, but their
impact is more gradual and may not achieve an equilibrium state similar to presses
disturbance (Lake 2000). Landscape-scale disturbance, such as terrestrial vegetation
clearing in a catchment, typically is a ramp disturbance because it is usually
characterized by a gradual change from one predominant land use condition to another.
This change in land use gradually increases disturbance impact on a stream
ecosystem, unless a threshold is reached (King et al. 2005, Walsh et al. 2005).
Landuse changes may manifest their influence on streams through land-cover
cascades, which couple terrestrial disturbance to instream changes in physicochemical
66
conditions relevant to stream biota (Burcher et al. 2007). Landscape disturbance often
increases sediment entering streams, affecting instream habitat directly through burial
and indirectly biota by reducing available habitat for biota (Smock 1997, Maloney and
Feminella 2006).
Much research has documented the negative effects of sediment on instream
faunal composition and diversity (Cordone and Kelly 1961, Lenat et al. 1981, Wood and
Armitage 1997, Angradi 1999). Sedimentation from landscape disturbance can alter
benthic macroinvertebrates behavior (i.e., as increased drift), directly causing mortality
(Newcombe and MacDonald 1991, Waters 1995). An important component of sediment
impacts on stream habitat relates to sedimentation-induced reductions in abundance of
submerged coarse woody debris (CWD). In sandy-bottom streams, CWD is a primary
source of benthic habitat heterogeneity (Smock et al. 1989, Benke and Wallace 1990,
Smock and Gilinsky 1992, Maloney et al. 2005). In this context, through its negative
effects on CWD excessive sedimentation can reduce habitat quality and quantity for
macroinvertebrates (Schofield et al. 2004).
It has long been known that CWD can greatly influence nutrient retention and
cycling and biotic communities in streams (Cummins 1974, Bilby 1981, Bisson et al.
1987). High retention of organic matter as leaf litter by CWD presence can affect
structure and function of a full range of benthic organisms from bacteria to fish (Benke
et al. 1985, Smock et al. 1989, Hall et al. 2000, Shields et al. 2006). However,
compared to other benthic macroinvertebrates, little is known about how landscape
disturbance and it effects on CWD affects populations of freshwater crayfish, which are
67
ubiquitous in many streams and can dominate macroinvertebrate biomass (Momot et al.
1978, Huryn and Wallace 1987).
Crayfish constitute the bulk of benthic macroinvertebrate biomass in many
freshwater systems (Mason 1974, Momot and Gowing 1977, Momot et al. 1978, Momot
1995, Rabeni et al. 1995), and play a significant role in many aquatic ecosystems
(Webster and Patten 1979, Huryn and Wallace 1987, Hart 1992, Creed 1994). Crayfish
have the potential to exert a substantial effect on benthic macroinvertebrates in many
freshwater systems, due to there high biomass, polyphagous feeding, and large size
relative to other benthic macroinvertebrates (Lodge et al. 1994, Usio and Townsend
2004, Usio et al. 2009). Changes to crayfish populations due to catchment disturbance
may influence ecosystem function by reducing a crayfish?s influence on basal resources
and other benthic macroinvertebrates.
Previous research at the Fort Benning Military Installation (FMBI) in western
Georgia demonstrated that catchment disturbance was inversely correlated with
instream CWD abundance and substrate particle size, and positively correlated with
streambed instability (Maloney et al. 2005). In another study at FBMI,
macroinvertebrate richness and overall biotic integrity decreased with increasing
catchment disturbance, apparently because of degraded habitat (Maloney and
Feminella 2006). Therefore, these streams are excellent systems to determine the
effects of catchment-level disturbance on habitat stability and crayfish populations.
Because of the multifunctional role that crayfish play in aquatic systems (Helms and
Creed 2005), understanding the effects of upland disturbance and instream habitat loss
68
on crayfish populations can have important implications for the management of stream
ecosystems (Parkyn and Collier 2004, Schofield et al. 2004).
Our study was designed to explore the influence of catchment-scale disturbance
and instream habitat on the density, biomass, and size frequency of crayfish at FBMI,.
The objectives were to 1) relate instream habitat to landscape-scale factors, specifically
catchment-scale disturbance 2) investigate the relationships between instream habitat
and crayfish population measures, and 3) relate crayfish population measures to
catchment-scale disturbance to understand how well disturbance can predict and
potentially influence population level variables of crayfish, and 4) determine if crayfish
response to catchment-scale disturbance was similar to other benthic
macroinvertebrates.
3.3 METHODS
3.3.1 Study area
FBMI is in the Southeastern Plains Level-3 ecoregion (Omernik 1987) (area =
735 km
2
) has a humid and mild climate and year-round precipitation (mean = 105 cm/y).
The primary land use is military training and includes dismounted infantry, tracked-
vehicle maneuvers (i.e., tanks), heavy weapons usage, and airborne training drop
zones (USAIC 2001, Dale et al. 2002). Undisturbed upland vegetation consists
primarily of longleaf pine (Pinus palustris) and loblolly pine (P. taeda), with some
hickories (Carya spp.), flowering dogwood (Cornus florida), and oaks (Quercus spp.).
Riparian vegetation is largely intact (canopy cover often >90%, Maloney et al. 2005),
and is dominated by mesic hardwoods including sweetbay magnolia (Magnolia
69
virginiana), water oak (Q. nigra), yellow poplar (Liriodendron tulipifera), red maple (Acer
rubrum), black gum (Nyssa sylvatica) and sweet gum (Liquidambar styraciflua)
(Cavalcanti 2004).
Much of the landscape disturbance at FBMI is from military training-associated
use of heavy tracked vehicles, which disrupts vegetative cover and exposes underlying
soils to erosion (Dale et al. 2002). In addition, forestry practices such as thinning,
timber harvesting, and controlled burning associated with restoration of the native
longleaf pine forest community are prevalent at FBMI (Noss 1989). Previous research
has also shown historical land-use, largely from agriculture prior to establishing FBMI as
a training faculty to be an important factor in contemporary stream conditions (Maloney
et al. 2008).
3.3.2 Study sites and landscape-scale measures
Eight 1
st
- and 2
nd
-order streams were selected as study sites (Table 3.1), with a
~100-m study reach established per stream. Channels were mostly sand and clay
substrate, and consisted of pool and run habitat unit types, with a current velocity range
of 0.05 ? 0.17m/s, depth of 0.06 ? 0.24m, width of 1.0 ? 2.1m, and discharge of 0.002 ?
0.044m
3
/s across seasons (Table 3.2). Study streams showed a baseline range of
CWD abundance (as m
2
of CWD per m
2
of stream bed); from ~12% of stream bottom in
LC to ~3% in SB4, and mean stream gradient ranging from 0.83% to 5.1% KM1 and
LPK, respectively (Table 3.1) (see also Maloney et al. 2006).
For each catchment, spatial and land-use/land-cover data were quantified with
Arcview? 3.2 GIS (Environmental Systems Research Institute, Redlands, CA) using
70
coverages from the SERDP Ecosystem Management Project (SEMP) data repository
(http://sempdata.wes.army.mil/). Catchment area (Area) was established from a 1993
digital elevation model (DEM, 10-m resolution); specific grid coordinates of sampling
sites were obtained from global positioning system (GPS) units. Disturbance levels
were defined as the % of bare ground on slopes > 5% and percent of unpaved road
cover within a catchment (%BGRD, Maloney et al. 2005). Previous research showed
that this metric was a reliable indicator of upland disturbance influence on multiple
measures of stream at FBMI, ranging from abundance of primary and secondary
consumer to whole-stream ecosystem metabolism (Houser et al. 2005, 2006; Maloney
et al. 2005, 2006, 2008).
3.3.3 Instream habitat measures
We quantified a full range of reach-scale (e.g., CWD, mean velocity and depth)
measurements for each study site. Area of each run and pool habitat were estimated
using 5 cross-sectional transects to determine average habitat width and 3 longitudinal-
transects to determine the length of each habitat unit. Velocity and depth were
measured at 5 evenly spaced points along each cross-sectional transect. We estimated
discharge seasonally (spring, summer, winter) at the downstream-most sampling point
of each site using the incremental method (Gore 1996). In addition, we used a modified
transect method to quantify the relative abundance of CWD associated with the stream
bed (Wallace and Benke 1984). CWD surveys were conducted annually (spring 2002
and 2003) by measuring all live, dead-submerged, and dead-buried wood pieces >2.5
cm in diameter in 15 cross-stream transects per stream (1-m long per transect). Live
71
wood was combined with dead wood in surveys because some sites had prominent
exposed roots in the stream bed, which could have functioned similarly to dead wood as
benthic habitat and/or sources of organic matter retention. In addition, we quantified
abundance of benthic particulate organic matter (%BPOM) using sediment cores (PVC
pipe, area = 2.01 cm
2
) taken from the upper 10 cm of the stream bed (n = 3) every 2 mo
from March to December 2003; cores were collected from the channel thalweg at 3
points ~25 m apart. In the laboratory, samples were oven-dried to a constant mass at
80?C for 24-48 h, desiccated, and weighed to determine total dry mass, and then ashed
in a muffle furnace at 550?C for 3 h. Ashed samples were desiccated and reweighed,
and %BPOM was determined as the difference between the dry and ashed masses
divided by the total dry mass (Minshall 1996). Previous research at FMBI has shown
that CWD and BPOM were strongly related to benthic macroinvertebrate assemblages
and whole stream metabolism (Houser et al. 2005, Maloney and Feminella 2006).
3.3.4 Crayfish sampling
The study animal, Procambarus versutus (Hagen, subgenus Pennides) occurs
within the southeastern plains and coastal plain of Alabama, Georgia, and Northern
Florida (Hobbs 1984). This species is confined to sandy streams of variable sizes
containing coarse woody debris (CWD) and leaf litter, and occurs in areas with
moderate to high flow (Hobbs 1981). Density of P. versutus varies greatly with habitat
conditions, with the highest densities occurring with high CWD (R. Mitchell, unpublished
data). In general, this crayfish is small compared to other species with a maximum size
of ~39 mm CL (first-form male).
72
We quantified Procambarus versutus (hereafter crayfish) from 3 adjacent run and
pool habitat units within each study reach. Crayfish were sampled at each habitat using
a backpack electroshocker (Smith-Root LR-24
?
) and block seines, using the 2-pass
removal-depletion method similar to fish sampling (Seber 1982). Crayfish were
sampled at each habitat over 3 seasons, spring (March), summer (July), winter
(December) 2003. In a study comparing different crayfish sampling methods, Rabeni et
al. (1997) demonstrated electroshocking was the most effective for collecting crayfish
from multiple habitats (i.e., in providing the highest abundance estimates). In our study,
we counted all crayfish sampled, measured them for carapace length (CL, nearest 0.1
mm), and sexed them (for animals with CL >6 mm) before returning them to the
collection point. CL was used to estimate biomass using a length-biomass regression
equation for Cambaridae (Benke et al. 1999).
3.3.5 Statistical analysis
We used Pearson?s correlation to assess relationships between landscape
disturbance, catchment area and instream habitat variables. The purpose of this
analysis was to determine the strength of the relationship among different scales, and to
determine the potential mechanism through which landscape disturbance and
catchment area indirectly influences crayfish populations through habitat influences.
Next, we examined the multivariate relationships between instream habitat and crayfish
population metrics using stepwise multiple regression to determine which instream
habitat measures had the greatest potential influence on crayfish populations. We then
tested for differences in crayfish population metrics between microhabitats (pools vs.
73
runs) using a nested ANOVA (pool/run within streams), for each season sampled.
Coefficient of variation (CV, as %) was calculated for all run and pool instream habitat
measures for comparison within and among streams. Additionally, CV was used to
assess differences in habitat stability between pools and runs, with lower CV values
indicating higher stability. Last, we examined relationships between crayfish population
metrics and catchment disturbance using linear regression to assess if disturbance had
an equal influenced on both run and pools. Crayfish population measures were tested
for normality and population variables that were not normal were log-transformed except
for proportional data, which was transformed using arcsine-square-root transformation
(Zar 1999). All statistical analysis was performed using SAS software (version 9.1, SAS
Institute, Cary, North Carolina). ? level was set at 0.05 for all analyses.
3.4 RESULTS
3.4.1 Instream habitat conditions
Instream habitat variables varied among streams and seasons (Table 3.2).
Percent areal coverage of CWD ranged from 12.4 (LC) to a low of 3.3 (SB3) and
%BPOM ranged from a high of 4.1 (LC) in summer, to a low of 0.06 (LPK) in winter.
Mean current velocity varied among streams and seasons, whereas mean width and
depth differed more by stream than among seasons, with KM1 and LPK (and BC2 for
depth) showing the highest and lowest mean widths and depths, respectively. Mean
stream area was roughly equivalent between runs (5.32 m
2
) and pools (5.05 m
2
).
Discharge did not differ substantially among seasons; however, mean discharge
74
differences were substantial among some streams, with LC and BC2 showing the
highest and lowest discharge (0.044 and 0.001 m
3
/s, respectively; Table 3.2).
3.4.2 Landscape-scale relationships with instream habitat
Stream habitat variables showed strongly contrasting associations with
disturbance intensity at the catchment scale. There was a significant negative inverse
relationship between annual (spring) CWD and disturbance intensity (Table 3.3).
%BPOM also was negatively correlated with disturbance intensity during spring and
summer, but not winter (Table 3.3). Depth was the only local-scale variable correlated
(negatively) with disturbance intensity (Table 3.3), and only in summer and winter.
Catchment area was unrelated to CWD or %BPOM; however, catchment area was
correlated with mean width and discharge for all seasons, and with mean velocity and
depth for spring and summer, respectively, as would be expected due to the relationship
between catchment size and discharge (Table 3.3). Mean CV of stream depth was
positively correlated with disturbance intensity across all seasons in runs (Fig. 3.1);
however, for pools, mean CV of stream depth was correlated with disturbance intensity
only in summer. No other mean CV of habitat measures were related to disturbance
intensity and, subsequently, there were not significant differences between pool and run
microhabitats.
3.4.3 Instream habitat relationships with crayfish measures
Stepwise multiple regression identified only models with only 1 or 2 significant
habitat variables showing relationships with crayfish population variables. Overall,
75
CWD was the strongest correlate (positive) of mean crayfish density across seasons
(Table 3.4). In addition, CWD was the strongest correlate (positive) of mean crayfish
biomass in spring. In contrast, %BPOM and discharge were stronger correlates (again
positive) of biomass in summer, whereas mean depth was the best correlate of biomass
in winter (Table 3.4). Mean crayfish CL was unrelated to any instream habitat variable
(Table 3.4).
Nested ANOVA revealed significant differences in crayfish density, biomass, and
mean CL among streams for most seasons, but not sex ratio (Table 3.5). There were
no significant difference in density or % females between runs and pools habitats for
any season, but crayfish biomass was higher in pools than runs in spring and winter,
and crayfish were larger in pools than runs in all seasons (Table 3.5, Fig. 3.2). Sex ratio
differed among streams in summer only but did not differ between pools and runs
(Table 3.5, Fig. 3.2). There was no significant interaction between stream and
microhabitat for any crayfish variable, indicating that differences in crayfish measures
between pools and runs were independent of differences among streams (Table 3.5).
Multiple regression of instream habitat variables revealed CWD to be the most
important factor explaining crayfish variables in runs (Table 3.6), whereas crayfish
variables in pools were explained by several microhabitat factors (CWD, %BPOM and
discharge; Table 3.6). Crayfish density in runs was positively related to CWD in spring,
and to CWD and % BPOM in summer, whereas biomass in runs was positively related
to CWD in both spring and summer. Summer was the only season when CL was
correlated with microhabitat variables (discharge in runs, depth in pools; Table 3.6).
Crayfish biomass was positively related to CWD and %BPOM in spring and in summer.
76
Similar to runs, summer was the only season showing a significant relationship to mean
CL, whereas discharge was positively related to mean CL.
3.4.4 Disturbance relationship with crayfish population measures
Analysis of the influence of catchment disturbance on crayfish measures showed
that density in runs was significantly related to disturbance intensity across all seasons
(Fig. 3.3a, b, c), whereas crayfish density in pools and combined pool and run density
showed little or no relationship to disturbance intensity, except in winter where crayfish
density in combined pool and run was significantly related to disturbance (R
2
= 0.55, p =
0.035). Similar to density, crayfish biomass was strongly related to disturbance intensity
in runs (Fig. 3.4c), whereas pools and combined pool and run biomass showed no
relationship to catchment disturbance, except spring where both pool and combined
pool and run biomass were significantly related to catchment disturbance (Fig. 3.4a, b;
R
2
= 0.76, p = 0.042, R
2
= 0.53, p = 0.005, respectively).
3.5 DISCUSSION
3.5.1 Influence of disturbance on instream habitat
Our results indicate that instream habitat, specifically CWD abundance, was
negatively correlated with catchment disturbance as was % BPOM and stream depth.
Catchment disturbance has been suggested by others in FBMI studies to affect
instream habitat and, thus, communities (Houser et al. 2005, Maloney and Feminella
2006,). The primary source of stable habitat in FBMI streams is CWD, similar to other
low-gradient sandy streams (Benke et al. 1984, Benke and Wallace 1990), and loss of
77
CWD from burial or scour in disturbed catchments may dramatically impact ecosystem
function (Houser et al. 2005, Maloney and Feminella 2006). Beyond contemporary land
use and its effects, historic land use, prior to military activities, also may exert a long-
term influence on stream ecosystems (Maloney et al. 2008). In many lowland streams,
sand intrusion into stream channels from upland disturbance can alter instream habitat
for decades to centuries (Hyatt and Naiman 2001, Wallace et al. 2001, Downes et al.
2006).
% BPOM and depth were negatively correlated with disturbance intensity, but
such relationships were not observed across all seasons. The absence of a relationship
between % BPOM and disturbance during winter likely occurred because of a lush
riparian zone in all study streams (> 90% cover, KOM, unpublished data) and
correspondingly high allochthonous inputs of leaf litter during late fall-early winter that
equaled or exceeded breakdown or export rates. Allochthonous inputs are the primary
source of BPOM in most small temperate-deciduous streams (Mulholland 1997), and
disturbed streams with low instream retention structures (e.g., CWD) likely will have low
BPOM, a pattern that would be exacerbated in highly disturbed catchments because of
high stream flashiness (Smock 1997, Maloney et al. 2005). Similarly, depth was
correlated with disturbance intensity only in summer and winter. These depth
relationships appear to be greatly influenced by habitat type. Within-habitat variation
(as CV) for depth in run microhabitats increased with increasing disturbance intensity
across all seasons, whereas for pools this relationship occurred only in summer. Others
have suggested that sediment intrusion into channels from eroding uplands decreases
streambed stability (Jain and Park 1989, Krone 1999, Maloney et al. 2005). In our
78
study, runs showed higher variability (i.e., less stable substrate) in depth than pools,
which may indicate runs are more influenced by sediment movement through channels
from upland/upstream sources than pools. Unfortunately, CWD was only measured at
the reach (vs. microhabitat) scale, so we cannot assess if CWD abundance also varied
more in runs than pools. Pools often form downstream of CWD (Wallace et al. 1995,
Quinn et al. 1997) and these deposition zones often are more stable and contain higher
BPOM than areas upstream of CWD (Smock et al. 1989). Thus, in our study, high %
BPOM and lower variability of depth in pools compared to runs in highly disturbed
catchments may be indicative of a more stable stream bed in pools than runs.
3.5.2 Influence of instream habitat on crayfish
Analysis of relationships between instream habitat and crayfish population
metrics suggests that crayfish are strongly influenced by abundance of CWD. Crayfish
density for both pools and runs combined was positively related to increasing CWD
across all seasons. Spring crayfish biomass also appeared to be strongly influenced by
CWD, whereas summer biomass appeared more related to % BPOM. Habitat variables
that influenced crayfish biomass were different than those that correlated with density,
and the strong inverse correlation of % BPOM with disturbance intensity suggests that
upland disturbance indirectly influenced biomass through different habitat measures
than those influencing density. Our findings are similar to others reporting land use
impacts on instream habitat and biota (Roy et al. 2003, Parkyn and Collier 2004,
Maloney and Feminella 2006). Upland disturbance can be considered an indirect
79
influence on stream biota by directly influencing instream habitat. For example, in
streams from New Zealand, Parkyn and Collier (2004) demonstrated that land use
changes can reduce habitat quality and quantity for crayfish, thus reducing density and
potential for population recovery from flood disturbance. In addition, the presence of
wood as tree roots and CWD, as well as instream cover such as leaf litter, was shown
to be positively related to crayfish abundance in streams in Britain (Smith et al. 1996)
and New Zealand (Naura and Robinson 1998). Streams depth also may decrease with
increasing catchment disturbance because of reduced CWD, the latter of which may be
important in pool formation (Parkyn and Collier 2004); others have shown that crayfish
populations are positively associated with water depth because deeper pools typically
have slower velocity and act as sinks for BPOM, thus increasing food availability in
pools compared to higher velocity microhabitats (Usio and Townsend 2000).
Crayfish typically showed higher population biomass and larger individual size in
pools than runs, but not higher density. Results of other studies also showing
differential crayfish size structure or microhabitat use, but the factors affecting such
patterns varied. Flinders and Magoulick (2007) found that small crayfish used shallow
habitats whereas large crayfish used shallow and deep habitats equally, suggesting
increased predation risk of smaller crayfish from fish in deep habitats and higher quality
food resources in shallow habitats. Others have suggested that larger crayfish find
refuge from terrestrial predators, and thus larger crayfish will more likely be found in
deeper water (Englund and Krupa 2000). Additionally, Lodge and Hill (1994) suggested
that juvenile crayfish are more susceptible to cannibalism than adults, which would
explain why smaller crayfish are less common in deeper water where larger crayfish
80
occur. This latter point may explain the observation in our study with a higher mean
size of crayfish in pools than runs. Further, fish predation risk is not likely a major factor
in our study. Maloney et al. (2006) reported low presence and relative abundance of
predacious fish in these same streams, sampled during the sample time period. Finally,
this pattern appears to be independent of sex ratio, with the ratios being equal between
run and pool habitats. Habitat quality and the influence of disturbance of the
microhabitats is a more likely reason for the decreasing density and biomass with
increasing disturbance observed in the current study.
Our findings suggest that instream habitat, specifically CWD abundance, is an
important variable for crayfish populations in runs but less so in pools. Other research
has shown a positive relationship between CWD and crayfish density. In addition, the
presence of riparian tree roots in the stream has been shown to influence crayfish
density, possibly providing a refuge for crayfish in disturbed catchments (Parkyn and
Collier 2004). Whereas crayfish density and biomass showed a positive relationship
with CWD, no relationship was found with crayfish size. Our findings suggest that CWD
acts as a refuge for crayfish, but it appears that increased CWD does translate to
increased food quality for P. versutus in the study streams.
3.5.3 Relationship between catchment disturbance and crayfish
One mechanism with which catchment disturbance influences streams is through
transport of sediment from upland areas of the catchment into streams via ephemeral
streams (Howarth et al. 1991, Quist et al. 2003). Most studies of catchment disturbance
have emphasized assemblage or community measures, rather than focus on single
81
populations. Many aquatic taxa are currently under pressure of species loss, and
nowhere are aquatic taxa more vulnerable than in southeastern US, particularly crayfish
(Master et al. 2000, Strayer 2006, Taylor et al. 2007). Changes to instream habitat
have caused significant impacts to stream biota, but it can be difficult to determine
which instream habitat component has the greatest direct influence. A measure of
catchment-level disturbance that can predict instream biological conditions may be
useful to managers and conservation biologists for monitoring imperiled stream biota.
That CWD and %BPOM were highly correlated with catchment disturbance
intensity suggests that disturbance acts indirectly on crayfish populations through the
CWD abundance and %BPOM in the stream channel. Our findings suggested that
catchment disturbance intensity was a good predictor of crayfish density and biomass,
with its greatest influence in runs. This result suggests that pools may act as a refuge
for crayfish under increased disturbance pressure, but perhaps only in streams where
aquatic crayfish predator presence and cannibalistic behavior is low. Others have found
that catchment disturbance can have a disproportionate impact on instream habitat
availability for benthic macroinvertebrate communities. Findings by Roy et al. (2003)
suggest that riffle habitats are more influenced by catchment disturbance than pools or
bank habitats. Additional results from Quinn et al. (1997) suggest that pool formation is
highly related to the presence of CWD. In our study, similar observations were made
where pools were typically associated with CWD in the form of debris dams or tree roots
(personal observations). This relationship would suggest that pools are a more stable
habitat than runs and that as the amount of the reach scale CWD decreases there
should be a disproportionately negative effect on habitat stability in runs.
82
In summary, P. versutus appears to be influenced by upland disturbance similar
to other aquatic macroinvertebrates through the degradation of habitat availability.
However, because of its use of both run and pool habitats it appears that this species
can occupy the more stable pool habitats as a refuge from increasing upland
disturbance. Such microhabitat flexibility may allow this species to avoid extirpation
under all but the most extreme cases of upland disturbance. Additionally, our research
suggests a strong land-cover cascade relationship between land-use and crayfish
(sensu Burcher et al. 2007), mediated through the direct linkage of land-use and habitat
availability (i.e. CWD). The likely association between CWD and pool habitats suggests
that these areas of the stream are more stable than run microhabitats, thus providing
more optimal conditions for survival of this crayfish.
83
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92
Table 3.1. Study stream locations, with catchment and disturbance characteristics.
UTM = Universal Transverse Mercator, %BGRD = percentage of catchment as bare
ground on slopes > 5% and % of unpaved roads in catchment. Catchments were
ordered in terms of increasing landscape disturbance.
93
Stream Stream
code
UTM Military land
use
Stream
order
Catchment
area (km
2
)
Disturbance
intensity
(% BGRD)
Bonham BC2
0710627N,
Infantry/
2
0.75 3.15
Tributary
3588976E Ranger
Lois Creek LC
0715377N
Infantry/
2
3.32 3.67
3597908E Ranger
Kings Mill Creek KM1
0720701N,
Infantry/
2
3.69 4.63
3600036E Ranger
Hollis Branch HB
0717848N
Infantry/
2
2.15 6.62
3583123E Ranger
Sally Branch SB2
0716808N
Heavy
2
1.23 8.12
Tributary 3584787E Machinery
Sally Branch SB3 0716673N Infantry/ 1 0.72 10.49
Tributary 3584684E Ranger
Little Pine Knot LPK 0719223N Heavy 2 0.33 11.26
Tributary 3585421E Machinery
Sally Branch SB4 0716005N, Heavy 1 1.00 13.65
Tributary 3584889E Machinery
94
Table 3.2. Mean (+1SE) instream habitat-scale variables. CWD = coarse woody debris
relative abundance. %BPOM = benthic particulate organic matter. Catchments were
ordered in terms of increasing landscape disturbance (see Table 3.1).
95
Stream
Stream
code
CWD
(% areal
coverage)
Season
%BPOM
Velocity
(m/s)
Depth
(m)
Wetted
stream width
(m)
Run area
(m
2
)
Pool area
(m
2
)
Discharge
(m
3
/s)
Bonham Creek BC2 10.1 Spring 2.20 (0.29) 0.05 (0.03) 0.09 (0.02) 1.2 (0.14) 2.72 (0.14) 3.96 (0.31) 0.004
Tributary Summer 1.85 (0.46) 0.03 (0.03) 0.24 (0.02) 1.1 (0.04) 5.43 (2.09) 3.47 (0.18) 0.001
Winter 0.83 (0.46) 0.06 (0.01) 0.19 (0.03) 1.0 (0.02) 4.05 (0.93) 3.46 (0.10) 0.005
Lois Creek LC 12.4 Spring 3.33 (0.61) 0.17 (0.02) 0.14 (0.02) 2.0 (0.11) 10.81 (2.68) 8.90 (2.32) 0.044
Summer 4.10 (0.37) 0.11 (0.04) 0.12 (0.02) 2.0 (0.11) 6.97 (2.27) 7.56 (2.27) 0.013
Winter 1.90 (0.87) 0.07 (0.02) 0.14 (0.02) 1.9 (0.06) 9.77 (0.43) 6.86 (0.57) 0.022
Kings Mill KM1 7.5 Spring 1.06 (0.52) 0.13 (0.02) 0.21 (0.02) 2.1 (0.13) 9.51 (2.44) 6.28 (1.51) 0.037
Creek Summer 1.85 (0.25) 0.13 (0.02) 0.22 (0.02) 1.9 (0.23) 7.85 (0.89) 8.96 (2.68) 0.020
Winter 1.13 (0.80) 0.09 (0.004) 0.21 (0.01) 1.8 (0.09) 5.00 (1.02) 8.39 (1.37) 0.029
Hollis Branch HC 6.5 Spring 2.30 (0.81) 0.08 (0.04) 0.17 (0.01) 2.0 (0.12) 5.71 (0.58) 8.47 (1.69) 0.018
Summer 0.79 (0.06) 0.08 (0.02) 0.13 (0.02) 1.8 (0.14) 5.89 (0.42) 6.99 (1.29) 0.013
Winter 2.45 (0.50) 0.07 (0.01) 0.17 (0.02) 1.9 (0.18) 8.60 (0.52) 10.80 (4.10) 0.018
Sally Branch SB2 8.7 Spring 0.95 (0.35) 0.15 (0.02) 0.12 (0.01) 1.4 (0.14) 3.27 (1.26) 4.24 (0.90) 0.027
Tributary Summer 1.64 (0.16) 0.13 (0.02) 0.11 (0.01) 1.4 (0.09) 5.89 (1.47) 4.05 (0.60) 0.009
Winter 1.02 (0.04) 0.12 (0.01) 0.12 (0.01) 1.5 (0.11) 3.35 (0.52) 5.84 (2.67) 0.016
Sally Branch SB3 3.3 Spring 1.14 (0.21) 0.09 (0.01) 0.10 (0.01) 1.3 (0.09) 2.21 (0.39) 2.52 (0.35) 0.007
Tributary Summer 1.37 (0.45) 0.08 (0.01) 0.07 (0.01) 1.3 (0.08) 3.78 (1.27) 2.39 (0.11) 0.004
Winter 1.39 (0.21) 0.08 (0.01) 0.09 (0.02) 1.3 (0.07) 4.76 (0.68) 2.79 (0.30) 0.008
Little Pine Knot LPK 3.98 Spring 1.15 (0.28) 0.06 (0.01) 0.19 (0.01) 1.9 (0.05) 3.61 (0.88) 1.85 (0.61) 0.003
Tributary Summer 1.13 (0.45) 0.12 (0.02) 0.06 (0.01) 1.0 (0.13) 1.83 (0.18) 1.49 (0.18) 0.002
Winter 0.06 (0.23) 0.06 (0.004) 0.08 (0.03) 1.0 (0.12) 3.51 (0.87) 1.94 (0.58) 0.003
Sally Branch SB4 3.6 Spring 0.57 (0.03) 0.11 (0.02) 0.11 (0.01) 1.5 (0.13) 4.31 (0.59) 3.43 (0.84) 0.012
Tributary Summer 0.56 (0.07) 0.01(0.02) 0.07 (0.01) 1.4 (0.08) 4.66 (0.64) 4.32 (0.61) 0.006
Winter 0.53 (0.10) 0.08 (0.02) 0.11 (0.02) 1.5 (0.15) 4.30 (0.80) 2.40 (0.51) 0.009
96
Table 3.3. Pearson?s correlation coefficients summarizing relationships between
landscape variables with instream habitat variables, by season. Bold correlation
coefficients were significant at ?=0.05. Disturbance intensity = %BGRD (percent of
bare ground on slopes >5% and unpaved roads within catchment). ND= no data (CWD
was measured in spring only).
97
CWD = coarse woody debris relative abundance. %BPOM = benthic particulate organic matter.
Variable CWD %BPOM Velocity Depth Width Discharge
Spring
Disturbance intensity -0.92 -0.74 -0.13 -0.09 0.39 -0.52
Catchment area 0.59 0.36 0.72 0.20 0.72 0.91
Summer
Disturbance intensity ND -0.67 0.28 -0.78 -0.51 -0.41
Catchment area ND 0.52 0.49 0.90 0.96 0.95
Winter
Disturbance intensity ND -0.45 0.17 -0.74 -0.36 -0.52
Catchment area ND 0.54 0.30 0.90 0.91 0.96
98
Table 3.4. Stepwise multiple regression results for crayfish population variables across
instream habitat variables. CWD = coarse woody debris relative abundance. Size =
carapace length (CL). %BPOM = benthic particulate organic matter.
99
Population
variables
Season Range Model variables R
2
?
coefficient
F p
Spring
Density 0.2-1.1 CWD, % BPOM 86.1 1.45, -0.97 25.23 0.003
Biomass 35.4-273.1 CWD 71.5 0.85 15.06 0.008
Size 11.6-16.1 ? ? ? ? NS
Summer
Density 0.2-0.7 CWD 71.4 0.85 14.97 0.008
Biomass 48.7-426.1 % BPOM, Discharge 87.7 0.71, 0.43 17.71 0.005
Size 13.0-20.0 ? ? ? ? NS
Winter
Density 0.2-1.0 CWD 51.2 0.72 6.29 0.046
Biomass 0.0-263.7 Depth 47.46 0.69 5.42 0.057
Size 12.3-19.7 ? ? ? ? NS
100
Table 3.5. ANOVA summary showing differences for crayfish population variables
among streams and between microhabitats. Habitat represents pools vs. runs. Mean
size = mean crayfish size (as carapace length). DF = degrees of freedom. Values are
F-statistics (p-value).
101
Effect
Season DF Density Biomass
Mean
Size Sex Ratio
Spring
Stream
8 8.84 (<0.0001) 6.12 (0.0002) 2.71 (0.024) 0.14 (0.996)
Habitat
1 1.64 (0.209) 11.41 (0.006) 11.47 (0.002) 0.79 (0.381)
Stream*Habitat
7 0.45 (0.883) 0.56 (0.799) 1.31 (0.282) 0.65 (0.709)
Summer
Stream 8 11.09 (<0.0001) 3.57 (0.004) 0.86 (0.362) 2.85 (0.026)
Habitat 1 0.06 (0.804) 3.44 (0.071) 5.48 (0.024) 0.27 (0.606)
Stream*Habitat 7 2.01 (0.073) 1.29 (0.219) 0.32 (0.856) 1.13 (0.377)
Winter
Stream 8 3.06 (0.010) 0.89 (0.537) 3.07 (0.015) 1.51 (0.212)
Habitat 1 0.03 (0.857) 4.75 (0.036) 7.91 (0.009) 0.02 (0.899)
Stream*Habitat 7 0.31 (0.958) 0.54 (0.815) 0.83 (0.575) 1.12 (0.385)
102
Table 3.6. Stepwise multiple regression results for run and pool crayfish samples. Size
= carapace length (CL). CWD = coarse woody debris abundance. %BPOM = benthic
particulate organic matter.
103
Crayfish
variables
Season Range Model variables Adj. R
2
?
coefficient
F P
Runs
Spring
Density 0.0-1.1 CWD 64.3 0.80 10.79 0.017
Biomass 0.0-300.6 CWD 59.4 0.77 8.77 0.025
Size 8.3-19.1 ? ? ? ? NS
Summer
Density 0.0-1.0 CWD, % BPOM 95.8 0.42, 0.63 81.10 <0.001
Biomass 0.0-235.9 CWD 84.0 0.91 31.53 0.001
Size 7.0-18.6 Depth 59.8 0.77 8.91 0.024
Winter
Density 0.0-1.3 ? ? ? ? NS
Biomass 0.0-137.9 ? ? ? ? NS
Size 10.1-17.9 ? ? ? ? NS
Pools
Spring
Density 0.4-1.4 ? ? ? ? NS
Biomass 44.07-392.0 CWD, % BPOM 81.68 1.36, -0.74 16.61 0.006
Size 14.7-19.9 ? ? ? ? NS
Summer
Density 0.3-1.1 ? ? ? ? NS
Biomass 66.5-616.4 % BPOM 53.31 0.73 6.85 0.040
Size 13.0-21.8 Discharge 52.8 0.72 6.71 0.041
Winter
Density 0.0-0.9 CWD 53.04 0.73 6.78 0.040
Biomass 0.0-392.5 ? ? ? ? NS
Size 13.7-16.7 ? ? ? ? NS
104
Figure 3.1. The amount of streambed variability expressed as coefficient of variation
(%CV) of depth in runs and pools plotted against the catchment disturbance intensity for
the 8 study streams across 3 seasons (top panel = spring, middle panel = summer,
bottom panel = winter).
105
Runs
20
40
60
80
100
120
140
CV of Depth
30
40
50
60
70
80
90
100
2 4 6 8 10 12 14 16
34
36
38
40
42
44
46
48
50
52
54
Pools
30
35
40
45
50
55
60
65
70
35
40
45
50
55
60
65
70
Disturbance Intensity (% catchment)
2 4 6 8 10 12 14 16
38
40
42
44
46
48
50
52
54
56
58
R
2
= 0.67
p = 0.013
R
2
= 0.76
p = 0.004
R
2
= 0.77
p = 0.004
R
2
= 0.75
p = 0.006
spring
summer
winter
106
Figure 3.2. Comparison of mean (+1SE) crayfish density, biomass, carapace length
(CL) and % of the population as females (% female) between run and pool
microhabitats across 3 seasons (spring, summer, winter). * p < 0.05.
107
Densi
t
y
(no./m
2
)
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Bioma
ss (mg/m
2
)
100
200
300
400
500
600
Spring Summer Winter
Cara
pace
Len
gth (mm)
10
12
14
16
18
20
Spring Summer Winter
% F
e
m
a
l
e
30
40
50
60
70
80
*
*
*
**
Pools Runs
108
Figure 3.3. Mean density of crayfish (number per m
2
) in runs plotted against catchment
disturbance intensity for the 8 study streams for spring (A), summer (B), and winter (C).
109
Figure 3.4. Mean biomass of crayfish per m
2
plotted against catchment
disturbance intensity for the 8 study streams across season. A = pools and runs, B =
pools, and C = runs.
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Disturbance Intensity
246810121416
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
R
2
= 75.40
p = 0.005
R
2
= 71.20
p = 0.008
R
2
= 63.70
p = 0.018
Density
(no./
m
2
)
A
B
C
110
Figure 3.4. Mean biomass of crayfish per m
2
plotted against catchment disturbance
intensity for the 8 study streams across season. A = pools and runs, B = pools, and C =
runs.
111
Spring
0
100
200
300
400
A
v
erage Biomass (mg/m
2
)
0
100
200
300
400
500
2 4 6 8 10 12 14 16
-50
0
50
100
150
200
250
300
350
Summer
0
100
200
300
400
500
0
100
200
300
400
500
600
700
Disturbance Intensity
2 4 6 8 10121416
-100
-50
0
50
100
150
200
250
300
Winter
0
50
100
150
200
250
300
0
100
200
300
400
500
2 4 6 8 10 12 14 16
0
50
100
150
200
250
R
2
= 50.50
p = 0.048
R
2
= 52.60
p = 0.042
R
2
= 84.40
p = 0.001
R
2
= 80.50
p = 0.003
R
2
= 75.90
p = 0.005
A
B
C
112
4. INFLUENCE OF THE CRAYFISH PROCAMBARUS VERSUTUS ON LEAF
BREAKDOWN AND BENTHIC MACROINVERTEBRATES IN A SANDY STREAM
4.1 SUMMARY
Crayfish have been shown to have strong effects on both basal resources (e.g. algae,
leaf litter) and benthic macroinvertebrate assemblages in high-gradient upland streams;
however, the trophic crayfish role within structurally simpler lowland, sandy streams
where leaf detritus is the primary basal resource is unknown. We conducted a 6-wk
enclosure-exclosure experiment in a sandy stream in eastern Alabama, USA, to assess
effects of the crayfish Procambarus versutus on leaf litter breakdown and
macroinvertebrate assemblage structure. We used hardware cloth cages as
experimental units, and 3 crayfish density treatments (0, 4, 12/m
2
), 1 cage control
treatment, and a no cage treatment containing artificial leaf packs of Fagus grandifolia
(American Beech), and quantified breakdown and macroinvertebrate assemblages.
Litter breakdown was unaffected by crayfish density, but macroinvertebrate density,
biomass, and richness all were significantly lower in the high- crayfish density (vs.
exclusion) treatment. Procambarus versutus appears to be an important determinant of
macroinvertebrate assemblage structure, but unlike other species of crayfish, has a
limited effect on leaf litter processing. Results from stable isotope analysis of P.
113
versutus muscle suggested this crayfish functioned more as a predator then a
detritivore, which confirms the results of the field experiment.
4.2 INTRODUCTION
Crayfish constitute the bulk of benthic macroinvertebrate biomass in many
freshwater systems (Mason 1974, Momot and Gowing 1977, Momot et al. 1978, Momot
1995, Rabeni et al. 1995), but a debate remains over their exact trophic role. Most
researchers have considered crayfish to be primarily omnivores (Webster and Patten
1979, Huryn and Wallace 1987, Hart 1992, Creed 1994), whereas others have argued
that because crayfish diets must contain enough high-protein from animal material to
maintain their biomass and growth, crayfish function more as carnivores (Momot et al.
1978, Momot 1995). Irrespective of their trophic position, crayfish have the potential to
exert a substantial effect on benthic macroinvertebrates in many freshwater systems
because of their high biomass, polyphagous feeding, and large size relative to other
benthic macroinvertebrates (Lodge et al. 1994, Usio and Townsend 2004, Usio et al.
2009).
Crayfish can influence macroinvertebrate assemblages and basal resources (e.g.
leaf litter, algae; Creed 1994, Parkyn et al. 1997), sometimes through ecosystem
engineering (Creed and Reed 2004), which involves creating or modifying habitats and
influencing resource availability for other species (Jones et al. 1994, 1997, Usio and
Townsend 2004, Helms and Creed 2005). Modifications of substrate conditions by
crayfish can either increase or decrease distributions of other benthic organisms,
depending on species or the nature of the change (Parkyn et al. 1997).
114
Researchers have suggested that the reason crayfish act as ecosystem
engineers is because of their omnivorous feeding and relatively large size compared to
other macroinvertebrates (Huryn and Wallace 1987, Parkyn et al. 1997, Usio and
Townsend 2000). Unlike keystone predators (sensu Paine 1966) whose direct effects
on secondary consumers cascade through food webs and indirectly affect basal
resources (Carpenter et al. 1985, Menge and Sutherland 1987, Power 1990),
omnivorous crayfish exert effects directly on multiple trophic levels. In this context,
crayfish often show strong direct trophic influences, thus offsetting or ameliorating
cascading effects developed from a top consumer (Diehl 1995).
Omnivore size may influence the likelihood and magnitude of effects on
intermediate consumers (animal prey) and basal resources, with influence increasing
with the size differential between omnivores and intermediate consumers (Diehl 1993,
1995). Experimental studies indicate that when top omnivores are disproportionally
larger than intermediate consumers, strong direct trophic effects of omnivores on
intermediate consumers and basal resources occur, often negating indirect effects and
trophic cascades (Polis and Holt 1992, Diehl 1993, Creed 1994, Pringle and Hamazaki
1998).
Previous experiments involving crayfish trophic position have focused on large,
long-lived species (Huryn and Wallace 1987, Lodge et al. 1994, Parkyn et al. 1997, Usio
2000, Helms and Creed 2005). For example, Huryn and Wallace (1987) studied the
effects of a long-lived (up to 13 y), slow maturing (~5 y) crayfish (Cambarus bartonii) on
leaf litter breakdown, and reported that litter breakdown and crayfish size were
correlated. Additionally, Creed and Reed (2004) reported this same species (~20 mm
115
carapace length) increased litter breakdown but also reduced abundance of large
chironomid larvae. In general, large long-lived crayfish have a significant impact on
both basal resources and macroinvertebrates, where impacts on benthic
macroinvertebrates can be both direct and indirect, mediated through alteration of basal
resources or habitat (Lodge et al.1994).
Few studies have assessed trophic influences of crayfish from warm, low-latitude
streams. Momot (1984) hypothesized that such species are short lived (2 y or less) and
require high amounts of animal protein to meet their metabolic demands. Species of
Procambarus primarily inhabit warm environments or the southeastern United States
where temperatures rarely go below freezing (Hobbs 1984), and have been shown to
grow and mature more rapidly than species from other crayfish genera (Pratten 1980,
Momot 1984, Huryn and Wallace 1987). Maintaining a high growth rate is likely to
require a greater need for a high protein diet, which, in streams, requires a high reliance
on animal material (Momot 1984, Whitledge and Rabeni 1997). In cases where crayfish
species rely on animal prey, they are more likely to influence benthic macroinvertebrate
assemblages and food web structure, relative to other predacious benthic
macroinvertebrates (Nystrom et al. 1996).
We present results from a field experiment designed to assess the influence of a
small, short-lived crayfish species on both a basal resource (leaf detritus) and benthic
macroinvertebrates colonizing leaf litter. In addition, we described crayfish trophic
position to assess its potential influence on the benthic food web.
116
4.3 Methods
4.3.1 Study area
The experiment was conducted in a forested section of Choctafaula Creek (32?
29? N, 85? 36? W), Macon County, Alabama, within the Tuskegee National Forest.
Choctafaula Creek is a 3
rd
-order stream that flows through the Piedmont and
Southeastern Plains ecoregions (Omernik 1987). Soils in the catchment range from
Cretaceous-age loamy to sandy sediments (USDA 1981). The dominant forest type in
the catchment is oak-hickory-pine, with riparian areas being dominated by hardwoods.
The study reach was approximately 150 m, composed mainly of pools and runs, with
few riffles and substrate reach was mostly sand with some gravel and coarse woody
debris in the active channel.
4.3.2 Study species
The study animal, Procambarus versutus (Hagen, subgenus Pennides) occurs
within the southeastern plains and coastal plain of Alabama, Georgia, and Northern
Florida (Hobbs 1984). This species is confined to sandy streams of variable sizes
containing coarse woody debris (CWD) and leaf litter, and occurs in areas with
moderate to high flow (Hobbs 1981). Density of P. versutus varies greatly with habitat
conditions, with the highest densities occurring with high CWD (R. Mitchell, unpublished
data). In general, this crayfish is small compared to other species with a maximum size
of ~39 mm carapace length (CL; first-form males).
117
4.3.3 Experimental design
We conducted an in-situ enclosure-exclosure experiment from October to
November 2005 (6-wk) to assess the effect of P. versutus (hereafter crayfish) density on
leaf pack and benthic macroinvertebrate assemblages within leaf packs. Cages (50 cm
L x 50 cm W x 35 cm H) were used either to enclose or exclude crayfish. Cages were
constructed of 3-mm-mesh hardware cloth, and positioned with one corner pointing
upstream to reduce accumulation of extraneous material by the current. We used a
randomized block design with 5 blocks with 5 treatments per block: 1) high density
(enclosure with 12 crayfish/m
2
), 2) low density (enclosure with 4 crayfish/m
2
), 3) no
crayfish (exclosure), 4) a cage control (downstream portion of cage open), and 5) an
uncaged control (base of cage only). Treatment densities bracketed those observed
within the study site (2?7/m
2
). All crayfish used in the experiment were collected from
runs within the study stream. O; only male crayfish with a CL of 17 mm to 20 mm were
used. Males were used to standardize the influence of sex and size on the experiment.
Cage control and uncaged treatments were accessible to all benthic organisms,
whereas coarse mesh in enclosures and exclosures effectively excluded both large and
small crayfish but not smaller macroinvertebrates. We placed cages in 5 rows (blocks),
with each row placed in a separate run with approximately equal depth (~0.25m) and
velocity (~0.39m/s).
We used abscised American beech (Fagus grandifolia) leaves, from the riparian
area of the study reach, for construction of artificial leaf packs placed in each cage (1
pack/cage), and secured packs with cable ties at the upstream-end of the cage. Leaf
packs were chosen for the experimental substrate because of its importance as both
118
food and habitat for many benthic macroinvertebrates, and was common throughout the
study reach. Packs weighed ~10 g (9.8?10.3 g dry mass), and were held with metal
binder clips at the leaf petiole. Beech was chosen because of its high abundance within
the riparian zone of the study reach. Cages were checked and cleaned daily by gently
scrubbing the hardware cloth to ensure adequate flow into cages, and water
temperature (recorded every 15 min with a HOBO temp logger) ranged from 7 to 22? C
over the experiment.
After the experiment we retrieved leaf packs from the cages by gently removing
them with a 250 ?m-mesh net. Leaf packs and associated macroinvertebrates were
placed on ice and transported to the laboratory and kept frozen until processed. In the
laboratory, leaves were thawed and individually rinsed over a 250-?m sieve to separate
macroinvertebrates and whole leaves/leaf fragments. Macroinvertebrates were
identified to the lowest possible taxonomic level (usually genus) using keys in Merritt
and Cummins (1996), except for larval Chironomidae, which were grouped into
Tanypodine and non-Tanypodine larvae. Macroinvertebrate biomass was estimated by
measuring length of animals (nearest mm) and converted length into ash-free dry mass
(AFDM) using length-mass equations in Benke et al. (1999).
4.3.4 Crayfish trophic position and foodweb analysis
Crayfish, conditioned detrital litter collected from the stream, and selected
primary and secondary consumers (below), were quantified for analysis of stable
isotopes at the end of the experiment (November 2005). We collected
Macroinvertebrates (10-20 individuals per sample) and a mixture of leaf litter from pools
119
and runs in the study reach to account for spatial variation in the isotope compositions
of foodweb components. Litter and macroinvertebrate samples were transported on ice
to the laboratory and then frozen (?10?C) until processed. Frozen samples were
thawed, then were dried at 50?C for 24 to 48 h, and then homogenized into a fine
powder with a mortar and pestle. Three to 5 samples were analyzed for isotope
analysis for each taxonomic group, except crayfish where n = 30. A higher number of
crayfish were collected, compared to other macroinvertebrates, to encompass a wide
range of crayfish sizes (5 to 34mm). Here, we chose to include a range of crayfish
sizes crayfish to incorporate ontogenetic changes in feeding, if they occurred. Isotopic
analysis was done at Colorado Plateau Stable Isotope Laboratory, Flagstaff, AZ, using
a Thermo Electron gas isotope-ratio mass spectrometer. Isotope ratio are reported in
standard delta (?) notation defined as the parts per thousand deviation from the
standard reference materials (air for N, Vienna Pee Dee belemnite carbonate for C), as:
?
13
C or ?
15
N
sample
= [(R
sample
? R
standard
) / R
standard
] ? 1000
where R is C
13
/C
12
or N
14
/N
15
(Peterson and Fry 1987, Hershey et al. 2007).
Organisms generally were identified to genus or species, except for
Chironomidae, which was grouped by subfamily. Leaf litter was readily available for
sampling, whereas because of interference with other biofilm components instream
primary producers (algae) were more difficult to sample; therefore, we used 2 primary
consumers to determine the isotopic baseline of the food web for both algae and leaf
litter sources (see Post 2002). Stenonema sp., a grazing mayfly, was used to represent
the algal source and Tipula sp., a shredding cranefly, was used to represent the leaf
litter source (Merritt and Cummins 1996). Absolute trophic position (TP), defined as an
120
organisms position relative to a basal resource (i.e. algae and detrital leaf litter), was
estimated for each taxon sampled. A 2-source (i.e., detritus leaf litter and algae) mixing
model was used to evaluate the relative contribution of each food source to a
consumer?s diet and TP (Post et al. 2000, Klinge et al. 1990). estimated as:
TP = ? + (?
15
N
sc
? [?
15
N
Tipula
? ? + ?
15
N
Stenonema
? (1 ? ?)] / ?
n
where ? is the trophic position of the organism used to estimate ?
15
N
base of food web
(i.e., ?
= 2 for primary consumers), ? is the proportion of N in the consumer ultimately derived
from litter and (1 ? ?) is the proportion of N contributed by algae, ?
15
N
sc
is the N isotope
value for any given secondary consumer, and ?
n
is the fractionation or enrichment in N
that occurs between trophic levels (?
n
= 3.4). The proportion of the dietary C derived
from litter (used in the previous equation) was estimated from the following equation
(Post et al. 2000):
? = (?
13
C
sc
? ?
13
C
Stenonema
) / (?
13
C
Tipula
? ?
13
C
Stenonema
)
4.3.5 Predictions and Analysis
We predicted that crayfish would have limited effects on basal resources
because of their relatively small size compared to other species of crayfish and, thus,
would have a low effect on altering available benthic habitat. In turn, because of their
relatively rapid growth rate and high protein requirements, compared to other larger
species of crayfish, we predicted P. versutus to have a strong direct effect on benthic
macroinvertebrates within litter, an effect that should vary depending on density of P.
versutus. Additionally, we predicted that P. versutus TP would be similar to other
benthic food web predators.
121
All data were analyzed for normality using a Kolmogorov-Smirnov test for
normality and homogeneity of variance using Levene?s test for equal variance (Zar
1999). Any response variables determined to be nonnormal or heteroscedastic were
log
10
-transformed, which then satisfied parametric assumptions. We used multivariate
analysis of variance (MANOVA) to test for overall effect of treatments and blocks on leaf
pack loss and macroinvertebrate response variables. We used ANOVA to test for
effects of treatments on specific response variables. For response variables showing a
significant difference we used Tukey?s pairwise comparison tests to determine where
differences among specific treatments resided.
4.4 RESULTS
4.4.1 Field experiment
Effects of crayfish on leaf breakdown.?Litter breakdown for individual treatment
units ranged from 31.1 to 88.4% loss, with the lowest individual loss occurring in the
open cage treatment and the highest loss in the moderate crayfish density treatment.
However, there was high variability across all blocks and treatments, with no significant
block effect (F
4,16
= 0.80, p = 0.545) and no significant treatment effect (F
4,16
= 0.17, p =
0.953) for % leaf pack loss (Fig. 4.1). High among-treatment block variability may have
been because of differences in water velocity at each experimental unit (mean %CV
within block = 29.72 and treatment = 34.76). Velocity ranged from 0.25 m/sec to 0.69
m/sec. There was no treatment effect on velocity (F
4,16
= 0.86, p = 0.511); however,
there was a marginally significant block effect (F
4,16
= 2.96, p = 0.052), suggesting that
122
velocity, through mechanical breakage, explained the high variability in leaf pack loss
during the experiment.
Effects of crayfish on macroinvertebrates.?The degree to which crayfish
influenced macroinvertebrate assemblages within leaf packs varied with treatment and
the macroinvertebrate measure. MANOVA showed an overall treatment effect for all
macroinvertebrate variables analyzed (Wilk?s ?, F
24,39
= 2.74, p = 0.002), but no block
effect (Wilk?s ?, F
24,39
= 0.605, p = 0.914). Most macroinvertebrate response variables
showed a significant difference in relation to the crayfish exclosure-enclosure
treatments. Overall, total macroinvertebrate density differed among treatments
(ANOVA, F
4,16
= 5.02, p = 0.008), being highest in the crayfish exclusion and lowest in
high-crayfish density and cage control treatments (Fig. 4.2A); a similar pattern occurred
for total biomass (F
4,16
= 3.94, p = 0.021, Fig. 4.2B), although the no-cage treatment did
not differ from the crayfish exclusion. Mean density of the mayfly Stenonema sp. also
differed among treatments (F
4,16
= 5.42, p = 0.004), being highest in crayfish exclusion,
low-density, and cage controls treatments, and lowest in the no-cage and high-density
treatments (Fig. 4.2C). Density of predacious Plecoptera followed a similar pattern (F
4,16
= 4.26, p = 0.015), except means were highest in exclusion and low-density treatments
and cage controls and lowest in the no cage and high-density treatments (Fig. 4.2D).
Mean Cheumatopsyche sp. density was highest in exclusions, intermediate in cage
control, and lowest in all other treatments (F
4,16
= 5.00, p = 0.008; Fig. 4.2E). Similar
patterns occurred for non-tanypodine Chironomidae (F
4,16
= 5.22, p = 0.005) and mean
Tipula sp. density (F
4,16
= 4.54, p = 0.012), except that the low-density crayfish
123
treatment was intermediate between the exclusion and the other treatments (Fig.
4.2F,G). Tanypodine chironomids showed no significant difference among blocks or
treatments.
In addition to an effect on Tipula sp. density, mean larval size of Tipula sp. also
strongly differed among treatments (F
4,16
= 9.88, p < 0.0001). Pairwise comparisons
showed that larval size in the crayfish exclusion was significantly higher than all other
treatments (Fig. 4.3) with larvae being almost twice as large in the crayfish exclusion
than in other treatments.
4.4.2 Foodweb analysis
The wide separation in C
13
and N
15
between 2 focal primary consumers (the
grazer Stenonema sp. consuming algae and the shredder Tipula sp. consuming
detritus, Fig. 4.4) suggested the presence of 2 distinct basal resources, algae and leaf
detritus. Crayfish position in the foodweb biplot indicated reliance on other
macroinvertebrates that obtained most of their energy from detritus (? = -0.28, Fig. 4.4).
In contrast, collector-filterer taxa (as Cheumatopsyche sp. and Chimarra sp.) received C
from a mixture of algae and detritus (? = 0.48). Unlike crayfish, other predacious
macroinvertebrates (as Perlesta sp. and Progomphus sp.) appeared to obtain most C
from grazers (? = 0.67, ?= 0.70), whereas other Odonata taxa (? = -0.26) and
Hexatoma sp. (? = 0.04) were more similar to crayfish in relying mostly on detritus as a
basal resource (Fig. 4.4). Last, benthic fishes in the food web appeared to receive C
from a combination of algae and detritus (Fig. 4.4).
124
The highest TP within the benthic food web was held by the blackbanded darter
(Percina nigrofasciata), with an absolute value of ~4. Crayfish held a TP (3.05) was
similar to predacious odonates (i.e., 3.24, 3.23, and 2.29, for Coenagrionidae,
Cordulegaster sp. (Odonata in Fig. 4), and Progomphus sp., respectively). TPs of
collector-filterers (caddisflies Cheumatopsyche sp. and Chimarra sp.) also were similar
to crayfish with absolute values of 2.97 and 2.87, respectively. Last, TPs of collector-
gatherer taxa (as non-tanypodine chironomids and Baetidae) were lower than crayfish,
with values of 2.56 and 2.12, respectively.
4.5 DISCUSSION
4.5.1 Influence on leaf litter breakdown
Our findings suggest that P. versutus may be similar other benthic
macroinvertebrate shredders in its inability to process leaf litter; however, it appears to
play a less important role in litter breakdown compared with other crayfish species
(Huryn and Wallace 1987, Parkyn et al. 1997, Usio 2000, Creed and Reed 2004). For
example, Huryn and Wallace (1987) found that leaf litter processing by the large long-
lived (~13 y) crayfish Cambarus bartonii was positively related to individual size. They
reported a litter consumption rate for this species to be 36 g dry mass m
-2
y
-1
, with its
greatest impact in late spring and summer when other shedder taxa were less abundant
or absent. In contrast, Usio and Townsend (2004) demonstrated that smaller-bodied
Paranephrops zealandicus crayfish (<23 mm orbital carapace length) had minimal or no
effect on litter breakdown. In our study, we observed P. versutus actively on leaf packs;
however, it is likely this species had little influence on overall leaf litter loss. One reason
125
why smaller-sized species such as P. versutus have limited impact on breakdown may
relate to latitudinal influences on growth and final size. In a study of crayfish across a
wide latitudinal gradient Momot (1984) suggested that individuals grow and mature
more slowly in cooler regions than in warmer regions, such that individuals in streams
from warmer regions may not reach sizes of species from streams in cooler regions.
This environmental influence on crayfish growth may have a substantial effect on a
crayfishes ability function like an omnivore, thus causing it to act more as a predator in
warmwater streams of the southeastern United States, and potentially in other similar
latitudes.
Researchers have speculated the primary reason why litter breakdown rates and
crayfish body size are related is because of ontogenetic differences in crayfish growth
rate, with older individuals growing more slowly and requiring less animal material to
maintain this lower growth rate than more rapidly growing younger crayfish. For
example, growth rate of Orconectes punctimanus from Missouri streams between 0- to
0.5-y was twice that of the 1.5- to 2.0-y old individuals (4.79 vs. 0.28 mg/mg AFDM/y,
Rabeni et al. 1995). It has been hypothesized that relative to older individuals younger
crayfish require a higher amount of animal protein to maintain their high growth rate, but
once they reach maturity this need is reduced, with a litter-based diet sustaining
metabolic demand (Lorman and Magnuson 1978, Momot 1995). In addition to crayfish
size, sex also can have a strong impact on litter breakdown, as males showing a
disproportionably higher effect on breakdown than females (Usio and Townsend 2002,
see also Chambers 1990). In our study, despite using only male crayfish no differences
126
in breakdown among treatments were observed; this result further supports the idea
that P. versutus has an extremely limited influence on leaf litter processing in streams.
4.5.2 Crayfish influence on macroinvertebrate assemblages
Unlike that for litter breakdown, results of our experiment suggest that P.
versutus has a significant effect on benthic macroinvertebrate assemblages within leaf
packs. Contrasting crayfish densities, particularly presence (vs. absence of P.
versutus), had a substantial influence on both benthic macroinvertebrate density and
biomass. However, P. versutus appears unlikely to act as an ecosystem engineer
because of its limited ability to affect litter breakdown; rather, biotic effects appear to be
from direct consumption of macroinvertebrates rather than indirect effects on benthos
through alteration of the leafpack habitat. Similar to our findings, one study within
macrophyte habitats of ponds reported that high crayfish density decreased
macroinvertebrate biomass and richness (Nystrom et al. 1996). However, other studies
have found that crayfish influence only certain macroinvertebrate taxa within the benthic
assemblage (Usio and Townsend 2002, 2004). Our findings suggest that P. versutus
has a greater influence on some macroinvertebrates compared to others.
Crayfish can be selective predators on benthic macroinvertebrates, altering prey
density and/or size structure (Crowl and Covich 1990, Weber and Lodge 1990, Lodge et
al. 1994). A primary reason for selective predation is that crayfish feed more on
sedentary (vs. mobile) taxa, which are less able to escape consumption (Nystrom et al.
1996, Usio and Townsend 2004); sedentary chironomid larvae often are a common prey
item (Whitledge and Rabeni 1997, Nystrom et al. 1996). In our study, a wide range of
127
taxa were affected by crayfish presence, even at low crayfish density; however, the
degree of vulnerability of individual taxa may be related to their mobility. Density of both
highly mobile Stenonema sp. and predacious Plecoptera nymphs (Acroneuria sp.,
Neoperla sp., Paragetina sp.) were negatively affected by crayfish, but only at high
crayfish density. Crayfish effects on these 2 groups likely occurred through indirect
emigration rather than from direct consumption. These more mobile taxa were less
prevalent in P. versutus guts (<10% of gut content for both groups, R. Mitchell,
unpublished data), suggesting that while they are prey items for P. versutus, they
compose a small portion of the overall diet.
Relative to mobile taxa, sedentary taxa (i.e., Chironominae and Cheumatopsyche
sp.) appeared more vulnerable to crayfish presence, occurring at low densities even
when crayfish density was low. Others have found chironomids to be vulnerable to
crayfish predation, although effects appear to be size class-specific. Usio and
Townsend (2004) found that medium- and large-sized tanypodine chironomid density
varied with crayfish density, with medium-size larvae being reduced in high-density
treatments and large larvae reduced in both high- and low-density treatments.
However, tanypods are more mobile than other chironomid taxa, whereas non-tanypods
(Chironominae) are relatively sessile and, thus, more vulnerable, usually remaining in
their tubes (Hershey 1986). Our study showed that non-tanypodine density was
substantially lower in all treatments except crayfish exclusion treatments. Additionally,
we found that tanypodine density did not differ between treatments, suggesting they
were less affected by crayfish than non-tanypod chironomids. This pattern also may
explain why sedentary net-spinning caddisflies (Cheumatopsyche sp.) were affected by
128
a range of crayfish densities in our study. Together, these findings suggest that P.
versutus greatly influences sedentary taxa, compared with more mobile taxa.
Density of Tipula sp., an abundant shredder in Choctafaula Creek, was reduced
in only the high-density crayfish treatment; larvae in the low-density treatment showed
an intermediate response compared with exclusion and high crayfish treatments.
However, mean size of Tipula sp. was strongly reduced in all treatments except those
where crayfish were absent. These data strongly suggest that P. versutus selectively
feeds on larger larvae and has a stronger effect on Tipula size structure than density.
Gut analysis of P. versutus verified Tipula sp. was consumed by crayfish, composing up
to 80% of P. versutus gut content (R. Mitchell, unpublished data), and this estimate is
likely to be conservative because of the digestive soft-body of Tipula sp. larvae. Others
also have reported higher effects of crayfish on prey size structure than density
(Nystrom et al. 1996, Usio and Townsend 2002, 2004), whereas others hypothesized
that crayfish indirectly influence prey by altering habitat conditions by bioturbation of
sediments (Creed and Reed 2004, Helms and Creed 2005). That leaf litter breakdown
did not differ among treatments suggests that P. versutus compensated for shredder
taxa (i.e., Tipula sp.) loss in the crayfish enclosure treatments. The relatively high
density and large size of some taxa in the exclusion treatment suggests that crayfish
probably had a more direct predatory influence on Tipula, which may apply to other
sedentary prey with wide size spectra (Usio and Townsend 2002).
129
4.5.3 Crayfish trophic relationships in leaf litter food webs
Stable isotope analyses of the leaf litter food web also indicated that P. versutus
is an important benthic predator. Other research has indicated that stable isotope
analysis is a good means of quantifying crayfish energy sources and thus indicating its
trophic position (Whitledge and Rabeni 1997, Nystrom 2005). Indeed, others using
stable isotope and gut content analyses have concluded crayfish are important
predators that consume as much animal material as all other benthic predators
combined (Rabeni et al. 1994). In our study, it appears P. versutus relies on taxa that
consume a greater amount of leaf litter than autotrophic matter; as a result, their
absolute trophic position is similar to other important benthic macroinvertebrate
predators, such as Odonata, but higher than predacious Plecoptera. Our results also
showed that taxa supported either completely or partially by primary production (i.e.,
algae) were enriched in N
15
compared to taxa supported by detritus. This pattern may
explain why some taxa, such as Cheumatopysche sp. and Chimarra sp., were
determined to be at a higher trophic level than would have been expected if the entire
food web was supported on detritus alone. Others have shown that many predaceous
stoneflies exhibit ontogenetic shifts from a herbivore-detritivore to a carnivorous diet,
which suggests that a predator?s trophic position will be reduced relative to predators
with a less variable diet over the course of its life history (Fuller and Stewart 1979,
Feminella and Stewart 1986). If P. versutus is predacious through most of its life, then
this may explain why this species has a higher trophic position than other benthic
invertebrate predators with more variable diet. Our results also suggest that P. versutus
influence on Stenonema sp. and predacious Plecoptera is indirect because, unlike
130
these taxa, most of its C appears to come from leaf litter rather than autotrophic
sources.
Our results and those from other studies (Huryn and Wallace 1987, Usio 2000,
Helms and Creed 2005) suggest that crayfish can have a substantial influence on
macroinvertebrate assemblages in streams. However, unlike other studies that have
focused on large long lived species, our findings suggests small short-lived crayfish may
have a different influence on stream ecosystems than larger species, acting less as an
omnivore or ecosystem engineer, and more like a predator. These findings further help
our understanding of the role crayfish play in heterotrophic ecosystems. Even though
this crayfish appears to play less of a role on basal resource processing such as leaf
litter breakdown, it still appears to have a substantial influence on the benthic
macroinvertebrate assemblages.
Our findings extend an understanding of the influence of crayfish from lower
temperate latitudes on stream ecosystem food webs; however, more experimental
evidence documenting the impact of small crayfish species from warmer latitudes and
from more sandy streams is needed, and further comparison to previous studies of
crayfish needed to fully assess the difference that crayfish may play in warmer sandy
coastal plain stream systems.
131
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137
Figure 4.1. Mean (? 1 SE) % remaining of American beech leaf litter within contrasting
crayfish density treatments. Differences among treatments are designated by different
letters using Tukey?s pair-wise comparisons and treatments with the same letter were
not significantly different. Treatments were crayfish exclusion (E), 1 crayfish enclosure
(1C), 3 crayfish enclosure (3C), open cage (CC), and no cage (NC).
138
E1C3CC NC
%
Le
af Loss
0
20
40
60
80
100
139
Figure 4.2. Mean (? 1 SE) abundance of focal macroinvertebrate taxa in contrasting
crayfish density treatments. A.?macroinvertebrate density, B.?macroinvertebrate
biomass, C.?log
10
-transformed Stenonema sp. density, D.?log
10
-transformed
predacious Plecoptera density, E.?Cheumatopsyche sp. density, F.?non-Tanypodine
Chironomidae density, G.?Tipula sp. density. Differences among treatments are
shown by different letters using Tukey?s pair-wise comparisons and treatments with the
same letter were not significantly different. Treatments were crayfish exclusion (E), 1
crayfish per enclosure (1C), 3 crayfish per enclosure (3C), open cage (CC), and no
cage (NC).
140
E1C3CCCNC
No
.
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F G
D
141
Figure 4.3 Mean (? 1 SE) length of Tipula sp. larvae in contrasting crayfish density
treatments. Differences among treatments are designated by different letters using
Tukey?s pair-wise comparisons such that treatments with the same letter were not
significantly different. Treatments were crayfish exclusion (E), 1 crayfish per enclosure
(1C), 3 crayfish per enclosure (3C), open cage (CC), and no cage (NC).
142
Excl 1 cray 3 cray Cage control No cage
Length (mm) of
Tipula
sp.
0
5
10
15
20
25
A
B
B
B
B
143
Figure 4.4. Stable isotope cross-plots of the Choctafaula Creek benthic food web. All
?
15
N and ?
13
C values are mean values (? 1 SE) from 3 to 5 samples per taxon, except
P. versutus, which was composed of 30 individuals.
144
?
13
C
-38-36-34-32-30-28-26
?
15
N
-2
0
2
4
6
8
10
12
14
Stenonema sp.
Tipula sp.
P. versutus
Benthic fishes
Collector-gathers
Collector-filters
Predacious
Plecoptera
Progomphus sp.
Odonata
Leaf litter
145
5. CONTRASTING DIET AND PRODUCTION OF THE CRAYFISH
PROCAMBARUS VERSUTUS FROM 3 COASTAL PLAINS STREAMS
IN WESTERN GEORGIA, USA
5.1 SUMMARY
We quantified diet, density, growth, and secondary production of populations of the
crayfish Procambarus versutus (Cambaridae) in 3 small coastal plain streams at Fort
Benning, Georgia, USA. Study streams had strongly contrasting levels of coarse woody
debris (CWD, 3?13% of streambed surface) and benthic particulate organic matter
(BPOM, particles ?2 cm diameter; 1?5% of bed substrate). We explored to degree to
which habitat and basal resource availability influenced crayfish production and trophic
position in benthic food webs. Instream habitat (as CWD) was assessed annually and
BPOM was assessed seasonally over the study. Crayfish were sampled monthly for 1y,
to estimate population density, individual size, and secondary production. In addition,
we sampled crayfish during spring and fall to assess trophic position. Mean annual
crayfish density and biomass was lowest in the stream with the lowest CWD and
BPOM, whereas density was highest in the high-CWD/BPOM stream, but not biomass.
Mean size of crayfish was highest in the intermediate-CWD stream. Annual crayfish
production tracked instream CWD, being highest in the high-CWD stream, intermediate
in the intermediate-CWD stream, and lowest in the low-CWD stream. Diet and stable
isotope analysis showed that annual production was derived primarily from consumption
146
of animal matter and secondarily from plant detritus. Variation in crayfish density,
biomass, size, and production may be explained by among-stream differences in food
quality and associated feeding behavior.
5.2 INTRODUCITON
Crayfish play an important role in many freshwater ecosystems, functioning as
processors of detritus, predators of other macroinvertebrates, and as important food
resources for fishes and terrestrial vertebrates (Taylor et al. 2007). Crayfish also
compose a significant portion of the benthic macroinvertebrate biomass in many
freshwater ecosystems (often >50% of total biomass; Huryn and Wallace 1987, Momot
1995), so changes in abundance of crayfish populations resulting from human
perturbations (e.g., habitat loss, chemical pollution, nonnative species invasions, see
Allan and Flecker 1993, Richter et al. 1997) could alter ecosystem function (Taylor et al.
2007).
Crayfish use a wide range of biotic and abiotic benthic habitats (e.g., gravel,
cobbles, submersed vegetation, wood, etc.) as refuge from predation by fishes and
terrestrial vertebrates (Stein 1977). Research has shown the importance of habitat
availability in reducing the impact of predation on crayfish populations; however,
surprisingly few studies have assessed the role of habitat conditions on intrinsic factors
regulating crayfish population dynamics such as growth and production (Stein 1977,
Mitchell and Smock 1991, Contreras-Balderas and Lozano-Vilano 1996). In addition,
most crayfish research has been done in upland streams containing primarily gravel
and/or cobble substrate (Momot 1995, Whitledge and Rabeni 1997, Evans-White et al.
147
2003), with virtually similar studies conducted in low-gradient sandy streams. High-
gradient streams often show a diverse mix of abiotic (gravel, cobble, boulder), and biotic
(CWD, macrophytes) substrates and, thus, high structural heterogeneity. In contrast, in
low-gradient sandy streams CWD is the main structural feature (Benke et al. 1984,
Roeding and Smock 1989, Rinella and Feminella 2005); hence, abundance of CWD can
be the primary determinant of benthic habitat in lowland streams (Huryn and Wallace
1987, Mitchell and Smock 1991).
Few studies have investigated the importance of available CWD habitat on
crayfish and macroinvertebrate populations in lowland streams. In addition to providing
primary habitats, CWD also retains benthic particle organic matter (Smock et al. 1989,
Maloney and Feminella 2006), which can increase energy flow from primary to
secondary consumers in benthic food webs (Wallace et al. 1997). For example, Hall et
al. (2000) found that reduction of leaf litter caused energy flow to become more even
across taxa and increased the number of predator pathways, which resulted from
increases in both prey abundance and diversity. The polyphagous behavior of crayfish,
however, may reduce their dependency on any single food resource, although crayfish
populations may still depend on CWD as a refuge from predators (interspecific and
intraspecific) (Huryn and Wallace 1987).
The purpose of our study was to quantify the influence of contrasting abundance
of instream CWD on crayfish population dynamics in sandy streams where CWD is the
primary benthic habitat. Specifically, we explored if crayfish density, biomass, diet, and
production would track variation in streams showing contrasting CWD abundance. We
predicted that high instream CWD would be associated with high crayfish density,
148
biomass, and secondary production because of high survival of individual crayfish over
time. We also assessed diet composition and trophic position of crayfish among
streams with contrasting CWD. Here, we predicted that high CWD would be associated
with high benthic particulate organic matter retention and macroinvertebrate density,
which, in turn, would increase 1) the amount of detrital matter in crayfish diets, and 2)
crayfish trophic position through high availability of prey resource abundance.
5.3 METHODS
5.3.1 Study streams
The study was done in small catchments at the Fort Benning Military Installation
(FBMI) in west-central Georgia (Fig. 5.1). FBMI is in the Southeastern Plains Level-3
ecoregion (Omernik 1987) encompassing an area of 735 km
2
, with a humid and mild
climate and year-round precipitation (mean = 105 cm/y). The predominant land use is
military training and includes dismounted infantry, tracked-vehicle maneuvers (i.e.,
tanks), heavy weapons usage, and airborne training drop zones. Upland vegetation in
study catchments consisted of longleaf pine (Pinus palustris) and loblolly pine (P.
taeda), with some hickories (Carya spp.), dogwood (Cornus florida), and oaks (Quercus
spp.). Riparian vegetation is largely intact (canopy coverage often >90%, Maloney et al.
2005), and was dominated by mesic hardwoods including sweetbay magnolia (Magnolia
virginiana), water oak (Q. nigra), yellow poplar (Liriodendron tulipifera), red maple (Acer
rubrum), black gum (Nyssa sylvatica) and sweet gum (Liquidambar styraciflua). Land
management at FBMI includes extensive restoration long-leaf pine forests by use of
149
selective harvesting and control burning to reduce density of nonnative trees (USAIC
2001, Dale et al. 2002).
Three low-order streams (1 per catchment) with bed substrate primarily of sand
and clay were selected for study. Study streams showed generally similar
physiocochemical conditions, although catchment size differed somewhat and affected
parameters such as stream depth and discharge (Table 5.1). Dissolved O
2
(DO) also
varied among streams, with SBT having the highest DO, and KMC and SBT having
similar DO (Table 5.1). Conductivity was uniformly low among study streams, ranging
from 14.3 ? 0.63 ?S/cm (mean +1SE) in BCT to 22.6 ? 3.2 in SBT (Houser et al. 2006).
5.3.2 Study animal
We studied the crayfish Procambarus versutus (subgenus Pennnides), which
was common in the study streams, FBMI in general, and throughout the Southeastern
Plains of Alabama, Georgia, and Northern Florida (Hobbs 1984). This species is
confined to lotic systems and occurs across a wide size range of sandy streams
containing variable amounts of coarse woody debris and leaf litter; it also been
associated with beds of Orontium aquaticum L. (Hobbs 1981). Promcambarus versutus
is a tertiary burrower, showing little or no burrowing behavior (Hobbs 1981), and is small
compared to other species in the genus with a maximum size of ~39 mm carapace
length (CL, first-form male). Little is known about the biology of this species other than
its general habitat and life cycle. Hobbs (1981) reported that first-form males occur
year-round and females in berry (reproductive state) occur in April. In our study, we
also found first-form males year-round, although females in berry were found in late
150
April and July in SBC (personal observations). No previous studies have examined the
feeding habitats of this species, and ours also is the first study investigating production
and trophic position of this species.
5.3.3 Coarse woody debris and benthic particulate organic matter sampling
To assess among-stream differences in habitat availability for P. versutus, we
used a modified transect method to quantify the relative abundance of instream CWD
associated (Wallace and Benke 1984). CWD surveys were conducted annually in
spring 2002 and 2003 by measuring all live, dead-submerged, and dead-buried wood
pieces >2.5 cm in diameter in 15 cross-stream transects per stream. Area sampled for
CWD included a 0.5 m upstream and downstream (1-m swath) along the center of the
cross-stream transects. CWD data were converted to planar area (m
2
of CWD per m
2
of stream bed) by multiplying the CWD diameter by length and then dividing by the area
sampled within each transect. We then expressed CWD abundance as an areal
percentage of the streambed area. Live wood was combined with dead wood in our
surveys because some sites had prominent exposed roots in the stream bed, which can
provided function similarly to dead wood as benthic habitat and/or a source of organic
matter retention.
We quantified abundance of benthic particulate organic matter (BPOM) using
sediment cores (PVC pipe, area = 2.01 cm
2
) taken from the upper 10 cm of the stream
bed (n = 24/stream/date) seasonally (spring, summer, winter), with 12 cores collected
randomly from both the thalweg (mid-channel) and the outer-third of the wetted channel.
In the laboratory, BPOM samples were oven-dried at 80?C for 24-48 h, desiccated and
151
weighed to determine total dry mass, and then ashed in a muffle furnace at 550?C for 3
h, desiccated, and reweighed. %BPOM was determined as the difference between the
dry and ashed masses divided by the total dry mass (Minshall 1996).
5.3.4 Crayfish sampling
We sampled P. versutus (hereafter ?crayfish?) monthly from each stream to
estimate population density, biomass, mean size, and production. Crayfish were
sampled from November 2002 to November 2003 using kick seines downstream of a
quadrate (area = 1 m
2
; mesh size = 0.32 mm; 5 samples/stream). Sampling usually was
done between 0900 and 1300 standard time, but 2 additional nighttime samplings were
done (April and September 2003) to ensure that capture rates did not vary over the 24-h
day-night cycle. Because of this species non-borrowing behavior (Hobbs 1981), the
non-significant difference between the daytime and nighttime sample suggests that the
daytime sampling adequately represented the crayfish population of each stream. Five
samples were collected randomly over a 100-m reach in each stream per date. All
crayfish collected were sexed and measured for carapace length (CL, nearest 0.1 mm)
in the field, and then returned to the collection point.
5.3.5 Crayfish density, biomass, and production
Crayfish density was estimated from captured individuals (from 1-m
2
quadrats,
see above), and enumerated in the field, whereas crayfish biomass was estimated from
CL using the Cambaridae length-biomass regression equation from Benke et al. (1999).
Biomass estimates was then converted to stream-specific monthly ash free dry mass
152
(AFDM)/m
2
. Monthly size class distribution was based on separating individuals into 5-
mm intervals (i.e. size class 1 = 0-5 mm; size class 2 = 6-10 mm; etc).
Crayfish production (P) was estimated using the size-frequency method (Hynes
and Coleman 1968, Hamilton 1969, Benke 1984). This method estimates a mean
cohort from samples taken throughout the year, and is the appropriate method in cases
when an actual cohort cannot be followed over time (Benke 2007). The mean cohort is
determined from the size-specific density (annual weighted means), and is assumed to
approximate the survivorship from one size class to the next. The size-frequency
method first determines production lost between adjacent size classes, by multiplying
mortality between adjacent size classes (?N: see table 5.2) by the mean biomass of
adjacent classes (W : see table 5.2) and then by the number of size classes (6 size
classes). Total production is then calculated by summing each individual size-specific
production loss. The size-frequency method assumes a development time of 1 y;
however, previous research has suggested that P. versutus has a lifespan of at least 2
y. For this reason, the production must be corrected by multiplying by 12/cohort
production interval (CPI), which we assumed was 24 mo, the interval defining the
lifespan of an individual of this species. Annual production/biomass ratios (P:B ) were
calculated for each stream from the mean annual biomass and annual production data
to estimate crayfish turnover rate (Benke 1984, 1993, 2007).
5.3.6 Crayfish diet and trophic position
We used stable N and C isotope ratios (?
15
N and ?
13
C, respectively) to generate
simplified food webs and determine crayfish trophic position. Additionally, crayfish diet
153
data were used to estimate the amount of each food resource that contributed to annual
crayfish production. Crayfish were collected in April 2006 (n = 175) and October 2006 (n
= 189) for diet analysis (~60 per stream). Thirty-three and 50 crayfish were collected in
October 2005 and October 2006, respectively, for stable isotope analysis. Crayfish
collected for stable isotope and diet were transported on ice to the laboratory and then
frozen (?10?C) until processed. Only crayfish tail muscle was used for the stable
isotope analysis. Crayfish used for diet analysis had their stomachs removed and
flushed into a gridded Petri dish, distributed evenly, and examined at 40x under a
dissecting microscope. Gut contents were sorted into 4 categories: sediment, detritus,
animal, or diatom/algae, and the relative composition of each category was estimated
as an areal percentage of the total gut composition (Helms and Creed 2005). We
further separated animal material into finer taxonomic categories, when possible. In
addition, we determined organic matter content of crayfish diets by flushing the gut
contents into pre-weighed aluminum dishes, drying samples at 60?C for 48h,
desiccating and weighing them, ashing them at 550?C for 3 h, and then re-desiccating
and weighing them to determine % AFDM (Minshall 1996). Proportional diet and AFDM
content data were analyzed for normality and, if non-normal, were arcsine-transformed
(Zar 1999) before comparing them among streams using one-way ANOVA.
We estimated material flow between basal resources and crayfish (as mg AFDM
m
-2
y
-1
)
for each stream, using the trophic basis of production method (Benke and
Wallace 1980, Benke et al. 2001). Briefly, we calculated total ingestion by individual
crayfish from annual crayfish production estimates divided by gross production
efficiency (GPE), which is equal to assimilation efficiency (AE = assimilation/ingestion)
154
multiplied by net production efficiency (NPE = production/assimilation). Crayfish AE
varies greatly with their diet, so we used AE values of 90% for animal matter, 40% for
algae, and 14% for leaf detritus based on data from Whitledge and Rabeni (1997). We
used an NPE value of 50% based on data from large predacious and omnivorous
stream macroinvertebrates (Benke and Wallace 1980, Smock and Roeding 1986, Smith
and Smock 1992, Benke et al. 2001). Finally, mean trophic position (TP) based on gut
content for crayfish was calculated as 1 plus the sum of the TP of the food item
multiplied by its fraction consumed by crayfish. For this calculation, detritus and
algae/diatoms would be considered at a TP = 1; an organism feeding only on detritus
(e.g. Tipula sp.) would be considered at TP = 2; and we assumed that animals feeding
on other animals (e.g. predacious Plecoptera) would be considered at TP = 3. We only
did analyzed gut content analysis of crayfish, so the above TPs were assumed for each
of the food items consumed by crayfish.
We used stable N isotope ratios (?
15
N) to assess the stream-specific level of
15
N-
enrichment and TP of crayfish sampled in autumn for 2 consecutive years (2005 and
2006, n = 35 and 49, respectively). We also quantified basal resources (as submerged
leaf litter) during both years (n = 4 per stream). Because of high variability in estimating
basal ?
15
N among streams, we standardized ?
15
N samples for each stream by setting
the mean basal resource (i.e. leaf litter) TP = 1. Next, we subtracted the difference
between the mean basal resource from mean crayfish ?
15
N value for that stream
(Cabana and Rasmussen 1996, Vander Zanden et al. 1997). Once we adjusted mean
crayfish ?
15
N, TP was determined as:
TP = ? +(?
15
N
crayfish
??
15
N
base
) / ?
N
155
where ? is the TP of leaf litter (i.e. 1) used to estimate ?
15
N
base,
?
15
N
crayfish
is the isotope
signature of an individual crayfish, ?
15
N
base
is the mean isotope signature of the basal
resource (litter), and ?
N
is the trophic fractionation of N, reported as 3.4 ? per tropic
level (Hershey et al. 2007). We used one-way ANOVA to test for differences in crayfish
levels of
15
N enrichment and TP among streams.
5.4 RESULTS
5.4.1 CWD and BPOM
CWD relative abundance (as % of the stream bed surface as CWD) significantly
varied among streams from a low of 3.26% in SBT to a high of 15.13% in BCT (F =
13.39, p < 0.0001). % CWD values in BCT and KMC were significantly higher than
SBT, whereas the difference in % CWD between BCT and KMC was nonsignificant
(Fig. 5.2). The ratio of mean CWD to mean wetted stream width was highest in BCT
(12.61), lowest in SBT (2.50), and intermediate in KMC (4.30).
% BPOM values from mid-channel and near-bank were similar, so these data
were combined for each stream. Among-season variation in % BPOM was low in KMC
and SBT (<2 mg AFDM/m
2
), and somewhat more variable in BCT (~4-6 mg AFDM/m
2
,
depending on season; Fig. 5.3). Among-stream patterns in % BPOM overall were
similar, being highest in BCT and lowest in KMC and SBT (Fig. 5.3). % BPOM in BCT
was higher than KMC and SBT in each season (spring: F = 19.54, p < 0.0001, summer:
F = 17.25, p < 0.0001, F = 7.61, p = 0.002; Fig. 5.3).
156
5.4.2 Crayfish density, biomass, size, and production
Daytime and nighttime sampling showed similar numbers of crayfish collected
during spring 2003 (F = 0.92, p < 0.36) and summer 2003 (F = 0.87, p < 0.28), so we
assumed that daytime sampling adequately reflected true abundance. Monthly crayfish
density varied seasonally, with highest densities in early spring and fall (Fig. 5.4A).
Among streams, BCT showed the highest density and SBT showed the lowest, whereas
KMC had intermediate densities. Biomass was lowest in winter and highest throughout
summer and early fall, especially in BCT (Fig. 5.4B). Mean crayfish size (as CL)
followed the same seasonal pattern as biomass although, unlike density and biomass,
monthly CL was highest in SBT especially in June and October (Fig. 5.4C).
Examination of crayfish size-frequency distributions did not easily suggest a 2-y
lifespan, hence the reason for using the size-frequency method to estimate production
for the 3 populations (Fig. 5.5).
Annual mean density ranged from 1.09 individuals/m
2
in SBT to 5.06
individuals/m
2
in BCT, Fig. 5.6). Annual density was significantly different among
streams (F = 33.89, p < 0.0001; Fig. 5.4A), with densities in BCT being higher than
KMC and SBT, and higher in KMC than SBT. Mean annual biomass ranged from 211.8
to 587.0 mg AFDM/m
2
(Fig. 5.4B, Fig. 5.6), which also differed among streams (F =
3.91, p = 0.029), being highest in BCT and lowest in SBT; biomass in KMC did not differ
from BCT or SBT. Mean annual CL also differed among streams (F = 5.13, p = 0.007)
and ranged from 11.6 mm in BCT to 13.4 mm in KMC (Fig. 5.4C). Tukey?s pairwise
comparisons showed that CL in KMC was higher than BCT, but because of high
among-date variation CL in SBT did not differ from KMC or BCT (Fig. 5.4C).
157
Annual crayfish production ranged from a low of 566.80 mg AFDM/m
2
/y in SBT
(Table 5.2) to a high of 1870.83 mg AFDM/m
2
/y in BCT (Table 5.4). Annual P:B was
highest in BCT (3.29, Table 5.4), lowest in KMC (2.50, Table 5.3), and intermediate in
SBT (2.57, Table 5.2).
5.4.3 Crayfish diet and trophic position
Amorphous detritus was the predominant food type in crayfish diets from all 3
streams, composing >50% of the total diet (Fig. 5.7). Animal matter was the 2
nd
-most
abundant food type (15?20%), with diatoms composing a comparatively smaller
proportion of the diet (0.16 to 2.8%). Detritus was the predominant food type in all
crayfish diets, but its relative amount differed among streams (spring 2006, F = 7.15, p
= 0.001; fall 2006, F = 5.87, p = 0.004). Pairwise comparisons revealed that BCT and
KMC were similar to each other, which were both higher than SBT (Fig. 5.7). The % of
animal matter in the diet did not differ among streams in spring 2006 but differ in fall
2006 (F = 7.15, p = 0.001), with BCT and KMC both showing higher % animal matter in
the diet than SBT (Fig. 5.7). The % diatom category strongly differed among streams in
both seasons (spring 2006, F = 6.02, p = 0.003; fall 2006, F = 15.00, p < 0.0001), with
KMC showing higher % diatoms than both BCT and SBT (Fig. 5.7). In addition to
among-stream variation in food items, the proportion of the total diet as organic matter
also varied (Fig. 5.8). % organic matter was lower in SBT than BCT and KMC in both
seasons (F = 14.20, p < 0.0001, F = 4.41, p = 0.018), whereas BCT and KMC did not
differ (Fig. 5.8).
158
Animal matter contributed most to annual crayfish production, followed by
detritus and diatoms, in all 3 streams (Tables 5.5, 5.6, 5.7), accounting for 66.89% of
production in BCT, 62.44% in KMC, and 63.57% in SBT. In contrast, detritus accounted
for only 31.15% of production in SBT, 36.19% in BCT, and 34.47% in KMC. Diatoms
accounted for a substantially lower amount of crayfish annual production than animal
matter or detritus (i.e., 3.09% in KMC, 1.24% in SBT, and 0.24% in BCT). Crayfish TP
calculated from gut content analysis showed little variation among streams, with SBT
having the highest TP (2.23), whereas KMC and BCT were almost identical with TP
values of 2.19 and 2.18, respectively.
Use of stable isotopes to estimate crayfish TP showed significant differences
among streams. In 2005, crayfish from SBT were less enriched in
15
N than KMC and
BCT (F
= 12.21, p < 0.0001, Fig. 5.9), whereas in 2006 crayfish in SBT were less
15
N-
enriched than KMC, but not different from BCT (F
= 8.42, p = 0.001, Fig. 5.9). Mean TP
of crayfish also differed among streams, with crayfish from SBT being lower than
crayfish from KMC and BCT in 2005 (F
= 12.09, p < 0.0001, Fig. 5.9); however, in fall
2006 only crayfish from SBT and KMC differed from each other; crayfish from BCT
showed an intermediate TP between KMC and SBT (F
= 8.45, p < 0.001, Fig. 5.9). TP
estimates from the stable isotope analysis were higher in both 2005 and 2006,
compared to the TP estimates from the gut content analysis.
159
5.5 DISCUSSION
5.5.1 Importance of CWD and its influence on basal resources
Instream habitat availability has been shown to influence both structure and
function of benthic macroinvertebrate assemblages, with decreases in both habitat
quality and quantity having negative effects on assemblages (Wallace and Benke 1984,
Bilby and Likens 1984, Benke and Wallace 1990, Maloney and Feminella 2006). Our
results also suggest that abundance of instream CWD has a substantial influence on
population density, production, diet, and trophic position of the crayfish Procambarus
versutus. However, our study included unreplicated streams of contrasting CWD, so
these results are only suggestive of the importance of CWD habitat on crayfish
populations. Few studies have investigated the influence of instream habitat availability
on crayfish populations across streams with varying habitat availability. Our research
thus adds to a general understanding of how CWD availability may influence benthic
macroinvertebrate assemblages in headwater systems of the southeastern US.
CWD is a key factor in retaining BPOM in a wide array of high- to low-gradient
streams (Bilby and Liken 1980, Bilby 1981, Smock et al. 1989, Wallace et al. 1995) and,
in many sandy low-gradient streams, instream CWD and roots from riparian vegetation
are the primary structures facilitating BPOM retention (Angermeirer and Karr 1984,
Smock et al. 1989). In our study, %BPOM was substantially higher in the stream
containing the highest CWD (BCT); however, and somewhat surprisingly, the
intermediate-CWD stream (KMC) did not display an intermediate %BPOM relative to the
low-CWD stream (SBT). One explanation for this disparity could be that our BPOM
sampling effort was inadequate to discriminate low levels of %BPOM in KMC and SBT.
160
Additionally, because of its smaller size relative to KMC, debris dams in BCT typically
crossed the entire channel, and accounted for a higher ratio of mean CWD to stream
width in BCT compared to KMC; in contrast, debris dams and logs in KMC rarely
crossed the entire channel and stream flow moved more easily around individual debris
dams or logs (R. M. Mitchell, personal observations). Smock et al. (1989) also found
that debris dams structure within the channel substantially influenced benthic organic
matter, with a stream with <50% perched logs (i.e. logs lying above stream channel or
only partially in stream channel) and only 21% of logs parallel to flow having ~9x as
much non-woody organic matter as the stream with >70% perched logs and ~50% of
the logs parallel to the flow.
Others have reported seasonal variation in organic matter storage in the stream
bed, with higher organic matter storage during and just after leaf fall, which decreases
with decomposition through spring and summer (Smock et al. 1989, Wallace et al.
1995). However, in our study there was no difference in % BPOM among seasons;
rather, %BPOM was highest in summer, at a time when other studies report lowest
BPOM storage (Smock et al. 1989). There are 2 possible explanations for this pattern.
First, several of the riparian tree and shrub species at FBMI show relatively slow
breakdown rates, including M. virginiana, N. sylvatica, rhododendron (Rhododendron
sp.), and American holly (Ilex opaca), and these litter inputs may persist longer in the
channel (Allan 1995), and drop their leaves later or continually throughout the year.
Second, high %BPOM in summer could have been resulted from drought conditions
over the study (R. M. Mitchell, personal observations), which could have decreased
processing rates. Others have equated the rapid decline of BPOM in late winter with
161
the increase in the number of high-energy flow events, and related increased
downstream transport of organic matter (Roeding and Smock 1989, Smock et al. 1989).
Additionally, drought conditions may cause trees to drop their leaves during summer
and thus increase the amount of BPOM during the summer, compared to winter BPOM
levels.
5.5.2 Crayfish density, biomass, and production
Crayfish often display habitat preferences and are thus influenced by habitat
quality (Huryn and Wallace 1987, Quinn and Janssen 1989, Mitchell and Smock 1991,
Jones and Bergey 2007). This prior research has focused on understanding crayfish
habitat use based on direct observation of habitat preference. However, unlike these
earlier studies we instead focused on understanding how instream habitat, in the form of
CWD, influenced P. versutus populations by quantifying CWD habitat at the reach scale
and relating it to population measures.
Direct complementarity between reach-scale crayfish density and CWD
abundance is consistent with observations by others. In a New Zealand stream,
densities of Paranephrops planifrons decreased with decreasing CWD as a function of
increasing catchment disturbance (Parkyn and Collier 2004). Unlike the latter study, P.
versutus density, biomass, and individual size did not show a similar pattern in our
study. The high and intermediate-CWD streams had similar crayfish biomass, both
being higher than the low-CWD stream, and mean size was highest in the high- and
intermediate-CWD and lowest in the low-CWD stream. It is possible that the similar
biomass observed in the high and intermediate-CWD streams was caused by higher
162
mean individual size in the intermediate-CWD stream and higher density in the high-
CWD stream, patterns that would suggest stream-specific variation in competition and
predation and their effects on crayfish biomass. Others have suggested that these
processes limit crayfish populations in combination with habitat availability (Stein 1977,
Mitchell and Smock 1991). In our study, high instream cover (as CWD) in the high-CWD
stream could have reduced intraspecific competition for available habitat, as well as
reducing predation because of high refuge, the combination of which would increase
survivorship. Alternatively, lower habitat availability in the intermediate-CWD stream
may have increased competition and individual mortaility, resulting in increased
individual size by reducing the abundance of smaller individuals in the population. Such
competition would be expected to occur in systems with minimal predator control of
crayfish by size-selective aquatic vertebrate predators (Stein and Magnuson 1976).
Such predation is unlikely in small streams at FBMI, as vertebrate predator abundance
is low (Maloney et al. 2006); however, the degree of crayfish consumption by terrestrial
predators, which can affect crayfish survivorship (Stein and Magnuson 1976), is
unknown. Others have reported that juvenile crayfish show high survival and growth
under high habitat complexity, especially when adult crayfish are present (Olsson and
Nystrom 2009). In our study, there was no evidence that adult crayfish directly affected
juveniles, although others have reported juveniles are less active during day and night
under low habitat complexity and when adults are present, which may reduce feeding
and decrease juvenile growth and survival (Olsson and Nystrom 2009).
Crayfish annual production in lotic ecosystems is highly variable, ranging from
200 to 8800 mg AFDM m
-2
y
-1
(Momot and Gowing 1977, Momot 1984, Huryn and
163
Wallace 1987, Mitchell and Smock 1991, Whitemore and Huryn 1999, Evan-White et al.
2003), which likely is caused by several environmental factors. Annual production of
crayfish from our study (530.15 ? 1779.17 mg AFDM m
-2
y
-1
) was within the low to
middle range of measured production for any stream. Others have observed that low
habitat availability strong influences crayfish production, and have suggested that low
productivity suboptimal conditions for growth (Mitchell and Smock 1989). However,
unlike annual production, annual P:B was in the upper end of ratios from other systems
(e.g., 0.5 ? 2.4; Momot and Gowing 1977, Momot 1984, Evan-White et al. 2003),
suggesting that turnover of P. versutus populations may be less influence by habitat
availability then population production. One possible reason for the low production of
crayfish populations relates to low overall productivity of these systems. Houser et al.
(2005) reported low gross primary productivity and high ecosystem respiration from
these and other streams at FBMI, suggesting that these systems are highly
heterotrophic. However, heterotrophy does not necessarily imply a system is
unproductive; but low basal resources in the form of allochthonous BPOM inputs in the
study streams may severely limit their productivity (Pimm 1984).
5.5.3 Crayfish diet and trophic position
The predominance of plant detritus in the diet of P. versutus, along with the
secondary importance of animal matter and diatoms, is consistent with other studies of
stream crayfish (Evans-White et al. 2003, Whitledge and Rabeni 1997, Momot et al.
1978). However, whereas plant detritus was the dominant component in the diets of all
3 crayfish populations studied, there was a difference in the amount of BPOM (primarily
164
allochthonous plant detritus) among streams, during both spring and fall. Crayfish from
both the high- and intermediate-CWD streams had significantly more plant detritus in
their diet compared to the low-CWD stream. This pattern may reflect differential BPOM
availability in the study streams and, thus, a potentially strong influence of BPOM on
crayfish diet. Individual P. versutus from SBT tended to show a higheer amount of
inorganic material in their gut compared to the other 2 streams, suggesting a reduced
food base in this stream. Catchment disturbance is likely to cause a decrease in BPOM
and previous research in FBMI streams found that %BPOM decreased with increasing
watershed disturbance (Maloney et al. 2005). Additionally, previous work at FBMI has
shown a direct link between several benthic macroinvertebrate parameters and
instream CWD (i.e. habitat) abundance, which, in turn, are both linked to catchment
disturbance (Maloney and Feminella 2006).
A somewhat surprising result was the high amount of inorganic material in
crayfish diets from the low-CWD stream (SBT) relative to BCT and KMC showing higher
CWD. Some studies have reported sediment constituting a large portion of crayfish
diets (Capelli 1980, Whiteledge and Rabeni 1997, Evans-White et al. 2003). However,
Helms and Creed (2005) reported that gut contents of Orconectes cristavarius were 50
to 100% sediment, suggesting this species actively consumes large amounts of
inorganic sediment, ostensibly to collect BPOM. In our study, P. versutus may show
similar sediment-based feeding in streams or conditions where plant detritus and animal
matter are low. In such streams particularly where sediment-laden BPOM is low, food
quality may significantly affect individual crayfish growth and survivorship.
165
After correcting the diet data for different AEs of the different diet components,
our estimates were similar to other studies (Whitledge and Rabeni 1997, Evans-White
et al. 2003). Animal matter contributed most to production, approximately twice as
much as plant detritus and considerably more than diatoms. We did not account for the
energetic influence of sediment to crayfish considerable production; however, others
have suggested crayfish may obtain energy from consumed sediment (Helms and
Creed 2005), largely from bacterial cells and exudates (Allan 1995, Hall and Meyer
1998). Future studies addressing the importance in conditioned sediments to crayfish
production may be needed to understand the energy sources available to crayfish more
fully.
Crayfish from the low-CWD stream (SBT) had the lowest
15
N enrichment for both
years of our study; relative to the high- and intermediate-CWD streams where
enrichment was less. This result suggests overall food quality is lower in the low-CWD
stream (SBT), as observed in the reduced detrital and animal matter in crayfish diets,
which, in turn, indicates that these crayfish are less likely to obtain adequate energy for
production. In addition, the trophic position of crayfish in SBT was lower than either of
the other study streams, suggesting that crayfish were feeding at a lower trophic level
and on lower-quality food than the other 2 streams. Others have shown that changes to
low habitat quality and food resources had bottom-up effects on crayfish populations,
specifically yielding smaller crayfish when food was limited by habitat conditions
(Nystrom et al. 2006). Others also have suggested that food resource alteration from
watershed disturbance may influence TP of predatory organisms (Parker and Huryn
2006), and result from higher TP and omnivores feeding behavior of crayfish,
166
disturbance is likely to impact crayfish similar to other benthic macroinvertebrates. We
did not sample the entire benthic macroinvertebrate assemblage; however, previous
research at FBMI indicated that increased disturbance and decreased CWD abundance
had negative effects on benthic macroinvertebrate assemblages in general (Maloney
and Feminella 2006). This result may suggest that benthic macroinvertebrate prey for
crayfish are reduced in SBT compared with KMC and BCT, which could explain both the
lower
15
N and TP in this stream.
In summary, our findings suggest that P. versutus may be influenced by instream
habitat conditions, which, in turn, have been shown to be influence by catchment
disturbance (Maloney et al. 2005). Multiple factors are attributable to the decline of
many crayfish species, including chemical pollution, introduction of nonnative species,
overexploitation, and habitat alteration linked to catchment land use (Richter et al. 1997,
Wilcove et al. 2000). Despite the importance of crayfish in many aquatic ecosystems,
>50% of all crayfish populations from North America are at risk of extinction; yet, there
remains only scant information on the life history and habitat requirements for most
species (Taylor et al. 2007). Understanding the influence of instream habitat conditions
on crayfish populations in general will aid in conservation efforts of this imperiled group.
Our study demonstrates that P. versutus populations exhibit considerable
variation in population and dietary measures, which appeared to track variation in
instream CWD abundance. Procambarus versutus populations appear denser under
conditions of high-CWD, however it also appears that mean size is highest under
intermediate-CWD populations. Under low-CWD conditions, P. versutus populations
appear to be highly impaired from both reduced habitat cover and food resource quality.
167
Even though P. versutus is a relatively widespread species, these results could be
useful in understanding how habitat degradation may influence crayfish populations,
and help further efforts to conserve more imperiled species of crayfish.
168
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Table 5.1. Watershed and physicochemical characteristics for streams where Procambarus versutus were collected.
Average stream slope (%) is from a 100 m stream reach where crayfish were collected. Mean temperature (?C) is the
mean annual temperature of each stream during the period crayfish were collected (Mean ?1SE). DO (dissolved oxygen,
mg/L), pH, and Ca
+
(mg/L) were taken from the downstream most point of study sites. Velocity (m/s), Depth (m), and
Wetted stream width (m) are reach averages from collection sites (Mean ?1SE). Discharge (m
3
/s) was taken from the
downstream most point of study sites.
Stream
Stream
code
Drainage
area (km
2
)
Mean
temperature
(?C)
Season
DO
(mg/L)
pH
Ca
+
(mg/L)
Velocity
(m/s)
Depth
(m)
Wetted
stream width
(m)
Discharge
(m
3
/s)
Bonham Creek BCT 0.75 16.78 (5.07) Spring 6.6 4.87 0.25 0.05 (0.03) 0.09 (0.02) 1.2 (0.14) 0.004
Tributary Summer 7.46 5.27 -- 0.03 (0.03) 0.24 (0.02) 1.1 (0.04) 0.001
Winter 8.36 6.42 0.28 0.06 (0.01) 0.19 (0.03) 1.0 (0.02) 0.005
Kings Mill KMC 3.69 16.98 (4.73) Spring 7.08 5.08 -- 0.13 (0.02) 0.21 (0.02) 2.1 (0.13) 0.037
Creek Summer 7.88 5.54 -- 0.13 (0.02) 0.22 (0.02) 1.9 (0.23) 0.020
Winter 7.23 7.50 0.26 0.09 (0.004) 0.21 (0.01) 1.8 (0.09) 0.029
Sally Branch SBT 1.95
17.25 (5.16) Spring 10.08 4.85 0.84 0.09 (0.01) 0.10 (0.01) 1.3 (0.09) 0.045
Tributary Summer 10.81 6.95 -- 0.08 (0.01) 0.07 (0.01) 1.3 (0.08) 0.007
Winter 11.36 6.50 1.44 0.08 (0.01) 0.09 (0.02) 1.3 (0.07) 0.025
177
Table 5.2. Calculation of P. versutus production by the size-frequency method, from
Sally branch tributary (SBT), Fort Benning Military Reservation, Georgia.
178
Size Group
Length
(mm)
Density
(No./m
2
)
N
Ind. Mass
(mg)
W
No. Lost
(No./m
2
)
?N
Biomass
(mg/m
2
)
B = N?W
Weight at
Loss
W =(W
1
+W
2
)/2
Weight
Loss
W ?N
?6
(mg/m
2
)
1 to 5 0.06 2.95 0.18
-0.43 10.66 -4.59 -27.56
6 to 10 0.50 18.37 9.05
0.20 38.49 7.70 46.19
11 to 15 0.29 58.61 17.13
0.06 153.00 9.41 56.49
16 to 20 0.23 247.39 57.09
0.06 446.13 28.60 171.59
21 to 25 0.17 644.88 107.48
0.15 816.17 123.47 740.83
26 to 30 0.02 987.45 0.02 19.75 987.45 19.75 118.49
Biomass = 210.68 Production (uncorrected) = 1133.59
Annual Production (corrected) = 566.80
Cohort P/B = 5.38
Annual P/B = 2.69
179
Table 5.3. Calculation of P. versutus production by the size-frequency method, from
Kings Mill creek (KMC), Fort Benning Military Reservation, Georgia.
180
Size Group
Length
(mm)
Density
(No./m
2
)
N
Ind. Mass
(mg)
W
No. Lost
(No./m
2
)
?N
Biomass
(mg/m
2
)
B = N?W
Weight at
Loss
W =(W
1
+W
2
)/2
Weight
Loss
W ?N
?6
(mg/m
2
)
1 to 5 0.23 2.92 0.67
-0.86 11.30 -9.73 -58.39
6 to 10 1.09 19.67 21.49
0.03 39.25 1.21 7.25
11 to 15 1.06 58.83 62.45
0.34 155.21 52.53 315.19
16 to 20 0.72 251.59 181.92
0.44 382.16 168.05 1008.30
21 to 25 0.28 512.72 145.27
0.21 699.42 144.37 866.20
26 to 30 0.08 886.11 0.08 70.89 886.11 70.90 425.33
Biomass = 482.69 Production (uncorrected) = 2622.27
Annual Production (corrected) = 1311.14
Cohort P/B = 5.43
Annual P/B = 2.72
181
Table 5.4. Calculation of P. versutus production by the size-frequency method, from
Bonham creek tributary (BCT), Fort Benning Military Reservation, Georgia.
182
Size Group
Length
(mm)
Density
(No./m
2
)
N
Ind. Mass
(mg)
W
No. Lost
(No./m
2
)
?N
Biomass
(mg/m
2
)
B = N?W
Weight at
Loss
W =(W
1
+W
2
)/2
Weight
Loss
W ?N
?6
(mg/m
2
)
1 to 5 0.52 2.84 1.49
-2.85 14.02 -39.92 -239.49
6 to 10 3.37 25.21 84.93
1.65 43.68 71.90 431.39
11 to 15 1.72 62.15 107.08
0.92 137.20 126.65 759.89
16 to 20 0.80 212.26 169.81
0.57 374.06 211.96 1271.79
21 to 25 0.23 535.85 125.03
0.19 835.33 156.36 938.14
26 to 30 0.05 1134.80 0.05 56.74 1134.80 56.74 340.44
Biomass = 545.08 Production (uncorrected) = 3741.65
Annual Production (corrected) = 1870.83
Cohort P/B = 6.86
Annual P/B = 3.43
183
Table 5.5. Calculation of production attributed to each food type and amount consumed
by P. versutus, from Sally branch tributary (SBT), Fort Benning Military Reservation,
Georgia (annual production = 566.80 mg/m
2
/yr).
184
Food type
in foregut
(%)
Assimilation
efficiency*
(AE)
Net
production
efficiency*
(NPE)
Relative
amount to
production
Production
attributed
to food
type (%)
Production
attributed
to food
type
(mg/m
2
/yr)
Gross
production
efficiency*
(AE x NPE)
Amount
food type
consumed
(mg/m
2
/yr)
Detritus 74.18 x 0.14 x 0.5
= 5.19 31.15 176.56 ? 0.07 = 2522
Algae/Diatoms 1.65 x 0.39 x 0.5
= 0.32 1.95 11.05 ? 0.20 = 55
Animals 24.17 x 0.92 x 0.5
= 11.12 66.89 379.13 ? 0.46 = 824
Chironomidae 20.22 x 0.92 x 0.5
= 9.30 55.94 317.07 ? 0.46 = 689
Tipulidae 1.48 x 0.92 x 0.5
= 0.68 4.07 23.07 ? 0.46 = 50
Ephemeroptera 0.00 x 0.92 x 0.5
= 0.00 0.00 0.00 ? 0.46 = 0
Trichoptera 1.36 x 0.92 x 0.5
= 0.62 3.74 21.20 ? 0.46 = 46
Predacious
Plecoptera
0.24 x 0.92 x 0.5
= 0.11 0.68 3.85 ? 0.46 = 8
Non-predacious
Plecoptera
0.88 x 0.92 x 0.5
= 0.40 2.46 13.94 ? 0.46 = 30
185
Table 5.6. Calculation of production attributed to each food type and amount consumed
by P. versutus, from King?s Mill creek (KMC), Fort Benning Military Reservation,
Georgia (annual production = 1311.14 mg/m
2
/yr).
186
Food type
in foregut
(%)
Assimilation
efficiency*
(AE)
Net
production
efficiency*
(NPE)
Relative
amount to
production
Production
attributed
to food
type (%)
Production
attributed
to food
type
(mg/m
2
/yr)
Gross
production
efficiency*
(AE x NPE)
Amount
food type
consumed
(mg/m
2
/yr)
Detritus 63.72 x 0.14 x 0.5
= 5.27 34.47 457.94 ? 0.07 = 6542
Algae/Diatoms 2.04 x 0.39 x 0.5
= 0.47 3.09 40.51 ? 0.20 = 203
Animals 18.80 x 0.92 x 0.5
= 10.45 62.44 818.68 ? 0.46 = 1779
Chironomidae 12.06 x 0.92 x 0.5
= 6.70 42.89 562.34 ? 0.46 = 1222
Tipulidae 2.66 x 0.92 x 0.5
= 1.48 9.43 123.64 ? 0.46 = 269
Ephemeroptera 1.20 x 0.92 x 0.5
= 0.67 4.25 55.72 ? 0.46 = 121
Trichoptera 1.26 x 0.92 x 0.5
= 0.70 4.48 58.74 ? 0.46 = 128
Predacious
Plecoptera
0.14 x 0.92 x 0.5
= 0.08 0.46 6.03 ? 0.46 = 13
Non-predacious
Plecoptera
1.44 x 0.92 x 0.5
= 1.70 5.10 66.87 ? 0.46 = 145
187
Table 5.7. Calculation of production attributed to each food type and amount consumed
by P. versutus, from Bonham creek tributary (BCT), Fort Benning Military Reservation,
Georgia (annual production = 1870.83 mg/m
2
/yr).
188
Food type
in foregut
(%)
Assimilation
efficiency*
(AE)
Net
production
efficiency*
(NPE)
Relative
amount to
production
Production
attributed
to food
type (%)
Production
attributed
to food
type
(mg/m
2
/yr)
Gross
production
efficiency*
(AE x NPE)
Amount
food type
consumed
(mg/m
2
/yr)
Detritus 65.60 x 0.14 x 0.5
= 5.43 36.19 677.05 ? 0.07 = 9672
Algae/Diatoms 0.16 x 0.39 x 0.5
= 0.04 0.24 4.49 ? 0.20 = 22
Animals 17.56 x 0.92 x 0.5
= 9.76 63.57 1189.29 ? 0.46 = 2585
Chironomidae 10.32 x 0.92 x 0.5
= 5.74 37.39 699.50 ? 0.46 = 1521
Tipulidae 2.98 x 0.92 x 0.5
= 1.66 10.78
201.68 ? 0.46 = 438
Ephemeroptera 0.03 x 0.92 x 0.5
= 0.01 0.08 1.50 ? 0.46 = 3
Trichoptera 3.10 x 0.92 x 0.5
= 1.72 11.25 210.47 ? 0.46 = 458
Predacious
Plecoptera
0.17 x 0.92 x 0.5
= 0.09 0.63 11.79 ? 0.46 = 26
Non-predacious
Plecoptera
0.96 x 0.92 x 0.5
= 0.53 3.46 64.73 ? 0.46 = 141
189
Figure 5.1. Locations of study catchments within Fort Benning Military
Reservation, GA. The dotted line within the western portion of the military
reservation designates the Chattahoochee River. BCT (Bonham Creek
Tributary) is the high-CWD stream, KMC (King?s Mill Creek) is the intermediate-
CWD stream, and SBT (Sally Branch Tributary) is the low-CWD stream.
190
Georgia
Fort Benning
KMC
BCT
SBT
191
Figure 5.2. Mean (? 1 SE) percentage of stream bottom covered by coarse woody
debris (CWD) for each of the 3 study streams. Differences among streams are shown
by letters above bars such that streams with the same letter are not significantly
different (Tukey?s pairwise test).
192
BCT KMC SBT
%
CWD of
st
ream bott
om
0
2
4
6
8
10
12
14
16
18
20
a
a
b
193
Figure 5.3. Mean (? 1 SE) percentage of benthic particulate organic matter from
sediment core samples. Differences among streams are shown by letters above bars
such that streams with the same letter are not significantly different (Tukey?s pairwise
test). A= spring, B= summer, and C= winter.
194
% BP
OM (mg
A
FDM/m
2
)
0
2
4
6
8
10
0
1
2
3
4
5
6
7
BCT KMC SBT
0
1
2
3
4
5
6
7
a
b
b
a
b
b
a
b
b
A
B
C
195
Figure 5.4. Mean (? 1SE) monthly density (A), biomass (B), and individual size as
carapace length (C) of the crayfish Procambarus versutus within the 3 study streams.
196
Number of
c
r
ay
fi
s
h
/m
2
-5
0
5
10
15
20
Bonham Creek Tributary
King Mill Creek
Sally Branch Tributary
N
o
v
0
2
D
e
c
0
2
J
a
n
0
3
F
e
b
0
3
M
a
r
0
3
A
p
r
0
3
M
a
y
0
3
J
u
n
0
3
J
u
l
0
3
A
u
g
0
3
S
e
p
0
3
O
c
t
0
3
N
o
v
0
3
Carapace length
(m
m)
5
10
15
20
25
Bi
omas
s/
m
2
-200
0
200
400
600
800
1000
1200
1400
1600
1800
A
B
C
197
Figure 5.5. Monthly size frequency distribution of the crayfish Procambarus versutus
within the 3 study streams. Width of each bar represents the percentage of total
individuals within each size class.
198
0
2
4
6
8
10
12
Size
C
l
as
s
0
2
4
6
8
10
12
N
0
2
4
6
8
10
12
D J F M A M J J A S O
BCT
KMC
SBT
199
Figure 5.6. Mean (? 1SE) annual density and biomass of the crayfish Procambarus
versutus within the 3 study streams. Differences among streams for annual density and
biomass are shown by different letters, such that streams with the same letter are not
significantly different (Tukey?s pairwise test).
200
Bi
om
ass (m
g
AFDM
/m
2
)
0
200
400
600
800
Biomass
Density
(
i
ndiv
iduals/m
2
)
0
2
4
6
8
10
Density
BCT KMC SBT
201
Figure 5.7. Mean (? 1SE) diet of the crayfish Procambarus versutus within the 3 study
streams as % gut-content for 4 gut-content categories. A = BCT (Bonham Creek
Tributary), B = KMC (King?s Mill Creek), and C = SBT (Sally Branch Tributary).
202
0
20
40
60
80
Sediment/Unknow
Amorphous Detritus
Animal
Diatoms
A
Spring 2006 Fall 2006
0
10
20
30
40
50
60
G
ut co
n
t
ent (%
)
0
20
40
60
80
B
C
203
Figure 5.8. Mean transformed % organic content of the diet of the crayfish Procambarus
versutus within the 3 study streams. Differences between study streams are designated
by different letters using Tukey?s pair-wise comparisons and treatments with the same
letter were not significantly different. A= spring 2006, B = fall 2006.
204
BCT KMC SBT
0
20
40
60
80
100
40
50
60
70
80
90
100
%
organ
i
c gut content
a
a
b
a
a
b
A
B
205
Figure 5.9. Mean (? 1SE)
15
N values for the crayfish Procambarus versutus (A) and
mean (? 1SE) crayfish trophic position (B) for fall 2005 and 2006. Within-year
differences among study streams are designated by letters above bars such that
streams with the same letter within a given year are not significantly different (Tukey?s
pair-wise test).
206
Mean Cray
f
i
sh
?
15
N
4.0
4.5
5.0
5.5
6.0
6.5
7.0
BCT
KMC
SBT
ab
a
ba
a
b
Fall 2005 Fall 2006
Trophic Position
2.0
2.2
2.4
2.6
2.8
3.0
ab
a
a
a
b
b
A
B