COMMUNITY STRUCTURE OF FRESHWATER MUSSELS
(BIVALVIA: UNIONIDAE) IN COASTAL PLAIN STREAMS
OF THE SOUTHEASTERN UNITED STATES

By

JAYNE BRIM BOX

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

UNIVERSITY OF FLORIDA

ACKNOWLEDGMENTS

I am appreciative of and would like to thank the following individuals for their
contributions to this project: Field Work: Andre Daniels, Ricardo Lattimore, Christine
O'Brien, Rob Robins, Stacy Rowe, Tim Hogan, Shane Ruessler, and Doug Weaver.
Laboratory Work: Amy Croft, Hannah Hamilton, Betsy Mueller, and Avo Oymayan,
Florida Caribbean Science Center, Gainesville, Florida. The above individuals spent
many long hours either collecting or processing samples, and to them I am greatly
indebted. I thank Noel Burkhead and Howard Jelks, who generously gave me laboratory
space to run experiments. I thank Bob Dorazio for the many hours he spent designing
this project and tutoring me on the nuances of statistical analysis. I thank Bob Butler of
the U.S. Fish and Wildlife Service for his support of this project and his efforts in
obtaining funding. I thank the five members of my committee, Loukas Arvanitis,
Katherine Ewel, Joann Mossa, Kenneth Fortier, and James D. Williams, who provided
unending guidance and support throughout this project. I especially thank Jim Williams
for his guidance, knowledge, and insights. To him I am greatly indebted. Funding for
this work was provided by the Florida Caribbean Science Center, Gainesville, Florida,
and the U. S. Fish and Wildlife Service, Jacksonville, Florida.

11

TABLE OF CONTENTS

page

ABSTRACT

CHAPTERS

1 INTRODUCTION 1

2 STUDY AREA 6

3 STREAMBED SUBSTRATE PROPERTIES 9

Introduction 9

Methods 12

Results 18

Discussion 28

4 ROLE OF ECOLOGICAL FACTORS AT THREE SPATIAL SCALES

Introduction 38

Methods 40

Results 47

Discussion 57

Stream Size 57

Substrate 58

Fish 60

Mussel/Fish Relationships 62

5 RESPONSE TO CATASTROPHIC BURIAL 65

Introduction 65

Methods 68

Results 71

Discussion 79

6 CONCLUSIONS 86

iii

APPENDIX

93

REFERENCES 95

BIOGRAPHICAL SKETCH 108

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

COMMUNITY STRUCTURE OF FRESHWATER MUSSELS
(BIVALVIA: UNIONIDAE) IN COASTAL PLAIN STREAMS
OF THE SOUTHEASTERN UNITED STATES

By

Jayne Brim Box
August 1999

Chair: Katherine C. Ewel

Major Department: Forest Resources and Conservation

The North American freshwater mussel (Bivalvia: Unionidae) fauna is the richest in
the world, and the southeastern United States has more species than any other region.
Freshwater mussels are also one of the most imperiled faunal groups in North America,
and a precipitous decline in freshwater mussel populations has been documented
throughout the southeastern region, including the Apalachicola, Chattahoochee, and Flint
(ACF) River basin of Alabama, Georgia, and Florida. The decline in freshwater mussel
populations in many river basins has been attributed, in part, to land-use modifications
that cause changes in sediment regimes. The specific associations that mussels have with
streambed sediments, however, are poorly understood, making it difficult to assess the
impacts that changes in sedimentation rates have on unionid mussels. In addition, the
biotic and abiotic attributes that define suitable habitats of individual mussel species are

V

poorly understood. Ecosystem-level studies of freshwater mussels are few, and it is
unclear what factors should he measured, and at what spatial and temporal scales, to
elucidate meaningful relationships between mussels, suitable habitat, and community
structure. In this study quantitative methods were used to evaluate the relative
importance of fish and abiotic characteristics on mussel community structure in the ACF
basin. Over 2,500 mussels, 7,200 fish, and 2,600 sediment cores were sampled at 30
locations in the basin. The response of four mussel species to catastrophic burial by sand
and fine sediments was also determined through laboratory experiments. Significant
relationships were detected between mussel and fish assemblage structure and macro- and
micro-habitat descriptors, but not between mussel and fish assemblage structure. Mussel
community structure was closely related to stream size and streambed substrate
properties, including stream order, link magnitude, substrate porosity, substrate sorting,
percentage of fine sediments, and mean sediment particle size. This study suggests that
in the ACF basin, freshwater mussels are habitat specialists whose distributions are tied
to suitable habitat defined by a combination of macro- and micro-habitat variables. In
addition, covering mussels with as little as 14 cm of sediments significantly decreased
their chances of extricating themselves from burial, suggesting that the fouling of North
American streams by erosional sediments may be a factor in the current decline of
unionid mussels.

VI

CHAPTER 1
INTRODUCTION

The North American freshwater mussel fauna is the richest in the world and
historically probably numbered over 300 species (Stansbery 1971). Within North
America, the southeastern United States has more freshwater species than any other
region, with about 80% of the fauna (Burch 1973). North America's freshwater mussel
fauna is in decline, however, with 7% of the species presumed extinct, 40% considered
endangered or threatened, 24% of special concern, 24% stable, and about 5%
undetermined (Williams and Neves 1995). There appears to have been a precipitous
decline in freshwater mussel populations throughout the southeastern region, including
the ACF basin, in the past 40 years (Heard 1975, Williams et al. 1993).

The ACF rivers form one of the largest drainages in the eastern Gulf of Mexico and
drain portions of east Alabama, west Georgia, and northwest Florida. Eastern Gulf of
Mexico river systems, including drainages from the Suwannee River west to the
Escambia River, are important areas for molluscan speciation and endemism, with about
56% of the fauna comprised of endemics (Butler 1989). Within this area, the ACF rivers
contain the greatest total number of mollusk species as well as endemics (Clench and
Turner 1956).

Mollusks are one of the best sampled invertebrate groups largely because of the
interest of shell collectors beginning in the 18th century (Barnes 1980). These

1

2

collections, many of which were made hy private individuals and were later donated or
purchased by natural history museums, form the backbone of our historical knowledge of
unionid mussels. Collections from the ACF rivers date back to 1833, when Timothy A.
Conrad traveled through the ACF basin, passing over both the Flint and Chattahoochee
rivers. Conrad (1834) was the first to note that freshwater mussels from rivers draining
the Gulf of Mexico differed from those of the Atlantic slope region, and that in the ACF
Basin, some mixing of these two faunal groups occurred. Later, van der Schalie (1938a)
also reported that the ACF basin consisted of a "strikingly peculiar fauna" that was
distinct from the Alabama drainage to the west and the Atlantic coastal drainages to the
east. The biological uniqueness of the basin is due to a combination of factors including
its geographic location, physiographic and geologic diversity, and unglaciated status
during the last glacial period (Adams and Hackney, 1992). Its relatively isolated
geographic location, between the Alabama Basin to the west and the southern Atlantic
Slope drainages to the east, is especially important, as faunal elements representing both
regions are present in the basin. In addition, the unique geological features that occur
where the upper Coastal Plain Physiographic Province meets the Piedmont has produced
a diverse animal fauna that includes both Coastal Plain (southern) and Piedmont
(northern) forms.

Although isolated collections have been made in the ACF Basin for over 160 years, a
comprehensive survey of the three major rivers of the basin and their tributaries was not
conducted until the early 1990s (Brim Box and Williams 1999). They determined that
the conservation status of ACF Basin mussel species included 13 (39%) species that were

3

currently stable, six (18%) species were of special concern, three (9%) that were
threatened, seven (21%) that were endangered, two that were extirpated (6%) and two
(6%) that were extinct. Their assessment of the conservation status of the 33 species of
mussels that occur in the ACF Basin revealed a picture of significant decline during the
past 30 years. In addition 1 1 of the 33 species (33%) had a reduced conservation status
within the basin compared to their range-wide status (Brim Box and Williams in press,
Williams et al. 1993).

The causal factors for the decline of freshwater mussel faunas are poorly understood
(Fuller 1974, Bogan 1993, Williams and Neves 1995), and much of the information that
links mussel declines to changes in their physical habitats is based on anecdotal or
descriptive information. One of the most ubiquitous factors that may adversely affect
mussel populations is excessive sedimentation caused, in part, by poor land-use practices.
Excessive sedimentation has been suspected as a cause of unionid mussel declines since
the late 1800s (Kunz 1898). The US Environmental Protection Agency (1990) cited
sediments as the number one pollutant of rivers in the United States, impairing > 40% of
the nation's river miles. This estimate is nearly 50% higher than the next pollutant.
Sediment production is closely tied with changes in land use, and increased sediment
production is thought to negatively impact unionid mussels. Although sedimentation is
often cited as a cause of the cataclysmic decline experienced by the majority of North
America's freshwater mussels, the role of streambed substrate composition in defining
suitable habitat for unionid mussels is unclear, and results are contradictory regarding the

4

strength of associations between streambed substrates and freshwater mussel
distributions.

Attempts to address causal factors of mussel declines are hampered by the lack of
knowledge of even basic aspects of their life histories and habitat requirements. The
biotic and abiotic attributes that define suitable habitats for individual mussel species are
poorly understood. Freshwater mussel communities reportedly are structured by three
types of environmental factors: 1) the distribution and availability of their host fish (Haag
and Warren 1998, Watters 1992), 2) drainage-level characteristics (e.g., stream area)
(Strayer 1983), or 3) micro-habitat variables, including substrate composition (Harman
1972, Leff et al. 1990, Layzer and Madison 1995). Much ambiguity remains over the
role of these three groups in structuring freshwater mussel communities, and results are
often contradictory concerning their usefulness in predicting the occurrence or density of
unionids in streams (Holland-Bartels 1990, Bauer et al. 1991, Strayer and Ralley 1993, Di
Maio and Corkum 1995). In order to address causal factors of freshwater mussel
declines, however, a better understanding must be gained of how such ecological factors
structure mussel communities.

The purpose of this study was to evaluate the relative importance of fish and abiotic
characteristics on mussel community structure. Mussel and fish assemblage structures
were correlated to each other and to macro- and micro-habitat descriptors at the site,
level. The strength of associations were tested between properties of streambed substrate
composition, including bulk density, porosity, sediment sorting, the percentage of fine
sediments, and mean particle size, and the distribution of individual mussel species at 30

5

stream sites in the ACF Basin of the eastern Gulf of Mexico. Finally, the responses of
four species of unionid mussels from the ACF basin to catastrophic burial by both fine
sediments and sand were evaluated.

CHAPTER 2
STUDY AREA

The ACE rivers form one of the largest drainages in the eastern Gulf coastal plain,
and drain portions of southeast Alabama, southwest Georgia, and northwest Florida. The
ACF basin encompasses approximately 50,800 km^(Leitman et al. 1983) and drains parts
of the Blue Ridge, Piedmont, and Coastal Plain physiographic provinces. The basin is
one of the largest and longest in the southeastern region and wholly or partially
encompasses 59 Georgia counties, 10 Alabama counties, and 8 Florida counties.

The Apalachicola River originates at the confluence of the Chattahoochee and Flint
rivers just north of the Florida/Georgia border. It is 1 82 km long and lies entirely within
the Coastal Plain physiographic province. It drains approximately 6,200 km^, about half
of which drains the Chipola River subbasin (Mattraw and Elder 1984). It is the largest
river in Florida, with monthly mean discharges of approximately 25,000 cubic feet per
second (cfs) and seasonal highs approaching 100,000 cfs (Livingston 1974). The river
has been named an Outstanding Florida Water (Florida Department of Natural Resources
1989). A distinctive feature of the Apalachicola River is its dense bottomland hardwood
forest that contains more than 1,500 trees per hectare (Mattraw and Elder 1984). The
average annual litter fall produced by this vegetation makes the Apalachicola floodplain
forest one of the most productive in warm temperate regions.

6

7

The Chipola River is the major tributary to the Apalachicola River and is the fourth
largest river in the basin, draining approximately 1,649 kml The Chipola River begins in
extreme southeastern Alabama, flows 177 km south into Florida, and empties into the
Apalachicola River, near Sumatra (Florida Department of Natural Resources 1989). The
river is considered a springfed river, containing many small spring runs as well as a first
magnitude spring, and is designated as an Outstanding Florida Water (Florida
Department of Natural Resources 1989). Two Chipola River tributaries were used in this
study: Baker and Spring (Merritt Mill) creeks, Jackson County, Florida.

The Chattahoochee River originates in the Blue Ridge Mountains of northern
Georgia and flows approximately 702 km to its confluence with the Flint River at Lake
Seminole on the tristate boundary. For much of this distance it forms the border of
Alabama and Georgia. The Fall Line, near Columbus, Georgia, marks the boundary of
the Coastal Plain and the Piedmont physiographic provinces. Nine Chattahoochee River
tributaries were used in this study: North Fork Cowikee Creek, Barbour County,
Alabama; Hog Creek, Clay County, Georgia; Kirkland and Sawhatchee creeks. Early
County, Georgia; Little Uchee Creek, Lee County, Alabama; Pumpkin Creek, Randolph
County, Georgia; Hatchechubee and Uchee creeks, Russell County, Alabama; Lime
Spring Creek, Stewart County, Georgia.

The Flint River originates in the crystalline rocks of the Piedmont physiographic
province, just south of Atlanta, and flows 564 km south to its confluence with the
Chattahoochee River. Approximately 193 km of the Flint River lies in the Piedmont
province, while the remaining 371 km are in the coastal plain, all within the state of

8

Georgia. Nineteen Flint River tributary sites were used in this study: Coolewahee and
Ichawaynachaway creeks. Baker County, Georgia; Swift and Cedar creeks. Crisp County,
Georgia; Spring Creek, Decatur County, Georgia; Hogcrawl Creek, Dooly County,
Georgia. Kiokee Creek, Dougherty County, Georgia; Muckalee Creek (two sites), Lee
and Sumter counties, Georgia; Aycocks Creek, Miller County, Georgia; Chokee and
Lime creeks, Sumter County, Georgia; Patsaliga Creek, Taylor County, Georgia;
Chickasawhatchee Creek, Terrell County, Georgia; Kinchafoonee Creek, Webster
County, Georgia; Jones and Abrams creeks, an unnamed tributary to Abrams Creek, and
an uimamed tributary to Mill Creek, Worth County, Georgia.

CHAPTER 3

STREAMBED SUBSTRATE PROPERTIES

Introduction

Freshwater mussels (Bivalvia: Unionidae) are considered the most endangered faunal
group in North America, with over 70% of the approximately 280 species considered
imperiled or extinct (Neves et al. 1997). Extinction rates for freshwater mussels are an
order of magnitude higher than expected background levels (Nott et al. 1995). Reasons
for the decline of freshwater mussel populations in the past century throughout North
America and especially the southeastern United States are poorly understood. Although
decreases in freshwater mussel populations can sometimes be attributed to specific
factors (e.g., dams and pollution), the importance of other factors is less clear. Much of
the information that links mussel declines to changes in their physical habitats is based on
anecdotal or descriptive information (Fuller 1974, Bogan 1993, Williams and Neves
1995).

Attempts to address causal factors of unionid mussel declines are hampered by the
lack of knowledge of even basic aspects of their life histories and habitat requirements.
For example, freshwater mussels' life histories are complex and include a glochidial stage
that parasitises a host fish, undergoes metamorphosis, and drops off to become a
free-living juvenile mussel. Many aspects of this relationship are unknown, and only
about a third of the fish hosts for North American unionids have been discovered

9

10

(Watters 1994a). In addition, the degree of host specificity (i.e., the number of host fish
per mussel species) probably varies from mussel species to species.

The biotic and abiotic attributes that define suitable habitats for individual mussel
species are also poorly understood. Freshwater mussel communities reportedly are
structured by three types of environmental factors: 1) the distribution and availability of
their host fish (Haag and Warren 1998, Watters 1992), 2) drainage-level characteristics
(e.g., stream area) (Strayer 1983), or 3) micro-habitat variables, including substrate
composition (Harman 1972, Leff et al. 1990, Layzer and Madison 1995). Much
ambiguity remains over the roles of these three general factors in structuring freshwater
mussel communities, and results are often contradictory concerning their usefulness in
predicting the occurrence or density of unionids in streams (Holland-B artels 1990, Bauer
et al. 1991, Strayer and Ralley 1993, Di Maio and Corkum 1995). It is imperative,
however, in the face of current mussel declines, that a better understanding be gained of
how such ecological factors structure mussel communities, especially because resource
managers must increasingly delineate suitable habitat in recovery plans for imperiled
mussel species.

One of the most ubiquitous factors that may adversely affect mussel populations is
excessive sedimentation caused, in part, by poor land-use practices (Brim Box and Mossa
1999). The US Environmental Protection Agency (1990) cited sediments as the main
pollutant of rivers in the United States, affecting > 40% of the nation's river miles. This
estimate is nearly 50% higher than the next pollutant. Excessive sedimentation has been
suspected as a cause of unionid mussel declines since the late 1 800s (Kunz 1 898).

11

Excessive amounts of sediments, especially fine particles, that wash into streams can
potentially affect mussels in many ways, although empirical studies examining the effects
of eroded sediments on invertebrates are lacking (Waters 1995). In addition, although
sedimentation is often cited as a cause of the cataclysmie decline experienced by the
majority of North America's freshwater mussels (Bogan 1993, Williams and Neves 1995,
Neves et al. 1997), the role of streambed substrate composition in defining suitable
habitat for unionid mussels is unclear, and results are contradictory regarding the strength
of associations between streambed substrates and freshwater mussel distributions. This
relationship, however, must be understood before the impact of anthropogenic sources of
erosional sediments on existing mussel populations can be evaluated.

There are several pssible reasons why meaningful relationships between unionid
mussel distributions and micro-habitat descriptors, such as streambed composition, have
eluded researchers: 1) mussels may be habitat generalists, occurring in many types of
substrate indiscriminately, 2) relationships between mussels and substrate composition
may be species- specific, although much of the literature refers to multiple species when
describing habitat preferences, and 3) there are several methodological problems with the
sampling designs used to elucidate meaningful relationships between mussels and
suitable habitat, including the number of samples collected, how samples are processed,
and statistical considerations for nonparametric data.

In this study we tested the strength of associations between properties of streambed
substrate composition, including bulk density, porosity, sediment sorting, the percentage
of fine sediments, and mean particle size, and the distribution of individual mussel

12

species at 30 stream sites in the Apalachicola, Chattahoochee, and Flint (ACF) basin of
the eastern Gulf of Mexico. Currently, over 60% of the mussel fauna of the basin are
either endangered (four species federally listed), threatened (two species federally listed),
of special concern, extirpated, or extinct. Only 13 of the 33 species known from the ACF
basin have populations regarded as stable (Brim Box and Williams, in press). Erosional
sediments were implicated early on (van der Schalie 1938a, Cleneh 1955) for mussel
declines in the basin, but most of that information is based on anecdotal evidence. The
objective of this study was to quantify relationships between streambed substrate
composition and the distribution of individual unionid mussel species in the ACF basin.
We also determined whether species could be regarded as habitat generalists or specialists
based on streambed substrate composition.

Methods

Mussels and sediments were collected from 30 sites in the Coastal Plain
Physiographic Province of the ACF basin (Fig. 3-1). These 30 sites represent a subset of
150 ACF tributary streams originally surveyed for mussels from 1991 to 1992 (Brim Box
and Williams, in press). Measurements of species diversity at each of the original 150
sites indicated that these sites included a wide range of mussel richness. Therefore, each
of the original 150 sites was assigned to one of six species richness categories (very low =
1-2 species; low = 3-4 species; medium = 5-6 species; medium high = 7-8 species; high =
9-10 species; very high = 11-12 species). Sites that were not in the coastal plain or where
no mussels were found were excluded from further consideration. From the remaining

13

t

Scale in km
0 48

Figure 3-1 . Study area: Thirty sampling sites in the coastal plain of the
Apalachicola, Chattahoochee, and Flint basin.

14

pool of 62 sites, five sites were randomly selected from each of the six species richness
categories to be the 30 sites used in this study. At each of the 30 sites, a 100-meter reach
was delineated and stratified for sampling into bank, slope, and channel habitats. These
habitats were defined by a combination of physical and geomorphic attributes of the
channel morphology. The bank habitat extended from the shoreline to the point in the
channel where the depth began to increase, indicating the beginning of the slope habitat.
The slope habitat ended where the gradient leveled out, indicating the beginning of the
charmel habitat. Visible changes in substrate (e.g., mud to sand) also were used to
demarcate these habitats and generally coincided with changes in gradient. Previous
sampling in the New River, Florida, a Suwannee River tributary that also drains into the
Apalachicola Region, indicated that mussel species composition and densities differed
significantly among these three habitats (J. Brim Box and L. Arvanitis, unpublished data).

Quadrats were used to collect samples of mussels and sediments from the bank,
slope, and channel habitats. In each habitat, 32 quadrats (0.25 mQ were selected
randomly from a grid for collecting mussels. This number was based on a method from
Downing and Downing (1992), given a 95% level of confidence and a precision of 20%
of the true mean number of mussels per m^ All mussels falling within or touching the
sides of the quadrats were placed into dive bags (noting quadrat number and habitat type),
identified to species, and returned to the substrate.

At each site and each quadrat a 4.7 cm-diameter core was collected from the top 8.5
cm of sediment for determination of bulk density, porosity, and sediment particle size
composition. Bulk density is the ratio of mass to volume (g/cmQ of the bed material and

15

varies with composition and compaction of the sediments (Gordon et. al. 1992). Porosity
is inversely related to bulk density and is the ratio, in percent, of the volume of void space
to the total volume of the sample (Friedman 1992). We were unable to collect sediment
cores from 195 quadrats that contained predominantly rock, and were unable to sieve 24
addition samples because of processing errors; therefore our total sample size was limited
to 2661 quadrats.

There are no standard methods for characterizing sediments in freshwater streams in
ecological studies (Bovee 1982, Gordon et al. 1992), but samples typically are divided
into a set of particle-size categories, and the relative proportion (by weight) in each of
these categories is measured. In this study, each quadrat sample was divided into 19
sediment particle-size categories that corresponded to 0.5 phi intervals of the Wentworth
scale (Wentworth 1922), and included pebble to clay-sized particles. Tbe choice of
particle size categories was guided by standard methods of fluvial geomorphology
(Mudroch and Azcue 1995) and to avoid the lack of resolution that can occur with fewer
size categories. The composition of sediment particle sizes larger than silt was
determined using a series of nested sieves (Folk 1980). The amount of silt and clay (i.e.,
fine sediments < 0.063 mm) in each sample was determined by pipette analysis (Folk
1980).

Statistical parameters of grain size are typically derived from a cumulative frequency
plot or measures of moments calculated from the weight of sediment in each size elass
(Lindholm 1987, Gordon et al. 1992). In this study, we back-calculated tbe number of
particles present in each of the 19 size classes by assuming the density of eaeh particle

16

was approximately 2.65 g/cm^ (the approximate density of quartz and sandy, siliceous
particles with little organic matter), and that each particle was spherical. These estimates
were then used to determine the mean particle size, sorting, and percentage of fine
sediments of each sediment core sample, by using a method of moments derived for
grain-size calculation (Lindholm 1987). Sorting, defined as the standard deviation of
each core divided by the mean particle size (Lindholm 1987), is a measure of the spread
of particle sizes in the substrate. Sorting classes usually range from very well sorted to
very poorly sorted (Gordon et al. 1992).

Species-specific associations between mussels and sediment were explored
statistically by testing whether the presence of mussels was independent of streambed
substrate properties, including bulk density, porosity, sorting, mean particle size, and
percentage of fine sediments. Presence was analyzed instead of mussel density owing to
the low number of mussels typically found in each 0.25 m^ quadrat. In each analysis the
number of quadrats in which mussels were present was computed for each of 10
categories of streambed substrate properties. The boundaries of these categories were
defined by 10 equally spaced percentiles (i.e., 10%, 20%, etc.) of the observed
distribution of each substrate attribute. In this way all categories included an
approximately equal number of quadrats (264 or 265 quadrats). Under the null
hypothesis of independence between mussels and substrate properties, the number of
quadrats with mussels present was expected to be equal in each of the 10 categories.
Departures from this equiprobable (null) model were tested using the deviance test
statistic, D, for binomial responses (Collett 1991):

17

/) = 2 Z 0,log \f.] + {tii ->^,)log(^)).

Here, n,- is the number of quadrats in the ith substrate property category; yi and y. are the
observed and expected numbers of quadrats with mussels present in the ith substrate
category. Under the equiprobable model, y . =tiip, where p is the maximum-likelihood
estimate of a constant probability of occurrence of mussels in substrates of different

compositions, i.e.

Like Pearsons statistic, the distribution of the deviance is approximately Xl
(where v = number of substrate property categories minus one) assuming: 1) the

equiprobable model is correct, 2) the number of quadrats in each substrate property

category is reasonable large, and 3) the expected number of quadrats with mussels present

is not too small (Collett 1991). Ten substrate property categories were used to ensure that

assumptions two and three were satisfied for all species of mussels found in at least 1%

(=26) of the 2661 quadrats. Under the equiprobable model, the 26 quadrats were

expected to be divided equally among the 10 bulk substrate property categories and, on
average, each category was expected to include about three quadrats with mussels {yi =
2.6). Simulations have shown that the distribution of deviance and Pearson's test
statistics are nearly wheny,- is at least two (Read and Cressie 1988). Therefore, for
each of the mussel species found in at least 1% of the samples, observed differences in

the presence of mussels at different levels of substrate properties were considered to have

more than chance outcomes (i.e, to have statistical significance) when the deviance test
statistic D exceeded the chi-squared critical value 26^ (a).

18

The categories used to define the 10 equally spaced percentiles of each of the five
substrate attributes were also used to examine relationships among these five sediment
properties. Spearman's rank correlation coefficient (p) was used to determine whether
these five properties were correlated. An alternative form of Spearman's rank correlation
coefficient, the Hotelling-Pabst test (Conover 1971), was used to test the null hypothesis
that substrate attributes were mutually independent. The alternative hypothesis of this
two-tailed test is that there is a tendency for a substrate attribute to be either positively (or
negatively) correlated with one of the other four substrate properties.

Results

Significant correlations were found among the five substrate properties measured
(Table 3-1). As expected, bulk density was almost perfectly inversely related to porosity
(Fig. 3-2); to reduce redundancy, only porosity was used in further analyses. Substrate
samples fell into three broad categories: 1) substrates that were well sorted, consisting of
small particle sizes (including a high percentage of fine sediments), with high porosity
(Fig 3-3a, b, c), 2) substrates that were moderately sorted, with larger particle sizes (i.e.,
sand), moderate porosity, and a low percentage of fine sediments (Fig 3-4 a, b, c, d), and
3) substrate that were poorly sorted, consisting of both large and small particles with a
high percentage of fine sediments present, and low porosity (Fig. 3-4 a, b, c, d). In this
study, samples with large mean particle sizes were either inundated with fine sediments
(Fig. 3-5a) or lacked a high percentage of fines (Fig. 3-5b). In the former case, those
substrates were also poorly sorted with low porosity. If samples were well sorted, then

19

Table 3-1 . Spearman rank values (p) for correlations of streambed substrate properties.
P-values are given in parenthesis, and relationships were considered significant at the
a = 0.05 level.

sediment property

porosity

sorting

percent fines

mean particle size

porosity

-0.97 (p < 0.001)

0.67 (p=0.033)

-0.99 (p< 0.001)

sorting

-0.99 (p< 0.001)

0.27 (p = 0.446)

0.73 (p=0.016)

percent fines

0.76 (p = 0.111)

0.27 (p = 0.446)

-0.99 (p< 0.001)

mean particle size

-0.89 (p = 0.005)

0.98 (p< 0.001)

-0.99 (p< 0.001)

20

Figure 3-2. Scatter plot of 2, 661 substrate samples. This plot
demonstrates the inverse relationship between sediment
bulk density and sediment porosity.

Mean particle size (mm)

21

0.11

0.1

0.09

0.08

0.07
0.06

0 2 4 6 8 10 12

65

60

_55

s.

t 50

O

o
Q.

45
40
35

0 2 4 6 8 10 12

Sorting (well to poor)

Sorting (well to poor)

Figure 3-3. Correlations between streambed substrate properties:
a) mean particle size and sediment sorting, b) porosity and sediment
sorting, and c) porosity and mean particle size.

0.11

22

(ujuj) 9Z|S spjyed ueav^

^C'JOOOCD-'tC'JOOO

r^h-N-CDCDCOCDCDLf)

(%) S0uy

Figure 3-4. Correlations between streambed substrate properties: a) mean particle size and porosity, b)
mean particle size and sediment sorting, c) porosity and percent fine sediments, and d) sediment sorting
and percent fine sediments.

23

a

low porosity
poorly sorted
large and small particles
high percentage fines

b

moderate porosity
moderate sorting
mostly large particles
low percentage fines

c

high porosity
well sorted
small particles
high percentage fines

Figure 3-5. Cartoon depiction of the three main substrate categories
found in this study.

24

samples with smaller particle sizes had higher porosities than samples with large mean
particle sizes (Fig. 3-5c). If samples were poorly sorted, than porosity was lowest in
substrates that contained both large and small particles.

A total of 2, 563 mussels were collected in the 2661 quadrat samples of the ACF
basin (Table 3-2). Of the 25 species of mussels collected, the majority were Elliptio
(70%) or Villosa (16%). Nine mussel species, Elliptio complanata. E. crassidens. E.
icterina. Toxolasma paulus. Uniomerus carolinianus. IJtterbackia imbecillis. Villosa
lienosa. V. vibex. and V. villosa were found in at least 1% of the 2661 quadrats. These
nine species were used to test whether mussel presence was associated with the following
differences in sediment composition: porosity, mean particle size, percentage of fine
sediments, and sediment sorting.

This study of mussels and microhabitat in the ACF basin revealed statistically
significant associations between mussel presence and substrate properties for eight of the
nine most abundant species encountered (Table 3-3). Six species were most common in
substrates with high porosity: Elliptio complanata. E. icterina. Toxolasma paulus.
IJtterbackia imbecillis. Villosa vibex and V. villosa (Table 3-4).

A significant difference between mussel presence and sediment sorting was detected
for six of the nine most abundant mussel species: Elliptio complanata. E. crassidens.
Villosa lienosa. Toxolasma paulus. Uniomerus carolinianus. and Utterbackia imbecillis
(Table 3-3). Of these six species, only E. crassidens was more common in poorly- sorted
substrates; the other five species were more common in well-sorted substrates (Table

3-4).

25

Table 3-2. Number of mussels collected and number of quadrats with mussels in 2,661
quadrat samples of sites within the ACF basin.

Species

Common name

Number
of mussels

Number of quadrats
with mussels

Anodonta sp.

1

1

Anodontoides radiatus

Rayed creekshell

3

3

Elliptio arctata

Delicate spike

8

5

Elliptio complanata

Eastern elliptio

1,495

458

Elliptio crassidens

Elephant ear

70

30

Elliptio icterina

Variable spike

195

88

Elliptio purpurella

Inflated spike

20

14

Elliptio sp.

21

16

Lampsilis claibomensis

Southern fatmucket

6

5

Lampsilis subangulata

Shinyrayed

6

6

Medionidus penicillatus

pocketbook

6

3

Megalonaias nervosa

Gulf moccasinshell

1

1

Pleurobema pvri forme

Washboard

17

12

Pvganodon erandis

Oval pigtoe

1

1

Ouincuncina infucata

Giant floater

13

11

Strophitus subvexus

Sculptured pigtoe

4

3

Toxolasma paulus

Southern creek mussel

97

69

Uniomerus carolinianus

Iridescent lilliput

52

37

Utterbackia imbecillis

Florida pondhom

82

47

Utterbackia peeevae

Paper pondshell

41

20

Villosa lienosa

Florida floater

266

121

Villosa vibex

Little spectaclecase

91

57

Villosa villosa

Southern rainbow

60

43

Villosa sp.

Downy rainbow

3

3

Unidentified

Total

4

2, 563

2

26

Table 3-3. Tests of lack of associations between mussel presence and five streambed
substrate properties. P-values are associated with the deviance test statistic.

Bulk

density

Porosity

Mean

particle size

Sorting

Percent

fines

Species

P-value

P-value

P-value

P-value

P-value

Elliptio complanata

<0.001

<0.001

0.2

<0.001

<0.001

Elliptio crassidens

0.23

0.29

<0.01

<0.01

0.15

Elliptio icterina

0.04

0.04

0.19

0.45

0.31

Toxolasma paulus

0.03

0.03

0

<0.001

<0.001

Uniomerus carolinianus

0.57

0.62

0.06

0.05

0.32

IJtterbackia imbecillis

0.02

0.02

0.28

0.04

0.03

Villosa lienosa

0.12

0.14

<0.001

<0.001

<0.001

Villosa vibex

0.05

0.05

<0.001

0.1

0.08

Villosa villosa

<0.01

<0.01

0.85

0.16

0.06

27

Table 3-4. Descriptions of the relationships between the nine most abundant species in
this study, and the four substrate properties tested. Not significant means P-values > 0.05
associated with the deviance test statistic.

Species

Porosity

Sorting

Fines (%)

Mean size

Elliptio complanata

high

well

low

not significant

Elliptio crassiden.s

not significant

poor

not significant

large particles

Elliptio icterina

not significant

not significant

not significant

not significant

Villosa lienosa

high

well

high

small particles

Villo.sa vibex

high

not significant

high

small particles

Villosa villo.sa

high

not significant

low

not significant

Toxolasma paulus

high

well

low

intermediate sizes

Uniomerus carolinianus

not significant

well

not significant

intermediate sizes

Utterbackia imbecillis

high

well

low

not significant

28

A significant difference between mussel presence and the percentage of fine
sediments was detected for six species: Elliptic complanata. Toxolasma paulus.
Utterbackia imbecillis. Villosa lineosa. V. vibex. and V. villosa (Table 3-3). Villosa
lienosa and Villosa vibex were most common in substrates with a high percentage of fine
sediments present, while the other four species were most common in substrates with a
low percentage of fine sediments (Table 3-4).

Mean particle size had the least predictive power of the four substrate properties
examined (Table 3-3). A significant difference between mussel presence and particle size
was detected for Elliptic crassidens. Villosa lienosa. V. vibex. Toxolasma paulus. and
Uniomerus carolinianus. Of these species, E. crassidens was most common in substrates
consisting of predominantly larger particle sizes, V. lienosa and V. vibex were most
common in small particle sizes, and T. paulus and U. carolinianus were most common in
substrates consisting of particles of intermediate sizes (Table 3-4).

Discussion

This study of mussels and microhabitat in the ACF basin revealed statistically
significant associations between mussel presence and substrate properties for eight of the
nine most abundant species encountered. Elliptic icterina was the only species that was
not associated with any of the four substrate properties tested. This was not surprising,
given that E. icterina has been reported from a variety of substrates in slight to moderate
current, and in streams, lakes, reservoirs, ponds, and large rivers (Johnson 1970, Heard
1979). In the ACF basin, E. icterina was found in a variety of habitats, including sand.

29

gravel, and silt deposits between rocks (Jenkinson 1973). Based on the results of this
study, E. icterina can be considered a habitat generalist.

Eight species tElliptio complanata. E- crassidens. Toxolasma paulus. Uniomerus
carolinianus. Utterbackia imbecillis. Villosa lienosa. V. vibex. and V. villosat were most
common in one of four broad substrate types; E- complanata. LJ. imbecillis. and V. villosa
were most common in highly porous, well-sorted substrates, with a low percentage of
fines. Villosa lienosa and V. vibex were most common in highly porous, well-sorted
substrates, with a high percentage of fines. Toxolasma paulus and II. carolinianus were
most common in well-sorted substrates of intermediate particle sizes, and E- crassidens
was most common in poorly-sorted substrates with large particle sizes.

Elliptio complanata. IJ. imhecillis. and V. villosa were more common in quadrats
with a low percentage of fine sediments. In the ACF basin E- complanata was reported
from sites with sand and limestone rock substrates, sand and fine sediments, and sand
(Brim Box and Williams 1999). In South Carolina, E- complanata densities were
significantly greater in sand and sand/mud substrates than in sand/gravel substrates (Leff
et al. 1990). However, in New York it was reported in a wide variety of substrates except
soft mud (Clarke and Berg 1959). Kat (1982) found that E- complanata grew slower in
muddy substrates, and speculated that these fine particle sizes may result in reduced
feeding efficiencies through interfering with filter feeding. The results of this study are
consistent with previous observations that this species is less common in substrates that

contain a high percentage of fine sediments.

30

The occurrence of Utterbackia imbecillis and Villosa villosa also decreased
progressively as the percentage of fine sediments per quadrat increased. This was
unexpected, in that previous studies have consistently documented the presence of IJ.
imbecillis in slackwater areas in mud or muddy sand (Clench and Turner 1956, Johnson
1970, Brim Box and Williams in press). In addition, LJ. imbecillis is thin-shelled,
unsculptured, and with no dentition, which are three morphological characters thought to
increase buoyancy in fine sediments (Watters 1994b). Villosa villosa had previously
been reported from muddy waters (Johnson 1970), mud and muddy sand (Heard 1979),
murky water and muddy substrates (Butler 1989), and sandy substrates (Brim Box and
Williams 1999). There was not a significant relationship between the presence of Elliptic
complanata. U. imbecillis. or V. villosa and particle size, and it appears these three
species can be found in a variety of substrate sizes excluding fine sediments, as long as
these substrates are well sorted with corresponding high porosities. Based on the results
of this study, Elliptio complanata. U. imbecillis. and V. villosa can be considered habitat
specialists.

Villosa lienosa and V. vibex were most common in high porous, well-sorted
substrates, and were the only species that were most common in substrates with a high
percentage of fine sediments present. This is consistent with descriptive studies, in which
V. lienosa was found in soft mud (Jenkinson 1973), in muddy substrates in detrital areas
(Clench and Turner 1956), and in substrates ranging from mud to sand and clay (Brim
Box and Williams 1999). Villosa vibex has also been reported from mud or soft sand.

especially in detrital areas (Johnson 1970, Heard 1979), and sandy mud bottoms

31

(Williams and Butler 1994). These species can also be considered habitat specialists,
because they were most common in well-sorted substrates with high porosity, a high
percentage of fines, and small mean particle sizes.

Toxolasma paulus and Uniomerus carolinianus were most common in well-sorted
substrates of intermediate particle sizes. In the ACF basin, T. paulus was reported from a
wide variety of habitats, from fine sand to rocky substrates (Jenkinson 1973), in mud and
sand (Heard 1979), and sand and rock, sand and clay , and sandy substrates (Brim Box
and Williams 1999). Little is known about the habitat preferences of LI. carolini anus.
other than that it has been found in muddy sand and sand in slight current (Heard 1979),
and in substrates ranging from sand and clay to sand and limestone rock (Brim Box and
Williams 1999). In this study, although T. paulus was most common in substrates of
intermediate particle sizes (i.e., sands), these substrates were also well sorted with a low
percentage of fines present. In contrast, there was not a significant relationship between
the presence of LI. carolinianus and porosity or percentage of fine sediments present.

This suggests that this species is less habitat-specific than T. paulus. although it too was
most common in well-sorted sediments of intermediate sizes.

Elliptio crassidens was the only species that was most common in poorly-sorted
substrates with large particle sizes. In the ACF basin E. crassidens was found in
mid-channel areas of moderate to strong currents, in substrates ranging from muddy sand,
sand, to rock (Johnson 1970, Heard 1979, Brim Box and Williams in press). Elliptio
crassidens. based on this study, can also be considered a habitat specialist.

32

This study suggests that individual mussel species can either be habitat specialists or
generalists in regard to streambed substrate properties. That habitat preferences differed
among species was not surprising, although specific examples of habitat requirements for
individual species based on empirical studies are rare. Habitat requirements are usually
based on observational or descriptive data (Clench and Turner 1956, Heard 1979), and the
same species have been judged tolerant or intolerant to changes in sedimentation regimes
in different studies (e.g., Stein 1972, Houp 1993). The species-level differences found
between mussels and substrate properties in this study are consistent with the ambiguity
concerning the relationship between mussels and micro-habitat descriptors. For instance,
some studies suggested strong habitat specificity (Kat 1982, Leff et al. 1990), whereas
others (Holland-Bartels 1990, Strayer et al. 1994, Layzer and Madison 1995) failed to
find statistically significant relationships between mussels and habitat descriptors. Part of
this ambiguity is also a result of the paucity of studies (e.g., Huehner 1987, Bailey 1989)
that have empirically tested for species-specific habitat preference and specificity,
although habitat-specific sampling is often required to determine invertebrate production
and function in streams (Smock et al. 1992).

Substrate particle size has been considered an important micro-habitat descriptor
when assessing associations between mussels and their physical habitats (Bronmark and
Malmqvist 1982, Salmon and Green 1983, Leff et al. 1990), although meaningful
relationships between unionid mussels and substrate composition have not always been
found (Lewis and Riebel 1984, Strayer and Ralley 1993, Layzer and Madison 1995, Di
Maio and Corkum 1995). For example, Strayer and Ralley (1993) concluded that

33

microhabitat-mussel associations, as estimated from discriminant analysis, were weak,
and that larger spatial scales might be more useful in predicting mussel occurrence.

They also suggested that descriptions of habitat based on fluvial geomorphology might be
more informative. Others have suggested that substrate stability, not composition, is
important in predicting mussel occurrence. In the Holston River, Virginia, the greatest
species densities were associated with stable mixed sand, gravel, and pebble substrates
(Neves and Widlak 1987). Freshwater mussels of the lower Cumberland River,

Kentucky, were abundant only in stable habitats composed of gravel in firm sandy clay
(Sickel 1982). Kat (1982) suggested that streambeds can be divided into high- and
low-quality microhabitats. High-quality microhabitats are characterized by stable
substrates, uncrowded conditions, and protection from scour; low-quality microhabitats
are characterized by unstable substrates and a significant reduction of energy input
available for growth and reproduction. Hydrologic variables such as the type of stream
flow or shear stress, or macrohabitat descriptors such as stream size may be more useful
than substrate composition in predicting mussel occurrence (Layzer and Madison 1995,

Di Maio and Corkum 1995).

Although relationships among four substrate properties and nine mussel species were
tested in this study, only one species fToxolasma paulus) had a significant relationship
with all four substrate properties. In addition, although Elliptio icterina was the third
most common species collected, its presence was not significantly related to any of the
four measures of substrate. Factors other than sediment composition are probably
important in defining the physical habitat of E. icterina and other mussel species. For

34

example in Ohio, water velocity was a better predictor of the distribution of E. dilatata
than sediment type (Huehner 1987), and in Great Lake tributaries E. dilatata was
associated with streams that were considered hydrologically stable (Di Maio and Corkum
1995).

The lack of correlation between substrate particle size and mussel distributions in
some studies may also be a result of inadequate sampling effort and improper substrate
particle size analysis. Associations between substrate composition and the aquatic fauna
are often evaluated based on a limited number of samples (e.g., 30) or particle-size
classes (e.g., 6). One hundred to 300 samples may be necessary to characterize
adequately the substrate at a particular site in rivers with spatially heterogeneous beds
(Wolcott and Church 1991). In addition, in this study substrate size had the least
predictive value of the five substrate properties originally measured. This is surprising, in
that substrate size is one of the most important sediment characteristics and has a direct
influence on sediment mobility (Hjulstrdm 1935). Historically, relationships between
benthic animals and substrate were based on sediment granulometry, and the main impact
of streambed sedimentation on benthos was thought to be a disruption of the positive
relationship between these animals and increasing substrate particles size (Waters 1995).
Substrate heterogeneity was later considered more important than substrate particle size,
because the abundance of aquatic insects was least in homogenous (i.e, well sorted)
substrates, and greatest in heterogeneous gravel, pebbles, and cobbles (Minshall 1984).
Minshall's (1984) hypothesis may not be true for unionid mussels. Five of the nine
species tested were most common in well-sorted or homogenous substrates.

35

Mussels may be more common in well-sorted substrates because of the high
porosity associated with well-sorted sediments. In this study, although two species were
most common in fine sediments, six of the nine most common species were more
common in high-porosity substrates than low-porosity substrates. None of the nine
species tested was significantly more common in low-porosity substrates. This is
consistent with Minshall's (1984) assertion that substrates consisting of gravel, pebble,
and cobbles can have a high abundance of aquatic animals. Presumably, these substrates
have fairy high porosities (as long as sands and fine sediments are absent), an observation
consistent with the distribution of mussels in this study.

The effects of fine sediments on freshwater mussels have been well documented
through descriptive studies (Ellis 1936, Chutter 1969, Stein 1972, Hartfield and Hartfield
1996, Neves et al. 1997). Excessive amounts of sediments, especially fine particles, that
wash into streams can affect mussels in many ways. Larger particles can become
surrounded or covered by finer sediments, and this embeddedness can reduce interstitial
flow rates (Hamilton and Bergersen 1984). Silt and clay particles can clog the gills of
mussels (Ellis 1936), interfere with filter feeding (Kat 1982, Aldridge et al. 1987), or
affect mussels indirectly by reducing the light available for photosynthesis and the
production of unionid food items (Davies-Colley et al. 1992, Kanehl and Lyons 1992).
Erosional sediments were implicated early on in the disappearance of nearly all species of
freshwater mussels in the main stem of the Chattahoochee River, which historically was
one of the most productive sites for collecting mussels in the entire eastern Gulf of
Mexico (Clench and Turner 1956, Brim Box and Williams in press). However, a positive

36

association was found between fine sediments and V. lienosa and V. vibex. two of the
species that disappeared from the river. This suggests that factors other than changes in
sediment composition were also responsible for eliminating the mussel fauna in the main
stem of the Chattahoochee River. Some possibilities include increases in pollution and
changes in hydrology induced by impoundments.

Although 25 species from 12 genera were collected in samples from the ACF basin,
some mussels were not present in sufficient numbers to assess their association with
sediment composition. Prior to this study we hypothesized that the mussel fauna of the
ACF basin comprised fine-sediment tolerant and fine-sediment intolerant species, and
that historical changes in sedimentation rates in the basin may have been responsible for
the current rarity of fine-sediment intolerant species, including six that are federally
threatened or endangered (USFWS 1998). We attempted to determine if the presence of
five rare species (Anodontoides radiatus. Lampsilis subangulata. Medionidus penicillatus.
Pleurobema pyriforme. Strophitus subvexusf varied significantly among different
substrate properties; however, these five species were present in only 27 of the 2661
quadrats sampled. In future studies of mussel-sediment associations in the ACF basin,
novel sampling designs are recommended to facilitate collecting rare species in greater
numbers than those encountered in this study.

The results of this study suggest that mussel communities in the ACF basin are
structured, in part, by properties of streambed substrate composition. Substrate porosity,
sorting, and the percentage of fine sediments present were useful in elucidating
meaningful relationships between mussel distributions and microhabitat. Substrate

37

particle size had the least predictive power of the five substrate properties measured.
These results suggest that the fouling of North American streams by erosional fine
sediments may be a factor in the current decline of unionid mussels and should be
explored as a causal factor of decline. In addition, because species may be habitat
specialists or generalists with regard to streambed substrate properties, other eeological
factors that may control mussel abundance and distribution, including the availability of
host fish, may also control mussel community structure in the basin and should be
examined.

CHAPTER 4

ROLE OF ECOLOGICAL FACTORS AT THREE PERSPECTIVES

Introduction

Freshwater bivalves are a highly specialized group of organisms, dominated by only
a few taxonomic groups, including the Unionidae, an exclusively freshwater family
whose greatest diversity (> 280 species) is found in North America. Freshwater mussels,
in contrast to most marine bivalves, have highly specialized life histories, including a life
stage called a glochidia that parasitises a fish host, undergoes metamorphosis, and drops
off to become a free living juvenile mussel. The mussel/fish relationship is often
species-specific, in that only certain fish species can serve as suitable hosts for a
particular mussel species (Brunderman and Neves 1993, Haag and Warren 1997).
Consequently, anthropogenic changes that affect either member in this relationship are
likely to have a serious impact on the diversity and abundance of freshwater mussels.

Since the early part of this century, 7% of the native North American mussel fauna
have become extinct, and an additional 72% of the fauna is considered endangered,
threatened, or of special concern (Williams et al. 1993), making freshwater mussels one
of the most imperiled faunas in North America (Master 1990). During this same period,
5% of the native North American fish fauna disappeared. An additional 364 species are
considered endangered, threatened, or of special concern (Williams et al. 1989). Because
these two faunas are inexorably linked, it seems reasonable to assume that the

38

39

disappearance of the host fish may also cause the extirpation of unionids from the same
river reaches or entire river systems. Alternatively, the same environmental stresses
(e.g., pollution, habitat alteration) may influence the abundance and distribution of fish
and mussels independently but along the same environmental gradients. The purpose of
this study was to evaluate the relative importance of fish and abiotic characteristics on
mussel abundance and diversity.

Although freshwater mussels are a conspicuous component of many North American
streams, and may exceed by an order of magnitude the biomass of other invertebrate taxa
(Negus 1966), the biotic and abiotic attributes that define suitable habitats for individual
mussel species are poorly understood. Ecosystem-level studies of freshwater mussels are
few, and it is unclear what factors should be measured, and at what spatial and temporal
scales, to elucidate meaningful relationships between mussels, suitable habitat, and
community structure. It has been suggested that freshwater mussel communities are
structured primarily by three types of enviroiunental factors: 1) the distribution and
availability of their host fish (Haag and Warren 1998, Watters 1995), 2) drainage-level
characteristics (e.g., stream area) (Strayer 1983), and 3) micro-habitat variables (e.g.,
flow, depth, substrate composition) (Harman 1972, Leff et al. 1990, Layzer and Madison
1995). Much ambiguity remains over the role of these three groups in structuring
freshwater mussel communities, and results are often contradictory concerning their
usefulness in predicting the occurrence or density of unionids in streams (Holland-Bartels
1990, Bauer et al. 1991, Strayer and Ralley 1993, Di Maio and Corkum 1995).

40

To evaluate the usefulness of these three sets of environmental factors in explaining
mussel community structure, quantitative samples of mussels, fish, and sediments were
collected from 30 sites in the Apalachicola, Chattahoochee, and Flint (ACF) basin of
Alabama, Florida, and Georgia. These rivers form one of the largest drainages in the
eastern Gulf of Mexico and are known for their high level of endemism (Butler 1989).
Although historically these rivers were known for their rich unionid mussel (Clench and
Turner 1956) and fish (Yerger 1977) faunas, we know of no studies that have examined
relationships between fish and mussel community structure in the basin. It also is not
clear if mussel or fish community composition can be tied to physical habitat descriptors,
such as streambed sediment composition, although in other river systems substrate
composition was important in delineating suitable habitat for fish (Peters 1967, Berkman
and Rabeni 1987) and other invertebrate taxa (Hynes 1960, Chutter 1969, Minshall
1984). The objective of this study was to correlate mussel and fish assemblage structures
to each other and to macro- and micro-habitat descriptors.

Methods

Mussels, fish, and sediments were collected from 30 sites in the Coastal Plain
Physiographic Province of the ACF basin (Fig. 3-1). These 30 sites represent a subset of
150 ACF tributary streams originally surveyed for mussels from 1991 to 1992 (Brim Box
and Williams, in press). Measurements of species diversity at each of the original 150
sites indicated a wide range of mussel richness. Therefore, each of the original 150 sites
was assigned to one of six species richness categories (very low =1-2 species; low = 3-4
species; medium = 5-6 species; medium high = 7-8 species; high = 9-10 species; very

41

high 11-12 species). Sites that were not in the coastal plain or where no mussels were
found were excluded from further consideration. From the remaining pool of 62 sites,
five sites were randomly selected from each of the six species richness categories to be
the 30 sites used in this study.

At each of the 30 sites, a 100-m reach was delineated and stratified for sampling into
bank, slope, and channel habitats. These habitats were defined by a combination of
physical and geomorphologic attributes of the channel morphology. The bank habitat
extended from the shoreline to the point in the channel where the depth began to increase,
indicating the beginning of the slope habitat. The slope habitat ended where the gradient
leveled out, indicating the beginning of the channel habitat. Visible changes in substrate
(e.g., mud to sand) also were used to demarcate these habitats and generally coincided
with changes in gradient. Previous sampling in the New River, Florida, a Suwannee
River tributary that also drains into the Apalachicola Region, indicated that mussel
species composition and density differed significantly among these three habitats (J. Brim
Box and L. Arvanitis, unpublished data).

At each of the 30 sites, mussels, fish, and sediments were collected from the same
100-m reach. Upstream and downstream sections were blocked off using nets. Fish were
collected using DC backpack electroshocking, one of the least selective of all active
fishing gears (Reynolds 1983). This technique is especially effective in coastal plain
streams that typically have high turbidity and multiple debris dams. Larger fish that
could be identified to species were measured and released. Any fish that could not be
identified in the field was preserved and identified in the laboratory. The total shock time

42

(sec) was recorded and used to calculate fish density per site, defined as the total number
offish captured per total shock time. Fish richness, abundance, and diversity {H") of
each of the 30 sites were determined from these data. Some fish species were classified
as obligate benthic species, based on either feeding or reproductive guilds, following
Burkhead et al. (1997). Fish considered obligate benthic species based on feeding guild
were benthic insectivores, whereas fish considered obligate benthic species based on
spawning guild included buriers, attachers, and cavity nesters. These fish were
subsequently referred to as obligate benthic feeders or obligate benthic breeders.

Quadrats were used to collect samples of mussels and sediments from the bank,
slope, and channel habitats. In each habitat, 32 quadrats (0.25 mQ were selected
randomly from a grid for collecting mussels. This number was based on an estimate
from Downing and Downing (1992), given a 95% level of confidence and a precision of
20% of the true mean number of mussels/ml All mussels falling within or touching the
sides of the quadrats were placed into dive bags (noting quadrat number and habitat
fyp^)j identified to species, and returned to the substrate. These data were used to
determine mussel species richness, abundance, diversity {H'), and evenness {S') per site.
Historical mussel richness for each site was also determined using museum records and
prior survey data (Brim Box and Williams, in press). The percentage of rare mussels,
those that had previously been considered endangered, threatened, or of special concern
in any part of their range (Williams et al. 1993, Williams and Butler 1994, USFWS
1998), was also determined. The percent stream area sampled was calculated as the total

43

area sampled by the quadrats (24 m^) divided by the stream area (width* length) and
multiplied by 100.

At each site and quadrat a 4.7- cm-diameter core was collected from the top 8.5 cm
of sediment for determination of bulk density, porosity, and sediment particle size
composition. Bulk density is the ratio of mass to volume (g/cm^) of the bed material and
varies with composition and compaction of the sediments (Gordon et. al. 1992). Porosity
is inversely related to bulk density and is the ratio, in percent, of the volume of void space
to the total volume of the sample (Friedman 1992). We were unable to collect sediment
cores from 195 quadrats that contained predominantly rock; therefore our total sample
size was limited to 2685 quadrats.

There are no standard methods for characterizing sediments in freshwater streams in
ecological studies (Bovee 1982, Gordon et al. 1992), but samples typically are divided
into a set of particle-size categories, and the relative proportion (by weight) in each of
these categories is measured. In this study, each quadrat sample was divided into 19
sediment particle-size categories that corresponded to 0.5 phi intervals of the Wentworth
scale (Wentworth 1922, and included pebble to clay-sized particles. The choice of
particle-size categories was guided by standard methods of fluvial geomorphology
(Mudroch and Azcue 1995) and by the desire to avoid the lack of resolution that can
occur with fewer size categories. The composition of sediment particle sizes larger than
silt was determined using a series of nested sieves (Folk 1980). The amount of silt and
clay (i.e., fine sediments < 0.063 mm) in each sample was determined by pipette analysis
(Folk 1980).

44

Statistical parameters of grain size are typically derived from a cumulative frequency
plot or measures of moments calculated from the weight of sediment in each size class
(Lindholm 1987, Gordon et al. 1992). In this study, we back-calculated the number of
particles present in each of the 19 size classes by assuming the density of each particle
was approximately 2.65 g/cm^ (the approximate density of quartz and sandy, siliceous
particles with little organic matter), and that each particle was spherical. These estimates
were then used to determine the average particle size, standard deviation, sorting,
skewness, and kurtosis of each sediment core sample, by using a method of moments
derived for grain-size calculation (Lindholm 1987). Sorting, defined as the standard
deviation of each core divided by the mean particle size (Lindholm 1987), is a measure of
the spread of particle sizes in the substrate. Sorting classes usually range from very well
sorted to very poorly sorted (Gordon et al. 1992). Skewness measures the asymmetry of
the substrate distribution, ranging from strongly fine-skewed (positive skewness) to
strongly coarse-skewed (negative skewness). Kurtosis measures the ratio between the
sorting in the tails of the distribution and sorting in the central portion of the distribution
(Lindholm 1987). The resulting distributions ranged from very platykurtic (flat peaked)
to extremely leptokurtic (central portion is better sorted than the tails of the distribution).

Spearman's rank correlation coefficient (p) was used to determine whether substrate
composition (as described by the above measures) and/or fish and mussel assemblage
structure were correlated at the site level. An alternative form of Spearman's rank
correlation coefficient, the Hotelling-Pabst test (Conover 1971), was used to test the null
hypothesis that attributes of the fish and mussel communities (e.g., species richness and

45

species abundance) and substrate composition were mutually independent. The
alternative hypothesis of this two-tailed test is that there is a tendency for an attribute of
the fish community to be either positively (or negatively) correlated with an attribute of
the mussel community, or for attributes of the fish and/or mussel community to be either
positively or negatively correlated with attributes of the substrate.

To examine whether mussel or fish assemblage structure varied with stream size or
subbasin, each stream was assigned a stream order (Shreve 1966), link magnitude
(Knighton 1984), and hydrologic unit (USGS 1975a, b and c). Stream order was
determined by designating each finger-tip tributary as first order (magnitude one), and
each subsequent stream link as a magnitude equal to the sum of all the first-order
segments that were tributary to it (Shreve 1966). Link magnitude measures the number
of first-order segments above a specific point on a stream and is more sensitive than
stream order for describing hydrological variability (Osborne and Wiley 1992, Haag and
Warren 1998). Hydrologic units correspond to cataloging units shown on USGS
hydrologic unit maps and are differentiated by physiography, climate, and hydrological
characteristics (Frick et al. 1996). The eight units encompassed in this study were
Chipola, Spring, Ichawaynochaway, Lower Flint, Kinchafoonee-Muckalee, Middle Flint,
Lower Chattahoochee, and Middle Chattahoochee- Walter F. George Reservoir (USGS
1975a, b, and c).

Morisita's Index of Similarity (!„,) was used to measure the similarity of mussel
community composition within stream order (Strahler 1957) and hydrologic unit. The
index varies from 0 (no similarity) to 1 .0 (complete similarity). Of the approximately

46

two dozen similarity indices available, Morisita's Index is the best overall measure of
similarity for ecological use (Krebs 1989). Coefficients of variation were calculated to
assess the variability of total mussel and fish abundance and richness in each stream order
and hydrologic unit. First- and second-order streams were pooled for these analyses,
because only two streams of each order were included in this study.

At least one species of rare mussel was found at 20 of the 30 study sites. A t-test
was used to assess if the 1 0 sites where no rare mussels occurred differed in habitat
quality from the other 20 sites, based on the percentage of fine sediments in the bank,
slope, and middle habitats. Relationships between mussel and fish assemblage structure
and macro- and micro-habitat variables, as described previously, were also examined for
these 20 sites.

A sub-set of the data was also used to determine whether the abundance of a mussel
species was related to the density of its host fish. Mussel-host fish relationships were
examined if two criteria were met: 1) if the host fish for a mussel species had been
reported in the literature and verified through laboratory experimentation and 2) if a
mussel species accounted for > 2% of the total mussel abundance in this study. Fish
density per site was defined as the number of fish of a particular species captured per
total shock time. The hypothesis that mussel abundance increased with increasing
host-fish density (a one-tailed test for positive correlation) was examined using
Spearman's rank correlation analysis. The following mussel/host-fish relationships were
examined; Elliptio icterina/Micropterus salmoides. Lepomis macrochirus (Keller and
Ruessler 1997); Utterbackia imbecillis/M. salmoides. L. macrochirus (Keller and

47

Ruessler 1997); Villosa Uenosa/M- salmoides. L. macrochinis (Keller and Ruessler
1997); Villosa yibex/M- salmoides. M- punctulatus. L. cvanellus (Haag and Warren
1997); Villosa villosa/M- salmoides (Keller and Ruessler 1997); Pleurohema pyriforme
/Pteronotropis hvpselopterus (O'Brien 1997).

Results

A total of 2, 662 mussels (Table 4-1) and 7, 665 fish (Table 4-2) were collected from
the 30 sites. Of the 25 species of mussels collected, the majority were Elliptio (70%) or
^iliosa (16%). Nine mussel species, Elliptio complanata. E. crassidens. E. icterina.
Toxolasma paulus, Uniomerus carolinianus. Utterbackia imbecillis. Villosa lienosa. V-
yjbex, and V- villosa were found in at least one percent of the 2685 quadrats. Of the 54
species of fish collected, the majority were cyprinids (51%), centrarchids (18%), or
percids (13%). Twenty species accounted for at least one percent of the fish surveyed
(Table 4-2).

Significant relationships were detected between mussel assemblage structure and
macro- and micro-habitat descriptors, fish assemblage structure and macro- and
micro-habitat descriptors, but not between mussel and fish assemblage structures (Table
4-3). The percentage of rare mussels was positively correlated with link magnitude (p =

0.463, p = 0.01) and stream order (p = 0.436, p = 0.016). Fish richness also increased
with increasing stream size. No trend was obvious, however, between mussel richness
and stream size. The highest mussel and fish abundance occurred in the smallest streams.

To determine if fish and mussel abundance

48

Table 4-1 . Total number of each species of mussel collected from
quadrats at 30 sites in the ACF basin from 1994 to 1995.

Species

Common Name

Total Number

Anodonta sp,

1

Anodontoides radiatus

Rayed creekshell

3

Elliptio arctata

Delicate spike

8

Elliptic complanata

Eastern elliptio

1,542

Elliptio crassidens

Elephant ear

70

Elliptio icterina

Variable spike

211

Elliptio purpurella

Inflated spike

21

Elliptio sp.

21

Lampsilis claibomensis

Southern fatmucket

6

Lampsilis subangulata

ShinjTayed pocketbook

7

Medionidus penicillatus

Gulf moccasinshell

12

Megalonaias nervosa

Washboard

1

Pleurobema pvri forme

Oval pigtoe

18

Pveanodon erandis

Giant floater

1

Ouincuncina infucata

Sculptured pigtoe

17

Strophitus subvexus

Southern creek mussel

4

Toxolasma paulus

Iridescent lilliput

99

Uniomerus carolinianus

Florida pondhom

53

Utterbackia imbecillis

Paper pondshell

83

Utterbackia peugvae

Florida floater

41

Villosa lienosa

Little spectaclecase

282

Villosa vibex

Southern rainbow

94

Villosa villosa

Downy rainbow

60

Villosa sp.

3

Unidentified

4

Total

2, 662

49

Table 4-2. Total number of each species of fish collected from 30 ACT
basin sites from 1994 to 1995.

Family

Species

Common name

Total number

Anguillidae

Anouilla rostrata

American eel

1

Aphredoderidae

Aohredoderus savanus

pirate perch

231

Atherinidae

Labidesthes sicculus

brook silverside

409

Catostomidae

Erimvzon sucetta

lake chubsucker

7

Catostomidae

Hvoentelium etowanum

Alabama hog sucker

6

Catostomidae

Minvtrema melanops

spotted sucker

36

Catostomidae

Moxostoma sp.

9

Centrarchidae

Ambloolites ariommus

shadow bass

1

Centrarchidae

Elassoma okefenokee

Okefenokee pygmy sunfish

2

Centrarchidae

Elassoma zonatum

banded pygmy sunfish

17

Centrarchidae

Lepomis auritus

redbreast sunfish

305

Centrarchidae

Leoomis cvanellus

green sunfish

91

Centrarchidae

Leoomis oulosus

warmouth

41

Centrarchidae

Leoomis macrochirus

bulegill

353

Centrarchidae

Leoomis maroinatus

dollar sunfish

21

Centrarchidae

Lepomis meoalotis

longear sunfish

10

Centrarchidae

Leoomis microlophus

redear sunfish

30

Centrarchidae

Lepomis punctatus

spotted sunfish

474

Centrarchidae

Microoterus punctulatus

spotted bass

15

Centrarchidae

Micropterus salmoides

largemouth bass

26

Centrarchidae

Pomoxis nioromaculatus

black crappie

1

Cyprinidae

Camoostoma oliooleois

largescale stoneroller

23

Cyprinidae

Cvorinella venasta

blacktail shiner

353

Cyprinidae

Hvbopsis winchelli

clear chub

65

Cyprinidae

Luxilus zonistius

bandfin shiner

2

Cyprinidae

Notemioonus crvsoleucas

golden shiner

40

Cyprinidae

Notroois buccatus

silverjaw minnow

232

Cyprinidae

Notroois chalvbaeijs

ironcolor shiner

10

Cyprinidae

Notropis cumminosae

dusky shiner

48

Cyprinidae

Notropis harperi

redeye chub

641

Cyprinidae

Notropis lonoirostris

longnose shiner

182

Cyprinidae

Notropis petersoni

coastal shiner

296

50

Table 4-2, continued

Family

Species

Common name

Total number

Cyprinidae

Notropis texanus

weed shiner

673

Cyprinidae

Notropis winchelli

clear chub

17

Cyprinidae

OosoDoeodus emiliae

pugnose shiner

76

Cyprinidae

PteronotroDis eurvzonus

broadstripe shiner

109

Cyprinidae

Pteronotropis hvoselopterus

sailfin shiner

1146

Cyprinidae

Semotilus thoreauianus

Dixie chub

6

Esocidae

Esox americanus americanus

redfin pickerel

43

Esocidae

Esox nicer

chain pickerel

2

Fundulidae

Fundulus lineolatus

lined topminnow

2

Fundulidae

Fundulus olivaceus

blackspotted topminnow

18

Ictaluridae

Ameiurus brunneus

snail bullhead

46

Ictaluridae

Ameiurus natalis

yellow bullhead

13

Ictaluridae

Ameiurus nebulosus

brown bullhead

1

Ictaluridae

Ameiurus serracanthus

spotted bullhead

8

Ictaluridae

Ictalurus punctatus

channel catfish

1

Ictaluridae

Noturus leotacanthus

speckled madtom

93

Pecidae

Percina niarofasciata

blackbanded darter

720

Percidae

Etheostoma edwini

brown darter

141

Percidae

Etheostoma swaini

gulf darter

106

Petromyzontidae

Ichthvomvzon aaaei

southern brook lamprey

30

Poeciliidae

Gambusia hobrooki

eastern mosquitofish

212

Soleidae

Trinectes maculatus

hogchoker

3

Total 7,665

51

O w

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bulk density -0.24 -0.28 -0.4122* -0.02 0.06 0.06 0.01 -0.3926* 0.13

52

decreased with stream size because of sampling effort (e.g., because 96 quadrats were
sampled per site, larger streams had proportionally less area surveyed), correlation
coefficients were calculated between mussel and fish abundance and either the percentage
of stream area surveyed per site or shock time. These correlations were not significant,
suggesting that the number of mussels and fish collected in this study were independent
of area or time sampled.

The smallest streams were the least variable in fish abundance and richness, whereas
the largest streams were the least variable in overall mussel richness and abundance
(Table 4-4). Small (first and second order) and medium-sized (third order) streams were
dominated by a single species, Elliptio complanata. This species accounted for 7 1 % of
the individuals collected in first/second order streams and 60% of the mussels collected in
third-order streams. Species evenness {J') decreased from large to small streams. Larger
streams (fourth and fifth order) were more diverse (//' = 2.69 for fifth order, 2.83 for
fourth order) and even {J' = 0.69 for fourth order and 0.71 for fifth order) than third {H' =
2.08, J' = 0.55) or first/second (//' = 1 .74, J' — 0.43) order streams. Fifth-order streams
were the least similar to one another in mussel composition, which was very similar for
all other stream orders (Table 4-5). Mussel assemblage structure within hydrologic units
ranged from very similar in Chipola (I„ = 0.91) to dissimilar in Ichawaynachaway(In, =
0.25).

Fish and mussel assemblage structure were correlated with several substrate
properties (Table 4-3). Mussel diversity was positively correlated with porosity (p =

53

Table 4-4. Coefficients of variation used to assess mussel and fish richness and
abundance. Variation per stream order was interpreted as cv < 25% = unvariable; 26%
< 50% = slightly variable; 51% < cv < 75% = moderately variable; cv > 76% = highly
variable.

Stream Order

Mussel abundance

Coefficient of
Mussel richness

Variation (%)
Fish abundance

Fish richness

1-2

95

43

63

13

3

153

59

90

49

4

111

40

75

24

5

78

26

104

35

Table 4-5. Similarity of mussel assemblage structure, based on Morisita'
Index (IJ values, within each stream order and hydrological unit. The
index ranges from 0 (no similarity) to 1.0 (complete similarity).

Stream Order

Morisita's Index (I J

1-2

0.71

3

0.83

4

0.76

5

0.11

Hydrologic Unit

Morisita's Index (I J

Chipola

0.91

Ichawaynachaway

0.25

Kinchafoonee

0.59

Lower Chattahoochee

0.86

Middle Chattahoochee

0.31

Middle Flint

0.60

Spring

0.60

Upper Flint

0.00

55

0.4018, p = 0.0277). Mussel richness was negatively correlated with the percentage of
fine sediments (p = -.6829, p = 0.0434), and positively correlated with mean particle size
(p = 0.4520, p = 0.0122). Mussel abundance was negatively correlated with the
percentage of fine sediments (p = -0.5193, p = 0.0033). The percentage of obligate
benthic feeders (but not breeders) was negatively correlated with sediment sorting (p =
-0.5546, p — 0.0015) and bulk density (p = -0.3926, p = 0.0319), and positively correlated
with porosity (p = 0.4091, p = 0.0248).

At the 20 sites where at least one species of rare mussel occurred, a significant
positive correlation (p = 0.5521, p = 0.01 16) was found between the presence of rare
mussels and obligate benthic breeders. Fish richness was positively correlated with
mussel richness (p = 0.5933, p = 0.0058) and sediment sorting (p = 0.4502, p = 0.0464).
Mussel diversity was negatively correlated with bulk density (p = -0.5027, p = 0.0239).
These 20 sites also had significantly less fine sediments present (t-test, p < 0.05) in all
three habitats (bank, slope, middle) than at the other 10 sites.

Mussel species used in this study to test host fish/mussel relationships employed one
of three reproductive strategies to attract potential host fish. Villosa lienosa. V. vibex and
V. villosa were considered displaying host specialists. Elliptio icterina and Pleurohema
pyriforme were considered nondisplaying host specialists, and Utterbackia imbecillis was
considered a host generalist. The abundance of only IJ. imbecillis was positively
correlated to the density of its host fish (Table 4-6).

Table 4-6. Correlations of mussel abundance with fish density (* significant correlation at a = 0.05).

56

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57

Discussion

Stream Size

Small and medium-sized streams were dominated by a single species, Elliptio
complanata. This species accounted for 71% of the individuals collected in first/second
order streams and 60% of the mussels collected in third-order streams. Not surprisingly,
species evenness also decreased from large to small streams. Larger streams (fourth and
fifth order) were more diverse and even than third or first/second order streams.
Therefore, the high level of similarity between small and medium-sized streams in this
study can partially be explained by the influence of a single, abundant species. These
results differ from what has been reported from other studies. In northwestern Alabama,
the mussel faunas of large stream sites were similar whereas the faunal composition of
headwater sites was variable, especially for sites in different drainages (Haag and Warren
1998). The variability could not be explained merely by host-fish availability or habitat.
Differences in mussel community structure in southern Michigan streams were attributed
to underlying geological differences that caused variability in channel geomorphology
among similar-sized streams (Strayer 1983).

The percentage of rare mussels increased with link magnitude and stream order and
was attributed to species replacement rather than addition, because no significant
relationship was found between mussel richness and stream size. Freshwater mussels
probably evolved from marine ancestors and moved upstream, and thus species richness
is thought to increase from the headwater to the mouth (Vannote et al. 1980). Mussel
richness increased downstream in other studies due to species addition (van der Schalie

58

1938b, Cvancara 1970, Haag and Warren 1998). It is not clear why species replacement
rather than addition occurred downstream in this study. Fish richness in this study did
increase with stream size, an observation consistent with other studies in which increased
species richness was due to a combination of species replacement and addition (Sheldon
1968, Edds 1993, Paller 1994).

Substrate

Mussel community structure, including diversity, richness, and abundance, was
correlated with aspects of substrate composition. For instance, mussel diversity was
positively correlated with porosity. Although the effects of deposited sediment on lotic
habitats have been well documented for other faunal groups, especially fish (Peters 1967,
Muncy et al. 1979, Berkman and Rabeni 1987), porosity has seldom been used to
describe the impacts of sedimentation on stream faunas. This is surprising, in that much
of the impact of deposited sediments on aquatic faunas relates to the filling of interstitial
spaces by fine sediments, and porosity is a measure of inter-particle space (Friedman et
al. 1992). Porosity was also negatively correlated with sediment sorting (p = -0.5898, p =
0.0006). This is not surprising, because sorting measures the spread of particle sizes in
the substrate (Gordon et al. 1992), and substrates with low porosity and high sorting may
indicate that interstitial pore spaces are filled with fine sediments. This hypothesis is
supported, albeit indirectly, by the observation that mussel richness and abundance
decreased as the percentage of fine sediments increased per site. Although there has been
much anecdotal information linking increased fine sediment production to changes in
freshwater mussel populations (Ellis 1931, van der Schalie 1938a, Clench 1955, Stein

59

1972, Bogan 1993, Williams and Neves 1995), definitive studies linking the two are
lacking (Brim Box and Mossa in press). However, it is possible that habitat suitability
for mussels is partly defined by the quality of the interstitial space, as it is for speleophilic
fish (Balon 1975) and their fry (Bustard and Narver 1975, Hillman et al. 1987).

Fish and mussel community structure in this study were closely related to streambed
substrate composition. Substrate properties, including grain size, provided little
predictive information about mussel assemblages in other studies (Layzer and Madison
1995, DiMaio and Corkum 1995, Haag and Warren 1998). The lack of association
between mussel community structure and micro-habitat variables in previous studies may
be related to difficulties associated with identifying and quantifying sediment loads, both
natural or human-induced, and quantifying the subsequent impacts on unionid mussels. It
is often not clear what physical properties of the streambed are important to measure, and
as a result, the same mussel species have been judged tolerant or intolerant in different
studies (e.g., Stein 1972, Houp 1993). In addition, conventional measurements of water
velocity, depth, substrate composition, and other micro-habitat variables have not always
provided the information needed to predict the occurrence or density of unionids in
streams (Holland-Bartels 1990, Strayer and Ralley 1993, Strayer et al. 1994). Part of the
problem relates to the sampling designs used to survey mussel populations and their
habitats. It is often difficult to devise a sampling scheme that accounts for differences in
the spatial heterogeneity of mussels and habitat-related variables. In addition, although
much of the literature on freshwater mussels, sediment transport, and channel change is
based on qualitative or anecdotal information, rigorous and sophisticated sampling

60

methods must be adopted to clarify relationships between these elements. Our ability to
correlate mussel assemblage structure in this study to aspects of substrate composition
may be related to both the number of samples collected (> 2, 500) and sediment size
fractions analyzed (19). Dividing substrate samples into too few particle categories can
obscure relationships between aquatic biota and substrate composition, and collecting too
few samples inhibits the ability to draw meaningful inference between mussels and
micro-habitat variables (Brim Box and Mossa 1999).

Fish

Freshwater mussel assemblage structure in this study was closely related to both
macro- and micro-habitat descriptors, but was poorly correlated to fish assemblage
structure. These results differ from several other studies that found aspects of the fish and
mussel assemblage to be closely linked (Watters 1992, Haag and Warren 1998). In Ohio
River tributaries mussel distribution and diversity were closely related to the distribution
and diversity of fish (Watters 1992). Aspects of the fish and mussel faunas were
correlated in two Black Warrior River tributaries, because the streams were relatively
unmodified by humans (Haag and Warren 1998). Similarly, in this study, when the 10
sites that contained no rare mussels were removed from analyses, significant relationships
were found between the percentage of rare mussels at the remaining 20 sites, the
percentage of obligate benthic breeders, and fish richness. These relationships were not
significant when all 30 sites were included. Because freshwater mussels are sensitive to
water quality and/or habitat degradation (Keller and Zam 1991, Goudreau et al. 1993,
Jacobson et al 1993), the lack of rare mussels at these sites suggests that significant

61

habitat degradation has occurred. This is supported by the fact that the 10 sites with no
rare mussels also contained a significantly higher percentage of fine sediments than the
other 20 sites. However, there was no attempt made in this study to score water or habitat
quality quantitatively at each site, other than in respect to substrate composition. Further
studies are needed to test the hypothesis that the lack of rare mussels at sites where they
historically occurred can be used as a quantitative tool for assessing habitat degradation.

The percentage of benthic obligate feeders was positively correlated with sediment
porosity and negatively correlated with sediment sorting. The results of this study
suggest that the distribution of obligate benthic fish species in the ACF basin may be
partially limited by substrate quality, as measured by porosity, sediment sorting, and the
percentage of fine sediments present. In northeast Missouri, the abundance of fish
classified as benthic insectivores decreased as the percentage of fine sediments increased
(Berkman and Rabeni 1987). In the Etowah River drainage of northern Georgia, 80% of
the imperiled fish fauna was comprised of obligate benthic species (i.e., species that
spawn, feed, or shelter on the stream bottom), and elevated sedimentation was considered
the primary source of degradation to benthic habitats (Burkhead et al. 1997). The tricolor
shiner, Cvprinella caerulea. a crevice spawner, suffered reduced number of spawns and
number of propagules spawned when exposed to increased levels of suspended sediments
(Burkhead and Jelks 1998).

Five of the 30 sites surveyed are directly below small dams. At three of these sites a
large number of mussels (> 350) and fish ( > 400) were collected. At the fourth site, 5
mussels and 433 fish were collected, whereas at the fifth site, a moderate number of

62

mussels (197) and fish (120) were found. One site sits on the fall line between the
Coastal Plain and Piedmont physiographic provinces and is in the Upper Flint hydrologic
unit, one site is in the Chipola hydrologic unit, and the other three sites are in the Middle
Flint hydrologic unit. These streams range in size from first to fourth order. Because of
the disparity in size and location of these streams within the ACF basin, the large number
of mussels and/or fish found at these sites is probably a result of their proximity to these
small dams. These results are unexpected, in that dams, both large (Williams et al. 1992)
and small (Watters 1996), often reduce mussel diversity and abundance through
fluctuating flow regimes, scour, dissolved oxygen sags, water temperature changes, and
changes in the fish fauna (Neves et al. 1997). Numerous detrimental effects on fish
downstream from dams have also been documented (Petts 1984, Ligon et al. 1995). For
example, in the Etowah River in northern Georgia, only five species of fish, including
one nonindigenous to the river, were found below Allatoona Reservoir, and the
ichthyofauna did not fully recover for 64 river km below the dam (Burkhead et al. 1997).
The exact factors controlling the local faunal structures at these sites are unclear,
including whether the large number of potential host fish present enhanced the
reproductive success of unionid mussels. Alternatively, mussels and fish were simply
responding similarly to the same local, environmental factors.

Mussel/Host-Fish Relationships

It has often been stated that freshwater mussels owe their distributional patterns to
the superimposed range, abundance, or density of their host fish. Significant
relationships between the abundance of host fish and mussels were found for two of six

63

mussel/fish pairs tested by Haag and Warren (1998). Both mussel species whose
abundance was correlated to the density of their host fish were nondisplaying
host-specialists found only in larger streams. Haag and Warren (1998) speculated that the
density-dependent relationship between these mussel species and their host fish provided
a mechanism to increase chances of glochidia infestation in large streams where host-fish
abundances were stable, but was a disadvantage for persistence in variable headwater
stream environments. Similarly, no correlation was found in headwater streams in Ohio
and Texas between fish and mussel richness, although in larger Texas streams mussel
diversity was correlated with fish diversity and not drainage area, and the relationship
between fish and mussels determined the number of unionid species (Watters 1992). In
southern Michigan streams, correlations found between freshwater mussel diversity,
distribution, and drainage area were related to the strong correlations that existed between
fish distributions and drainage area, and between unionid mussels and fish (Strayer 1983).

In this study, the two mussel species considered nondisplaying host-specialists were
found in first- to fifth-order streams, and so it is doubtful that there is some longitudinal
pattern to their distribution and abundance that is linked to the availability of their host
fish. Also, it is curious that the only positive correlation found in this study between a
mussel species and its host fish was for Utterbackia imbecillis. a non-displaying host
generalist. Over a dozen host fish have been identified for U. imbecillis (Trdan and Hoeh
1982, Watters 1994), and glochidial parasitism in this species may be facultative rather
than obligate (Fuller 1974). In addition, only a few field studies have linked the
extirpation of unionids with the extirpation of their host fish, and most of that evidence is

64

anecdotal (Davenport and Warmuth 1965, Sickel 1982, Arter 1989). Other factors can
often be implicated in the disappearance of individual mussel populations. For instance,
the extirpation of many of the mussel species from the Caney Fork River system in
Tennessee was not correlated with the disappearance of fish hosts as supposed, but rather
was caused by the release of cold water from a dam in the study area (Layzer et al. 1993).
The lack of correlation in this study between the abundance of mussel species and their
host fish may indicate that other factors, such as suitable habitat, are more important in
delineating freshwater mussel distributions than host fish availability. Suitable host fish
may be available in sufficient numbers that relationships between the two faunal elements
appear to be density independent. In addition, factors that control the current distribution
of both mussels and fish in the basin may include stream size and habitat suitability.
However, because mussels are, in most cases, obligate parasites on fish, it cannot be
ignored that host fish must be available at suitable times in sufficient numbers to
complete the unionid reproductive cycle. In addition, the lack of sufficient suitable host
fish may explain the paucity of recent recruitment for many mussel species in the basin
(Brim Box and Williams 1999, O'Brien and Brim Box 1999) and should be explored.

CHAPTER 5

RESPONSE TO CATASTROPHIC BURIAL

Introduction

The greatest freshwater mussel diversity in the world is found in North America and
comprises approximately 300 species within two families, Unionidae and
Margaritiferidae (Turgeon et al. 1988). Currently 21 taxa (7% of the fauna) are presumed
to be extinct, and an additional 120 taxa (40% of the fauna) are considered to be
threatened (Williams and Neves 1995). Causes of the decline in unionid populations are
not fully known, but the following factors have been implicated: impoundments,
excessive sedimentation, overharvesting, commercial dredging, industrial and municipal
pollution, in-channel and floodplain gravel or sand mining, channelization, and
introduction of nonindigenous mollusks such as the Asian clam, Corbicula fluminea. and
the zebra mussel. Dreissena polymorpha tBogan 1993, Williams et al. 1993).

Perhaps one of the most ubiquitous factors that may adversely affect mussel
populations is excessive sedimentation caused, in part, by poor land use practices.
Excessive sedimentation has been suspected as a causal factor in the decline of unionid
mussels since the late 1800s (Kunz 1898). The Environmental Protection Agency cited
sediments as the number one pollutant of rivers in the United States, impairing over 40%
of the nation's river miles (U.S. Environmental Protection Agency 1990). This estimate
is nearly 50% higher than the estimate for the next factor.

65

66

Most sediments in fluvial systems originate within the river channel or from erosion
in the accompanying watershed. Studies of the effects of sedimentation on riverine biota
have focused primarily on sediments supplied from the watershed, which is not surprising
because it is estimated that 60% of the approximately 9058 x 10® tonnes of soils lost each
year from cropland in the United States is deposited in rivers, streams and reservoirs
(USDA 1989). Although crop farming is considered to be the most widespread human
activity that has increased sediment loads in North American rivers (Meade et al. 1990),
other significant sources of waterborne sediments include erosion from upland gullies,
roads, highway ditches, construction sites, and surface mined areas.

Increased sediment loads produce conspicuous changes in the physical character of
many rivers (Waters 1995). However, the effects of increased sedimentation on unionid
mussels are not well understood, although anecdotal evidence suggests that changes in
sedimentation rates and patterns may alter the composition and abundance of mussel
faunas. In the Mississippi, Tennessee, and Ohio rivers, erosional silt may have destroyed
a large portion of the mussel population by directly smothering the animals (Ellis 1931).

In the North Fork of the Red River, Kentucky, the mussel fauna changed during an
1 1 -year period from species that were intolerant of chronic sedimentation to species that,
because of their morphology and behavior, were considered to be highly tolerant of
sedimentation (Houp 1993). The sources of sedimentation in this river included coal
mining in the headwaters of the river, disturbances from a stream relocation project, and
logging practices in the watershed. In the Olentangy River, Ohio, increased
sedimentation may have led to the extirpation of 14 unionid species (Stein 1972).

67

The southeastern region of the United States contains more freshwater mussel
species (about 270) than any other region in North America (Williams and Neves 1995).
The majority of imperiled mussel species are found in southeastern rivers (Master 1990).
In the Apalachicola, Chattahoochee and Flint (ACF) River basin in Alabama, Florida, and
Georgia, unionid mussel diversity is greatly reduced from historical levels (Brim Box and
Williams 1999). Six species of ACF mussels were recently listed as endangered or
threatened by the U. S. Fish and Wildlife Service (USFWS 1998), and two additional
species are presumed to be extinct (USFWS 1994). The decline in freshwater mussel
populations in the basin has been attributed, in part, to land use modifications that cause
changes in sediment regimes and, correspondingly, increase sediment transport in streams
(Williams and Butler 1994, USFWS 1998, Brim Box and Williams in press). The
specific associations between unionid mussels and stream sediments, however, are poorly
understood, making it difficult to assess the impacts of changes in sedimentation rates.
Previous experimental studies (Ellis 1936, Vannote and Minshall 1982) have shown that
high mortality rates can occur when mussels are intentionally buried by even small
amounts of sediments. The effects of catastrophic burial on ACF mussels are not known,
although historical changes in sediment production in the basin (Glenn 1911, van der
Schalie 1938a, Clench 1955, Faye et al. 1980) suggest that mussel beds have periodically
been covered by erosional sediments. The objective of this study was to evaluate the
responses of four species of unionid mussels from the ACF basin to catastrophic burial by

both fine sediments and sand.

68

Methods

Four species of mussels, Quincuncina infiicata. Elliptio complanata. E. crassidens and
Yillosa lienosa, were used to assess the effects of catastrophic burial by sand and fine
sediments. Quincuncina infucata were collected from the Ochlockonee River, Grady
County, Florida, on 29 October 1996. Elliptio complanata were collected from Spring
Creek, a tributary of the Chipola River, Jackson County, Florida, on 30 January 1997.
Yillosa lienosa were collected from Kinchafoonee Creek, a tributary of the Flint River,
Webster County, Georgia, on 29 August 1997. Elliptio crassidens were collected from
the Chipola River, Calhoun County, Florida, on 7 September 1997. Adult mussels were
collected by hand and transported in coolers with ambient temperature river water to
flow-through current tanks at the USGS/BRD laboratory, Gainesville, Florida. Mussels
were held for a week before each experiment in order to acclimate them and to assess if
any mortality resulted from transport.

All experiments were conducted in 3 3 -liter, aerated aquaria, with about 4 inches of
sand that served as a base sediment for the mussels. All aquaria were maintained at 20 C
with a 12-hour photoperiod throughout the experiments. In each of 16 aquaria, 20
mussels of a single species were placed with their anterior end in the sediment. After 24
hours, mussels were checked to make sure they were partially buried in the base sediment
and were actively filtering.

To assess the response to catastrophic burial, mussels were buried in either sand or
fine (diatomaceous earth ) sediments. The sand was collected from the Suwannee River,
and a subsample was run through a series of 13 sieves. The sediment used in the

69

experiments consisted of approximately 99% sand-sized particles, 1% silt-sized particles,
and less than one percent granule gravel-sized particles. The fine sediments were
purchased commercially to avoid possible contamination with heavy metals that may
adhere to river-borne fine sediments. Four amounts of sedimentation (1 cm, 4 cm, 7 cm
and 14 cm) for each treatment were based on field observations of sediment transport in
the ACF basin. Two replicates of 20 mussels each were used in each trial (i.e., sediment
type/sediment amount combination). Thus, 320 mussels of each species were tested.

Mussels were checked for emergence daily over a ten day period. Mussels that
emerged from burial and were visibly filtering on the sediment surface were considered
successful migrants and were removed fi-om the treatment aquaria. Any mussel that
emerged but was dead was also removed, but was not counted as a success. At the end of
ten days, all remaining mussels were removed from the aquaria and recorded as buried
alive or dead.

Statistical Methods

Logistic regression models were used to evaluate the effects of sedimentation
amount and sediment type on migration success. Logistic regression models differ from
linear regression models in that the conditional distribution of the outcome variable
follows a binomial distribution with the probability given by the conditional mean, 7t(x)
(Hosmer and Lemeshow, 1989). This model was defined as

gpCH-piX

The logit transformation, g(x), was used in place of k(x), because it transforms the
relationship to one that is linear in its parameters. It is also continuous and ranges from

70

negative infinity to infinity (Hosmer and Lemeshow, 1989). The logit transformation
was defined as

In logistic regression, the log likelihood function, L(B), is minimized as a function of
the unknown parameters, B == {pg, ). The log likelihood function is defined as

The deviance, D, was used to assess the significance of sediment type and amount on
migration success and was defined as

The change in D (referred to as the residual deviance) with and without the independent
variable was evaluated as G = D(model without variable) - Z)(model with variable). The
likelihood ratio test statistic, G, will follow a chi-square distribution under the hypothesis
that is equal to zero (Hq: /3; = 0).

Odds ratios were used to quantify the impact of both sediment type (sand, fine
sediment) and sediment amount (1, 4, 7 or 14 cm) on the probability of migration
success. The odds ratio, \\f, was defined as the ratio of the odds for x=l to the odds of
x=0, or

The odds ratio approximates how much more likely (or unlikely) it is for the outcome to
be present among those with X=1 than among those with X=0 (Hosmer and Lemeshow

L(B) = ln{l(B) = L{ynn [7u(x,)] -l- (1 -y/)ln [1 -7t(x,)]}

7i(0)/[l-;t(0)]

1989).

71

For each of the four species, overdispersion first was assessed. This occurs when a
linear logistic model is considered adequate, but the residual mean deviance exceeds
unity, thus invalidating the assumption of binomial variability (Collett, 1991). If
overdispersion was not detected, the main effects of sediment type and amount on
migration success, as well as any interactions between these two variables, were
evaluated using goodness of fit and analysis of maximum likelihood estimates (Stokes et
al., 1995). If interactions between the independent variables were not significant,
sediment amount was modeled as a continuous variable, and odds ratios were used to
quantify the relative significance of sediment type and amount on migration success.

Results

Of the 320 Elliptio complanata buried, 258 migrated successfully through overlying
sediments while 62 failed to migrate. One hundred percent of the E. complanata buried
in 1 and 4 cm of fine sediments or sand migrated (Fig. 5-la). In comparison, 48% of the
E. complanata buried in 14 cm of sand migrated, while 28% successfully migrated in 14
cm of mud.

The residual deviance for the model that included the main effects of sediment type
and amount, as well as their interactions, was not significant (5.51 < X^8,.95>)> indicating
that overdispersion was not present. In addition, the change in deviance on adding the
interaction term in the model was 1 . 1 7 on 3 df, which also was not significant (x^^.ss ~
7.81), and the interaction terms were dropped from the model. Based on the likelihood
ratio test statistic, G, both sediment type (G, = 9.03) and sedimentation amount (G]= 145)
had a significant effect (x^ ,95 = 3.84) on migration success.

72

as + P91BJ6!LU jBL|i J0qujnu 0Bbj0av

Figure 5-1. Average number of mussels that migrated per sediment treatment for each of the four species.

73

Preliminary analysis suggested that both sediment type and amount had a significant
effect on migration success, amount was modeled as a continuous variable. The residual
chi-square (x^s), or score goodness of fit statistic was 0.4821, suggesting that the main
effects model adequately fit the data. In addition, analysis of the maximum likelihood
estimates indicated that both sediment type and amount were significant at the 0.05 level.
The following model was produced from these data:

g{x) = 4.84 + 1.21(sediment type) - 0.4347 (sedimentation amount)

The migration success of Elliptio complanata was negatively associated with burial
amount. The odds ratio for sediment type, 3.35, indicated that E. complanata were three
times more likely to migrate vertically in sand than in mud, adjusted for sediment
amount. The odds ratio for amount, 0.65, suggests that the odds of migrating decreased
per level increase in amount. Based on this ratio, it was estimated that E. complanata
were 440 times more likely to migrate in 1 cm of sediment than in 14 cm of sediment,
adjusted for sediment type.

Of the 320 Elliptio crassidens buried, 219 migrated successfully through overlying
sediments while 101 failed to migrate. Migration success was over 90% for E. crassidens
buried in 1 or 4 cm of mud or sand (Fig. 5-lb). In comparison, only 5% of the
individuals buried in 14 cm of mud successfully migrated, while 15% successfully
migrated through 14 cm of sand.

The residual deviance for the main effects model of sediment type and amount, as
well as their interactions, was not significant (10.9 < X%,.95)> indicating that
overdispersion was not present. In addition, the change in deviance on adding the

74

interaction term in the model was 7.0, which also was not significant (%% 95, = 7.81), and
the interaction terms were dropped from the model.

Preliminary analysis indicated that sediment amount (G, = 206), but not type (Gi=
1.71) had a significant effect on migration success, and therefore sediment amount was
modeled as a continuous variable. Although sediment type did not have a significant
effect on migration success, it was retained in the model (Stokes et al., 1995). The
residual chi-square, Xrs,i > was 2.60, indicating that the main effects model adequately fit
the data. Analysis of the maximum likelihood estimates also indicated that sedimentation
amount, but not type, had a significant effect on migration success. The following model
was produced from these data:

g(x) = 4.24 + 0.49(sediment type) - 0.48 (sedimentation amount)

The migration success of Elliptio crassidens was negatively associated with burial
amount. The odds ratio for amount, 0.61, is the extent that migration success decreased
per each cm increase in amount, adjusted for sediment type. Based on this odds ratio, it
was estimated that E. crassidens were over 900 times more likely to migrate in 1 cm of
sediment than 14 cm of sediment. The odds ratio for sediment type, 0.65, indicated that
E. crassidens were 1.5 times more likely to migrate vertically in sand than mud, adjusted
for amount.

Of the 320 Ouincuncina infucata buried, 1 87 migrated successfully through
overlying sediments while 133 failed to migrate. For this species, migration success
varied considerable among sedimentation amounts (Fig. 5-lc).

75

The residual deviance for the model that included the main effects of sediment type
and amount, as well as their interactions, was not significant (8.6 ^ s 95j)> indicating that
overdispersion was not present. However, the change in deviance on adding the
interaction term in the model was 20.94 ( i,.9s ~ 7.81), and the interaction terms were

retained in the model. The following model was produced from these data:

g(x) = -2.51 + 0.31(mud) + 3.36(one) + 4.06(four) + 3.48(seven) +1.35(one*mud)

- 0.31(four*mud) - 2.13 (seven*mud)

where mud = 1, sand = 0, and sediment amounts were either 0 or 1 . Based on this model,
mussels buried in 14 cm of mud were over 100 times less likely to migrate than mussels
buried in 1 cm of mud, and 28 times less likely to migrate in 7 cm of mud than 1 cm of
mud (Table 5-1). Mussels buried in 14 cm of sand also had low odds of migrating, about
30 times less than in 1 cm of sand, but mussels buried in 7 cm of sand were just as likely
to migrate as those buried in 1 cm of sand. At 7 cm, Ouincuncina infucata were six
times more likely to migrate through sand than mud.

76

Table 5-1. Odds ratios and parameter estimates, based on maximum
likelihood estimates, for Ouincuncina infucata. for all sediment amounts
and types.

Sediment Type

Sediment Amount (cm)

Logit

Odds of Migrating

Sand

14

-3

0

Sand

7

1

3

Sand

4

2

5

Sand

1

1

2

Mud

14

-2

0.11

Mud

7

-1

0

Mud

4

2

5

Mud

1

3

12

77

Of the 320 Villosa Ijenosa buried, 251 migrated successfully through overlying
sediments while 69 failed to migrate. One hundred percent of the V. lienosa buried in 4
and 7 cm of mud migrated, as did those buried in 1 or 4 cm of sand (Fig. 5- Id). In
comparison, 30% of the V. lienosa buried in 14 cm of sand migrated, while 12.5%
migrated in 14 cm of mud.

The residual deviance for the model that included the main effects of sediment type
and amount, as well as their interactions, was not significant (7.72 < g 95,), indicating
that overdispersion was not present. However, the change in deviance on adding the
interaction term in the model was 1 1.9, which was significant ( x%„95 = 7.81), and
therefore the interaction terms were retained in the model. The following model was
produced by these data:

g (x) = -0.85 - l.lO(mud) + 15.53(one) + 15.53(four) + 2.80(seven) +
1.10(mud*four). +13.84(mud*seven) - 9.92(mud*one)
where mud = 1 , sand = 0, and sediment amounts were either 0 or 1 . In general, the
estimated probabilities for migrating in either sediment type were high for 1 , 4 or 7 cm of
sediment, and decrease significantly in 14 cm of sediment (Table 5-2). The estimated
odds ratios suggest that Villosa lienosa were about a million times less likely to migrate
in 14 cm of sand or mud than 4 or 7 cm of mud, or 1 or 4 cm of sand. Mussels were 3
times more likely to migrate successfully in 14 cm of sand than 14 cm of mud.

78

Table 5-2. Odds ratios and parameter estimates, based on maximum
likelihood estimates, for Villosa lienosa. for all sediment amounts and
types.

Sediment Type

Sediment Amount (cm)

Logit

Odds of Migrating

Sand

14

-1

0

Sand

7

2

7

Sand

4

15

> 1,000,000

Sand

1

15

> 1,000,000

Mud

14

-2

0.14

Mud

7

15

>1,000,000

Mud

4

15

> 1,000,000

Mud

1

4

39

79

Discussion

Covering mussels with as little as 14 cm of sediments significantly decreases their
chances of extricating themselves from burial. Increased sediment loading, because it is
so ubiquitous, may therefore be an important cause of freshwater mussel declines.

More Elliptio complanata migrated in this study than any other species. This was
not surprising, given that this species is often both widespread and abundant (Taylor
1985, Strayer and Ralley 1991, Downing et al. 1993) and has been reported from a
variety of habitats, from small creeks to large rivers, as well as from ponds, lakes and
reservoirs (Counts et al, 1991). It was the most common species encountered in a recent
survey of the ACT Basin and occurred at 32% of 324 sites surveyed (Brim Box and
Williams 1 999). Elliptio complanata is often the most abundant unionid at a particular
site outside of the ACE Basin, and sometimes can be the only species present at a location
(Clarke and Berg 1959, Counts et al. 1991).

Elliptio complanata was the only species of the four tested for which migration was
significantly affected by sediment type. Elliptio complanata was three times more likely
to migrate through sand than mud, adjusted for rate. Although this species is found in a
wide variety of habitat types, it may grow faster (Kat, 1982), occur in higher densities
(Leff et al. 1990), and burrow more efficiently in sandy substrates (Lewis and Riebel
1984). In the ACE Basin, Brim Box and Williams (in press) found 93% of 2,524
specimens at sites that contained predominantly sand, sand and limestone rocks, or sand
and fine sediments (silts and clays). The results of this study suggest that E. complanata
is adept at moving through sandy sediments, as only 23 of the 160 mussels buried in sand

80

failed to migrate successfully. In addition, although migration success in sand was
significantly higher than in mud, the success rate in mud was also relatively high: 75% of
all animals buried in mud successfully migrated.

There is some evidence to suggest that Elliptio crassidens is more common in sandy
habitats than fine sediments, although sediment type did not have a significant effect in
this study. In Florida, Elliptio crassidens was reported from muddy sand, sand, and rock
substrates in moderate currents (Heard 1979), and in southeastern Georgia, it occurs in
strong currents in the sandbars of large rivers and creeks (Johnson 1970). In the ACE
Basin this species is known primarily from sites with sand and limestone rock substrates
(Brim Box and Williams 1999). Alternatively, Hamilton et al. (1997) suggested E.
crassidens may be a habitat generalist, in that it has been found in a range of substrate
types. This is consistent with this study, in that sediment amount but not type had a
significant effect on migration success.

Successful migration was recorded for only 5% of the Elliptio crassidens that were
buried in 14 cm of mud and 15% buried in 14 cm of sand. In comparison, 28% of the E.
complanata buried in mud and 48% buried in sand successfully migrated. This
experiment was not designed to compare species (e.g., mussels of multiple species were
not buried in the same aquaria at the same time). These results do suggest, however, that
because both of these species are in the same genus, the effects of catastrophic burial are
species-specific.

Migration success for Villosa lienosa in this study was high in both mud and sand at
all sediment amounts except 14 cm. In 14 cm of sediment, this species was three times

81

more likely to migrate through sand than mud. High migration success (over 85%) in
both sediment types except at 14 cm may help to explain why this species, like Elliptio
complanata, is widespread and abundant in the ACF Basin (Brim Box and Williams
1999). Yillosa lienosa was able to extricate itself from burial in both sand and mud, and
there is some evidence to suggest that it may be a habitat generalist, as it has been
reported from a wide variety of habitat types, from soft mud to underneath rocks in fast
current (Jenkinson 1973), to sandy substrates in slight to moderate current (Heard 1979),
to muddy substrates in detritus-rich areas (Clench and Turner 1956).

Quincuncina infucata was the least likely to successfully migrate of the four species
tested. About 59% of all Q. infucata buried successfully migrated. Migration success for
this species was low for mussels buried in 14 cm of mud (10%) or sand (8%). In contrast,
over 70% of the mussels buried in 7 cm of sand migrated, as compared to 30% in mud.
Observations of Q. infucata in the ACF Basin suggest that this species is usually found in
sand-bottomed pools and in rocky areas with swift currents (Jenkinson 1973), to sand,
muddy sand and fine gravel substrates in small to large streams with moderate current
(Heard 1975, 1979). The inability of Q. infucata to migrate through overlying sediments
may partly explain why this species has disappeared from the entire main channel of the
Chattahoochee River, several Chattahoochee River tributaries, and portions of the
Apalachicola River, and why it was recently considered a species of special concern in
the basin (Brim Box and Williams 1999).

The mussel fauna of the ACF basin is in decline. Although specific causal factors
have been poorly documented, sediment erosion associated with basin and riparian land

82

use changes has numerous potential effects on benthic invertebrates and their habitats
(Chutter 1969, Waters 1995). Changes in sediment production have been particularly
well documented in the Chattahoochee River system since early this century, and of the
four major rivers of the basin, the Chattahoochee River has suffered the most serious
decline in mussel populations. For instance, 30 species were historically known from the
Chattahoochee system, but only about half of those species persist there today (Brim Box
and Williams 1999). Of the eight species that were recently listed as federally threatened
or endangered (USFWS 1998) or extinct (USFWS 1994), six historically occurred in the
Chattahoochee basin, but only two of these species persist there, and only in a few
tributary streams. None of the six species has been collected from the main stem of the
Chattahoochee River in over 20 years. All four of the species that were used in this study
were historically found in the Chattahoochee River system. Elliptio complanata and
Villosa lienosa are still found in large numbers in several Chattahoochee River
tributaries, while Elliptio crassidens and Ouincuncina infucata are rare there (Brim Box
and Williams 1999). None of these species was found in the main channel of that river.

Reductions in the mussel fauna of the ACF Basin during the past 150 years may
have been caused by species-level responses to changes in substrate composition that
resulted from changes in sedimentation patterns. Soil erosion in the Piedmont and
Coastal Plain physiographic regions was noted early (Glenn 1911), and intensive land
clearing for cotton and row-crops in the 1 9th century led to extensive erosion and gully
formation in this region (Bennett 1939). In the counties that border the Chattahoochee
River, settlement began in the 1750s, land was converted to cotton plantations, and by the

83

Civil War severe soil erosion was evident (Trimble 1974). Tenant fanning with
conesponding poor farming practices after the Civil War exacerbated the problem, and
erosive land uses continued until about the 1930s. During this period, erosional
sediments filled streams and covered floodplains (Trimble 1974), and by the late 1930s it
was estimated that 44 percent of the land in Georgia had reached the gullying stage, and
22 percent of the land had been abandoned due to erosion, although these high figures
were latter disputed (Magilligan and Beach 1993). Correspondingly, as early as 1915 the
historically diverse mussel fauna of the Chattahoochee River at Columbus, Georgia, was
in decline, and by 1929 it was apparently extirpated (Clench and Turner 1956). Erosional
sediment was implicated early on for mussel declines in the ACF basin (van der Schalie
1938a), especially in the Chattahoochee River system (Clench 1955, Clench and Turner,
1956). Clench (1955) also noted that while the Flint River also suffered from silting, a
series of large springs mitigated the negative impacts of sedimentation. However, it is
cautioned that further experiments and field studies are needed to draw inference between
historical changes in sediment deposition within the Chattahoochee River and mussel
extirpations.

Several mechanisms for the intolerance of some unionid species to increased levels
of sediment deposition seem possible and are likely to differ among species.

Sediment deposition may impact freshwater mussels by interfering with feeding and/or
respiration, as it does for other invertebrates, particularly Odonata, Trichoptera, and other
families of Bivalvia (Hynes 1960, Minshall 1984, Robinson et al. 1984). Inorganic silt
in suspension reduced the amount of food available to the common mussel, Mytilus

84

edulis, through dilution, rather than by affecting the amount of material filtered by the
mussel (Widdows et al. 1979). Hard clams, Mercenaria mercenaria. had significantly
lower clearance rates and algal ingestion rates with increasing sediment loads (Bricelj and
Malouf 1984), and juvenile hard clams had significantly lower growth rates at suspended
fine sediment concentrations of 44 mg/L (Bricelj et al. 1984). Suspended clays and fine
silts can also settle out of the water column, even in turbulent streams, and stick to
benthic invertebrates, which can be damaged by the accumulation of these particles on
their body surfaces (Davies-Colley et al. 1992). The main impacts of excess
sedimentation on unionids are often sublethal, and detrimental effects may not be
immediately apparent. Elliptio complanata had significantly lower growth rates in
muddy substrates than in a sand/gravel/clay mix, possibly because the fine sediments in
suspension in the muddy substrates clogged gill filaments and reduced feeding
efficiencies, which was especially apparent at higher population densities (Kat 1982).

Migration rates varied considerably for the four mussel species used in these
experiments, suggesting the ability to migrate vertically through overlying sediments is
species-specific. These results are consistent with other laboratory studies that have
examined the impacts of gradual or catastrophic burial on unionid mussels. When
Fusconaia flava were intentionally buried with silt and sand in an Upper Mississippi
River experiment, 55% of the individuals died when buried under 10 cm of material
(Marking and Bills 1980). In this same experiment, two other species, Lampsilis
siliquoidea and L- cardium. were more adept at moving vertically through the deposited
material and suffered lower mortality rates. In laboratory trials Gonidea angulata were

85

able to move vertically under varying rates of sedimentation, while Margaritifera falcata
remained buried until they died (Vannote and Minshall 1982). This may partially explain
why, in the Salmon River Canyon in Idaho, populations of M. falcata were buried alive in
canyon reaches that were aggrading with sand and gravel caused by mining, logging,
irrigation diversion, and massive slope failure of a tributary stream caused by hydraulic
mining activities (Vannote and Minshall 1982). The dead, buried populations of M.
falcata were found intact in beds that were inundated by sand and gravel bars, and G-
angulata replaced M- falcata in reaches aggrading or inundated with sand. In the ACT
Basin, the ability of V. lienosa and E. complanata to migrate through both mud and sand
may help to explain why these two species are widespread and common in the basin, and
20 other species are either extinct, extirpated, endangered, threatened or of special

concern.

CHAPTER 6
CONCLUSIONS

Whereas other authors have suggested that habitat is only of secondary importance
when describing fish and mussel distributions, the results of this study suggest that fish
and mussel community structure is closely related to stream size and suitable habitat.

This is not surprising, in that lotic fish faunas are often closely tied to landscape- level
processes (Schlosser 1991) and in the ACF basin, fish and mussel community structure is
regulated, in part, by interactions at the stream- floodplain interface (Michener et al.

1998). In addition, in streams that were historically degraded, some fish species may
have recovered, whereas mussels have not. For example, Pteronotropis hypselopterus.
the only known host fish in the basin for Pleurobema pyriforme. occurred at 16 sites,
whereas P. pyriforme were found at only six. Thus, because fish are vagile and mussels
are not, it is possible that fish can recolonize stream reaches much more quickly than
mussels. This notion could be tested in the Chattahoochee River drainage, where
historical levels of sedimentation were much higher than present levels (Kundell and
Rasmussel 1995), fish populations can be diverse and locally abundant, and mussel
communities are depauperate.

The causes for the decline of freshwater mussels in North America are not well
understood, although possible causes were summarized by van der Schalie (1938a),

Fuller (1974), Williams et al. (1993), and Bogan (1993). These include habitat

86

87

degradation, the introduction of exotic bivalves including the Asian clam, Corhicula
fluminea, and the zebra mussel, Dreissena polvmorpha. pollution and impoundments,
although in most cases, the information implicating these factors is qualitative and/or
anecdotal. Overharvesting, commercial dredging, in-channel gravel or sand mining,
channelization, and excess sedimentation caused, in part, by poor land use practices, are
also thought to impact unionids. van der Schalie (1938a) speculated the following factors
had contributed to the decline of the North American mussel fauna in the previous
decade: silting, pollution by sewage, mine and industrial wastes, power-dam
developments, and unrestricted mussel gathering for the pearl button industry. Bogan
(1993) suggested that the causes of unionid mussel declines are poorly known due to the
cumulative lack of knowledge of unionid life history, ecology, distribution, fish hosts,
and systematics.

Sedimentation processes have changed within the ACF basin over the past 200 years,
and these changes may have impacted unionid mussel populations early on, especially in
the Chattahoochee River drainage. In 1826, Richard Blount, a surveyor of the
Georgia- Alabama state line, wrote that he counted 36 trout (probably bass, genus
Micropterus) in the Chattahoochee River, near present day Lanett, Alabama, while
standing on the bank of the river, and that this was possible because the water was so
clear (Trimble 1974). Soil erosion in the Piedmont and Coastal Plain physiographic
provinces was noted early on, and intensive land clearing for cotton and row crops in the
19th century led to extensive gully formation in this region (Bennett 1939). In the
counties that border the Chattahoochee and Flint rivers, settlement began in about the

88

1750s, l&nd was converted to cotton plantations, and by the Civil War severe soil erosion
was evident (Trimble 1974). The most striking example of soil erosion in the basin is
Providence Canyon, Georgia's "Little Grand Canyon," where a group of seven
gullycanyons with up to 100 m of relief started forming in the mid- 1800s (Magilligan and
Beach 1993). Tenant farming with corresponding poor farming practices after the Civil
War exacerbated the problem, and erosive land uses continued until about the 1930s.
During this period, erosional sediments filled streams and covered floodplains (Trimble
1974). Begirming in the 1930s, erosion had decreased due to a combination of improved
soil conservation practices, the transition of farmland to pasture and forest, and an overall
decrease in agriculture. The average annual concentration of total suspended sediment in
the Chattahoochee River near Atlanta was about 400 ppm in the mid- 1930s (when
records are first available), compared to 1960s levels of less than 50 ppm (Hewlett and
Nutter 1969). This decrease in sediment yields had one potentially negative effect on
unionid mussels, however, in that lower stream order tributaries have incised into their
aggraded floodplains, and this headward incision produced new sources of high sediment
yield and led to continued valley aggradation (Trimble 1974).

By the mid-1970s, in the upper Chattahoochee River, the estimated average annual
erosion ranged from approximately 900 to 6,000 tons per square mile per year (Faye et al.
1980). Erosion yields were highest in watersheds with high percentages of agricultural
and transitional land uses, and lowest in urbanized watersheds. Conversely, estimated
average suspended sediment yields were highest in predominantly urban watersheds (800
tons per year) as compared to mostly forested watersheds (300 tons per year). A large

89

part of the sediment discharged from urban streams was probably due to channel erosion
(Faye et al. 1980). Increased sediment loads, especially fine sediment, can negatively
affect unionid mussels through several mechanisms. Fine silt and clay particles can clog
the gills of mussels (Ellis 1936), interfere with filter feeding (Kat 1982, Aldridge et al.
1987), or limit burrowing activity (Marking and Bills 1980, Vannote and Minshall 1982).
Fine sediments also may affect mussels indirectly by reducing the light available for
photosynthesis and thus reducing the availability of unionid food items (Kanehl and
Lyons 1992).

Difficulties in identifying and quantifying sediment loads, whether natural or
human-induced, have made it hard to assess the impacts of sedimentation on unionid
mussels. The same species have been judged tolerant or intolerant in different studies. In
addition, it is not clear what physical properties of the streambed are important to
measure. Conventional measurements of water velocity, depth, substrate composition,
and other microhabitat variables have not always provided the information needed to
predict the occurrence or density of unionids in streams (Holland-B artels 1990, Strayer
and Ralley 1993). Part of the problem relates to the sampling designs used to survey
mussel populations and their habitats. It is often difficult to devise a sampling scheme
that accounts for differences in the spatial heterogeneity of mussels and the spatial
heterogeneity of habitat-related variables.

Some researchers considered substrate particle size to be an important microhabitat
descriptor when assessing associations between mussels and their physical habitats
(Bronmark and Malmqvist 1982, Salmon and Green 1983, Leff et al. 1990), whereas

90

others have failed to find meaningful relationships between unionid mussels and substrate
composition (Lewis and Riebel 1984, Strayer and Ralley 1993, Di Maio and Corkum
1995, Layzer and Madison 1995). For example, Strayer and Ralley (1993) concluded that
microhabitat-mussel associations, as estimated from discriminant analysis, were weak,
and that larger spatial scales might be more useful in predicting mussel occurrence. They
also suggested that descriptions of habitat based on fluvial geomorphology might be more
informative. Others have suggested that substrate stability, not composition, is important
in predicting mussel occurrence. In the Holston River, Virginia, the greatest species
densities were associated with stable mixed sand, gravel, and pebble substrates (Neves
and Widlak 1987). Freshwater mussels of the lower Cumberland River, Kentucky, were
abundant only in stable habitats composed of gravel in firm sandy clay (Sickel 1982).

Kat (1982) suggested that streambeds can be divided into high- and low-quality
microhabitats. High-quality microhabitats are characterized by stable substrates,
uncrowded conditions, and protection from scour; low-quality microhabitats are
characterized by unstable substrates and a significant reduction of energy input available
for growth and reproduction. Some authors have suggested that hydrological variables
such as the type of stream flow or shear stress, or macrohabitat descriptors such as stream
size may be more useful than substrate composition in predicting mussel occurrence.

The lack of correlation between substrate particle size and mussel distributions in
some studies may be a result of inadequate sampling effort and improper substrate
particle size analysis. Associations between substrate composition and the aquatic fauna
are often evaluated based on a limited number of samples (e.g., 30) or particle-size

91

classes (e.g., 6). One hundred to 300 samples may be necessary to adequately
characterize the substrate at a particular site in rivers with spatially heterogeneous beds
(Wolcott and Church 1991).

In the Apalachicola River basin, substrate composition was clearly important in
determining where some species of mussels occurred. However, substrate composition
was not the only factor that determined the distribution and abundance of mussels in the
basin. There are several possible reasons for the lack of an apparent association between
substrate properties and some species of freshwater mussels. First, some species may be
generalists with respect to substrate composition, surviving equally well in many types of
substrates. Second, factors other than substrate composition may be important in
defining the physical habitat of some mussel species. This finding is consistent with
other studies where, for example, water velocity was a better predictor of mussel
distribution than substrate type (Huehner 1987). Third, although 2, 713 quadrats were
sampled for mussels and sediments, rare unionids were not found in enough quadrats to
draw inferences between their presence and substrate composition. More quadrat
samples may have resulted in statistically significant mussel-substrate associations for
some of the less common mussel species encountered in this study.

In conclusion, these results indicate that some mussel species are habitat specialists
whose distributions are closely tied to aspects of streambed substrate composition.
However, there remains considerable debate and uncertainty regarding the associations
between anthropogenic erosional sediments and freshwater mussels. The relative
significance of human activities to sediment production, and their subsequent effects on

92

freshwater mussels, is difficult to evaluate. Some of the apparent associations between
increased sediment loads and unionid mussels may involve long lag times, and/or may
include potential impacts on host fishes and juvenile mussels. Quantitative work is
needed to determine the mechanisms through which human-induced sedimentation affect
freshwater mussels, as well as to determine the sediment properties important to measure.
In addition, numerous studies have documented the adverse effects of human-induced
sedimentation on fish communities, but few studies have examined how these effects
influence the availability of suitable host fish for freshwater mussels. More quantitative
work is needed to document the specific effects that changes in sediment regimes have on
host fish-mussel interactions, including how increased turbidity affects the reproductive
success of mussels that use visual lures to attract hosts.

Marine bivalves are life-history generalists known for their high degree of habitat
specificity (Stanley 1973, Vermeij 1989, Hurlbut 1991, Morton 1992). Freshwater
mussels, in contrast, have highly specialized life histories but are frequently referred to as
habitat generalists (Holland-Bartels 1990, Strayer and Ralley 1993, Strayer 1994, Haag
and Warren 1998). This study suggests that in the ACF basin, freshwater mussels are
habitat specialists, whose distributions are tied to suitable habitat defined by a
combination of macro- and micro-habitat variables. In addition, this study suggests that
meaningful relationships between mussels, fish, and their suitable habitat, defined at both
macro- and micro-spatial scales, can be obscured if past habitat alterations and
corresponding faunal shifts are not accounted for at the community level.

APPENDIX

LIST OF STUDY SITES

Chattahoochee River Drainage. ALABAMA: Barbour County: North Fork Cowikee
Creek at unnamed/unnumbered dirt road ca. 7.5 air mi E of Spring Hill ca. 14 air mi
NNW of Eufaula. Lee County: Little Uchee Creek below CR 77 below Meadows Mill
Pond ca. 7 air mi NW of Crawford ca. 1 1 air mi SE of Opelika. Rnssell County: 1)
Hatchechubee Creek at U.S. Rt 431/Alabama Rt 1 ca. 8 air mi WNW of Jakin; 2) Uchee
Creek at Alabama Rt 169 ca. 5.5 air mi N of Seale. GEORGIA: Clay County: Hog
Creek at Georgia Rt 266 ca. 5.5 air mi ENE of Fort Gaines. Early County: 1) Kirkland
Creek at U.S. Rt 84/Georgia Rt 38, 1.75 air mi WNW of Jakin; 2) Sawhatchee Creek at
U.S. Rt 84/Georgia Rt 38, ca. 5 air mi. WNW of Jakin. Randolph County: Pumpkin
Creek at CR 27 ca. 6.5 air mi WSW of Benevolence ca. 7.5 air mi NW of Cuthbert.
Stewart County: Lime Spring Branch at CR 148 ca. 6.25 air mi SE of Westville ca. 7
air mi SE of Lumpkin.

Chipola River Drainage. FLORIDA: Jackson County: 1) Spring Creek 200 m below
Merritts' Mill Pond dam; 2) Baker Creek on unnamed dirt road near Jenkins Pond ca. 7
air mi NNW of Marianna.

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94

Flint River Drainage: Baker County: 1) Coolewahee Creek at Georgia Rt 91, 2.0
road mi NW of junction Georgia Rt 37/ Georgia Rt 91 in Newton; 2) Ichawaynachaway
Creek at Georgia Rt 216, 4.8 road mi WNW of junction Georgia Rt 37/Georgia Rt 216
ca. 13.25 air mi WNW of Newton. Crisp County: 1) Swift Creek at CR 33 ca. 9 air mi
SW of Cordele; 2) Cedar Creek at CR 20 (Byrds Mill Rd) ca. 4.75 air mi SW of Cordele.
Decatur County: Spring Creek at U.S. Rt 84/Georgia Rt 38 ca. 0.75 air mi SW of
Brinson. Dooly County: Hogcrawl Creek at Georgia Rt 329 ca. 4.7 air mi E of
Montezuma. Dougherty County: Kiokee Creek ca. 1 air mi N of Georgia Rt 253 ca. 5.6
air mi W of Albany. Lee County: Muckalee Creek at Georgia Rt 195 ca. 3.5 air mi NE
of Leesburg. Miller County: Aycocks Creek at CR 190 ca. 3.25 air mi WSW of Boykin
ca. 5.75 air mi S of Colquitt. Sumter County: 1) Chokee Creek at U.S. Rt 280/Georgia
Rt 30 ca. 2.25 air mi E of Leslie; 2) Lime Creek at CR 53 (Spring Creek Church Rd/Joe
Stewart Rd) ca. 14.25 air mi ESE of Americus; 3) Muckalee Creek at U.S. Rt.

19/Georgia Rt 3 in Americus. Taylor County: Patsiliga Creek at junction Georgia Rt.
208/Georgia Rt 137 ca. 7.5 air mi NNE of Butler. Terrell County: Chickasawhatchee
Creek at Cr 130 ca. 4.5 air mi SW of Chickasawhatchee ca. 8.5 air mi S of Dawson.
Webster County: Kinchafoonee Creek at CR 123 ca. 5.25 air mi NW of Preston.

Worth County: 1) Abrams Creek at Georgia Rt 300 ca. 4.25 air mi SSW of Oakfield;

2) Jones Creek at Georgia Rt 300 ca. 1.25 air mi SSW of Oakfield; 3) Abrams Creek
tributary (unnamed) at CR 123 below an impoundment ca. 6.25 air mi SSE of Oakfield;

4) Mill Creek tributary (unnamed) at CR 12 below Mercer Mill Pond ca. 7.25 air mi SSW

of Oakfield.

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BIOGRAPHICAL SKETCH

Jayne Brim Box received a Bachelor of Arts degree in journalism from The Ohio
State University in December 1983. She served as a fisheries extension agent in the
United States Peace Corps from 1984 to 1986. She received a Master of Science degree
in biology from the University of South Carolina in May 1991 . She worked as an aquatic
ecologist for the Biological Resources Division of the United States Geological Survey
from 1991 to 1999.

108

I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.

Catherine C. Ewel, Chair
Professor of Forest Resources and
Conservation

I certify that 1 have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.

James D. Williams, CoChair
T^ociate Professor of Fisheries
and Aquatic Sciences

I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.

Uc^

Loukas G. Arvanitis
Professor of Forest Resources and
Conservation

I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.

Kenneth M. Portier
Associate Professor of Statistics

I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.

Joaifii Mossa

Sfsociate Professor of Geography

This dissertation was submitted to the GracM^ Faculty of the School of Forest
Resources and Conservation in the College of Apiculture and to the Graduate School and
was accepted as partial fulfillment of the requirements for the degree of Doctor of
Philosophy.

August 1999

Director, Forest Resources and
Conservation

Dean, Graduate School