Unionidae) in Ohio Brush Creek Watershed

Spatial Distribution of Freshwater Mussels (Unionidae) in Ohio Brush Creek Watershed,

Southern Ohio

A thesis presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Master of Arts

Jason K. Brown

November 2010

This thesis titled

Spatial Distribution of Freshwater Mussels (Unionidae) in Ohio Brush Creek Watershed,

Southern Ohio

JASON K. BROWN

has been approved for

the Department of Geography

and the College of Arts and Sciences by

James M. Dyer

Professor of Geography

Benjamin M. Ogles

Dean, College of Arts and Sciences 3

ABSTRACT

BROWN, JASON K., M.A., November 2010, Geography

Spatial Distribution of Freshwater Mussels (Unionidae) in Ohio Brush Creek Watershed,

Southern Ohio (77 pp.)

Director of Thesis: James M. Dyer

Between July and October 2005, 42 sites across Ohio Brush Creek watershed were surveyed to assess the spatial distribution of native freshwater mussels (Unionidae).

Freshwater mussel shells were recorded at 28 out of 42 sites representing 14 native species. A total of thirteen species were recorded at 19 sites as living or fresh dead.

Associations between the presence, diversity, and abundance of freshwater mussels and coarse-scale variables (drainage area, stream gradient, and percent land cover) and fine- scale variables (200 meter stream-reach habitat features based on Ohio EPA’s Qualitative

Habitat Evaluation Index (QHEI)) were explored using correlation and chi-square analysis. The presence, diversity, and abundance of mussel shells were associated with both coarse- and fine-scale variables. Drainage area and stream reaches with excellent channel development, high amounts of habitat cover, maximum water depths > 1 meter, and riffle depths > 5 cm were all associated with the presence, diversity, and abundance of mussels. Stream gradient was also associated with mussel shell presence and diversity, however was not associated with shell abundance due to the high abundance of fat mucket shells in upper reaches of the watershed. Sites with the highest diversity and abundance occurred along the mainstems of Ohio Brush Creek and the West Fork.

Thirty-seven native mussel species have been recorded in the watershed. Unfortunately 4 over 40% of these species are listed as either endangered, threatened, or of special concern. Sedimentation due to agricultural runoff and deforestation of riparian corridors has been identified as the primary threat to freshwater mussels in Ohio Brush Creek watershed. It is imperative to collect data that can be explored to find spatial and temporal patterns that exist amongst the mussel community in Ohio Brush Creek watershed. This data can also be used to help guide stream habitat restoration and native mussel re-establishment projects in the watershed.

Approved: ______

James M. Dyer

Professor of Geography

I dedicate this work to my wife Susan Brownknight and our son Lennon Brown.

Without their support, patience, love, and understanding this project would have never

been accomplished.

ACKNOWLEDGMENTS

I would like to thank my committee members Dr. James Dyer, Dr. Timothy

Anderson, and Dr. Gaurauv Sinha for their advice and service during this project. I would especially like to thank my advisor Dr. James Dyer for his support, patience, and knowledge. I would also like to thank the staff at the Richard and Lucile Durrell Edge of

Appalachia Preserve System (EOA) in Adams County, Ohio. They provided me with the opportunity to learn about the magnificent lives of mussels in Ohio Brush Creek and inspired me to be a steward to this planet. Thank you Bedel, Zloba, Pete, Lucy, and

Rich!

TABLE OF CONTENTS

Page

Abstract ...... 3 Dedication ...... 5 Acknowledgments...... 6 List of Tables ...... 9 List of Figures ...... 11 Chapter 1: Introduction ...... 12 Chapter 2: Literature Review ...... 17 Natural History ...... 17 Factors Affecting the Distribution of Freshwater Mussels ...... 20 Threats to Freshwater Mussels ...... 22 Chapter 3: Methodology ...... 25 Study Area ...... 25 Land Use ...... 27 Geology ...... 27 Climate ...... 28 Survey Methods ...... 29 Qualitative Habitat Evaluation Index (QHEI) ...... 32 GIS Analysis ...... 36 Statistical Analysis ...... 37 Chapter 4: Results ...... 40 Mussel Assemblage ...... 40 Coarse-Scale Variables ...... 48 Drainage Area and Stream Gradient ...... 48 Land Cover Analysis ...... 50 Fine-Scale Variables ...... 54 Qualitative Habitat Evaluation Index (QHEI) ...... 54 Chapter 5: Discussion ...... 66 Variation in Year-to-Year Mussel Survey Results ...... 66 8

Spatial Distribution of the Mussel Community ...... 68 Relationship between the QHEI and Freshwater Mussels ...... 69 Conclusion ...... 70 References ...... 74 9

LIST OF TABLES

Page

Table 3.1: Qualitative Habitat Evaluation Index (QHEI) metrics and scoring ranges ...... 33

Table 3.2: General narrative ranges assigned to Qualitative Habitat Evaluation Index (QHEI) scores ...... 35

Table 3.3: U.S. EPA 2001 National Land Cover Data (NLCD) classifications ...... 37

Table 3.4: List of variables used in statistical analysis to assess relationships with the presence of mussels at each site (n=42) ...... 39

Table 4.1: Species recorded from Ohio Brush Creek watershed including Museum Collections (MC) from The Ohio State University and the Edge of Appalachia Preserve and previous survey data from Watters in 1987 and 1996, Matter in 2004, and results from this survey in 2005 ...... 40,41

Table 4.2: Number of live and fresh dead mussel shells collected from Ohio Brush Creek and its major tributaries: West Fork, Baker Fork, and Little West Fork ...... 47

Table 4.3: Pearson correlation coefficients for drainage area and stream gradient vs. mussel species richness and abundance at each site (n=19) ...... 49

Table 4.4: Pearson correlation coefficients for percent forest and agriculture land cover vs. mussel species richness and abundance at each site with the presence of living and fresh dead mussel shells (n=19)...... 53

Table 4.5: Contingency table with a pattern of observed and expected frequencies suggesting an association between excellent channel development and the presence of mussels...... 59

Table 4.6: Results of chi-square test between channel development and the presence of mussels...... 59

Table 4.7: Statistic measuring the strength of the association between channel development and the presence of mussels ...... 59

Table 4.8: Contingency table with a pattern of observed and expected frequencies suggesting an association between a high number of instream cover types and the presence of mussels ...... 60

Table 4.9: Results of chi-square test between the number of instream cover types and the presence of mussels...... 60

Table 4.10: Statistic measuring the strength of the association between the number of cover types and the presence of mussels...... 60

Table 4.11: Contingency table with pattern of observed and expected frequencies suggesting an association between maximum depths > 1 m and the presence of mussels...... 61

Table 4.12: Results of chi-square test between maximum depths and the presence of mussels ...... 61

Table 4.13: Statistic measuring the strength of the association between maximum depths and the presence of mussels ...... 61

Table 4.14: Contingency table with a pattern of observed and expected frequencies suggesting an association between riffle depths > 5 cm and the presence of mussels ...62

Table 4.15: Results of chi-square test between riffle depths and the presence of mussels ...... 62

Table 4.16: Statistic measuring the strength of the association between riffle depth and the presence of mussels ...... 62

Table 4.17: Spearman correlation coefficients for significant QHEI metric components vs. mussel species richness and shell abundance at each site (n=42) ...... 63

LIST OF FIGURES

Page

Figure 2.1: Luring methods used by freshwater mussel species ...... 19

Figure 3.1: Location of study area showing Ohio Brush Creek and its major ...... 26

Figure 3.2: Location of study area showing physiographic regions of Ohio ...... 28

Figure 3.3: Forty-two sites along Ohio Brush Creek and its major tributaries ...... 31

Figure 4.1: Sites with the presence of living and/or fresh dead mussel shells (n=19) ....43

Figure 4.2: Species Richness at sites with the presence of living and/or fresh dead mussel shells (n=19) ...... 44

Figure 4.3: Species Abundance at sites with the presence of living and/or fresh dead mussel shells (n=19) ...... 45

Figure 4.4: Scatterplot between mussel species richness and abundance for sites with the presence of living and/or fresh dead shells (n=19) ...... 46

Figure 4.5: Scatterplots between drainage area (a,b) and stream gradient (c,d) vs. mussels species richness and abundance ...... 49

Figure 4.6: Results of GIS land cover analysis: percentages of land cover classifications present in Ohio Brush Creek watershed ...... 51

Figure 4.7: Ohio Brush Creek Watershed 2001 Land Cover Map ...... 52

Figure 4.8: Scatterplots between percent land cover {forest (a, b) and agriculture (c, d)} vs. mussel species richness and abundance at each site with the presence of living and fresh dead mussel shells (n=19) ...... 54

Figure 4.9: Scatterplots between mussel species richness and shell abundance and Qualitative Habitat Evaluation Index (QHEI) total scores (a, b) and three individual metrics – cover score (b, c), channel morphology score (e, f) and pool-glide/riffle- run quality score (g, h) ...... 56,57

Figure 4.10: 2D dot plots between mussel species richness and shell abundance and Qualitative Habitat Evaluation Index (QHEI) metric components – channel development (a, b), number of instream cover types (c, d), maximum depths (e, f), riffle depths (g, h), and the presence of pools > 70cm (i, j) ...... 63,64, 65 12

CHAPTER 1: INTRODUCTION

Freshwater mussels inhabit standing or flowing water bodies that are unpolluted and rich with oxygen, calcium, and suspended food particles. They improve water quality by filtering out suspended particles and pollutants. Biologists have designated mussels as “biological monitors” that can be used to indicate past and present water quality conditions of freshwater systems (Helfrich et al. 2003). A sudden kill of freshwater mussels in a stream can be a reliable indicator of toxic contamination, and a gradual decrease in populations usually indicates chronic water pollution problems

(Helfrich et al. 2003).

The greatest diversity of freshwater mussels found in the world resides in the continental United States (Turgeon et al. 1988; The National Native Mussel Conservation

Committee 1997). Worldwide, about 1,000 freshwater mussel species have been identified, and 300 of these occur in North America (Helfrich et al. 2003). Freshwater mussels are considered one of the most imperiled groups of animals in North America

(Strayer et al. 2004). The USGS Upper Midwest Environmental Sciences Center (2003) estimates that about 70% of the 300 native species are considered extinct, endangered, threatened, or of special concern. Sixty-two mussel species have been recorded in Ohio

(Watters 1995). Of these, 14 are listed as federally endangered, 27 are state endangered, and 11 are threatened or of special interest in the state (Watters 1995).

Mussel distribution, diversity, and abundance appear to be controlled by both coarse- and fine-scale variables (Vaughn and Taylor 2000). In a hierarchical watershed system, coarse-scale variables (e.g., geology, gradient, land use/land cover, drainage 13 area) affect fine-scale variables (e.g., substrate, flow velocity, channel morphology, water quality) (Vaughn and Taylor 2000). The identification of coarse- and fine-scale variables influencing mussel distribution and analysis of mussel/habitat relationships would provide conservation biologists with the proper information to actively protect freshwater mussel habitat and threatened mussel beds. An increase in fundamental knowledge of factors contributing to distribution and abundance of mussel populations would serve as an important resource to conservation biologists and resource managers for locating populations at risk.

Mussel populations and species diversity have rapidly declined within the last 50 years due to impoundments, sedimentation, channelization and dredging, water pollution, and competition with the nonindigenous zebra mussel ( Dreissena polymorpha ) (Neves

1997). The decreasing trend in native mussel populations has inspired an increase in mussel research (Strayer et al. 2004).

Ohio Brush Creek watershed located in southern Ohio is home to 125 plant and animal species of concern on the state or federal level (USDA 1993). A total of 37 native mussel species have been recorded in the watershed (Matter 2006). Sixteen of these species are listed as endangered, threatened, or of special concern, including the federally endangered Clubshell ( Plueroblema clava ) (Ohio Division of Wildlife 2008).

The main stems of Ohio Brush Creek and the lower West Fork are designated by the Ohio Environmental Protection Agency as exceptional warmwater habitat (Ohio EPA

2010). According to the Ohio EPA waters that are exceptional are “capable of supporting and maintaining an exceptional or unusual community of warmwater aquatic organisms 14 having a species composition, diversity, and functional organization comparable to the seventy-fifth percentile of the identified reference sites on a statewide basis” (Ohio EPA

2010 p.4).

The primary water quality threat to the watershed is sedimentation from excessive soil erosion derived from cropland, pastureland, and forestland (USDA 1993). It is estimated that sheet and rill erosion from cropland averages 1,184,500 tons per year

(USDA 1993). Ephemeral gully and gully erosion averages 255,550 tons per year

(USDA 1993). According to the USDA Forest Service (1993) “Farming and livestock grazing adjacent to and through these watercourses are allowing sediment, chemical- laden runoff, and animal waste to enter the stream corridors” (p.26). Removal of forested stream corridors for cropland has also been identified as contributing factor to excessive erosion due to unstable streambanks (USDA 1993). An estimated 889 miles of streambank in the watershed are in need of stabilization (USDA 1993).

Previous surveys on the mussel community of the Ohio Brush Creek Watershed have primarily focused on species abundance and richness. Matter (2006) found species richness to be stable and possibly increasing over a 17-year period from 1987 to 2004.

However, he found that the abundance of several species was decreasing. These species were relatively widespread and abundant during previous studies (Matter 2006). Factors that are responsible for changes in the mussel community are diverse and can be difficult to identify (Matter 2006). Matter (2006) suggested that “it is more probable that differences in the number of species result from changes in the relative abundance of species and sampling probability” (p.3). During the 17-year period species that had 15 decreased abundance did so across most sites. Matter (2006) noted that this suggests a mechanism or mechanisms acting at streamwide scales. During the Matter survey factors that may impact local sites (e.g., disturbance from bridge construction, gravel mining, and acute siltation) were observed (Matter 2006). Matter (2006) did not rule out that

“changes in abundance simply reflect variability in populations or sampling probability”

(p.3).

To date, no analysis has been performed to evaluate factors that affect the spatial distribution of the mussel community in Ohio Brush Creek watershed. The primary goal of this study was to find spatial patterns that exist between coarse-scale (drainage area, stream gradient, and land cover) and fine-scale (derived from QHEI) variables and the presence, diversity, and abundance of freshwater mussels in Ohio Brush Creek and its surrounding tributaries. A secondary goal of this study was to explore associations between data collected from the Ohio Environmental Protection Agency’s (Ohio EPA)

Qualitative Habitat Evaluation Index (QHEI) and the presence of mussels.

This research addresses the following questions and others regarding factors that affect the spatial distribution of freshwater mussels.

Research questions:

• Does drainage area and stream gradient affect the distribution of freshwater

mussels in Ohio Brush Creek watershed?

• Does percent forest and agriculture land cover affect the diversity and abundance

of mussel shells? 16

• Can the Ohio EPA’s Qualitative Habitat Evaluation Index (QHEI) be used to

collect data of fine-scale variables that are associated with the presence of mussel

shells?

• Which QHEI metric components are associated with the presence of mussel

shells?

• Are the presence, diversity, and abundance of mussels in Ohio Brush Creek

watershed more closely associated with coarse- or fine-scale variables?

An analysis on the spatial distribution of the mussel community of Ohio Brush

Creek watershed will provide important data to conservation and preservation agencies

(e.g., Edge of Appalachia Preserve, Ohio EPA, Ohio Division of Wildlife, National

Resources Conservation Service) in their continued effort to protect Ohio’s rare and/or endangered fauna. The creation of GIS layers and map of the spatial distribution of mussels in the Ohio Brush Creek Watershed can serve as a guide to the presence of active mussel bed sites and potential mussel bed habitat. Habitat quality evaluations of mussel bed sites can be used for future research and monitoring of these valued sites.

CHAPTER 2: LITERATURE REVIEW

Freshwater mussels are a long-lived species that require an understanding of their natural history and modern history in order to project the status of future populations.

This chapter will first describe the natural history of freshwater mussels then summarize factors that contribute to their distribution, diversity, abundance, and survival.

Natural History

Freshwater pearly mussels (Bilvalvia: Unionidae) first appeared during the

Triassic over 200 million years ago and reached a great diversity by the end of the

Cretaceous some 65 million years ago. They are adapted to freshwater and are dispersed throughout rivers, streams, lakes, and ponds around the globe. In North America they are most commonly found in large river systems like the Tennessee, Ohio, and Mississippi, but they have also been found in smaller streams that have suitable habitat (Helfrich et al.

2003). Pearly mussels are simple, soft-bodied animals that are enclosed by two shells connected by a ligament (Helfrich et al. 2003). Pearly mussel shells are primarily formed of calcium carbonate extracted from water and secreted in successive layers within the shell (Helfrich et al. 2003). These bivalve shells are designed as the primary source of defense from predation and sedimentation. Muskrats, raccoons, herons, fish, and humans are all known predators of freshwater pearly mussels.

Freshwater pearly mussels are filter-feeding, essentially immobile animals that acquire oxygen and food across an extensive gill surface, and release metabolic waste into the surrounding water (Watters 1995). Many species are known to live up to 20 to 18

30 years, with some living up to 140 years (Bauer 1987). Research on the diet of freshwater mussels has shown that they feed on a mixture of algae, bacteria, detritus, and small animals (Allen 1921, Silverman et al. 1997, Strayer et al. 2004). Strayer et al.

(2004) noted, “scientist are still a long way from knowing precisely what constitutes the unionacean diet or being able to quantitatively assess the quality or quantity of mussel food in a given habitat” (p. 431). The limitations of available mussel food in nature will continue to be a focus in future mussel research. Feeding strategies and diet of freshwater mussels is complicated and dynamic and may vary across environments, species, and life stages and certainly has important consequences for mussel populations

(Strayer et al. 2004).

Freshwater pearly mussels have a unique reproduction strategy. The production of sperm and eggs for North American mussels is initiated by changes in water temperature (Watters 1995). Males release sperm into the water, which is taken up by females of the same species, downstream through incoming water. Eggs are fertilized in a specialized region of the gills, called marsupia (Watters 1995). The eggs develop into larval shells, called glochidia, which are formed from concretions in the gills that act as a source of calcium carbonate (Silverman et al. 1985). According to Strayer (2008), “the developed larvae are obligate, more or less species-specific parasites of fish” (p.13). The glochidia will continue to develop over a period of days to months, depending on the species. Of the nearly 300 known species of mussels in North America, only one - the salamander mussel - is known to use a non-fish host (Watters 1995). However, according 19 to Watters (1995), the specific fish hosts for most freshwater mussel species are still unknown.

Freshwater mussels use different methods for releasing glochidia and attracting host species (Figure 2.1). Many mussel species use a luring method in which the mussel modifies a part of its thin tissue lining inside each shell, called the mantle, to resemble a fish, insect or other food item (Watters 1995). The lure usually pulsates in the water in a

Figure 2.1. Luring methods used by freshwater mussel species (Barnhart 2008).

swimming-like motion. Once a predator comes in contact with the lure, glochidia are released and attach to the gills or scales of the predator. Glochidia will die if they do not attach to a host within 24 hours of being released. Once attached, the glochidia will feed on the dead cells of the host for a certain amount of time, depending on water temperature and species (Watters 1995). After this amount of time the glochidia develop into a juvenile and drop from the host into the substrate. They will burrow into the substrate or attach to a larger object on the substrate using a byssal thread (Watters 1995). 20

Freshwater mussels burrow in the sand and gravel substrates of streams and lakes and usually only leave a small portion of their shells and siphons exposed. Movement is slow and occurs with the extension and contraction of the foot. Mussels only move for short distances during their lifetime. Disturbances due to flooding, drought, poor water quality, or predators are the main causes for mussel movement (Helfrich et al. 2003).

Factors Affecting the Distribution of Freshwater Mussels

Fish diversity can have significant controls over the broad-scale distribution of freshwater mussels (McRae et al. 2004). Watters (1992) suggested that freshwater mussels owe their distributional patterns to the ranges of their fish hosts. Watters (1992) found that in high order streams the number of freshwater mussel species is directly related to the number of fish species present. However, McRae et al. (2004) noted that the influence of other ecological factors on mussel distribution is less clear. Several studies have found that fine-scale habitat measures (e.g., flow velocity, substratum) determine the suitability of freshwater mussel habitat (van der Schalie 1938; Strayer

1993; Vaughn 1997). Other studies have shown that fine-scale measures poorly predict the occurrence and species composition of freshwater mussels in water systems (Tevesz and McCall 1979; Strayer 1981; Holland-Bartels 1990; Layzer and Madison 1995;

McRae et al. 2004). Therefore, it might be more useful to examine potential habitat across large spatial scales for determining the distribution of freshwater mussels in streams (Strayer and Ralley 1993). 21

Strayer (1993), Vaughn (1997) and Arbuckle and Downing (2002) have shown regional factors (e.g., land use, geology) can have a strong effect on mussel distribution.

The impacts of regional factors on mussel distribution are the result of a hierarchical watershed system; regional factors in turn affect finer-scale processes. Land use influences discharge and amount of sedimentation. Geology of a region influences hydrology, controls substrate, flow velocity, and helps to determine water chemistry and turbidity (McRae et al. 2004). Therefore, it is important to observe and monitor all factors contributing to mussel distribution, not only at the macro-scale but also at the micro-scale.

Habitat quality (e.g., wooded riparian zones, available oxygen, hydrologic variability, and substrate) is a major factor contributing to freshwater mussel distribution and abundance. Wooded riparian zones control temperature (shading), slow erosion, and filter pollutants. Streams with increased dissolved oxygen levels will provide suitable habitat for mussels. Hydrologic variability can also have a strong effect on mussel distribution and abundance (Poff et al. 1997). Strayer (1993) found in New York that some mussel species occurred more consistently in hydrologically stable streams than in unstable (flashy) streams. Hydrologically unstable streams will have events of increased water flow that can scour and bury individual mussels with sediment.

Substrate quality is also an important factor for determining mussel distribution and survival in a streambed. Freshwater mussels may occupy a variety of substrate types

(Sietman et al. 1999). This has added to the difficulty in predicting mussel distribution and abundance at fine spatial scales (Strayer 1981). Some substrates have been 22 considered inhospitable to most mussels (e.g., shifting sediment, bedrock) (Sietman et al.

1999). Bedrock limits freshwater mussels from burrowing and anchoring in place. Finer sediments that accumulate on bedrock and remain undisturbed can provide suitable substrate for mussel species (Sietman et al. 1999). McRae et al. (2004) found a significant relationship between mussels and the size classes of gravel. Generally more mussels were found in fine gravel than on any other substrate.

It is clear that numerous coarse- and fine-scale factors contribute to the distribution, diversity, and abundance of freshwater mussels in North America. Broad- scale distribution patterns are best predicted by fish diversity and coarse-scale landscape variables (e.g., geology, gradient, basin area, land use, land cover). Fine-scale variables are important to the understanding of mussel biology, but seem to lack statistical and predictive power when considering the overall spatial distribution of freshwater mussels.

However, in order to properly identify mussel habitat, fine-scale measures should not be ignored. Rather, it is important to evaluate landscape variables at both coarse- and fine- scales. Conservation biologist must understand these processes to effectively monitor mussel populations and to identify potential threats to those populations.

Threats to Freshwater Mussels

Across the globe freshwater mussels are among the most imperiled groups of organisms (Strayer et al. 2004). Riccardi and Rasmussen (1999) estimate that freshwater mussels have a substantially higher extinction rate (1.2% per decade) than all other aquatic and terrestrial faunal groups. They found that 35 of 297 mussel species in North 23

America have been lost since 1900 and project that in the absence of effective conservation action at least 127 imperiled mussel species will disappear within the next century. This projection infers a future continental extinction rate of 6.4% per decade

(Riccardi and Rasmussen 1999).

According to Strayer et al. (2004), “overharvesting, widespread habitat destruction, pollution, land-use change, and exotic species introductions have caused many mussel populations to decline or disappear” (p. 430). Overharvesting of mussel beds by historic (e.g., pearl button industry) and present-day (e.g., cultured pearl industry) economic activities have contributed to declines in mussel populations. Richter et al. (1997) indicated that significant agricultural impacts increased sedimentation, toxic chemical contamination, habitat destruction and fragmentation, altered the hydrologic regime and nutrient inputs, and changed fluvial geomorphology and turbidity. Poole and

Downing (2004) suggested that landscape changes may have a more severe effect on mussel species biology than biotic changes. They found that following habitat alteration, biodiversity may decline for decades (Poole and Downing 2004). Organisms with low dispersal like freshwater mussels may therefore face a long-term extinction debt (Tilman et al. 1994; Hanski and Ovaskainen 2002; Poole and Downing, 2004).

These conclusions suggest that as more and more land is altered, mussel populations will not only face short-term threats but also long-term threats. Because of these numerous factors affecting mussel distribution, diversity, and abundance it is important for resource managers and conservation biologist to continue to research 24 mussel biology and begin to enact conservation measures to protect, and possibly restore, habitat for mussel populations. 25

CHAPTER 3: METHODOLOGY

Study Area

Ohio Brush Creek watershed is home to a large amount of biodiversity. Several unique habitats can be found, from wetlands to xeric barrens, and low grasslands to mature forest (Adams Soil and Water Conservation District 1995). As stated previously, the mainstem of Ohio Brush Creek is designated as an exceptional warm water habitat by the Ohio Environmental Protection Agency (OEPA). It is home to over 60 species of fish ranging in size from tiny rainbow darters to the flathead catfish which can weigh over 70 pounds (Adams Soil and Water Conservation District 1995). Thirty-seven species of native freshwater mussels have been recorded in the watershed (Matter 2006). Over 40% of these species are listed as either endangered, threatened, or of special concern,

The Ohio Brush Creek Watershed is located in southern Ohio approximately 80 miles south of Columbus and is 65 miles east of Cincinnati. The 434 mi 2 watershed is

located in Adams, Highland, Brown, Pike, and Ross Counties (Figure 3.1). The

watershed is made up of 200.5 total stream miles including the mainstem and all

tributaries. The average gradient per mile is 8.7 feet. The major stream systems are Ohio

Brush Creek, Cherry Fork, West Fork, Baker Fork, and Lick Fork. Ohio Brush Creek is a

tributary of the Ohio River.

Figure 3.1. Location of study area showing Ohio Brush Creek and its major tributaries. 27

Land Use

In 1995, forest and agriculture were the dominant land cover types in Ohio Brush

Creek watershed (Adams Soil and Water Conservation District 1995). Agricultural land consisted of cropland (39%) and pastureland (21%). Corn, soybean, and tobacco were all cultivated in the watershed. Dairy and beef cattle were the dominant livestock throughout the watershed with pork producers also present. Thirty-four percent of the watershed was forested (Adams Soil and Water Conservation District 1995).

Geology

The Ohio Brush Creek Watershed is located within three physiographic regions

(Ohio Division of Geological Survey 1998) (Figure 3.2). The northwest section of the watershed is located in the Till Plains and is composed of glacial deposits of unconsolidated sand and gravel. The northeast section of the watershed is situated in the

Unglaciated Alleghany Plateau. This area is regarded as the foothills of the Appalachian

Mountains and is predominately an area of shale and sandstone. The southern section of the watershed lies in the Bluegrass Region, which represents Ohio’s largest area of unglaciated limestones and dolomites. Seventeen soil series are represented in the watershed. These soils range from extremely shallow, dry soils to deep, well drained or wet soils (Adams Soil and Water Conservation District1995).

Figure 3.2 . Location of study area showing physiographic regions of Ohio (Ohio Division of Geological Survey 1998).

Climate

Normal precipitation (1971-2000) at Peebles in Adams County (see Figure 3.1) is

43.14 inches (NOAA 2002). In 2005, the year in which mussels were sampled for this study, total precipitation at West Union, 14 miles south of Peebles, was 44.52 inches

(NOAA 2005). Stream discharge at West Union was low between June and October 29 during 2005 as compared to annual stream discharge statistics from 1927 to 2009 (USGS

2010). The average stream discharge at West Union in June (1927-2009) is 264 cubic feet per second (cfs), however during June 2005 stream discharge was only 33.5 cfs

(USGS 2010). Stream flow in July 2005 was 81.6 cfs which was closer to the average discharge for July of 177 cfs (USGS 2005). Stream discharge during August, September, and October 2005 ranged between 26.1 and 22.7 cfs while the normal range for August,

September, and October (1926-2009) is 147 to 103 cfs (USGS 2010). Lower stream flows can expose stranded mussels or mussel beds making it easier to locate mussel shells whereas high flow conditions can make surveying for mussels difficult.

Survey Methods

Between July 11 th and October 1 st , 2005, 42 sites along Ohio Brush Creek and its major tributaries were surveyed (Figure 3.3). Study sites were selected using previous census data from Watters (1996), Matter (2006) and from data collected by staff at the

Richard and Lucile Durrell Edge of Appalachia Preserve System. Sites were chosen to survey areas where mussels have been found in past surveys and to make sure all major tributaries were represented. Sites were surveyed for freshwater mussels by one person- hour searches using snorkel and mask, glass-bottom buckets (as needed), and by searching muskrat middens, gravel bars, and along the stream bank for fresh dead or weathered shells. These methods are consistent with previous mussel surveys along Ohio

Brush Creek (Matter 2006). A scientific collection permit was obtained from the Ohio

Department of Natural Resources – Division of Wildlife (ODNR-DOW) for the 30 collection of mussels shells. A research permit was obtained from the Edge of

Appalachia Preserve to gain access to sites located on Preserve property. Permission was obtained from private landowners via telephone or in-person to gain access to sites located on private land. Several state, county, and township bridge locations were also used to gain access.

At each site all live, fresh dead, and weathered mussel shells were collected for identification along a 200 meter segment of stream. This survey focused on adult mussel shells. Juvenile mussels are important indicators of the viability of mussel beds however they are difficult to locate and therefore were not included in this survey. Watters (1995) was used for mussel shell identification. Although they were found throughout the watershed, the Asian clam ( Corbicula fluminea ) and peaclams (Family Sphaeriidae) were not included in analysis because they are not indigenous to North America. All single valve shells found were counted as an ‘individual’ shell. All living mussels were carefully returned to the same location as found. Collected dead shells of significance

(e.g. rare and/or endangered species) have been deposited with staff at the Edge of

Appalachia Preserve to be added to the Preserve’s mussel collection. 31

Figure 3.3. Forty-two sample sites along Ohio Brush Creek and its major tributaries.

Qualitative Habitat Evaluation Index (QHEI)

Each site was evaluated using the Ohio EPA’s Qualitative Habitat Evaluation

Index (QHEI). The QHEI provides a measure of habitat that corresponds to physical factors that affect fish communities and are known to be important to other aquatic organisms including freshwater mussels (Ohio EPA 1989). The QHEI is composed of six interrelated metrics, each of which has been shown to be correlated with stream fish communities (Ohio EPA 1989): substrate, instream cover, channel morphology, riparian zone and bank erosion, pool/glide and riffle/run quality, and gradient (Table 3.1). Each of the metrics are scored individually and then summed to provide the total QHEI site score. The maximum possible site score is 100. Below is a brief description of each

QHEI metric, following Ohio EPA (2006).

Table 3.1 . Qualitative Habitat Evaluation Index (QHEI) metrics and scoring ranges (Ohio EPA 2006).

The substrate metric accounts for two components, substrate type and substrate quality. This metric takes into account variables like substrate origin, embeddedness (the degree that coarse substrates are surrounded, impacted, or covered by fine substrates), and silt cover. The instream cover metric scores the presence of ten instream cover types and the amount of overall instream cover at each site. The channel morphology metric scores the quality of stream channel features including channel sinuosity, channel development, channelization, and channel stability. The riparian zone and bank erosion metric underscores the quality of the riparian buffer zone and floodplain vegetation.

Three components are scored along both left and right stream banks (looking downstream). These include riparian zone width, floodplain quality, and extent of bank erosion. The pool/glide and riffle-run quality QHEI metric score emphasizes the quality of pool, glide and/or riffle-run habitats including pool depth, the diversity of current velocities in pools and riffles, pool morphology, riffle-run depth, riffle-run substrate, and riffle-run substrate quality. The gradient metric accounts for the drop in elevation through the sampling area and is calculated from USGS 7.5 minute topographic maps.

The metric takes into account the varying influence on gradient with stream size.

High QHEI scores have been shown to correlate with streams that have high biological diversity and integrity. The results of a study conducted by the Ohio EPA

(1989) suggest a relationship between QHEI scores and the Index of Biotic Integrity

(IBI), which measures species richness, composition, abundance, and tropic composition of fish located in a sample area (Karr 1981). QHEI and IBI scores were compiled across

471 sites in Ohio. Results of linear regression models suggested that QHEI scores are 35 significantly correlated with the IBI (r 2 = 0.45) (Ohio EPA 1989). It is important to note that the QHEI is designed to be explanatory and not predictive (Ohio EPA 1989). The

QHEI was designed to fill the gap between completely subjective habitat assessments and more intensive assessments involving quantitative methods (Ohio EPA 1989). In order to communicate general habitat quality to the public general narrative categories were assigned by Ohio EPA to QHEI scores (Table 3.2). These narrative ranges are not always predictive of aquatic assemblages at any given site (Ohio EPA 2006).

Table 3.2 . General narrative ranges assigned to Qualitative Habitat Evaluation Index (QHEI) scores (Ohio EPA 2006).

QHEI Range Narrative Rating Headwaters (< 20 mi 2) Larger Streams (>20 mi 2) Excellent > 70 > 75 Good 55 to 69 60 to 74 Fair 43 to 54 45 to 59 Poor 30 to 42 30 to 44 Very Poor < 30 < 30

It is also important to note that the QHEI relies on specific definitions of habitat characteristics, therefore regular training is a necessity (Ohio EPA 1989). The author received training from Ohio EPA in 2005 and since then has performed over seventy-five

QHEI assessments in Ohio. The author is also certified by Ohio EPA as a Level III

Qualified Data Collector (QDC) for stream habitat assessment (QHEI). 36

GIS Analysis

Drainage area (mi 2) and stream gradient (ft/mi) were calculated for each site using the U.S. Geological Survey (USGS) StreamStats Web Application for Ohio (Koltun et al.

2006). StreamStats was developed to facilitate the estimation of streamflow statistics at ungaged locations on streams (Kotun et al. 2006). A 10-meter (32.81 ft) resolution digital elevation model (DEM) is used by StreamStats to calculate the stream network and drainage area contributing to any chosen point (Koltun et al. 2006). Site drainage area calculations were downloaded as Geographical Information Systems (GIS) shapefiles and incorporated into a database developed for Ohio Brush Creek watershed.

GIS data for the study area are available upon request.

Drainage basins for each site served as the boundary for the land cover analysis.

The U.S. Environmental Protection Agency (USEPA) 2001 National Land Cover Data

(NLCD) was used to calculate percent land cover for each site (Homer et al. 2004). This

30-meter resolution land cover data distinguishes 16 different land cover classifications

(Table 3.3).

ArcGIS 9.3.1 Spatial Analyst Tools were used to calculate percent land cover for the entire watershed and for each study site’s drainage area (ESRI 1999-2009). All sites

(n= 42) were included in the analysis.

Table 3.3. USEPA 2001 National Land Cover Data Classifications (Homer et al. 2004).

11 – Open Water 51 – Dwarf Scrub * 12 – Perennial Ice/Snow 52 – Shrub / Scrub 21 – Developed, Open Space 72 – Grassland / Herbaceous 22 – Developed, Low Intensity 72 – Sedge / Herbaceous * 23 – Medium Intensity 74 – Moss * 24 – Developed, High Intensity 81 – Pasture Hay 31 – Barren Land 82 – Cultivated Crops 32 – Deciduous Forest 90 – Woody Wetlands 41 – Evergreen Forest 95 – Emergent Herbaceous Wetlands 43 – Mixed Forest * Alaska Only

Statistical Analysis

The objective of the statistical analysis was to explore relationships between coarse- and fine-scale variables and the presence of freshwater mussels at each site

(n=42) (Table 3.4). Mussel species richness and shell abundance was also analyzed with all variables to further explore relationships. Data collected from StreamStats (drainage area and stream gradient) and percent land use/cover were used to represent coarse-scale variables (Table 3.4). These coarse-scale variables were chosen because they have been found in previous studies to be associated with mussel distribution. Qualitative Habitat

Evaluation Index (QHEI) total score and individual metric scores were used to present fine-scale variables. The QHEI was chosen to represent fine-scale variables because of its known association with fish communities. Freshwater mussels are associated with fish diversity and abundance therefore I expect to find associations between QHEI components and the presence of mussel shells. Subsets of the primary components that make up individual QHEI metric scores were used to determine the occurrence of 38 mussels at a site. All statistical analysis was performed using Predictive Analytics Soft

Ware (PASW) 17 (Kinnear and Gray 2010).

Since the QHEI is an index developed by ranking habitat variables (see Table 3.1) all QHEI metrics were treated as ordinal (or categorical) data. Scatterplot graphs were developed to explore relationships between QHEI total scores, along with individual metric scores, and mussel species richness and shell abundance. Chi-square goodness-of- fit tests were generated to identify the most important QHEI metric components for determining the occurrence of mussels at a site. Observed patterns from the chi-square test results were further explored by generating 2D dot plots and Spearman correlation coefficients.

Drainage area (mi 2), stream gradient (ft/mi), and percent land cover (forest and agriculture) for all 42 sites were analyzed with mussel species richness and abundance by generating Pearson correlation coefficients and XY scatterplots.

Table 3.4. List of variables used in statistical analysis to assess relationships with the presence of mussels at each site (n=42).

Variable List

Dependent Mussel Presence or Absence

Species Richness

Shell Abundance

Independent Drainage Area (mi 2)

Stream Gradient (ft/mi)

Land Cover Percent Forest Percent Agriculture Percent Developed

QHEI Total Score (0 to 100)

QHEI Substrate Score (0 to 20) No. of Substrate Types (0 to 10) Substrate Quality (silt heavy, silt moderate, silt normal, silt free) Substrate Embeddedness (extensive, moderate, normal, none)

QHEI Instream Cover Score (0 to 20) No. of instream cover types (none, low, moderate, high) Presence and quality of pools > 70 cm (none, low, moderate, high) Instream cover amount (<5%, 5-25%, 25-75%, >75%)

QHEI Channel Morphology Score (0 to 20) Sinuosity (none, low, moderate, high) Channel development (poor, fair, good, excellent) Channel stability (low, moderate, high)

QHEI Riparian Zone and Bank Erosion Score (0 to 10) Riparian width (none, <5m, 5-10m, 10-50m, >50m) Bank erosion (heavy/severe, moderate, none/little)

QHEI Pool-Glide/Riffle-Run Quality Score (0-20) Maximum depth (<0.2m, 0.2-0.4m, 0.4-0.7m, 0.7-1m, >1m) Riffle depth (<5cm, 5-10cm, >10cm) Run depth (maximum depth <50cm, maximum depth >50cm) Riffle/Run substrate (unstable, moderately stable, stable) Riffle/Run embeddedness (extensive, moderate, low, none)

QHEI Gradient Score (0-10) 40

CHAPTER 4: RESULTS

Mussel Assemblage

A total of 39 species of freshwater mussels have been recorded during previous surveys on the mussel community of the Ohio Brush Creek Watershed, including the non-indigenous Asian clam (Corbicula fluminea ) and zebra mussel ( Dreissena polymorpha ) (Table 4.1). During this 2005 survey, fourteen species of indigenous freshwater mussels were identified at 28 of the 42 sites in Ohio Brush Creek watershed, based on the presence of 932 living, fresh dead, and weathered shells (Table 4.1).

Table 4.1 . Species recorded from Ohio Brush Creek watershed including Museum Collections (MC) from The Ohio State University and the Edge of Appalachia Preserve and previous survey data from Watters in 1987 and 1996, Matter in 2004, and results from this survey in 2005. Common Name Scientific Name MC 1987 1996 2004 2005

Mucket Actinonaias ligamentina X X Slippershell Alasmidonta viridis X X Threeridge Amblema plicata X X X X X Cylindrical Papershell Anodontoides ferussacianus X X X X Asian Clam Corbicula fluminea X X X X X ⃰ ⃰Purple Wartyback Cyclonaias tuberculata X X Zebra Mussel Dreissena polymorpha X †Elephant Ear Elliptio crassidens X ‡Snuffbox Epiobasma triquetra X Wabash Pigtoe Fusconaia flava X X X X Plain Pocketbook Lampsilis cardium X X X X X †Sharp-ridged Pocketbook Lampsilis ovata X Fatmucket Lampsilis radiata luteola X X X X X

[Table 4.1continued ] 41

[Table 4.1 continued] Common Name Scientific Name MC 1987 1996 2004 2005 †Yellow Sandshell Lampsilis teres X X White Heelsplitter Lasmigona complanata X X X X Fluted-shell Lasmigona costata X X X X Fragile Papershell Leptodea fragilis X X X X ⃰Black Sandshell Ligumia recta X †Washboard Megalonaias nervosa X ⃰Threehorn Wartyback Obliquaria reflexa X X X X Round Hickorynut Obovaria subrotunda X X ‡Clubshell Pleurobema clava X X X †Ohio Pigtoe Pleurobema cordatum X ⃰ ⃰Round Pigtoe Pleurobema sintoxia X Pink Heelsplitter Potamilus alatus X X X X X Pink Papershell Potamilus ohiennsis X X ⃰ ⃰ Kidneyshell Ptychobranchus fasciolaris X X X X X Giant Floater Pyganodon grandis X X X X X †Rabbitsfoot Quadrula cylindrica X †Monkeyface Quadrula metanevra X †Wartyback Quadrula nodulata X Pimpleback Quadrula pustulosa X Mapleleaf Quadrula quadrula X X X X X ⃰ ⃰Salamander Mussel Simpsonaias ambiqua X Squawfoot Strophitus undulatus X X X X Lilliput Toxolasma parvus X Pistolgrip Tritogonia verrucosa X X X X X ⃰Fawnsfoot Truncilla donaciformis X X X ⃰ ⃰Deertoe Truncilla truncata X X X X X TOTAL SPECIES 39 22 14 20 15 ‡ Federal and state listed, endangered † State listed, endangered ⃰ State listed, threatened ⃰ ⃰ State listed, of special concern Extirpated from Ohio

Species richness at all 42 sites ranged from 0 to 12 per site, with the greatest richness occurring along the mainstem of Ohio Brush Creek. Abundance of all individual shells ranged from 0 to 212 per site, averaging 22. Considering only living and/or fresh dead shells (n=240), 13 species were found at 19 sites (Figure 4.1). Species richness of only living and/or fresh dead individuals ranged from 0 to 10 per site, while abundance ranged from 0 to 75 shells, averaging 13 per site (Figures 4.2 and 4.3). Scatterplots indicate a positive correlation between species richness and abundance of individual shells (Figure 4.4).

Figure 4.1 . Sites with the presence of living and/or fresh dead mussel shells (n=19).

Figure 4.2 . Species richness at sites with the presence of living and/or fresh dead mussel shells (n=19).

Figure 4.3 . Species Abundance at sites with the presence of living and/or fresh dead mussel shells (n=19).

Figure 4.4 . Scatterplot between mussel species richness and abundance for sites with the presence of living and/or fresh dead shells (n=19).

The greatest mussel species diversity occurs in the mainstem of Ohio Brush Creek and the West Fork (Table 4.2). The other major tributaries with the presence of mussel shells were Baker Fork, which is located in the upper reaches of the watershed, and the

Little West Fork, a tributary to the West Fork of Ohio Brush Creek. No mussel shells were found during this survey in Lick Fork, Cedar Run, Cherry Fork, Elk Fork, Buck

Run, Georges Creek, Little East Fork, Bundle Run, Beasely Fork, and Semple Creek.

See Fig. 3.1.

Table 4.2 . Number of live and fresh dead mussel shells collected from Ohio Brush Creek and its major tributaries: West Fork, Baker Fork, and Little West Fork. Numbers in parentheses indicate number of sites sampled. No mussel shells were found in Lick Fork (n=4), Cedar Run (n=3), Cherry Fork (n=2), Elk Fork (n=1), Buck Run (n=1), Georges Creek (n=1), Little East Fork (n=1), Bundle Run (n=1), Beasely Fork (n=1), and Semple Creek (n=1). See Figure 3.1.

Mainstem West Little Baker Ohio Brush Creek Fork West Fork Fork Species (n=15) (n=7) (n=2) (n=2) Threeridge 41 0 0 0 Wabash Pigtoe 4 0 0 0 Plain Pocketbook 121 8 0 0 Fatmucket 221 126 20 1 White Heelsplitter 119 1 0 0 Fluted-shell 18 0 0 0 Fragile Papershell 29 0 0 0 Threehorn Wartyback 2 0 0 0 Pink Heelsplitter 53 0 0 0 Giant Floater 16 3 0 0 Mapleleaf 98 2 0 0 Pistolgrip 39 0 0 0 Deertoe 9 0 0 0 Total Shells 771 140 20 1

The most dominant species in the watershed was fatmucket ( Lampsilis radiata luteola ) located at 27 sites, and accounting for nearly half of all individuals collected.

Other common species were plain pocketbook ( Lampsilis cardium ), white heelsplitter

(Lasmigona complanata ), and mapleleaf ( Quadrula quadrula ); combined these three species accounted for over one-third of all individuals collected. The rarest species were 48 kidneyshell ( Ptychobranchus fasciolaris ), wabash pigtoe ( Fusconaia flava ), and threehorn wartyback ( Obliquaria reflexa ); each species was found at less than three sites and combined only accounted for seven total individuals. Of these three rare species, only the threehorn wartyback was found alive. The non-indigenous Asian clam

(Corbicula fluminea ) was found throughout the watershed and was located in all major tributaries.

Coarse-Scale Variables

Drainage Area and Stream Gradient

Correlations between drainage area, stream gradient, and mussel species richness and abundance of all living and/or fresh dead shells collected at 19 sites are represented in Table 4.3 and Figure 4.4. Site drainage area was positively correlated with mussel species richness at each site (Table 4.3 and Figure 4.5a). Abundance of mussel shells was not significantly correlated with site drainage area. Sites with drainage areas < 150 mi 2 did not have more than three species present whereas sites with drainage areas > 150

mi 2 had between four and 12 species present (Figure 4.5a). Stream gradient (ft/mi) at

each site was negatively correlated with mussel species richness (Table 4.3 and Figure

4.5b). Nine sites with stream gradients > 10 ft/mi were devoid of mussel shells (Figure

4.5c, d).

Table 4.3 . Pearson correlation coefficients for drainage area and stream gradient vs. mussel species richness and abundance at each sites (n=19).

Coarse-Scale Variables Species Richness Abundance Drainage Area .561 ** .202 Stream Gradient -.482 * -.088 ** Correlation is significant at the 0.01 level (Two-tailed) * Correlation is significant at the 0.05 level (Two-tailed)

a) b)

c) d)

Figure 4.5. Scatterplots between drainage area (a,b) and stream gradient (c,d) vs. mussel species richness and abundance. Pearson correlation coefficient values are given in Table 4.3. 50

Land Cover Analysis

Forest and agriculture are the dominant land cover types in Ohio Brush Creek watershed (Figures 4.6 and 4.7). Forty-five percent of the watershed is covered by deciduous forest with an additional four percent covered by evergreen forest and one percent covered by mixed forest. Pastureland is the most dominant agricultural land use covering twenty-five percent of the watershed. Cultivated cropland is also prevalent throughout the watershed representing fourteen percent of the agricultural land. Six percent of the watershed is developed primarily with open space (4%) and low intensity development (1%). Less than 1% of the watershed is medium to high intensity development. Grassland and herbaceous cover represents 4% of the land shrub/scrub land covering only 2%. Only 0.05% of the watershed is barren land (rock, sand, clay) and less than one percent is covered by open water and wetlands.

Figure 4.6. Results of GIS land cover analysis: p ercentages of land cover classifications present in Ohio Brush Creek watershed . Data source: 2001 National Land Cover Database (Homer et al. 2004).

Figure 4.7. Ohio Brush Creek Watershed 2001 Land Cover Map with location of sites with the presence of living and/or fresh dead shells (n=19). Source: 2001 National Land Cover Database (Homer et al. 2004). 53

Percent forest cover ranged from 19 to 82 percent at all sites (n= 42). The range for percent forest cover at sites with the presence of living and fresh dead mussel shells ranged between 25 and 54 percent (n=19). Percent agriculture (pasture/hay and cultivated cropland) ranged from 10 to 75 percent at all sites (n=42) and ranged between

36 and 58 percent for sites with living and fresh dead shells (n=19). Percent developed land ranged from two to 11 percent for all sites (n=42) and between four and seven percent at sites with living and fresh dead shells (n=19).

At each site (n=42) percent forest and agriculture land cover values were not significantly correlated with mussel species richness and abundance. However a small association between species richness and percent forest and agriculture land cover was found when examining sites with the presence of living and fresh dead shells (n=19)

(Table 4.4 and Figure 4. 8). At these sites (n=19) no association was found between abundance of shells and percent forest and agriculture land cover (Table 4.4 and Figure

4.8).

Table 4.4. Pearson correlation coefficients for percent forest and agriculture land cover vs. mussel species richness and abundance at each site with the presence of living and fresh dead mussel shells (n=19).

Land Cover Species Richness Abundance Percent Forest .398 * .062 Percent Agriculture -.373 * -.030 ** Correlation is significant at the 0.01 level (Two-tailed) * Correlation is significant at the 0.05 level (Two-tailed)

a) b)

c) d)

Figure 4.8. Scatterplots between percent land cover {forest (a,b) and agriculture (c,d)} vs. mussel species richness and abundance at each site with the presence of living and fresh dead mussel shells (n=19). Pearson correlation coefficient values are given in Table 4.17.

Fine-Scale Variables

Qualitative Habitat Evaluation Index (QHEI)

Qualitative Habitat Evaluation Index (QHEI) scores for sites with the presence of living and/or fresh dead mussel shells (n=19) ranged from 66 (good) to 87 (excellent)

[out of 100 total points] (Figure 4.9a, b). Visual inspection of scatterplots between mussel species richness and abundance and QHEI scores suggested a relationship between high QHEI total scores, and three components of the overall QHEI scores: 1) 55 instream cover, 2) channel morphology, and 3) pool/glide and riffle/run quality (Figure

4.9). No relationships were observed between mussel species richness and shell abundance and the remaining QHEI metric scores: substrate, riparian zone/bank erosion, and gradient. A relationship does not appear between abundance of mussel shells and the pool-glide/riffle-run quality score (Figure 4.9h).

Site A199 had an excellent habitat score (n=87) and the highest species richness

(n=10) and shell abundance (n=75) (Figure 4.9a, b). Site FID4 also had excellent habitat scores and high abundance (n=27) however only had two species present; fat mucket

(n=26) and plain pocketbook (n=1) (Figure 4.9a, b). Site A195 also had two species present (pink heelsplitter and giant floater) but low abundance (n=3). Sites FID44 and

A209, each had eight specie present and high abundance between 20 and 25 shells. Site

A194 had seven species present representing fifteen shells. Site A192 also had fifteen shells but only five species. Site FID32 had six species present but only nine shells.

Each of these sites had excellent habitat scores ranging between 81 and 85. Site FID30 also had five species present representing twelve shells however this site had the lowest

QHEI score at 76. A score of 76 is still considered excellent habitat according to Ohio

EPA narrative values but is on the lower end of the range (Ohio EPA 2006).

56 a) b)

c) d)

[Figure 4.9 continued ] 57

[Figure 4.9 continued] e) f)

g) h)

Figure 4.9. Scatterplots between mussel species richness and shell abundance and Qualitative Habitat Evaluation Index (QHEI) total scores (a, b) and three individual metrics – cover score (b, c), channel morphology score (e, f) and pool-glide/riffle-run quality score (g, h) for sites with the presence of living and/or fresh dead mussel shells (n=19).

QHEI Metric Components

Chi-square goodness-of-fit tests were generated to identify important QHEI metric components for determining the occurrence of mussels at a site. A subset representing 16 individual metric components (see Table 3.4) was used to explore 58 associations between fine-scale variables and the presence of mussel shells. Of the sixteen metric variables only four showed an association with the presence of mussel shells. Only the results of these four fine-scale variables are represented in the following pages.

Results of chi-square tests and Spearman correlations between mussel presence/absence and QHEI metric components suggest a relationship between the presence of mussels at sites with excellent channel development, a high amount of habitat cover types, maximum pool depths > 1m, and riffle depths > 5cm (Tables 4.5 - 4.16).

Table 4.5. Contingency table with a pattern of observed and expected frequencies suggesting an association between excellent channel development and the presence of mussels.

Mussels

Absent Present Total Channel excellent Count 2 16 18 Development Expected Count 9.9 8.1 18.0 % within Channel Development 11.1% 88.9% 100.0% good Count 9 3 12 Expected Count 6.6 5.4 12.0 % within Channel Development 75.0% 25.0% 100.0% fair Count 10 0 10 Expected Count 5.5 4.5 10.0 % within Channel Development 100.0% .0% 100.0% poor Count 2 0 2 Expected Count 1.1 .9 2.0 % within Channel Development 100.0% .0% 100.0% Total Count 23 19 42 Expected Count 23.0 19.0 42.0 % within Channel Development 54.8% 45.2% 100.0%

Table 4.6. Results of chi-square test for channel development and the presence of mussels. The chi-square value 25.741 is significantly larger than the .05 level.

Degrees of Freedom Asymptotic Significance

Value (df) (2-sided) Pearson Chi-Square 25.741 a 3 .000 N of Valid Cases 42 a. 3 cells (37.5) have an expected count less than5. The minimum expected count is .90.

Table 4.7. Statistic measuring the strength of the association between channel development and the presence of mussels.

Symmetric Measure Value Approximate Significance Spearman Correlation .768 .000 N of Valid Cases 42 60

Table 4.8. Contingency table with a pattern of observed and expected frequencies suggesting an association between a high number of instream cover types and the presence of mussels.

Mussels

Absent Present Total No. of 8 - 10 (high) Count 4 16 20 Instream Expected Count 11.0 9.0 20.0 Cover % within No. of Instream Cover Types 20.0% 80.0% 100.0% Types 4 - 7 (moderate) Count 15 3 18 Expected Count 9.9 8.1 18.0 % within No. of Instream Cover Types 83.3% 16.7% 100.0% 1 - 3 (low) Count 4 0 4 Expected Count 2.2 1.8 4.0 % within No. of Instream Cover Types 100.0% .0% 100.0% Total Count 23 19 42 Expected Count 23.0 19.0 42.0 % within No. of Instream Cover Types 54.8% 45.2% 100.0%

Table 4.9. Results of chi-square test between the number of instream cover types and the presence of mussels. The chi-square value 18.001 is significantly larger than the .05 level.

Asymptotic Significance

Value Degrees of Freedom (df) (2-sided) Pearson Chi-Square 18.991 a 2 .000 N of Valid Cases 42 a. 2 cells (33.3%) have expected count less than 5. The minimum expected count is 1.81.

Table 4.10 . Statistic measuring the strength of the association between the number of cover types and the presence of mussels.

Symmetric Measure Value Approximate Significance Spearman Correlation .665 .000 N of Valid Cases 42

Table 4.11. Contingency table with a pattern of observed and expected frequencies suggesting an association between maximum depths > 1 m and the presence of mussels.

Mussels

Absent Present Total Maximum Depth >1m Count 2 10 12 Expected Count 6.6 5.4 12.0 % within Maximum Depth 16.7% 83.3% 100.0% 0.7- 1m Count 10 8 18 Expected Count 9.9 8.1 18.0 % within Maximum Depth 55.6% 44.4% 100.0% 0.4- 0.7m Count 10 1 11 Expected Count 6.0 5.0 11.0 % within Maximum Depth 90.9% 9.1% 100.0% 0.2- 0.4m Count 1 0 1 Expected Count .5 .5 1.0 % within Maximum Depth 100.0% .0% 100.0% Total Count 23 19 42 Expected Count 23.0 19.0 42.0 % within Maximum Depth 54.8% 45.2% 100.0%

Table 4.12. Results of chi-square test between maximum depths and the presence of mussels. The chi-square value 13.662 is significantly larger than the .05 level.

Degrees of Freedom

Value (df) Asymptotic Significance (2-sided) Pearson Chi-Square 13.662 a 3 .003 N of Valid Cases 42 a. 3 cells (37.5%) have an expected count less than 5. The minimum expected count is .45.

Table 4.13. Statistic measuring the strength of the association between maximum depths and the presence of mussels.

Symmetric Measure Value Approximate Significance Spearman Correlation .570 .000 N of Valid Cases 42

Table 4.14. Contingency table with a pattern of observed and expected frequencies suggesting an association between riffle depths > 5 cm and the presence of mussels.

Mussels

Absent Present Total Riffle Depth >10cm Count 1 1 2 Expected Count 1.1 .9 2.0 % within Riffle Depth 50.0% 50.0% 100.0% 5-10cm Count 3 11 14 Expected Count 7.7 6.3 14.0 % within Riffle Depth 21.4% 78.6% 100.0% <5cm Count 19 7 26 Expected Count 14.2 11.8 26.0 % within Riffle Depth 73.1% 26.9% 100.0% Total Count 23 19 42 Expected Count 23.0 19.0 42.0 % within Riffle Depth 54.8% 45.2% 100.0%

Table 4.15. Results of chi-square test between riffle depths and the presence of mussels. The chi-square value 9.818 is significantly larger than the .05 level.

Degrees of Freedom Asymptotic Significance

Value (df) (2-sided) Pearson Chi-Square 9.818 a 2 .007 N of Valid Cases 42 a. 2 cells (33.3%) have an expected count less than 5. The minimum expected count is .90.

Table 4.16. Statistic measuring the strength of the association between riffle depth and the presence of mussels.

Symmetric Measure Value Approximate Significance Spearman Correlation .445 .003 N of Valid Cases 42 63

These results are consistent when assessing correlations between mussel species richness and shell abundance and QHEI metric components at all sites (n=42). Sites with the presence of living and or fresh dead shells were associated with excellent channel development, a high amount of habitat cover types, maximum pool depths > 70cm, and riffle depths > 5cm (Table 4.17 and Figure 4.10).

Table 4.17. Spearman correlation coefficients for significant QHEI metric components vs. mussel species richness and shell abundance at each site (n=42).

QHEI Metric Components Species Richness Abundance Channel Development .789 ** .785 ** # of Instream Cover Types .701 ** .693 ** Maximum Depth .620 ** .603 ** Riffle Depth .591 ** .483 ** Presence and Quality of Pools > 70cm .441 ** .444 ** ** Correlation is significant at the 0.01 level (Two-tailed)

a) b)

[Figure 4.10 continued ] 64 c) d)

e) f)

g) h)

[Figure 4.10 continued ] 65

i) j)

Figure 4.10 . 2D dot plots between mussel species richness and shell abundance and Qualitative Habitat Evaluation Index (QHEI) metric components – channel development (a, b), number of instream cover types (c, d), maximum depths (e, f), riffle depths (g, h), and the presence of pools > 70cm (i, j) for all sites (n=42). Each circle represents a site.

CHAPTER 5: DISCUSSION

Variation in Year-to-Year Mussel Survey Results

Mussel diversity and shell abundance found during this survey were lower than the Watters 1987 and Matter 2004 surveys, however similar to the Watters 1996 survey

(see Table 4.1). As noted by Matter (2006) variations in sampling dates and stream conditions can affect the interpretation of inter-annual species differences.

The 1987 survey was conducted during drought conditions in September and

October (Watters 1996). Watters (1996) recorded these survey conditions as

“exceptional” (p.2). This was due to “… the stranding of numerous mussels, rendering collection extremely easy” (Watters 1996, p.2). In contrast the Watters 1996 survey was conducted during April, August, and September under high flow conditions (Matter

(2006)). During this survey Watters (1996) found that “… no mussels were stranded or otherwise unburried” (p.2). Watters (1996) noted that “this alone could account for most of the departure in terms of diversity of 1996 from 1987” (p.2).

The Matter 2004 survey was conducted in July under normal flow conditions and mussel diversity recorded was closer to Watters 1987 survey results (Matter 2006).

During this 2005 survey stream flow was normal in July while flow was relatively low during August, September, and October (USGS 2008). The majority of species that were recorded in 2004 but not 2005 were rare species that could be harder to find due to their low abundance and natural variation in substrate location. It is possible that differences in survey methods may explain some of the variation between 2004 and 2005. Matter

(2006) surveyed 100 meters stream reaches with 1 person-hour searches, whereas 200 67 meter stream reaches were surveyed with 1 person-hour searches in this 2005 survey. It is possible that 1-person hour may not have been enough time to comprehensively survey a 200 meter site. Factors that affect year-to-year variation may be numerous however I cannot conclude what factors explain the variation between my 2005 survey and previous surveys conducted in Ohio Brush Creek watershed.

Only two state-listed species were recorded during this survey: threehorn wartyback ( Obliquaria reflexa ) and deertoe ( Truncilla truncata ). The threehorn wartyback is threatened in Ohio and was recorded in all previous surveys except for 1996

(see Table 4.1). Deertoe is listed as a species of special interest in Ohio and was recorded in all previous surveys (see Table 4.1). The federally- and state-endangered Clubshell

(Pleurobema clava ) was not recorded during this survey and has not been recorded in

Ohio Brush Creek since the Watters 1996 survey. Five additional state endangered species that have been recorded in Ohio Brush Creek were not recorded during this survey: ridged pocketbook ( Lampsilis ovata ), yellow sandshell ( Lampsilis teres ), washboard ( Megalonaias nervosa ), rabbitsfoot ( Quadrula cylindrical ), and wartyback

(Quadrula nodulata ). Continued surveys need to be conducted throughout the watershed to determine if these species are present or whether they have been extirpated from the watershed. It should be noted that it can be challenging to locate endangered and threatened species due to the fact that mussels can be patchily distributed even within a mussel bed (USACE 2010). In many cases these rare species cannot be collected in sufficient numbers to determine density and/or demography with any degree of certainty

(USACE 2010). 68

Spatial Distribution of the Mussel Community

The majority of mussel diversity is located in the mainstem of Ohio Brush Creek, and the lower stretches of the West Fork at sites with high drainage areas and low stream gradients (see Table 4.2). These findings were consistent with both Watters (1987, 1996) and Matter (2006) surveys. No native mussel shells were recorded at fifteen sites located along headwater streams (< 20 mi 2) during this and previous surveys. Sites with low diversity and/or no mussels were located at sites with low drainage areas (see Figure 4.5).

These results are consistent with other studies related to species-area relationships.

Watters (1992) found that the high degree of association between mussel species and drainage area is partially the result of correlations between fishes and drainage area, and between mussels and fishes. The results of Watters (1992) study suggest that mussel species are mostly correlated with fish diversity in large river systems (e.g., Ohio River) and more correlated with drainage area in smaller stream systems (e.g., Ohio Brush

Creek).

Many of the sites with no mussels present in the watershed have high stream gradient, therefore suitable habitat for mussels is limited. Streams with a high stream gradient typically dry up during summer months and therefore are devoid of mussels

(Watters 1996). Streams with high gradients can also produce high volumes of overland flow and can produce large amounts of sediment that can cause stream conditions that are unsuitable for mussels (Arbuckle and Downing 2002).

Results of Pearson correlation coefficients provide further evidence of the strong relationship between drainage area, stream gradient, and mussel diversity in Ohio Brush

Creek (see Table 4.3). However, abundance of mussel shells was not significantly associated with drainage area and stream gradient. This is likely due to the high abundance of fatmucket ( Lampsilis radiata luteola ) shells located at a site along the West

Fork (FID 4) (see Figure 4.5). Fatmuckets are habitat generalists and were common throughout the watershed. They are the most widespread freshwater mussel species in the world and can tolerate nearly all substrate types and flow regimes (Watters 2009).

The non-indigenous Asian clam ( Corbicula fluminea ) was also found throughout the watershed and in all major tributaries. Asian clams compete for food with native mussels however little evidence has been found to suggest that Asian clams are detrimental to native mussels (Watters 2009). No zebra mussels ( Dreissena polymorpha ) or quagga mussels ( Dreissena rostriformis bugensis ) were found.

Relationship between the QHEI and Freshwater Mussels

It is not surprising to find associations between the presence of freshwater mussels and QHEI scores. The six interrelated QHEI metrics: substrate, instream cover, channel morphology, riparian and bank erosion, pool and riffle quality, and gradient have been shown to be correlated with fish communities and other aquatic life, including invertebrates (Ohio EPA 1989). Three QHEI metrics were consistently associated with mussel species richness: instream cover, channel morphology, and pool and riffle quality

(see Figure 4.6c, e, g). Two of these metrics, channel morphology and pool and riffle 70 quality, have been found to be correlated with Index of Biotic Integrity (IBI) scores (Ohio

EPA 1989). Results of the chi-square test and Spearman correlations suggest that sites with excellent channel development, high amount of instream cover, maximum depths greater than one meter, and riffle depths greater than five centimeters are more likely to have the presence of freshwater mussels in Ohio Brush Creek watershed (Tables 4.4 to

4.15).

Conclusion

Results of this study suggest the importance of collecting both coarse- and fine- scale variables when assessing the presence, diversity, and abundance of freshwater mussels in North American watersheds. Both coarse- and fine-scale variables were associated with mussels in Ohio Brush Creek watershed.

Coarse-scale variables (e.g., low drainage area and high stream gradient) can limit suitable habitat for mussels and therefore are often void of mussel shells. An analysis of these variables can be used to help select survey sites within a watershed boundary when implementing a mussel survey. Percent land cover is also an important coarse-scale variable to consider when assessing mussel populations. Sites with forested watersheds were positively associated with species richness and abundance. In contrast sites dominated by agricultural land were negatively associated with species richness and abundance. These results suggest the importance of restoring and preserving forested land especially along floodplains and riparian zones. 71

Fine-scale variables derived from the QHEI were also associated with the presence, diversity, and abundance of mussel shells. These data provide more detail related to site-specific characteristics for suitable mussel habitat. The QHEI is an effective tool that can be used to collect habitat data that is associated with the presence of mussel shells. QHEI scores can be used to help set target goals for stream enhancement and restoration efforts to increase fish and mussel habitat. QHEI data can also be used to assess long-term changes in stream reach features and to identify harmful impacts (e.g., channel modification, pollution, and deforestation of riparian corridors).

Thirty-seven native mussel species have been recorded in the watershed.

Unfortunately over 40% of these species are listed as either endangered, threatened, or of special concern. Only 14 species were recorded during this survey which was lower than previous surveys. It is difficult to determine the variation between results of this study and previous surveys. It is also difficult to determine why 40% of the species recorded in the watershed are listed species that are declining or have been extirpated. There are several threats to the mussels living in the watershed. Poaching is known to occur in the watershed which is why local agencies and organizations keep a close eye on the watershed. Results of this study will be shared with the Ohio Division of Wildlife

(ODW). Sedimentation due to erosion has also been noted as a threat to mussels and other aquatic life in the watershed. Pastureland and cropland has been used in the watershed for over 200 years and it is possible that long-term impacts from these land use practices are causing declines in mussel species that are being observed over a long- period of time. This potential impact speaks to the need to survey for juvenile mussels 72 living in the watershed which will help identify viable mussel beds. Results of this study can help guide future surveys for juvenile mussels.

Recommendations:

• Use the results of this study to help guide the implementation of a quantitative assessment of the mussel community of Ohio Brush Creek and its major tributaries. This survey would include scuba diving and substrate dredging techniques to help locate both rare species and juvenile mussels.

• The mussel community of Ohio Brush Creek watershed should be assessed every five to ten years for both adult and juvenile shells. QHEI scores should be recorded at each survey site.

• Ohio EPA QHEI scores should be recorded at each site when surveying for mussels. These scores can be used for guiding stream habitat restoration and enhancement projects.

• An updated watershed management plan should be developed for Ohio Brush Creek watershed. This plan should focus on water quality threats from non-point and point sources (e.g., agricultural runoff, wastewater) and what actions need to be implemented to mitigate these sources (e.g., livestock exclusion fencing, riparian and floodplain restoration and preservation, and stream channel restoration).

If threats to freshwater mussels are not recognized and controlled within areas near mussel habitat it is possible that mussel populations in North America could face a staggering decline in abundance and diversity within the next century. This is why governmental agencies such as the U.S. Fish and Wildlife service and USGS are creating programs state by state to identify existing mussel populations and to locate potential habitat. Organizations such as The Nature Conservancy and The National Native Mussel

Conservation Committee are focusing on preserving stream habitat for the protection of mussel populations. The National Native Mussel Conservation Committee created a 73 document in 1998 for the National Strategy for the Conservation of Native Freshwater

Mussels . This document identifies ten problems facing the protection of freshwater mussels in North America and list ten goals for overcoming these problems. The Nature

Conservancy’s Freshwater Initiative is an aggressive program for conserving freshwater biodiversity incorporating threat abatement and adaptive management at watersheds in 25

U.S. states and seven countries in Latin America and the Caribbean.

These organizations are playing an active role in the conservation of freshwater mussels in North America. With continued research on identifying factors contributing to mussels distribution, diversity, and abundance combined with the protection of suitable habitat for mussels these imperiled organism may have a chance for survival into the future. As important biological indicators of the health of our streams, we must take an active approach in protecting these animals. Considering our own need for healthy freshwater, this in return will benefit our own survival. 74

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