MICROHABITAT USE BY THE REDSIDE DACE ( ELONGATUS) IN OHIO

Brian J. Zimmerman

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

December 2009

Committee:

Dr. Jeffrey G. Miner, advisor

Dr. Trevor E. Pitcher

Dr. Karen V. Root

ii

ABSTRACT

Dr. Jeffrey G. Miner, advisor

Few studies have attempted to characterize microhabitat use by cyprinids, particularly

over a broad temporal scale. In this study, I quantified the physical in-stream characteristics of

habitat use by the redside dace, Clinostomus elongatus using a one-square meter spatial scale.

These characteristics were delineated in four Ohio streams that contained substantial populations of redside dace. Individual redside dace locations within the study site were recorded, along with stream velocity, depth, proximity to woody debris, and distance to the edge of the wetted stream channel, seasonally throughout the study. Redside dace positions within the stream were found to be non-random in relation to most variables and seasons. Generally, redside dace oriented toward positions with slower current velocities (0.00-0.08 m/s observed versus 0.00-

0.19m/s based on randomization sampling), greater depths (0.33-0.84m observed versus 0.07-

0.35m random), closer to woody debris (0.00-1.61m observed versus 0.53-5.64m random), and further from the edge of the wetted stream channel (0.60-1.93m observed versus 0.17-0.71m random). From this study it is clear that redside dace are drawn to particular habitat features.

Additionally, there were some differences observed for the different seasons which may be important for the persistence of populations over time. During winter they stayed closest to woody debris (average of cells with redside dace present for all sites during winter 0.32m; spring

0.86m; summer 0.55m; fall 0.78m). In spring they used areas that were shallower (spring 0.53m; summer 0.60m; fall 0.58m; winter 0.69m) and with higher velocities (spring 0.05m/s; summer

0.01m/s; fall 0.03m/s; winter 0.03m/s) because of spawning activities in riffles and runs. These differences in microhabitat use would have been missed if this study had not covered a time span of a full year.

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DEDICATION

Special thanks to my parents for encouraging me to turn my love of fish into a career. Also, thanks to my wife for always encouraging me to see the positive outcome, when things did not

go my way during the process of completing my degree.

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ACKNOWLEDGEMENTS

This project was funded by a grant from the North American Native Fishes Association.

Additional funds and equipment were provided by the BGSU aquatic ecology lab. I would like

to thank my wife, Julie, for helping with much of the field work. Others that contributed to help

in the field included Dale Zimmerman, Andrew Nidy, Justin Baker, Mark Binkley, Dr. Ken

Baker, Sarah Opfer, Troy Fagan, Shad Swanson, Jordan Wise, and Heather Leudecke. I would

also like to thank Paul Pira (Geauga County Park Biologist) for helping locate a suitable study site in the drainage. I appreciate the patience that my committee has had during the completion of this thesis, as I have gone on to start a career during this process. Lastly, I would like to thank my family for being supportive and encouraging me to continue moving toward the completion of my degree.

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TABLE OF CONTENTS

Page

INTRODUCTION…………………………………………………………………………… 1

METHODS…………………………………………………………………………………... 3

Study Sites……………………………………………………………………………. 3

Field Observations…………………………………………………………………… 3

Statistical Analysis…………………………………………………………………… 5

RESULTS……………………………………………………………………………………. 7

DISCUSSION………………………………………………………………………………... 9

REFERENCES………………………………………………………………………………. 15

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LIST OF TABLES/FIGURES

Figure/Table Page

1. Table 1…………………….……………………………………………………. 20

2. Figure 1…………………………………………………………………………. 24

3. Figure 2…………………………………………………………………………. 25

4. Figure 3…………………………………………………………………………. 26

5. Figure 4…………………………………………………………………………. 27

6. Figure 5…………………………………………………………………………. 28

1

INTRODUCTION

Many studies have been conducted concerning habitats of economically important sport fishes (Matthews et al. 1992; Williams & Eversole 2001; Kelsch & Wendel 2004; Daugherty &

Sutton 2005; Brenden et al. 2006; Fore et al. 2007; Johnson 2008; Kobler et al. 2008; Kuhn et al.

2008). However, many fewer studies quantify habitat requirements of non-game fishes (Brown

1991; Gray & Stauffer 2001; Jordan 2002; Scott & Mayden 2008). A major step in conserving non-game fishes is to gain a better understanding of their basic habitat requirements (Skyfield &

Grossman 2008).

Each species’ fundamental niche is determined by environmental factors that are critical to its maintenance in a habitat. These habitat requirements need to be thoroughly understood, so restoration projects of formerly suitable habitat can be developed with the intent to reestablish locally extirpated populations or allow depleted populations to recover naturally (Bond & Lake

2003). Microhabitat studies of stream fishes are typically conducted by marking the position of individual fish and parameterizing variables for that position (Chipps et al. 1994; Gray &

Stauffer 1999; Skyfield & Grossman 2008). Some of these studies take into account the availability of surrounding habitat that is not in use (Harding et al. 1998; Skyfield & Grossman

2008). Additionally, previous microhabitat studies have often been conducted during a single season (Chipps et al. 1994; Harding et al. 1998; Gray & Stauffer 1999) and few studies have taken into account seasonal changes of habitat use (but see Hill & Grossman 1993; Kessler &

Thorp 1993; Skyfield & Grossman 2008).

This study quantified microhabitat use by redside dace (Clinostomus elongatus) over an annual cycle. Redside dace are broadly distributed in the Lake Erie, Lake , and the upper

Ohio River drainages basins with an isolated population in the upper basin

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(Page & Burr 1991). Redside dace are considered imperiled throughout much of their extensive

distribution (e.g., Ontario ) and have been extirpated from some states (e.g. Ontario

MNR, 2005; DNR, 2007; Maryland, NatureServe Explorer 2009; Mighigan DNR, 2009;

West Virginia DNR, 2009).

There are a few older accounts of redside dace habitat requirements that are summarized

in Trautman (1981) and Becker (1983) but these are primarily anecdotes and opinions. In

addition, Novinger and Coon (2000) compared habitat use by redside dace addressing

microhabitat, metabolic rate, and temperature requirements in , where they are

endangered, and compared them with New York populations, where they are fairly abundant.

Their study found that redside dace preferred mid-water focal points in the deepest part of pools positioned beneath over-hanging cover with greater than expected frequencies. However, this study did not take into account seasonal variation in habitat use. Most recently Reid et al. (2008) studied the effectiveness of a rapid stream habitat assessment for detecting differences between streams that currently had redside dace and streams where they have been found historically but have not been found recently. Their study was a more broad scale stream reach assessment and was limited because it did not take into account details that may have directly pertained to redside dace specifically, such as small differences in substrate and flow rates over time. In the present study, the comparison of observed in-stream positions of redside dace were compared against random positions to determine if redside dace were using specific microhabitats. In addition, there was also observation as to whether seasonal changes had an effect on microhabitat use of redside dace.

3

METHODS

Study Sites

Using current Ohio EPA stream survey data, I located four streams that contain

substantial populations of redside dace, Clinostomus elongatus (personal communications C.

Boucher, Environmental specialist Ohio EPA). The four study sites included Clear Creek

(hereafter CC, a Black River tributary near Lodi, Ohio lat 41.0134 long -82.0844), an unnamed

tributary to the East Branch of the Chagrin River (hereafter CR, on the Geauga County Park

Mayer Preserve lat 41.5676 long -81.3203), Rathburn Run (hereafter RR, a Killbuck Creek tributary near Wooster, Ohio lat 40.8164 long -82.0231), and Town Fork, a tributary of Yellow

Creek (hereafter TF, in Jefferson Lake State Park lat 40.4602 long -80.8097). Two of these streams are in the Lake Erie drainage (CC and CR) and two are in the drainage (TF and RR).

Field Observations

These stream sites with extant populations are small (typically 2-10 m wide, wetted

width), forested, and have predominantly stable stream channels. The length of stream included

in each study site for this microhabitat analysis was determined by choosing the smallest possible

stretch that included all major habitat types (pool, riffle, and run), so that seasonal distribution

shifts could be quantified. At each site I laid out a one-meter grid using marker flags (Figure 1),

and in each meter square, the substrate type, current velocity, depth, and presence/absence of

woody debris were quantified. The physical habitat features (substrate type, presence and position of woody debris, and the width and position of the wetted stream channel) were drawn out by hand on large graph paper to create a map of the one-meter grid study area. Depth and current velocity were measured at each marker flag (all four corners of each square meter).

4

Depth was measured in centimeters using a meter stick and current velocity was taken at mid-

depth using a Marsh-McBirney Flo-Mate Model 2000 portable flow meter. Once the field data

collection was completed, I then used the habitat maps to determine the value of each of the four

variables used in this study for every one square meter cell. Current velocity and depth were

determined by averaging the measurements taken at each of the four corners of the cell. Distance to woody debris was measured as the shortest distance to woody debris from a given cell and

when wood was present within the cell a value of 0 was assigned. Distance to shore was also

determined by measuring the shortest distance to the edge of the wetted stream channel from a

given cell, and, if that cell touched or included the edge of the wetted stream channel a value of 0

was assigned. I then assessed the effect of each of these four variables on the in-stream position

of redside dace.

Each site was visited once or twice during each season to quantify any changes in stream

conditions (including current velocity and depth) and where the redside dace were positioned

within the one meter grid mapped area. There were no data collected for CR in the fall because of poor sampling conditions and trouble getting permission to access the stream. Because of the

variability in the number of trips to a stream, when there were two sampling events in a season at

a stream, these data were combined, thus, resulting in a total of 15 site-season data sets. The

corners of the grid remained up for the duration of the study, so stream condition changes and the

position of the fish could be properly incorporated into the site maps. This allowed for

discernment of what habitat features were being used by this species during each season.

I used visual observation to locate the redside dace in the distributional grid. This was done by

approaching the stream quietly and sitting still, at a central point where the entire study area

could be clearly seen, for a period of at least 15 minutes before placing any markers (i.e.,

5

identifying fish locations). This allowed fish to come back out from hiding, after the initial

approach of the observer, and resume normal activity. Redside dace are rather active fish. This

was accounted for by observing a single fish for a period of 5 minutes. After this period I placed

a marker (fishing weight with brightly colored tape attached) into the center of the general area

the fish had been. This would then be repeated for multiple fish. This process was used because

capturing the fish (e.g., seining) would cause inaccurate estimates of the in-stream position of the

fish as they will attempt to escape capture (Santos et al., 2004). Because redside dace forage

near the surface, and are strikingly colored, visual identification was not difficult (Becker, 1983).

Statistical Analysis

Randomization routines (Manly 1991) were used to examine which microhabitat variables (current velocity, depth, distance to shore, and distance to woody debris) were related

to the in-stream position of the redside dace. To illustrate how this was done, I will use the

example of looking at the effects of current velocity in Rathburn Run in the spring. During this

season Rathburn Run was visited twice, during which, measurements were taken for 313 one

square meter cells, 22 of which were observed with redside dace present. The randomization

routine, which was set up as a macro in Microsoft Excel, would randomly draw 22 cells (in this

case using the values for current velocity in each of these cells) regardless of whether they did or

did not have redside dace present. This was then repeated for 1000 iterations which created a null

distribution for potential current velocities at Rathburn Run in the spring season. The peak of this

null distribution curve was the mean random distribution. Then the average current velocity of

the 22 cells observed with redside dace present was compared to this null distribution. If the

observed mean current velocity fell within the top 25 iterations on either end of the null

distribution curve (2.5% at either end) the observed mean was considered to be significantly

6 different from random (p< 0.05). Similarly, if this observed mean fell within the top 5 on either end, it was significant at p<0.01, and if the observed mean fell beyond 0.05 on either end of curve this was a highly significant result (p< 0.001). This allowed for determination of whether the redside dace were randomly positioned in the stream or if the environmental variables that were measured influenced their in-stream position.

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RESULTS

The number of redside dace observed in the four stream sites ranged from a low of 10 at

RR in summer to a high of 43 at CC in winter (Table 1). The total number of watered stream cells during the low flow conditions of fall were 115, 277, and 345 in streams, TF, CC, and RR, respectively (Table 1). During most sampling events (11 of 15 site-season combinations) redside dace were observed in microhabitats with mean current velocity significantly less (p < 0.05) than the randomized means, suggesting that redside dace were actively avoiding higher current velocity areas like riffles and runs (Figure 2). Only in spring at RR when redside dace were observed spawning did they use higher current velocity areas significantly more than at random

(p < 0.05), and in fall at Clear Creek (CC) when average reach current velocity was less than

0.02 m. sec-1. Redside dace use the highest current velocities in spring while spawning in shallow water (average of cells with redside dace present for all sites: spring 0.05m/s; summer 0.01m/s; fall 0.03m/s; winter 0.03m/s).

The mean depths for the cells with redside dace were consistently greater than the mean of the randomized selection of cells (i.e., 14 of 15 comparisons, Figure 3). This positive relationship was observed in all four streams and in each season. Redside dace were consistently found in the deepest portion of pools and these data suggest that redside dace were actively seeking out these deeper areas. They were found in the shallowest water in spring during spawning (average of cells with redside dace present for all sites: spring 0.53m; summer 0.60m; fall 0.58m; winter 0.69m). For these small streams, redside dace were generally found in the deepest sections in all seasons.

Redside dace were consistently found near woody debris in all seasons and in all streams

(Figure 4). Distance between cells containing redside dace and woody debris was found to be

8

significant (versus the randomized distributions) in all instances with a significance level of p <

0.001 for all but three stream-season combinations. Generally, redside dace were farthest from

woody debris in spring when spawning, which I observed, and closest to wood in winter when

they are the least active (average of cells with redside dace present for all sites: spring 0.86m;

summer 0.55m; fall 0.78m; winter 0.32m). Although redside dace consistently aggregate around

woody debris, analysis of fish distance from shore compared to a randomized distribution indicates that redside dace are significantly away from shore habitat in most sites and seasons

(Figure 5) and thus may not use shoreline debris. Consistently (12 of 15 comparisons, p < 0.05), redside dace were observed farther from shore than would be expected from a randomized

distribution even though woody debris generally extended from shore (e.g., Figure 1).

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DISCUSSION

All too often basic life history information is qualitatively observed but not quantified.

The intent of this study was to quantitatively assess microhabitat usage by redside dace

throughout the year. The redside dace of the four study streams (CC, CR, RR, and TF) displayed

nonrandom use of microhabitat based on the four variables tested in this study. Generally, they

avoided areas with high current velocities and shallow depths, and were found close to woody

debris away from the stream edge.

In all but four instances, cells containing redside dace had significantly lower current

velocities than cells that were randomly chosen. This suggests that redside dace were actively

avoiding high current velocities, although these lower velocity locations were also areas of

greater depths near woody debris. It is possible that the importance of any one of these habitat

features is being masked by the interaction between them (i.e., autocorrelation). For example,

Hygelund & Manga (2002) demonstrated that the presence of woody debris influences flow patterns.

Redside dace appear to seek out deeper portions of streams in pools. The observed depth of the cells where redside dace were observed was consistently greater than the randomized mean depth. This can likely be attributed to a trade off between prey capture success and predator avoidance (Werner et al. 1983). Redside dace are visual feeders, often capturing flying by jumping into the air just above the surface (Novinger & Coon 2000). If they stayed in shallower water it may be easier for them to capture more food, but it likely is also easier for avian or terrestrial predators to capture them when they are in shallower water (Hill & Grossman

1993).

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As with depth, there is no doubt that redside dace are attracted to woody debris. In all

cases, the observed mean distance from woody debris was significantly different from the

randomized mean I tested my observations against. This may be explained by redside dace using

the wood as hiding places from predators, shielding themselves from stronger current velocities,

or as areas of abundant food supplies. Redside dace feed almost entirely on larvae and

other invertebrates (Becker 1983; Novinger & Coon 2000), and higher invertebrate densities can

be found near woody debris (Burcher & Smock 2002). Woody debris also adds complexity to the

stream channel (Angermeier & Karr 1984), which in turn slows current velocities (Hygelund &

Manga 2002) and may lessen the effort redside dace must exert to hold position in the stream.

The same complexity added to the stream by woody debris also would provide hiding places

(Angermeier & Karr 1984) for redside dace to retreat to when threatened by predators both in the

stream and from out of the stream. In my study streams, creek chub, Semotilus atromaculatus,

represented the only piscivorous fish species (personal observation, Zimmerman 2006), but in

other systems redside dace co-occur with various trout species or other predatory fishes (e.g., the

Mad River in west central Ohio, Trautman 1981).

Finally the observed mean distance from the shoreline was found to be significant in all

four seasons for three of the four streams with only one exception. This possibly shows that

redside dace are actively choosing to be further away from the shoreline. However, this variable

did not have as strong of a relationship as the others and is influenced by the size of the stream.

This is likely the reason for only one season being found to have a significant observed mean at

the CR site. This stream was the smallest and in some portions of the study site it was only 2-3m

wide causing all cells to be within 0-1.5m from the edge of the wetted stream channel.

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Some seasonal differences in habitat use were observed during this study. In spring,

redside dace were found using shallower waters with swifter current velocities than the rest of

the year in all four study streams. This can be explained by my observation of redside dace

actively spawning during spring sampling events in CR and RR. It is also possible that redside

dace were preparing to in the two streams where spawning was not actually observed

which would account for these differences. Alternatively the higher current velocities could be

explained simply by higher springtime discharges typical of streams in the region during the

spring season (USGS 2009). This spawning activity was observed in relatively shallow water at

the top or bottom end of riffles in run or pool tail out habitats. Spawning occurred over the

shallow pits dug out by creek chubs and common white suckers, Catostomus commersonii

(personal observation, Zimmerman 2006). Additionally, during winter, redside dace were

observed closest to woody debris. It is possible that because fish have reduced activity in cold

temperatures (Thibault et al. 1997) they were seeking shelter from high flow velocities (Todd &

Rabeni 1989), or predators (Angermeier & Karr 1984) by staying near woody debris, allowing

them to expend less energy.

Generally my findings are in agreement with those of Novinger & Coon (2000) who

found that redside dace used the deepest part of pools, mid-water focal positions, and positions

beneath overhanging vegetation. The present study also found that redside dace held positions in

the deepest part of pools. I did not record the position of redside dace within the water column

but can anecdotally offer that they did indeed display a preference for mid water positions during

my observations as suggested by Novinger & Coon (2000). My study did not address out of

stream cover such as over hanging vegetation as did theirs but rather in-stream cover, in the form of woody debris. My study clearly showed, regardless of season or stream, that the proximity of

12 woody debris was an important factor in determining the in-stream position of redside dace. This consistent pattern of redside dace using positions in deep pools, and with an abundance of cover

(in or out of stream) near by in Michigan, New York, and now Ohio should be carefully considered by managers developing conservation plans for this species.

Additional factors at a larger landscape scale should be considered when developing conservation plans for this and other species. In North America, effects of landscape alterations on non-game species are often overlooked because of a perceived lack of their importance to human needs (Cooke et al., 2005). Generally, population declines of these species are not monitored until they are in serious trouble, and only then is protective action contemplated

(Cooke et al., 2005). However, species of economic importance (e.g., sport and commercially harvested species) are often protected at great lengths when numbers begin to decline (Cooke et al., 2005). Moyle (1995) found that 63% of California’s native fish fauna is either already extinct or in danger of becoming so. This Pacific coast fauna is probably one of the most imperiled fish faunas of the continent, but it is certainly not the only community severely impacted by habitat alteration and other anthropogenic disturbances. Cooke et al. (2005) suggest that the entire family Catostomidae is in jeopardy, and suggest they be used as sentinels for the conservation of entire aquatic ecosystems.

Redside dace are a perfect example of a species easily affected by anthropogenic alterations. They are typically found in small streams that are easily altered. In Ontario Canada nearly the entire range of redside dace is threatened by urban expansion. Urbanization causes streams to have increased fluctuation in flow rates as a result of impervious surfaces (parking lots and streets) and storm drains directing water into streams more quickly (Wang et al. 2001).

These same impervious surfaces prevent recharge of ground water which in turn causes streams

13

in these settings to become intermittent during dry periods (Wang et al. 2001). These effects alter the amount and quality of water in streams, which, in turn, has effects on the fish that live there.

In Ohio, many redside dace populations have been severely reduced in size or in some

cases extirpated from entire drainage basins (Trautman 1981; personal communication, Dr. T.

Cavender, Curator emeritus, Ohio State University Museum). In the Cuyahoga River basin with one of the most severely reduced populations, streams are heavily affected by urbanization. In other portions of the state redside dace populations have been affected by the channelization of

streams to promote better drainage for farming. Examples of this in Ohio are the East Fork of the

White Water River and the upper part of Sugar Creek where no redside dace were found during

intensive seining investigations (unpublished data. Zimmerman 2006). Lau et al. (2006) found

that the quality of habitat features such as riffle/run, pool/glide, channel morphology, substrate,

and in-stream cover were degraded in channelized row cropland streams and this resulted in the

loss of smallmouth bass (Micropterus dolomieu), spotted sucker (Minytrema melanops), rainbow darter (Etheostoma caeruleum), and several other species. It has also been suggested that redside dace require cool temperatures (Trautman 1981). Novinger & Coon (2000) found the optimal growth temperature for redside dace was between 24.5 and 24.7oC. Stream temperature could be

altered by either urbanization or channelization. Overhanging riparian vegetation can also play a

role in moderating temperatures by shading streams from direct sunlight (Novinger & Coon

2000).

In conclusion, all of these factors need to be carefully considered by managers when

developing conservation plans for this species. My study offers valuable information on the

importance of in-stream cover in the form of woody debris. It also appears that deep, wide, pools

14 with slow current velocities are important habitat features for good redside dace habitat. It is also important to take into account that although pool habitat is where redside dace spend the majority of their time, they do utilize shallow areas just above or below riffles for spawning and may be dependent upon larger nest building fish species for reproduction. It also is necessary to take into account larger scale habitat features and processes not addressed during this study, such as riparian vegetation, anthropogenic effects on the landscape, and temperature. Hopefully, the information provided by this study on the microhabitat of redside dace will contribute to the understanding and conservation of this unique species.

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Table 1.

Season Variable ______Stream System______Winter Chagrin R. tributary Clear Creek Rathburn Run Town Fork # of Cells (events) 74 (1) 313 (2) 392 (2) 229 (2) # RSD observed each event 15 20,23 20,7 20,10

Current Velocity Mean (m.sec-1) 0.02 0.12 0.08 0.10 Range 0.00-0.10 -0.06-0.61 -0.03-0.54 -0.04-0.56 SD 0.02 0.15 0.11 0.13 Depth Mean (m) 0.33 0.24 0.17 0.23 Range 0.00-0.99 0.01-0.98 0.00-0.60 0.00-0.85 SD 0.26 0.24 0.16 0.23 Distance to Wood Mean (m) 0.63 4.38 3.58 2.30 Range 0.00-2.50 0.00-12.50 0.00-13.00 0.00-8.13 SD 0.76 3.33 3.37 1.99 Distance to Shore Mean (m) 0.48 0.84 0.76 0.54 Range 0.00-1.75 0.00-3.00 0.00-3.00 0.00-3.00 SD 0.56 0.82 0.78 0.72

21

Table 1 (continued)

Season Variable ______Stream System______Spring Chagrin R. tributary Clear Creek Rathburn Run Town Fork # of Cells 160 (2) 158 (1) 313 (2) 227 (2) # RSD observed each event 20,20 20 20,20 20,20

Current Velocity Mean (m.sec-1) 0.07 0.12 0.06 0.15 Range -0.02-0.73 -0.01-1.09 -0.01-0.57 -0.05-0.84 SD 0.12 0.22 0.10 0.18 Depth Mean (m) 0.17 0.22 0.17 0.29 Range 0.00-0.70 0.01-0.89 0.00-0.60 0.00-0.93 SD 0.17 0.25 0.16 0.27 Distance to Wood Mean (m) 0.51 4.29 3.10 2.16 Range 0.00-2.13 0.00-12.50 0.00-13.00 0.00-8.13 SD 0.66 3.48 3.83 2.08 Distance to Shore Mean (m) 0.33 0.76 0.82 0.04 Range 0.00-2.50 0.00-2.50 0.00-3.00 0.00-2.38 SD 0.54 0.76 0.82 0.58

22

Table 1 (continued)

Season Variable ______Stream System______Summer Chagrin R. tributary Clear Creek Rathburn Run Town Fork # of Cells 60 (1) 190 (2) 191 (1) 230 (2) # RSD observed each event 11 15,20 10 20,8

Current Velocity Mean (m.sec-1) 0.00 0.01 0.04 0.01 Range 0.00-0.01 0.00-0.19 0.00-0.32 -0.04-0.82 SD 0.00 0.03 0.06 0.15 Depth Mean (m) 0.35 0.20 0.11 0.23 Range 0.01-0.99 0.00-0.74 0.01-0.43 0.00-0.81 SD 0.26 0.22 0.10 0.22 Distance to Wood Mean (m) 0.53 3.37 1.17 2.48 Range 0.00-2.13 0.00-11.75 0.00-5.75 0.00-7.25 SD 0.64 3.12 1.53 1.83 Distance to Shore Mean (m) 0.40 0.63 0.20 0.73 Range 0.00-1.75 0.00-3.00 0.00-2.13 0.00-3.00 SD 0.53 0.89 0.39 0.81

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Table 1 (continued)

Season Variable ______Stream System______Fall Chagrin R. tributary Clear Creek Rathburn Run Town Fork # of Cells NA (0) 277 (2) 345 (2) 115 (1) # RSD observed each event NA 20,22 4,13 20

Current Velocity Mean (m.sec-1) NA 0.03 0.03 0.17 Range NA -0.02-0.32 -0.01-0.23 -0.04-0.78 SD NA 0.06 0.05 0.19 Depth Mean (m) NA 0.22 0.13 0.24 Range NA 0.00-0.85 0.00-0.51 0.01-0.88 SD NA 0.22 0.12 0.22 Distance to Wood Mean (m) NA 3.90 2.09 2.44 Range NA 0.00-12.00 0.00-10.75 0.00-7.25 SD NA 3.20 2.49 1.88 Distance to Shore Mean (m) NA 0.88 0.49 0.72 Range NA 0.00-3.00 0.00-2.00 0.00-3.00 SD NA 0.93 0.62 0.80

Table 1. Mean, range, and standard deviation of the four environmental variables obtained from all cells of the grids used to quantify redside dace (Clinostomus elongatus) habitat use in each of the four tributaries in each season. When the site was sampled twice in one season, data from the two sampling events were pooled for summary statistics. Additionally, the average number of cells in each grid is presented and the number of sampling dates is indicated in parentheses. The number of redside dace (RSD) observed in each even is indicated also.

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Figure 1. Example of distributional grid used to measure variables used in this study. The stream is flowing from right to left in the diagram. Woody debris is any woody material in the stream including roots, down trees, brush, and sticks. Boulders are large rocks (1/3 m in diameter or larger). Mud is soft silt and or clay substrate. Organic debris was an area of decaying leaf littler and bits of wood as a substrate. Cobble is golf ball-size up to but not including boulder-sized rocks. Course sand or fine gravel is pea-size gravel down to sand material as a substrate. Solid flat substrate included a solid hard pan clay bottom and an area of solid bedrock. Loose shale is pieces of bedrock that have broken loose and piled up during periods of high discharge.

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Figure 2. Actual mean current velocity at microhabitat locations where redside dace were found (dark bars) versus randomized mean velocities (white bars). Data are presented for each season at four streams in Ohio in which redside dace are common. Habitat use in each site and season were tested independently where *=p<0.05, **=p<0.01, and ***=p<0.001. Error bars represent one standard deviation. No comparison was conducted at the East Branch of the Chagrin River in fall because of logic problems collecting data.

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Figure 3. Actual mean depths at microhabitat locations where redside dace were found (dark bars) versus randomized mean depths (white bars). Data are presented for each season at four streams in Ohio in which redside dace are common. Habitat use in each site and season were tested independently where *=p<0.05, **=p<0.01, and ***=p<0.001. Error bars represent one standard deviation. No comparison was conducted at the East Branch of the Chagrin River in fall because of logic problems collecting data.

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Figure 4. Actual mean distances to wood at microhabitat locations where redside dace were found (dark bars) versus randomized mean distances to wood (white bars). Data are presented for each season at four streams in Ohio in which redside dace are common. Habitat use in each site and season were tested independently where *=p<0.05, **=p<0.01, and ***=p<0.001. Error bars represent one standard deviation. No comparison was conducted at the East Branch of the Chagrin River in fall because of logic problems collecting data.

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Figure 5. Actual mean distances to shore at microhabitat locations where redside dace were found (dark bars) versus randomized mean distances to shore (white bars). Data are presented for each season at four streams in Ohio in which redside dace are common. Habitat use in each site and season were tested independently where *=p<0.05, **=p<0.01, and ***=p<0.001. Error bars represent one standard deviation. No comparison was conducted at the East Branch of the Chagrin River in fall because of logic problems collecting data.