EFFECTS OF SPATIAL AND TEMPORAL VARIABILTY OF SHOAL HABITAT ON STREAM FISH ASSEMBLAGES IN CHATTAHOOCHEE TRIBUTARIES, ALABAMA Except where reference is made to the work of others, the work described in this thesis is my own or was done in collaboration with my advisory committee. This thesis does not include proprietary or classified information ___________________________ Ronald Adam Kennon Certificate of approval: _____________________________ _____________________________ Jack W. Feminella Carol E. Johnston, Chair Professor Associate Professor Biological Sciences Fisheries and Allied Aquacultures _____________________________ _____________________________ Michael J. Maceina George W. Folkerts Professor Professor Fisheries and Allied Aquacultures Biological Sciences ________________________ Joe F. Pittman Interim Dean Graduate School EFFECTS OF SPATIAL AND TEMPORAL VARIABILTY OF SHOAL HABITAT ON STREAM FISH ASSEMBLAGES IN CHATTAHOOCHEE TRIBUTARIES, ALABAMA Ronald Adam Kennon A Thesis Submitted to the Graduate Faculty of Auburn University in Partial Fulfillment of the Degree of Master of Science Auburn, AL December 17, 2007 iii EFFECTS OF SPATIAL AND TEMPORAL VARIABILTY OF SHOAL HABITAT ON STREAM FISH ASSEMBLAGES IN CHATTAHOOCHEE TRIBUTARIES, ALABAMA Ronald Adam Kennon Permission is granted to Auburn University to make copies of this thesis at its direction, upon request of individuals or institutions and at their expense. The author reserves all publication rights. ________________________________ Signature of Author ________________________________ Date of Graduation iv VITA Ronald Adam Kennon, was born in Columbus, GA on November 4, 1978, and raised in Phenix City, Alabama. He attended Auburn University and graduated with a Bachelors degree in Fisheries and Allied Aquacultures in 2002. After graduation, he worked as a fisheries technician in the Fish Biodiversity Lab at Auburn University from 2002-2004. In January 2005 he began graduate school at the Department of Fisheries and Allied Aquacultures. On October 29, 2005 he married Whitney Lynn Reed of Memphis, Tennessee. On January 10, 2006 they had their first child Savannah Ruth Kennon. v THESIS ABSTRACT EFFECTS OF SPATIAL AND TEMPORAL VARIABILTY OF SHOAL HABITAT ON STREAM FISH ASSEMBLAGES IN CHATTAHOOCHEE TRIBUTARIES, ALABAMA Ronald Adam Kennon Master of Science, December 17, 2007 (B.S., Auburn University, 2002) 108 Typed Pages Directed by Carol E. Johnston Abiotic factors associated with habitat quality may have profound effects on fish assemblage structure. Variability in physical habitat parameters as well as temporal fluctuation in characteristics such as water depth and flow often dictate species persistance in stream mesohabitats. Few studies have extended the study of abiotic factors to habitat patch size or spatial relationship, however. Linkages between fish assemblages and the temporal and spatial variation of shoal habitats in three streams (Little Uchee, Wacoochee, and Halawakee) of the Chattahoochee River basin in east vi Alabama were investigated. Richness, composition, and density of fishes were quantified to determine their relationship with habitat type, size, physical parameters and spatial distribution. Tributaries of the Chattahoochee River in Alabama were found to have unique shoal fish assemblages. Comparison of adjacent pool/shoal fish assemblages revealed higher richness in shoals than pools and also showed low similarity between the two habitats, demonstrating the uniqueness of these habitat types. Many fishes were habitat specialists, species found in shoal samples > 75% of species occurrence included: shoal bass, Micropterus cataractae; bluefin stoneroller, Campostoma pauciradii; blackbanded darter, Percina nigrofasciata. These species showed variability with size, quality, and position of shoal habitats. Drought conditions were evident in 2006, causing a significant change in the size of shoal habitat patches sampled in both 2005 and 2006. Richness and density of fishes increased in 2006 across all shoals of all sizes. Fish assemblages varied annually and were best predicted by shoal volume, substrate composition, and CV of depth and flow. Spatial distribution of shoals in watersheds predicted composition and density of fishes. Results from this study suggest that shoal size may be a better predictor of species richness than spatial position. Shoals acted as islands providing structure and resources for stream fishes. Stream fish from all families were present in shoal habitats. For this reason, reaches of streams that contain shoal habitat should be the focus of managers charged with conserving stream fishes. vii ACKNOWLEDGEMENTS I would like to thank my committee members, Dr. Jack Feminella, Dr. George Folkerts and Dr. Mike Maceina for their helpful suggestions and timely assistance with this thesis, and my advisor, Dr. Carol Johnston for giving me a chance to attend graduate school and work under her tutelage. Without her patience mentoring and valuable guidance, completion of this thesis would not have been possible. I would also like to thank Van Atkins, Phillip Cleveland, Andrew Henderson, Dan Holt, Mark Mackenzie, Matt Marshal, Nick Ozburn, Steve Rider, and David Stormer for helping in various aspects of this project. This thesis was supported in part by the State Wildlife Grants Program (SWG). viii Style Manual or journal used: Ecology of Freshwater Fish Computer software used: Microsoft Office Word 2003, Microsoft Office Excel 2003, ESRI ArcMap version 9.1, SPSS 11.0 ix TABLE OF CONTENTS Page LIST OF TABLES ..........................................................................................................x LIST OF FIGURES.......................................................................................................xii INTRODUCTION...........................................................................................................1 STUDY AREA................................................................................................................7 MATERIALS AND METHODS .....................................................................................8 DATA ANALYSIS .......................................................................................................10 RESULTS .....................................................................................................................12 TEMPORAL ENVIRONMENTAL AND BIOTIC VARIATION..................................14 HABITAT QUALITY OF SHOALS .............................................................................14 HABITAT SIZE/QUALITY AND FISH ASSEMBLAGES...........................................15 SPATIAL DISTRIBUTION OF FISH ASSEMBLAGES ..............................................16 DISCUSSION ...............................................................................................................19 CONCLUSIONS...........................................................................................................26 LITERATURE CITED..................................................................................................28 APPENDIX...................................................................................................................36 x LIST OF TABLES Page Table 1. Names and descriptions of physical variables used in principal component analysis and regression analyses ....................................................................................37 Table 2. Species list and type of habitat in which each species was collected .................38 Table 3. Jaccard similarity values and richness for Little Uchee Creek pools and shoals sampled in 2005 (P=pool,S=shoal) .......................................................................39 & 40 Table 4. Jaccard similarity values and richness for Wacoochee Creek pools and shoals sampled in 2005 (P=pool,S=shoal) ................................................................................41 Table 5. Jaccard similarity values and richness for Halawakee Creek pools and shoals sampled in 2005 (P=pool, S=shoal) .............................................................................. 42 Table 6. Paired t-test (n = 8) results for temporal variability in environmental variables between years. Values marked in bold are significant at alpha = .05 ..............................43 Table 7. Paired t-test (n = 8) results for temporal variability in biotic variables between years. Values marked in bold are significant at alpha = .05 ............................................44 Table 8. Jaccard similarity index and richness of replicated shoals in Little Uchee Creek in 2005 and 2005 ...........................................................................................................45 Table 9. Jaccard similarity index and richness of replicated shoals in Wacoochee Creek in 2005 and 2005 ...............................................................................................................46 Table 10. Jaccard similarity index and richness of replicated shoals in Halawakee Creek in 2005 and 2005 ...........................................................................................................47 Table 11. Eigenvalues, percent, and cumulative variance of principal components for 2005 ..............................................................................................................................48 Table 12. Eigenvalues, percent, and cumulative variance of principal components for 2006 ..............................................................................................................................49 xi Table 13. Component loadings of environmental variables on principal components for 2005 and 2006. Variables in bold were used in regression analyses ..........................50 Table 14. ANOVA of PC variables selected from the principal component analysis for Little Uchee, Wacoochee, and Halawakee Creek shoals. Values marked in boldface are significant at the alpha = .05 level............................................................................51 Table 15.Bonferroni post-hoc analysis of selected principal components in 2006...........52 Table 16. ANOVA of 2006 Environmental variables for Little Uchee, Wacoochee, and Halawakee creeks....................................................................................................53 Table 17. ANOVA of 2005 Environmental variables for Little Uchee, Wacoochee, and Halawakee creeks....................................................................................................54 Table 18. Standardized coefficients, representing the change in a dependent variable that result from a change of one standard deviation in an independent variable, for multiple regression of species richness and fish density against environmental principlal components in 2005 and 2006. Significant coefficients are marked in bold. Significance test at alpha = .05. PC1 from 2005 and 2006 represented volume/size. PC2 from 2005 and 2006 represented proportion of bedrock. In 2005, PC3 represented CV of current velocity. PC3 and PC4 in 2006 represented CV of depth and current velocity, respectively. In 2005, PC4 represented proportion of boulder. r 2 values given with corresponding figures ....................................................................................................55 Table 19. Pearson correlations for shoal size and fish variables in 2005 and 2006..........56 Table 20. Component loadings of spatial variables on principal components combined for 2005 and 2006. Variables in bold were used in regression analyses. .........................57 Table 21. Standardized coefficients, representing the change in a dependent variable that result from a change of one standard deviation in an independent variable, for multiple regression of species richness and fish density against spatial principal components. Significant coefficients are marked in bold. Significance test at alpha = .05. PC1 represented proximity index. PC2 represented link magnitude. r 2 values given with corresponding figures ....................................................................................................58 Table 22. List of proximity ranges for species found in shoals in the Chattahoochee River drainage.........................................................................................................................59 Table 23. Longitudinal succession of fish families in shoals for 2005 and 2006. (Upper = headwater sections, Middle = middle reaches of streams, Lower = lower reaches of streams ..........................................................................................................................60 xii LIST OF FIGURES Page Figure 1. Shoal sites sampled in Little Uchee, Wacoochee, and Halawakee Creeks in Alabama during summer 2005 and 2006 ........................................................61 Figure 2. Fish species composition from pool and shoals in Little Uchee Creek from 2005 and 2006........................................................................................................................62 Figure 3. Fish species composition from pool and shoals in Wacoochee Creek from 2005 and 2006........................................................................................................................63 Figure 4. Fish species composition from pool and shoals in Halawakee Creek from 2005 and 2006........................................................................................................................64 Figure 5. Fish species composition of pool habitats in Little Uchee Creek in 2005 ..........................................................................................................................65 Figure 6. Fish species composition of pool habitats in Wacoochee Creek in 2005 ..........................................................................................................................66 Figure 7. Fish species composition of pool habitats in Halawakee Creek in 2005 ..........................................................................................................................67 Figure 8. Fish species composition of shoal habitats in Little Uchee Creek in 2005 and 2006 ...........................................................................................................68 Figure 9. Fish species composition of shoal habitats in Wacoochee Creek in 2005 and 2006 ...........................................................................................................69 Figure 10. Fish species composition of shoal habitats in Halawakee Creek in 2005 and 2006 ...........................................................................................................70 Figure 11. Uchee Creek gauge from July 2004 ? Jan 2007.............................................71 Figure 12. Principal component analysis plots of environmental variables of shoals in 2005 ..............................................................................................................................72 xiii Figure 13. Principal component analysis plots of environmental variables of shoals in 2006 ..............................................................................................................................73 Figure 14. Linear relationship of species richness and CV of current velocity of shoals in 2005 ..............................................................................................................................74 Figure 15. Linear relationship between species richness and % of boulder in shoals in 2005 ..............................................................................................................................75 Figure 16. Linear relationship of the total fish density/m 2 and shoal volume in 2005 ..........................................................................................................................76 Figure 17. Linear relationship between juvenile fish density/m 2 and shoal volume in 2005 ..........................................................................................................................77 Figure 18. Linear relationship between adult fish density/m 2 and shoal volume in 2005 ..........................................................................................................................78 Figure 19. Linear relationship between number of adult C. pauciradii/m 2 and shoal volume in 2005.....................................................................................................79 Figure 20. Linear relationship between number of adult C. venusta/m 2 and the proportion of bedrock in 2005.........................................................................................................80 Figure 21. Linear relationship between number of cyprinids/m 2 and shoal volume in 2005 ..........................................................................................................................81 Figure 22. Linear relationship between species richness and shoal volume in 2006 ..............................................................................................................................82 Figure 23. Linear relationship between number of juvenile P. nigrofasciata/m 2 and shoal volume in 2006..............................................................................................................83 Figure 24. Linear relationship between number of cyprinids/m 2 and shoal volume in 2006..............................................................................................................84 Figure 25A. Species-area relationship for shoals in 2005 ...............................................85 Figure 25B. Species-area relationship for shoals in 2006 ...............................................86 Figure 26. Linear relationship between number of C. pauciradii/m 2 and CV of current velocity in 2006.............................................................................................87 Figure 27. Size and distribution of shoal habitats in Little Uchee Creek .........................88 Figure 28. Size and distribution of shoal habitats in Wacoochee Creek ..........................89 xiv Figure 29. Size and distribution of shoal habitats in Halawakee Creek ...........................90 Figure 30. Linear relationship between species richness and proximity index in 2006 ..........................................................................................................................91 Figure 31. Linear relationship between number of cyprinids/m 2 and link magnitude in 2005 ..............................................................................................................................92 Figure 32. Linear relationship between number of cyprinids/m 2 and link magnitude in 2006 ..............................................................................................................................93 Figure 33. Linear relationship between number of centrarchids/m 2 and link magnitude in 2006 ..............................................................................................................................94 1 INTRODUCTION In the last 100 years, three genera, 27 species, and 13 subspecies of freshwater fishes have become extinct in North America alone (Miller et al. 1989). A number of factors have contributed to loss of fish diversity, although habitat alteration is often cited as the most significant contributor to freshwater fish decline. Physical alteration of habitat is responsible for 73% of the declines and extinctions of North American species (Miller et al. 1989; Helfman et al. 1997). The rapid loss of freshwater fish species due to habitat degradation emphasizing the importance of understanding relationships between fishes and their habitats critical for species conservation. Stream ecologists have adopted ideas from landscape ecology and metapopulation biology to describe patterns and relationships among stream biota and their habitats. The concept of patch dynamics depicts streams as spatially continuous longitudinal and lateral mosaics of habitats and resources (Pringle et al. 1988; Townsend 1989). Pringle et al. (1988) and Townsend (1989) utilized the theory of island biogeography (MacArthur & Wilson 1967) and other landscape concepts to explain how specific patch characteristics determine stream biotic and abiotic processes over various spatial and temporal scales. The theory of island biogeography attempts to explain the correlative effect of area and proximity of patches (i.e. islands) on species richness. The theory states that the size of an island and its location are indicators of the total number of species expected to exist there 2 (Wilson 1992). The concept of islands has been applied to many kinds of isolated habitats such as coral reefs, natural lakes, and individual pools and riffles all have been viewed as patches (Matthews 1999; Angermeier & Schlosser 1989) The size and physical characteristics of habitat patches play a significant role in determining the structure of fish assemblages (Schlosser 1982). Studies have shown that size of habitats (Minckley 1984; Taylor 1996), stream width (Robinson & Buchanan 1988; Smith & Miller 1986; Gelwick 1990), depth (Hocutt & Stauffer 1975; Paller 1994; Sheldon 1968; Taylor et al. 1993; Peterson and Rabeni 1996; Harvey & Stewart 1991), volume (Angermeier & Schlosser 1989; Taylor 1997), temperature (Hynes 1970; Magnuson et al. 1979; Shuter et al. 1980; Rahel & Hubert 1991; Kelly et al. 1980; Baltz et al. 1991; Hughes 1998) and habitat heterogeneity (Schlosser 1987a) determine assemblage structure. The River Continuum Concept (RCC) Vannote et al. 1980) first described the longitudinal change in stream attributes for networks of streams from headwaters to large rivers. These changes can affect the richness, density and composition of fish assemblages (Gorman & Karr 1978; Angermeier & Karr 1983; Schlosser 1987a; Rahel & Hubert 1991; Lyons 1996). Changes in assemblages are apparent and well documented throughout the entire network of a watershed, but within parts of these networks, longitudinal relationships may be obscured by local factors. Montgomery (1999) proposed the Process Domain Concept (PDC) as a means to explain local factors that influence ecosystem structure and function. Process domains are predictable areas of a stream where physical habitat type, structure, and dynamics are governed by geomorphic processes (Naiman et al. 2005). These processes are determined 3 by such natural environmental variables such as geology, climate, and vegetation. Walters et al. (2003) identified relationships between stream geomorphology and fish assemblages and concluded that species composition was predicted by reach-level geomorphic variables of stream slope, bed texture, bed mobility, and tractive force. The spatial and temporal variability of geomorphic processes can control habitat quality, availability, and disturbance, thereby creating a mosaic of habitat patches within a stream. The mosaic of resources can govern the availability of habitat types and, ultimately, control fish assemblage structure and species interactions (Fausch 2002). Stream networks are dendritic systems, so the movement of fishes can only occur in an up- or downstream direction, a constraint that can cause them to be highly susceptible to habitat fragmentation (Zwick 1992; Rieman & McIntyre 1995; Rahel et al. 1996; Dunham et al. 1997). In this context, fish cannot move between distant patches without first passing intervening patches; thus, the lack of suitable intervening patches can isolate populations (Fagan 2002). Concepts presented by Schlosser (1991, 1995a, 1995b) emphasize fish movement as a means of transporting different life stages across landscape scales. The ranging movement of fish is a facultative response to resource abundance and distribution of resources along the riverscape (Behnke 1992). Mobile fish species requiring extensive ranges can become isolated (Hanski et al. 1996). Anthropogenic disturbance can cause habitat fragmentation by disconnecting reaches of stream that were once contiguous. Isolation of habitat patches reduces emigration and alters the genetic integrity of populations (Macarthur & Wilson 1967; Kindvall & Ahlen 1992; Sjogren-Gilve & Ray 1996). The connectivity of patches occurring within a stream mosaic is critical for the 4 proliferation of stream fish populations (Fausch 2002). The movement of stream fishes among resource patches at the landscape scale allows for recolonization after anthropogenic or natural disturbances, causing a reduction in local extinction rates as long as habitat quality remains intact. Because fishes use different habitats for a variety of life history stages (i.e. diurnal vs. nocturnal, spawning vs. nonbreeding, and juvenile vs. adult), it is important to consider the spatial and temporal variability of habitats (Matthews 1999). Studies that are limited in scale can overlook important patterns and interactions of stream fishes, which could be made more apparent with multi-scaled approaches. Recent studies have used multi-spatial and multi-temporal scaled approaches to overcome the difficulties of observing patterns and processes that may not be apparent in single scaled approaches. Schlosser (1982) noted the importance of temporal and spatial variation in habitat diversity (depth, velocity, and substrate) of streams. Lancaster (2000) and Palmer et al. (2000) used experimental designs focused on stream habitat patches ranging in type and size to provide data at multiple spatial and temporal scales, thus, they were able to draw conclusions about how patch structure in a stream landscape affects the distribution of invertebrates. A multi-scaled study by Gido et al. (1997) found spatial variation to be greater than temporal variation for the abundance of three fish species in streams, while a single species showed temporal variation. The authors also found that timing of spring run-off has the greatest temporal effect on fish communities. Matthews (1990) showed that the abundances of 3 darters were affected by both spatial and temporal variation in riffles. Variation in species diversity of stream fishes was best explained by temporal and spatial-scaled approaches (Tripe and Guy 1999). Spatial 5 variation in diversity was explained by longitudinal position, whereas temporal variation revealed high diversity in summer and low diversity in late fall and early spring (Tripe and Guy 1999). Gelwick (1990) described variation in stream fish assemblages of pools and riffles on both spatial and temporal scales. Assemblage structure was related to longitudinal position of pool habitats, although most of the variation in richness and abundance within riffle habitats was temporal. Species diversity, abundance and composition were determined by spatial position of habitats more so than temporal variation in 2 Texas streams (Ostrand 2002). Dunham et al. (1999) investigated patterns in bull trout (Salvelinus confluentus) occurrence in terms of physical, biotic, landscape characteristics, and distance to the nearest patch, and found that both patch area and isolation were related to bull trout occurrences. Smith and Kraft (2005) reported that a combination of small-scale habitat variables and stream position within a watershed influenced fish assemblages. Magoulick (2000) found high temporal variability in richness and densities of fishes in stream pools. The above studies have shown that systematically censusing coarse-grained habitat features along entire streams and quantifying finer-grained variables within those habitats provide a more accurate depiction of patch dynamics of stream organisms across whole watersheds. Although fine spatial (e.g. 50- to 500-m reaches of stream) and temporal (e.g. hours to weeks) scaled studies are of limited use to managers, studies conducted at both fine and broad scales have become the emphasis of resource managers and conservation biologists for insight on managing populations across watersheds Preserving metapopulations and maintaining genetic integrity of stream fishes is a primary concern for agencies and managers charged with conserving fishes. Conservation 6 efforts aiming to sustain threatened and endangered fish species benefit from data describing the spatial and temporal habitat requirements of stream fishes. The ability to quantify the habitat requirements of Evolutionarily Significant Units (ESU?s), species, subspecies, or populations with extremely low abundance is essential for their successful management (Grossman et al. 1995). Research investigating the effects of habitat size, character, and spatial position on the distribution of stream fishes will help resource managers focus their efforts on populations that are in serious decline as a result of habitat loss or fragmentation. In my study, I examined how temporal variation, size, quality and spatial distribution of shoals affected fish assemblages. I investigated variations in species richness, composition, density, relative abundance and size of stream fishes. My objectives were to: 1) compare how shoal and pool fish assemblages differ, 2) investigate temporal habitat variability in relation to shoals and their fish assemblages, 3) evaluate how the size and physical character of shoals affects fish assemblages, and 4) investigate how the spatial distribution of shoals within a stream affects fish assemblages. 7 STUDY AREA The Chattahoochee River begins in the Appalachian Mountains of northeastern Georgia and flows 430 miles to Lake Seminole near the Georgia-Florida border. The river system flows through 3 physiographic provinces: The Appalachian Plateau, the Piedmont, and the Coastal Plain. Three streams, Halawakee Creek, Wacoochee Creek, and Little Uchee Creek were chosen for study based on physiographic and faunal similarities (Boschung & Mayden, 2004). Study streams occur in the Piedmont physiographic province. The study area encompasses a large portion of east-central Alabama and ranged in elevation from 50 to 125 m above sea level. Watershed drainage areas ranged from 85 km 2 for Wacoochee Creek to 255 km 2 for Halawakee Creek. Streams channels were characterized by alternating sand-bottom pools, gravel riffles, and bedrock-boulder shoals with moderate to swift currents. Typically, shoals consist of exposed and submerged bedrock formations, with bedrock composing > 20 % of the habitat area. These geological formations constrict the flow of water in streams and create heterogeneous conditions and resources for fishes and other organisms. In my study, shoal habitats were bounded by stretches of pool/riffle/run habitat ranging from 50 to 5000 m, and are spatially positioned throughout the main stem of the study streams creating a close proximity among some and the isolation of others. Shoal habitats were once common throughout most of the Piedmont region, but numerous shoal habitats have been altered by reservoir construction and channelization, and the remaining still are threatened (Marcinek et al. 2003). These study streams contain some of the last remaining shoals in the Piedmont of the Chattahoochee River drainage in Alabama. 8 MATERIALS AND METHODS Sampling sites were selected by locating shoals within the main stem of each of the three study streams. Canoes were used to locate all shoal habitats, and selected on the basis of accessibility. Shoals sites were chosen to provide spatial coverage of the Chattahoochee River drainage in Alabama. Streams were sampled during the summer low-water period from 23 May to 31 August 2005 and 25 May to 31 August 2006. In summer 2005, 18 shoals and 18 pools adjacent to shoals were sampled in the 3 study streams to compare habitat use by fishes. In summer 2006, 8 of the original 18 shoals were resampled, as well as 12 additional shoals (Fig. 1). To quantify the physical structure of shoals, we used the transect method of Bain and Stevenson (1999). At each site, 5-10 transects were established such that no 2 transects were closer than 5m. The number of transects depended on the size of the habitat, such that an area 3x the width of each unit was surveyed. Each site was georeferenced with GPS. Link magnitude for each site was obtained using 7.5-min. topographical maps. Information on environmental variables were obtained at each site, including total depth, mean current velocity, and substrate were taken at 1.0-m intervals along each transect (Table 1). Temperature was recorded at the center of each shoal. Depths were recorded with a meter stick. Current velocity was measured with a Marsh McBirney Flowmate flow meter. Stream wetted width was measured with a standard tape measure. Coefficients of variation (CV) were estimated for depth, current velocity, and width to look at the heterogeneity of shoals. Habitat unit length was measured with a hip chain nearest meter. Habitat area (m 2 ) was calculated as the product of the length and mean width of the study site. Shoal volumes were calculated by multiplying mean width, 9 mean depth, and length. Substrate composition was categorized according to particle diameter using the Wentworth classification: (1) bedrock (no particles), (2) boulder (>256 mm), (3) cobble (64-256 mm), (4) pebble (16-36 mm (5) gravel (2-15 mm), (5) sand (0.06-1 mm), and (6) silt (0-0.5 mm) (Wentworth, 1922). Simpson?s diversity index was used to calculate substrate diversity for each site as a measure of habitat heterogeneity (Simpson 1949). Shoal habitats were sampled with backpack shockers, seines, and dipnets. Starting at the downstream end of a shoal, 2-3 passes were made per site. The size of the area sampled was obtained after fish sampling to estimate fish density, calculated by dividing abundance in the shoal by the area of the shoal sampled. Pool habitats were sampled with a minimum of 10 seine hauls. Each seine haul covered a distance of 5 m and was made in both downstream and upstream directions. Specimens were anesthetized in MS-222, placed in 10% formalin, transferred to 50% ethanol, identified, and deposited in the Auburn University Fish Collection. The most abundant fish species (Campostoma pauciradii, Cyprinella venusta, Lepomis, auritus, and Percina nigrofasciata) were grouped into juvenile and adult size classes based on size at maturity (Boschung and Mayden, 2004), and were used as total, juvenile, and adult densities in the statistical analysis. Sizes classifications were based on the assumption of ontogenetic niche shifts and predation risk strongly affecting size of fish (Werner & Gilliam, 1984) and, thus, an important part of assemblage structure. 10 DATA ANALYSIS The same areas were sampled in both years for the replicated sites, so comparisons of environmental variables, richness, and fish densities for similar months between years were made using paired t -test on log-transformed data. Spearman rank correlations were used to look at compositional differences in pool shoal assemblages by stream (Lehman and D?Abrera 1998). The Jaccard similarity index (JSI) was used to compare assemblages of shoal and pool habitats and replicated shoal sites. JSI = j/r j represents the number of species in common between sites, and r represents the total number of species present in both sites (Krebs 1999). Jaccard similarity is a measure of community similarity that is based only on the presence and absences of species. Values range from 1 to 0, with 1 indicating a complete similarity between habitats, and 0 indicating complete dissimilarity (no shared species). To improve normality, all environmental, spatial and fish variables were log 10 (x+1)-transformed, except for temperature, which was square root-(x+1) transformed, and the substrate composition variables, which were arcsine transformed. Linear regression analysis was used to describe the species-area relationship of each year for shoal habitats and the densities of fishes. To reduce the 16 environmental variables of shoals to fewer dimensions and remove collinearity, a principal component analysis (PCA) was performed with varimax rotation (Gordon 2005). PCs were retained for each year because of temporal variation in dependent variables. All variables with eigenvalues >1 and loading strongly (>.80) on measured environmental variables were retained. To 11 use environmental variables from all streams as predictor variables in the multiple regression analyses and to test the degree of similarity among shoals in the 3 study streams, ANOVA was used on PC environmental variables selected from the PCA. Multiple regression was used to examine relationships between selected PCs and the dependent fish variables species richness, total, juvenile, and adult densities, and density of the 4 most common species. Environmental variables selected by PCA were put into multiple regression models for each year. Spatial variables for each site were obtained using ARCGIS (v.9), including, distance to nearest neighbor habitat and distance to the mainstem Chattahoochee River. A proximity index was adopted from Gustafson and Parker (1992), which determines the isolation of patches. This index is given by: PXi = ? ( Sk /n k ) Where PXi is the proximity index for focal patch i, and then with the specified search distance, s k is the area of patch k with in the search buffer, and n k is the nearest neighbor distance between the focal patch and nearest patch. Low values (< 7.0) indicate patches are relatively isolated from other patches within the specified buffer distance, and high values (>7.0) indicate patches are relatively connected to other patches Gustafson and Parker (1992). In order to include all shoals in this study into the analysis, a 5 km distance was chosen as the specified search distance. To reduce the 4 spatial variables of shoals to fewer dimensions and remove collinearity, a PCA was performed with varimax rotation. PCs were retained for the combination of years because spatial variation did not change by year. All variables with eigenvalues >1 and loading strongly (>.70) on 12 measured spatial variables were retained. Multiple regression analysis was performed on selected spatial PCs to examine variation in fish variables. PCs were regressed by year to analyze the effects of a shoal?s spatial position on fish assemblages. RESULTS A total of 2,164 specimens representing 41 species in 12 families were collected from pool and shoal habitats in Little Uchee, Wacoochee, and Halawakee creeks. Dominant families in Little Uchee creek were Centrarchidae (40%), Cyprinidae (28%), and Catostomidae (8%), (Fig. 2), with the species Cyprinella venusta representing 34%, Percina nigrofasciata 30%, and Lepomis auritus 7% of fish relative abundance. Dominant families in Wacoochee Creek were Cyprinidae (47%), Centrarchidae (22%), and Ictaluridae (11%), (Fig. 3), with the species P. nigrofasciata representing 34%, C. venusta 20%, and Ameiurus brunneus 10% of fish relative abundance. Dominant families in Halawakee Creek were Centrarchidae (34%), Cyprinidae (30%), and Catostomidae (9%), (Fig. 4), with P. nigrofasciata representing 20%, L. auritus 12%, and L. macrochirus 11% of fish relative abundance. This survey showed that Little Uchee, Wacoochee, and Halawakee shoal and pool faunas contained 5 fishes endemic to the Apalachicola River System, including C. pauciradii, Notropis hypsilepis, Moxostoma lachneri, A. brunneus, and Micropterus cataractae. Thirty-four species were found in pool habitats, and 16 of these species were found exclusively in pools (Table 2). Eighteen species were common to both shoal and pool habitats, whereas 6 species were found exclusively in shoals, including C. 13 pauciradii, L. zonistius, N. hypsilepis, M. cataractae, P. nigrofasciata, and Etheostoma swaini (Table 2). Jaccard similarity indices revealed high dissimilarity in assemblage compositions between habitat types (Tables 3,4, & 5). Scores showing low values (< .50) indicate a high degree of community difference between habitats. Species richness was higher in shoals than in pools, with the exception of site 12 on Little Uchee Creek, the most downstream site. Species composition at the family level differed among streams in pool habitats. Results from Spearman rank correlation show significant differences between the pool assemblages of Little Uchee and those Wacoochee and Halawakee. Wacoochee and Halawakee pool assemblages were similar (r s = 1, p < .01). Little Uchee pools contained primarily of Cyprinidae (83%) and Centrarchidae (13%) (Fig. 5). Wacoochee pools were composed primarily of Centrarchidae (45%) and Cyprinidae (33%) (Fig. 6). Halawakee pools were composed primarily of Centrarchidae (54%) and Cyprinidae (32%) (Fig. 7). Results from Spearman rank show non-significant differences between the assemblages of shoals at the family and species level (r s = 1, p < .01). Little Uchee shoal compositions were composed primarily of Centrarchidae (44%) and Cyprinidae (33%) (Fig. 8), with P. nigrofasciata representing 37%, C. venusta 23%, and L. auritus 8% of shoal relative abundance. Wacoochee shoals were composed primarily of Cyprinidae (44%) and Centrarchidae (28%), (Fig. 9), with P. nigrofasciata representing 39%, C. venusta 22%, and C. pauciradii 4% of shoal relative abundance. Halawakee shoals were composed primarily of Cyprinidae (43%) and Centrarchidae (28%) (Fig. 10), with P. nigrofasciata representing 25%, L. auritus 14%, and C. pauciradii 9% of shoal relative abundance. 14 TEMPORAL ENVIRONMENTAL AND BIOTIC VARIATION Stream drying was greater in 2006 than in 2005, with average depth of shoals significantly lower in 2006 than in 2005 (n = 8, p < .001) (Table 6). Shoal volumes were significantly lower in 2006 than in 2005 (p < .01). The difference in discharge between years was also evident from the Uchee Creek stream gauging station (Fig. 11). The gauge on Uchee Creek is the only reference gauge for stream levels in the Chattahoochee watershed of Alabama. Current velocities were significantly lower in 2006 than in 2005 (p < .001). Species richness of shoals was significantly higher (p < .001) in 2006 than in 2005 (Table 7). Total fish density, density of juveniles, and adults was significantly higher (p < .01) in 2006 than in 2005. Densities of the families Cyprinidae and Centrarchidae were not significantly different (p > .05) between years. Jaccard similarity analysis of replicated shoals revealed scores ranging from moderate (.60) to low (.23). In 2006, there was an increase in the presence of all families represented in the shoal assemblages (Tables 8,9, and 10). HABITAT QUALITY OF SHOALS The first 4 PCs of the rotated PCA explained 70.7 and 71.4% of the environmental variation among shoals in 2005 and 2006, respectively (Tables 11 and 12). Component loadings for environmental variables on the first 4 PCs differed by years (Table 13; Figs. 12 and 13). PC1 from 2005 and 2006 were volume/size dimensions, loading positively on volume and depth in 2005, and volume and area in 2006. PC2 from 2005 and 2006 represented substrate components, loading negatively on proportion of 15 bedrock in 2005, and positively on proportion of bedrock in 2006. In 2005, PC3 represented habitat heterogeneity dimension loading positively on CV of current velocity. PC3 and PC4 in 2006 also represented habitat heterogeneity dimensions loading positively on CV of depth and current velocity, respectively. In 2005, PC4 reflected a substrate component, loading positively on proportion of boulder. ANOVA of selected environmental variables showed shoal volume differing significantly (p > .05) among the 3 streams in 2006 (Table 14). Boneferroni post-hoc test showed that shoal volume was higher in Little Uchee than Wacoochee (Table 15). ANOVA revealed no significant difference in the other 14 environmental variables among streams in 2006 (Table 16). In 2005, ANOVA of the 16 environmental variables showed significant differences in proportion of sand between Wacoochee and the other 2 streams (Table 17), but differences in proportion of sand were not significant in 2006. Results from ANOVA suggest that the physical character of shoals in these streams was not significantly different; therefore, shoal data from all streams were pooled in regression analyses. HABITAT SIZE / QUALITY AND FISH ASSEMBLAGES In 2005, CV of current velocities and proportion of boulder predicted species richness (Table 18; Figs. 14 and 15). CV of current velocities showed a positive relationship, while proportion of boulder showed a negative relationship with richness. Total, juvenile, and adult fish densities were significant in 2005, indicating a negative relationship with volume (Fig. 16,17, and 18). Densities of adult C. pauciradii were negatively related to volume in 2005 (Fig. 19). Densities of adult C. venusta were 16 positively related to the proportion of bedrock in 2005 and significantly predicted by the regression model (Fig. 20). Densities of cyprinids were negatively related shoal volume in 2005 (Fig. 21). In 2006, the shoal volume significantly predicted species richness (Fig. 22). In 2006, there was a significant relationship between total fish densities and volume, but was not significantly predicted by the regression model. Densities of juvenile P. nigrofasciata and cyprinids were negatively related to volume in 2006 (Fig. 23 and 24). For shoal habitats in 2005, the species-area relationship was not significant (P > .05; Fig. 25A), but was significantly positive for area (p < .002) in 2006 (Fig. 25B). In 2005, densities adult C. pauciradii were negatively correlated (p < .05) with shoal area (Table 19). Densities of C. pauciradii were positively related to the heterogeneity of current velocities in 2006 (Fig. 26). SPATIAL DISTRIBUTION OF FISH ASSEMBLAGES The amount of available shoal habitat differed by stream. Little Uchee consisted of 9.5% shoal habitat and 90.5% of pool/riffle/run habitats. In Little Uchee, shoals included both isolated and connected patches, and most were located in the middle reaches of the stream (Fig. 27). Wacoochee consisted of 12% shoal habitat and 88% of pool/riffle/run habitats. In Wacoochee, shoals expressed both isolation and connectivity, and had a high frequency in both headwater and lower reaches (Fig. 28). Halawakee consisted of 5% shoal habitat and 95% of pool/riffle/run habitats. Shoals in Halawakee were more isolated than connected (Fig. 29). 17 The first 2 PC?s of the rotated PCA explained 74.26% of the variance in shoal position for both years (Table 20). PC1 was the connectivity dimension loading positively on proximity index and negatively on distance to nearest neighbor (Table 20). PC2 was a linear spatial dimension loading positively on distance to Chattahoochee and negatively on link magnitude (Table 20). In 2006, species richness was inversely related to proximity index in shoals (Table 21; Fig. 30), and, density of focal species was not significantly correlated with proximity index or link magnitude. In 2005, the densities of cyprinids showed a significant negative relationship with link magnitude (Fig. 31). In 2006, link magnitude was a significant predictor of cyprinid density (Table 21; Fig. 32). In 2006, the density of centrarchids showed a significant positive relationship with link magnitude (Table 21; Fig. 33). However in 2006, the model did not significantly explain the variation in centrarchid densities. The ranges in proximity indices varied by species (Table 22). Most species proximity indices ranged from (0.47 to 32.62). Hybopsis sp. winchelli had the highest average proximity average (15.12), but was found in the full range of proximities. L. zonistius had one of the highest proximity averages (14.12), with proximity indices ranging from (7.79 to 17.98). Micropterus cataractae had one of the highest proximity averages (14.05), with proximity indices ranging from (7.05 to 32.61). Both Luxilus zonistius and M. cataractae had the highest ranges of proximity indices of all species found in shoals (Table 22). To examine longitudinal zonation of fishes by stream, shoal sites were grouped based on the link magnitude of each site (Table 23). Stream reaches were partitioned into 18 (link magnitude. 10-20 = upper reaches, link magnitude 21-34 = middle reaches, and link magnitude 35-41 = lower reaches). In upper Little Uchee, species compositions of shoal habitats consisted primarily of the families Cyprinidae (43% of total), Centrarchidae (29%), and Catostomidae (14%), with C. pauciradii, C. venusta, P. nigrofasciata showing the highest relative abundance. Shoals in the middle reaches of Little Uchee consisted primarily of Cyprinidae (37%), Centrarchidae (27%), and Catostomidae (18%), with C. venusta, N. texanus, and P. nigrofasciata showing the highest relative abundance. Shoals in the lower reaches consisted primarily of the families Centrarchidae (43%), Cyprinidae (29%), and Catostomidae (14%). C. venusta, L. auritus, M. cataractae, and Hybopsis sp. showed the highest relative abundance in lower shoal assemblages. Shoals in upper Wacoochee consisted primarily of the families Cyprinidae (46%), Centrarchidae (27%), and Ictaluridae (13%), with C. venusta, L. zonistius, and P. nigrofasciata showing the highest relative abundance. Dominant families in lower Wacoochee shoals were Cyprinidae (43%), and Centrarchidae (36%), with C. venusta, A. brunneus, and L. auritus showing the relative highest abundance. Halawakee shoals consisted primarily of the families Cyprinidae (34%), Catostomidae (20%), and Centrarchidae (20%) in the upper reaches, where C. pauciradii and Hybopsis sp. showed the highest relative abundance. Shoals in middle reaches of Halawakee consisted primarily of the families Cyprinidae (34%), Centrarchidae (33%), and Catostomidae (13%), with L. auritus and L. macrochirus in highest abundance. Lower Halawakee shoals consisted primarily of Cyprinidae (34%), Centrarchidae (33%), Catostomidae (13%), and Ictaluridae (13%), with L. auritus, L. macrochirus, and M. 19 punctulatus in highest abundance, but held substantial numbers of C. pauciradii and Hybopsis sp. cf winchelli. DISCUSSION Shoal habitats had unique fish assemblages in comparison to pools. Size, physical characteristics, temporal variability and spatial distribution of shoals played a key role in structuring assemblages. Species compositions in pools showed significant difference among streams. There was no significant difference in the assemblages of shoals among streams. With the exception of the presence of M. cataractae, which was common in shoals of Little Uchee Creek, but was not present in high numbers in the other study streams. The results from pool and shoal comparisons in Wacoochee and Halawakee support results found for pools in other studies where centrarchids have dominated pools, while cyprinids are restricted to shallower habitats (Power & Matthews 1983, Power et al. 1985). Results from shoal and pool assemblage comparison show a higher number of species using shoals more than pools in 2005. These results suggest that fishes may be utilizing shoal habitats for spawning substrate, thermal refuge or a dissolved oxygen resource. Wootton (1998) suggested that structurally complex habitats usually have higher number of species than more homogeneous habitats because structurally complex habitats provide fishes with more ways of making a living. My study supports Wootton?s (1998) hypothesis, as shoals are more structurally complex and did, in fact, support more species than pools. 20 Data from my study indicates that temporal variation occurred in physical and hydrological habitat, species richness, and fish densities in the study streams. Shoal habitats experienced high temporal variability between 2005 and 2006. The physical characteristics of depth and volume showed significant variation between years. Based on data from our replicated shoal sites, drought conditions were evident in 2006, and thus likely influenced fish assemblages, by increasing densities and the presence all families of fishes. Changes in physical characteristics of streams caused by fluctuations in discharge have been shown to alter composition and stability of fish assemblages (Grossman et al. 1982). Natural droughts in harsh stream environments are speculated to have only transient effects on fish assemblages under natural conditions (Matthews & Marsh-Matthews 2003), and present-day fish assemblages are thought to be tolerant of environmental stressors such as droughts (Matthews 1987). Hubbs (1990) speculated that reduced flows decrease water availability and increase thermal oscillations, and that thermal effects of reduced flows may have more impact on fishes than the direct effects. . In this study there was no significant difference between temperatures in streams in 2005 and 2006 (p > .05) (Table 6). In 2006, richness, densities, and the presence of all families of fishes increased in shoals, most likely due to decreased water levels. Results from replicated shoals sites suggest that these relationships were true for shoals of all sizes. Schlosser (1985) documented increased densities of fishes in a dry year, and attributed the increase densities to increases in juvenile fishes because of stable conditions in the stream. Magoulick (2000) documented increases in total fish densities, large central stonerollers, and small sunfish with increases in pool volume for a dry year. Gelwick (1990) showed 21 temporal patterns related to changes in richness and fish abundance for riffles and pools. Increases in richness and densities suggest community dynamics such as: crowding, predation, low fecundity, variations in productivity, and increased competition for resources. It is assumed that fishes choose habitats to improve fitness (Behnke 1992). The results of habitat selection may be seen at different spatial scales (Kramer et al. 1991). The reduction in volume between years had a dramatic impact on shoal size in my study. Schlosser (1989) suggests that patch volume may be a more appropriate measure of patch size in streams. In the case of my study, shoal volume was a better predictor of species presence than area and length in 2006. A positive relationship was found between shoal size and species richness in 2006, where larger patches of habitat generally contained more species than smaller patches. This relationship was not evident in 2005 and could be contributed to increase water levels, which could have allowed fishes to disperse throughout the stream. Temporal variation seems to be a controlling factor determining variation in species richness and densities of fishes. Species-area relationships revealed in my study suggest that fish populations are responding to size of shoals. This result is critical for understanding metapopulation dynamics of stream fish and indicates the importance of temporal variability and habitat size. Numerous studies in a variety of habitat types have documented volume as a limiting factor in fish assemblages (Schlosser 1982; Taylor 1997; and Magoulick 2000). Although the species- area relationship has been documented for pool and riffle habitats (Angermeier & Schlosser 1989) no such relationship has been described for shoal habitats. Few consistent relationships existed between the physical variables and fish variables within or between years. Consequently, fish assemblages varied considerably 22 between years, and the abiotic variables measured at the patch scale varied in their ability to predict variations in fish assemblages. In 2005, richness was predicted by CV of current velocities and proportion of boulder substrate. Increases in the heterogeneity of current velocities showed increases in the number of species present. Increased competition and interaction between species may force some species to occupy different niches within a habitat (Wootton 1998). Increased variability in current velocities may limit the competition and interaction of species thereby allowing more species to occur in a particular habitat. Conversely, as the proportion of boulder in a shoal increased the number of species present decreased. Walters et al. (2003) found species compositions to be limited by geomorphic variables, citing bed texture, bed mobility, and tractive forces as predictors. Shoals with abundant boulder habitat also contained larger black bass and sunfish suggested biotic variables as a factor controlling richness. In 2005, densities of total and juvenile fishes were negatively correlated to shoal volume. Harvey (1991) found that juvenile fishes move into the shallow water to avoid predation by larger fish. In 2005, adult fish densities were predicted by shoal volume. In other words, as the volume of shoals increased the densities of adult fishes decreased. This could be attributed to the increased water levels in 2005 allowing fishes to disperse into the abundant habitat available to them. Since flows were elevated in 2005, there may be some correlation to the harsh conditions associated with high water levels. Adult fishes often retreat to deeper pools to avoid metabolic costs of maintaining position in fast current velocities (Elliot 1976). In 2006, the total density of fishes was inversely related to volume, but was not significantly predicted by the model. Densities of fishes in 2006 may have decreased due to predation risk, since there were significantly more 23 species using shoals. Depth of habitat has been shown to influence predation risk (Power, 1987; Schlosser, 1987a,b). Densities of C. pauciradii, a species endemic to the Chattahoochee drainage, was inversely related to volume in 2005. C. pauciradii may be selecting shallower habitat to avoid predation by larger fishes found in larger shoals (Schlosser 1987b). Another explanation for decreased densities may be that Campostoma species are grazers that feed on periphyton (Fowler and Taber, 1985). Light is commonly though to be a limiting factor in the distribution and abundance of stream periphyton (Allan 1995). So, deeper shoals may not support dense growth of periphyton, and, therefore, may not be preferred by C. pauciradii. C. pauciradii were positively related to the heterogeneity of current velocities in 2006. Current influences the distribution of periphyton, provides a continual renewal of gases and nutrients for proliferation, and can control the biomass of periphyton colonies (Allan 1995). This may be one reason why C. pauciradii. occupied shoal habitats with a high degree of current velocity variation. Density of C. venusta showed a significant positive relationship to proportion of bedrock in shoals in 2005. Like most Cyprinella, C. venusta are crevice spawners (Boschung & Mayden 2004), so an increase in the availability of preferred spawning habitat may account for increase densities of shiners. Density of P. nigrofasciata decreased with an increase in the volume of shoals. Predator avoidance may explain why P. nigrofasciata prefer habitats with lower volumes. The density of cyprinids was negatively related to shoal volume in both 2005 and 2006. Cyprinids may also be avoiding predation risk by occupying shallower shoals. Schlosser (1987b) showed that bass in an experimental stream caused cyprinids to seek refuge in shallow structurally 24 complex habitats to avoid predation. Schlosser (1987b) also noted the implications for crowding suggesting increases in intra- and inter-specific competition for resources. This could be critically important for specialist species that live exclusively in habitats that are preferred by all species during times of extended disturbance. In my study, crowding in shoals could have an impact on shoal specialist populations, who may not be able to survive such biotic constraints. Results from the spatial analysis further support the concept of longitudinal zonation, which is one of the most commonly cited concepts of fish assemblages (Sheldon 1968; Horowitz 1978; Evans & Noble 1979; Schlosser 1982; Minckley 1984; Oberdorff et al. 1993). Both abiotic and biotic variables have been shown to change with stream order (Vannote et al. 1980). Some commonly observed changes with increase in stream order have been documented as environmental heterogeneity (Matthews & Styron 1981; Williams et al. 1996), habitat structure (Gorman & Karr 1978; Schlosser 1982), and biotic interactions (Matthews et al. 1987; Capone and Kushlan 1991). Headwater and downstream reaches contrast in the variability in environmental conditions and fish assemblage structure. Headwater reaches are generally depauperate and comprised of species tolerant of harsh conditions (Rahel & Hubert 1991). Environmental conditions in the lower reaches of streams are comparatively stable and less variable, allowing more species to exist. It is speculated that in lower reaches biotic interactions, such as predation and competition, may be more important in structuring fish assemblages (Matthews & Styron 1981; Schlosser 1987b; Lohr & Fausch 1997). Longitudinal patterns described by researchers are evident in the shoal habitats of my study. Centrarchids were added to assemblages in the lower reaches of both Little Uchee and 25 Halawakee. M. cataractae and M. punctulatus were present in the assemblages of shoals in the lower reaches of Little Uchee. M. cataractae was present in very low numbers in the lower reaches of Halawakee Creek. Typically, M. punctulatus dominated the assemblages of Halawakee Creek shoals. Wacoochee is a smaller stream, so there was no zonation in species compositions; here, cyprinids dominated the shoals throughout the entire length of the stream. Proximity indices were negatively correlated to species richness in 2006, suggesting that as proximity of neighbors increased the number of species present decreases. These results are contrary to the theory of island biogeography (MacArthur and Wilson 1967) which suggests that as the proximity of an island increases so too does the number of species occupying the island. Interestingly, some of the larger shoals in 2006 had low proximities indices and high richness. This suggests that the effects of shoal size may override the effects of proximity in stream systems. Smaller shoals may have a certain carrying capacity of species regardless of proximity, and may experience more instability in assemblage structure than larger shoals. Larger shoals could also have well-established assemblages with biotic variables expressing more control over assemblage structure. Proximity index ranges differed by species. Most species were found in the full range of proximities. Only L. zonistius and M. cataractae were present in shoals with higher ranges of proximity indices. The differences in proximity indices for these fishes suggested that some species might have a requirement for habitat connectivity, while others do not. M. cataractae is one of the largest species in these stream systems and has the highest range and one of the highest averages of proximities indices of all species, 26 suggesting that this species may require a high frequency of large shoal habitat in a reach of stream. Because of their large sizes, migration may be beneficial to M. cataractae. Roff (1988) suggested that migration is correlated to increased size at maturity, and stated that small individuals do not migrate as far as larger individuals. By moving from shoal to shoal throughout the corridor of a reach of stream, M. cataractae may be able to improve gene flow and increase survival. CONCLUSIONS Shoals are unique and rare habitat units in stream ecosystems. These structurally complex habitats provide fishes with several key resources. Shoal and pool assemblages are different from one another, as are assemblages in a particular habitat type between years of contrasting stream flow. In my study shoal volume, substrate, flow, and depth indicated variability in fish assemblages. Size of shoal habitats indicated the number of species expected to be present. The variability in the densities of certain species suggests that these species may be selecting shoals based on their physical characteristics and resources. The spatial and temporal variability in shoals causes fluctuations in the availability and quality of shoals. Although proximities of shoals did not influence assemblage structure, longitudinal arrangement and watershed position did play a role in predicting the occurrence of fishes. The interaction of spatial position and temporal pattern cause changes in the structure of fish assemblages emphasizing the importance of patch connectivity to some species. Conservation of fish communities requires an understanding of populations and habitat characteristics. Understanding temporal and spatial variability in fish assemblages is imperative if fisheries managers want to establish 27 long-term monitoring or detect the effects of anthropogenic disturbances. There are few resource agencies with multi-scaled data sets for managing stream fishes and their habitats. Data collected at landscape scales give managers a broad template for viewing the dynamics of fish communities in stream systems. 28 LITERATURE CITED Allan, J.D. 1995. Stream ecology: structure and function of running waters. Kluwer Academic Publishers. Dordrecht, Netherlands. Allan, J. D. & Flecker, A. S. 1993. Biodiversity conservation in running waters. BioScience 43: 32- 43. Angermeier P.L. & Karr, J.R. 1983. Fish communities along environmental gradients in a system of tropical streams. Environmental Biology of Fishes 9: 117-135. Angermeier P.L. & Schlosser, I.J. 1989. Species-area relationship for stream fishes. Ecology 70: 1450-1462. Bain, M.B. & Stevenson, N.J. 1999. Aquatic habitat assessment: common methods: Bethesda, MD, American Fisheries Society. Baltz, D.M., Vondracek, B., Brown, L.R. & Moyle, P.B. 1991. Seasonal changes in microhabitat selection by rainbow trout in a small stream. Transactions of American Fisheries 120: 166-176. Behnke, R.J. 1992. Native trout of western North America. American Fisheries Society Monograph 6: 270-275 Boschung, H.T. & Mayden, R.L. 2001. Fishes of Alabama. Smithsonian Books. Washington. Capone, T.A., & Kushlan, J.A. 1991. Fish community structure in dry-season stream pools. Ecology. 72: 983-992. Dunham, J. B., Vinyard, G.L. & Rieman, B.E. 1997. Habitat fragmentation and extinction risk of Lahontan cutthroat trout. North American Journal of Fisheries Management 17: 1126?1133. Elliot, J.M. 1976. Energy loss in waste products of brown trout (Salmo trutta L.). Journal of Animal Ecology 45: 561-580. Evans, J.W. & Noble, R.L. 1979. The longitudinal distribution of fishes in an east Texas stream. American Midland Naturalist 101: 333-334. Fagan, W. F. 2002. Fragmentation and extinction risk in dendritic metapopulations. Ecology 83: 3243?3249 29 Fausch, K. D., Torgersen, C.E., Baxter, C.V. & Li, H.W. 2002. Landscapes to riverscapes: bridging the gap between research and conser vation of stream fishes. BioScience 52: 483? 498. Flieshman, E., Ray, C., Sjogren-gulve, P., Boggs, C.L. & Murphy, D.D. 2002. Assessing the roles of patch quality, area, and isolation in predicting metapopulation dynamics. Conservation Biology 16: 706-716 Fowler, J.F. & Taber, C.A. 1985. Food habits and feeding periodicity in two sympatric stonerollers (Cyprinidae). American Midland Naturalist 113: 217-224. Gelwick, F.P. 1990. Longitudinal and temporal comparisons of riffle and pool fish assemblages in a northeastern Oklahoma Ozark stream. Copeia 4: 1072-1082. Gido, K.B., Propst, D.L. & Molles, M.C. 1997. Spatial and temporal variation of fish assemblages in secondary channels of the San Juan River, New Mexico and Utah. Environmental Biology of Fishes 49: 417-434. Gordon, N.D., McMahon T.A., Finlayson, B.L., Gippel, C.J., Nathan, R.J. 2005. Stream hydrology: an introduction for ecologists. John Wiley and Sons Ltd. West Sussex, England. Gorman, O.T. & Karr, J.R. 1978. Habitat structure and stream fish communities. Ecology 59: 507-515. Grossman, G.D., Moyle, P.B. & Whitaker, J.O., Jr. 1982. Stochasticity in structural and functional characteristics of an Indiana stream fish assemblage: a test of community theory. American Naturalist 120: 423-454. Grossman, G.D., Hill, J. & Petty, J.T. 1995. Observations on habitat structure, population regulation, and habitat use with respect to evolutionarily significant units: a landscape perspective for lotic systems. American Fisheries Society Symposium 17: 381-391. Grossman, G.D., Ratajczak, R.E., Jr., Crawford, M. and Freeman, M.C. 1998. Assemblage organization in stream fishes: effects of environmental variation and interspecific Interactions. Ecological Monographs 68: 395-420. Gustafson, E.J. and Parker, G.R. 1992. Relationship between landcover proportion and indices of landscape spatial pattern. Landscape Ecology 7: 101-110. Hanski, I. & Simberloff, D. 1997. The metapopulation approach, its history, conceptual domain, and application to conservation. Ecology, Genetics and Evolution 48:5?26. Harvey, B.C. 1991. Interactions among stream fishes: predator-induced habitat shifts and 30 larval survival. Oecologia. 87: 336-342. Harvey, B.C. & Stewart, A.J. 1991. Fish size and habitat depth relationships in headwater streams. Oecologia 87: 336?342. Helfman, G. S., Collette, B. B. & Facey, D.E. 1997. The diversity of fishes. Blackwell Science, Malden, Massachusetts. Hill, J.K., Thomas, C. & Lewis, O. 1996 Effects of habitat patch size and isolation on dispersal by Hesperia comma butterflies: implications for metapopulation structure. Journal of Animal Ecology 65: 725?735. Hocutt, C.H. & Stauffer, J.R. 1975. Influence of gradient on the distribution of fishes in Conowingo Creek, Maryland and Pennsylvania. Chesapeake Science 16: 143-147. Horowitz, R.J. 1978.Temporal variability patterns and distributional patterns of stream fishes. Ecological Monographs 84: 307-321. Hubbs, C. 1990. Declining fishes of the Chihuahuan Desert. In: Papers from the third Symposium on Resources of the Chihuanhuan Desert Basin, United States and Mexico. (Eds A.M. Powell, R.R. Hollander, J.C. Barlow, W.B. McGillivray & D.J. Schmidly) Chihuahuan Desert Research Institute. Alpine, TX. pp. 89-96. Hughes, N.F. 1998. A model of habitat selection by drift-feeding salmonids at different scales. Ecology 79: 281-294. Hynes, H.B.H. 1970. The ecology of running waters. University of Toronto Press, Toronto. Kelly, G. A., Griffith, J.S. & Jones, R.D. 1980. Changes in distribution of trout in Great Smokey Mountain National Park. Wildlife Service Technical Paper 102. 1900-1970 Kindvall, O. & Ahlen, I. 1992. Geometrical factors and metapopulation dynamics of the bush cricket Metrioptera bicolor. Conservation Biology 6: 520?529 Kramer, D.L., Rangeley, R.W. & Chapman, L.J. 1991. Habitat selection: patterns of spatial distribution from behavioral decisions. Behavioral Ecology of Fishes. Oxford University Press, Oxford. pp. 37-80 Krebs, C.J. 1999. Ecological Methodology. Menlo Park, California: Addison-Welsey Educational Publishers, Inc. Lancaster, J. 2000. Geometric scaling of microhabitat patches and their efficiency as refugia during disturbance. Journal of Animal Ecology 69: 442-457 Lehman, E.L. & D?Abrera, H.J.M. 1998. Nonparametrics: statistical methods based on 31 ranks, Englewood Cliffs, NJ: Prentice-Hall, 292, 300 and 323. Lohr, S.C. & Fausch, K.D. 1997. Multiscale analysis of natural variability in stream fish assemblages of a western Great Plains watershed. Copeia 706-724. Lyons, J. 1996. Patterns in the species composition of fish assemblages among Wisconsin streams. Environmental Biology of Fishes. 45: 329-341. Macarthur, R. H. & Wilson, E.O. 1967. The theory of island biogeography. Princeton University Press, Princeton. Magnuson, J. J., Crowder, L.B. & Medvick, P.A. 1979. Temperature as an ecological resource. American Zoologist 19: 331-343 Magoulick, D.D. 2000. Spatial and temporal variation in fish assemblages of drying stream pools: The role of abiotic and biotic factors. Aquatic Ecology 34: 29-41. Marcinek, P.A., Freeman, M.C., & Freeman, B.J. 2003. Distribution and abundance of three endemic fishes in shoals of the Upper Flint river system. Proceedings of the 2003 Georgia Water Resources Conference. Matthews, W.J. 1990. Spatial and temporal variation in fishes of riffle habitats: A comparison of analytical approaches for the Roanoke River. American Midland Naturalist 124: 31-45. Matthews, W.J. & Styron, J.T., Jr. 1981. Tolerance of headwaters vs. mainstream fishes for abrupt physiochemical changes. American Midland Naturalist 105: 149-158. Minckley, W.L. 1984. CuatroCie ?negasfishes: research review of a local test of diversity versus habitat size. Journal of Arizona-Nevada Academy of Science. 19: 13?21 Miller, R. R., Williams, J.D. & Williams, J.E. 1989. Extinctions of North American fishes during the past century. Fisheries 14: 22-38. Mongomery, D. 1999. Process domains and the river continuum. Journal of the American Water Resources Association 35: 397?410. Naiman, R.J., Decamps, H. & McClain, M.E. 2005. Riparia: ecology, conservation, and management of streamside communities. Elsevier, Amsterdam. Oberdorf, T., Guilbert, E. & Lucchetta, J.C. 1993. Patterns of fish species richness in the Seine River basin, France. Hydrobiologia 259: 157-167. Ostrand, K.G. & Wilde, G.R. 2002. Seasonal and spatial variation in a prairie stream-fish 32 assemblage. Ecology of Freshwater Fish 11: 137-149. Paller, M.C. 1994. Relationship between fish assemblage structure and stream order in South Carolina coastal plain streams. Transactions of American Fisheries 123: 150-161. Palmer, M.A, Swan, C.M., Nelson, K., Silver, P. & Alvestad, R. 2000. Streambed landscapes: evidence that stream invertebrates respond to the type and spatial arrangement of patches. Landscape Ecology 15: 563-576 Peterson, J.T. & Rabeni, C.F. 1996. Natural thermal refugia for temperate warmwater stream fishes. North American Journal of Fisheries Management 16: 738-746. Peterson, J.T. & Rabeni, C.F. 2001. The relation of fish assemblages to channel units in an Ozark stream. Transactions of American Fisheries Society 130: 911-2001. Phillips, B.W. & Johnston, C.E. 2004. Fish assemblage recovery and persistence. Ecology of Freshwater Fish 13: 145-153 Power, M.E. 1987. Predator avoidance by grazing stream fish in temperate and tropical streams: importance of stream depth and prey size. In: Kerfoot W.C., Sih A. (eds) Predation: direct and indirect impacts in aquatic communities. University Press of New England. Hanover, NH. pp. 333-351. Power, M.E., & Matthews, W.J. 1983. Algae-grazing minnows (Campostoma anomalum), piscivorous bass (Micropterus sp.) and the distribution of attached algae in a small prairie-margin stream. Oceologia 60: 328-332. Power, M.E., Matthews, W.J. & Stewart, A.J. 1985. Grazing minnows, piscivorous bass, and stream algae: dynamics of a strong interaction. Ecology 66: 1448-1456. Pringle, C.M. 2003. What is hydrological connectivity and why is it important? Hydrological Processes 17: 2685-2689. Pringle C.M, Naiman, R.J., Bretschko, G., Karr, J.R., Oswood, M.W., Webster, J.R., Welcomme, R.R. & Winterbourne, M.J. 1988. Patch dynamics in lotic systems: The stream as a mosaic. Journal of the North American Benthological Society 7: 503?524. Poizat, G. & Pont, D. 1996. Multi-scale approach to species-habitat relationships: juvenile fish in a large river section. Freshwater Biology 36: 611?622. Rahel, F.J. & Hubert, W.A. 1991. Fish assemblages and habitat gradients in a Rocky Mountain ? Great Plains stream: biotic zonation and additive patterns of community change. Transaction of the American Fisheries Society 120: 319?332. Rahel, F.J., Keleher, C.J. & Anderson, J.L. 1996. Potential habitat loss and population 33 fragmentation for cold water fish in the North Platte River drainage of the Rocky Mountains: response to climate warming. Limnology and Oceanography 41: 1116- 1123. Reid, W. V. 1997. Strategies for conserving biodiversity. Environment 39: 16 43. Richter, B. D., Braun, D.P., Mendelson, M.A. & Master, L. L. 1997. Threats to imperiled freshwater fauna. Conservation Biology 11: 1081-1093. Riemand, B.E. & McIntyre, J.D. 1995. Occurrence of bull trout in naturally fragmented habitat patches of varied size. Transactions of the American Fisheries Society 124: 285?296. Robinson, H. W. & Buchanan, T.M. 1988. The fishes of Arkansas. University of Arkansas Press, Fayetteville. Roff, D.A. 1988. The evolution of migration and some life history parameters in marine fishes. Evolutionary Biology of Fishes 22: 133-146. Roth, N. E., Allan, J.D. & Erickson, D.L. 1996. Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology 11: 141-156. Schlosser, I.J. 1982. Fish community structure and function along two habitat gradients in a headwater stream. Ecological Monographs 52: 395-414. Schlosser, I.J. 1987a. A conceptual framework for fish communities in small warmwater streams, in community and evolutionary ecology of North American stream Fishes (eds. W.J. Matthews and D.C. Heins). University of Oklahoma Press, Norman. 17-24. Schlosser, I.J. 1987b. The role of predation in age and size related habitat use by stream fishes. Ecology 68: 651-659. Schlosser, I.J. 1990. Environmental variation, life history attributes, and community structure in stream fishes: implications for environmental management and assessment. Environmental Management 14: 621?628. Schlosser, I. J. 1991. Stream fish ecology: a landscape perspective. BioScience 41: 704- 712. Schlosser, I.J. 1995a. Critical landscape attributes that influence fish population dynamics in headwater streams. Hydrobiologia. 303:71?81. Schlosser, I.J. 1995b. Dispersal, boundary processes, and trophic-level interactions in 34 streams adjacent to beaver ponds. Ecology 76:908?925. Schlosser, I.J. & Angermeier, P.L. 1995. Spatial variation in demographic processes in lotic fishes: Conceptual models, empirical evidence, and implications for conservation. American Fisheries Society Symposium. 17: 360?370. Schlosser, I.J & Kallemeyn, L.W. 2000. Spatial variation in fish assemblages across a beaver-influenced successional landscape. Ecology 81: 1371?1382. Schmutz, S. & Jungwirth, M. 1999. Fish as indicators of large river connectivity: the Danube and its tributaries. Hydrobiologia 3: 329?348. Sheldon, A.S. 1968. Species diversity and longitudinal succession in stream fishes. Ecology 49: 193-198. Shuter, B.J., Maclean, J.A., Fry, F.E.J. & Regier, H.A. 1980. Stochastic simulation of temperature effects on first-year survival of smallmouth bass. Transactions of the American Fisheries 109: 1-34. Simpson, E. H. 1949. Measurement of diversity. Nature 163: 688. Sjogren-gulve, P. & Ray, C. 1996. Using logistic regression to model metapopulation dynamics: large-scale forestry extirpates the pool frog. Metapopulations and Wildlife Conservation. Island press, Washington, D.C. Smith, T. A. & Kraft, C.E. 2005. Stream fish assemblages in relation to landscape position and local habitat variables. Transactions of the American Fisheries Society 134: 430-440. Smith, M. L. & Miller, R.R. 1986. The evolution of the Rio Grande Basin as inferred from its fish faunas. The Zoogeography of North American freshwater fishes. John Wiley and Sons, New York. pp. 458-485 Stanford, J.A. & Ward, J.V. 1993. An ecosystem perspective of alluvial rivers: connectivity and the hyporheic corridor. Journal of the North American Benthological Society 12 : 48?60. Taylor, C.M., Winston, M.R. & Matthews, W.J. 1993. Fish species-environment and abundance relationships in a Great Plains river system. Ecography 16: 16-23. Taylor, C.M. 1996. Abundance and distribution within a guild of benthic stream fishes: local processes and regional patterns. Freshwater Biology 36: 385-396. Taylor, C.M. 1997. Fish species richness and incidence patterns in isolated and connected stream pools: effects of pool volume and spatial position. Oecologia 110: 560-566 35 Tripe, J.A. & Guy, C.S. 1999. Spatial and temporal variation in habitat and fish community characteristics in a Kansas Flint Hills stream. Ecology of Freshwater Fish 8: 216-226. Townsend, C.R. 1989. The patch dynamics concept of stream community ecology. Journal of the North American Benthological Society 8: 36?50. Turner, M.G. 1989. Landscape ecology: the effect of pattern on process. Annual Review of Ecology and Systematics 20: 171?197. Vannote, R.L., Minshall, G.W., Cummins, K.W., Sedell, J.R. & Cushing, C.E. 1980.The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences 37: 130- 137. Walters, D.M., Leigh, D.S., Freeman, M.C. & Pringle, C.M. 2003. Geomorphology and fish assemblages in a Piedmont River basin, U.S.A. Freshwater Biology 48: 1950- 1970. Ward, J.V. 1998. Riverine landscapes: biodiversity patterns, disturbance regimes, and aquatic conservation. Biological Conservation 83: 269?278. Ward, J.V. & Stanford, J.A. 1983. The serial discontinuity concept of lotic systems. Dynamics of lotic ecosystems. Ann Arbor Science. Ann arbor, Michigan Ward, J.V., Tockner, K. & Schiemer, F. 1999. Biodiversity of floodplain river ecosystems: ecotones and connectivity. Regulated Rivers: Research & Management 15: 125?139. Wentworth, C. K. 1922. A scale of grade and class terms for clastic sediments. Journal of Geology 30: 377?-392. Werner, E.E. & Gilliam, J.F. 1984. The ontogenetic niche and species interactions in size-structured populations. Annual Review Ecology and Systematics15: 393-425. Wheeler, A. P. & Allen, M.S. 2003. Habitat and diet partitioning between shoal bass and largemouth bass in the Chipola River, Florida. Transactions of the American Fisheries Society 132: 438-449. Wiens, J.A. 2002. Riverine landscapes: taking landscape ecology into the water. Freshwater Biology 47: 501?515. Wilson. E.O. 1992. The diversity of life. W.W. Norton & Company. New York, New York. pp. 222-228. Wootton, R.J. 1998. Ecology of teleost fishes. Kluwer Academic Press. Dordrecht, 36 Netherlands. pp. 195-215. Zwick, P. 1992. Stream habitat fragmentation ? a threat to biodiversity. Biodiversity and Conservation 1: 80-90 37 APPENDIX. COLLECTION LOCALITIES FOR ALL SITES SMAPLED FROM RECENT SURVEY OF LITTLE UCHEE, WACOOCHEE, AND HALAWAKEE CREEKS. COLECTION RECORDS INCLUDE DATE, LOCALITY, GPS OF COLLECTION SITE. Site # Date Stream ID Long Lat Locality County 1 8/4/05 & 8/1/06 LU -85.2786 32.5494 2 mi. NW of Meadows Mill, CR 144 Lee 2 5/22/06 LU -85.2543 32.5283 Meadows Mill Lee 3 6/5/05 LU -85.2446 32.5000 2 river miles down from CR 175 Lee 4 5/23/06 LU -85.2089 32.5383 5 river miles down from CR 175 Lee 5 7/10/05 &5/23/06 LU -85.2123 32.5386 5.5 river miles down from CR 175 Lee 6 6/30/05 LU -85.2032 32.5374 3.5 river miles N of CR 240 Lee 7 6/30/05 LU -85.1938 32.5287 2 river miles N of CR 240 Lee 8 7/29/05 &7/23/06 LU -85.1800 32.5069 Moffitts Mill at CR 240 Lee 9 6/5/30 LU -85.1794 32.5061 300m down from CR 240 Lee 10 8/11/05 &7/23/06 LU -85.1783 32.5017 1.5 river mi down from CR 240 Lee 11 7/7/06 WA -85.1646 32.6181 1.98 river mile N of CR 279 Lee 12 7/7/06 WA -85.1639 32.6182 1.9 river mile N of CR 279 Lee 13 7/7/06 WA -85.1623 32.6200 1.56 river mile N of CR 279 Lee 14 7/7/06 WA -85.1618 32.6196 1.55 river mile N of CR 279 Lee 15 7/7/06 WA -85.1598 32.6183 1.5 river mile N of CR 279 Lee 16 7/7/06 WA -85.1590 32.6182 1.2 river mile N of CR 279 Lee 17 7/7/06 WA -85.1560 32.6180 1 river mile N of CR 279 Lee 18 8/4/5 &8/2/06 WA -85.1506 32.6162 3 miles N of Bleeker, CR 279 Lee 19 6/9/05 &8/2/06 WA -85.1152 32.6281 1.5 river miles down from CR 379 Lee 20 6/9/05 WA -85.1097 32.6278 2.5 river miles down from CR 379 Lee 21 6/9/05 WA -85.1078 32.6289 3 river miles down from CR 379 Lee 22 6/18/05 HA -85.2947 32.7156 2.3 mi NW of Bean Mill, CR 177 Lee 23 7/27/06 HA -85.2720 32.7067 1.26 river mile N of Hwy 29 Lee 24 7/27/06 HA -85.2718 32.7063 1.25 river mile N of Hwy 29 Lee 25 7/27/06 HA -85.2715 32.7056 1.2 river mile N of Hwy 29 Lee 26 7/27/06 HA -85.2709 32.7050 1 river mile N of Hwy 29 Lee 27 6/18/05 &7/27/06 HA -85.2669 32.6967 Bean Mil, Hwy 29 Lee 28 6/17/05 HA -85.2427 32.6916 2.5 river miles down from CR 390 Lee 29 6/17/05 HA -85.2361 32.6869 4 river miles down from CR 390 Lee 30 6/17/05 HA -85.2297 32.6922 4.5 river miles down from CR 390 Lee 31 6/13/06 HA -85.2064 32.6883 500m N of CR 259 Lee 32 7/25/05 &7/18/06 HA -85.2044 32.6864 Mouth of Halawakee Cr., CR 259 Lee 38 Table 1. Names and descriptions of physical variables used in principal component analyses and regression analyses Environmental Variable Description Temp Mean water temperature (?C) within shoal Depth Mean shoal depth (cm) CV Depth Coefficient of variation of depth Thalweg Thalweg depth of shoal (m) Velocity Mean current velocity (m/s) CV Velocity Coefficient of variation of velocity Width Mean shoal width (m) Length Shoal length (m) Area Shoal area (m 2 ) Volume Shoal volume (m 3 ) Bedrock Proportion bedrock in shoal Boulder Proportion boulder in shoal Cobble Proportion cobble in shoal Gravel Proportion of gravel in shoal Sand Proportion sand in shoal SubDiv Simpson?s diversity index for substrate 39 Table 2. Species list and type of habitat in which each species was collected. (P = pool, S = shoal) Species Habitat type % occurrence in shoal % occurrence in pool Lepisosteus oculatus P 0 100 Amia calva P 100 Anguilla rostrata P 0 100 Dorosoma cepedianum P 100 Campostoma pauciradii S 100 0 Cyprinella venusta P,S 70 29 Ericymba buccata P,S 77 22 Hybopsis sp. winchelli P,S 86 13 Lythurus atrapiculus P,S 33 66 Luxilus zonistius S 100 0 Nocomis leptocephalus P 66 33 Notropis ammophilus P 0 100 Notropis baileyi P,S 54 45 Notropis hypsilepis S 100 0 Notropis longirosris P 0 100 Notropis texanus P,S 57 42 Cyprinus carpio P 0 100 Opsopoeodus emiliae P 100 Semotilus thoreauianus P,S 85 14 Hypentelium etowanum P,S 83 16 Minytrema melanops P,S 66 33 Moxostoma lachneri P,S 77 22 Ameiurus brunneus P,S 94 5 Noturus leptacanthus P,S 65 34 Gambusia affinis P 0 100 Fundulus olivaceus P 100 Labidesthes sicculus P 0 100 Lepomis auritus P,S 75 25 Lepomis cyanellus P,S 80 20 Lepomis gulosus P,S 33 66 Lepomis macrochirus P,S 66 33 Lepomis megalotis P,S 33 Lepomis microlophus P 0 100 Lepomis miniatus P 100 Micropterus cataractae S 100 0 Micropterus punctulatus P,S 83 16 Micropterus salmoides P,S 75 25 Pomoxis nigromaculatus P,S 33 67 Perca flavescens P 0 100 Percina nigrofasciata S 100 0 Etheostoma swaini S 100 40 Table 3. Jaccard similarity values and richness for Little Uchee Creek pools and shoals sampled in 2005 (P = pool, S= shoal). Site # 1S 1P 3S 3P 5S 5P 6S 6P Species L. oculatus A. calva A. rostrata D. cepedianum C. pauciradii 9 14 1 3 C. venusta 5 1 24 7 45 15 26 C. carpio E. buccata 1 2 H. sp. winchelli 1 L. zonistius L. atrapiculus 6 N. leptocephalus N. baileyi N. hypsilepis N. longirosris N. texanus 3 6 5 6 3 1 O. emiliae S. thoreauianus H. etowanum 3 3 1 M. melanops M. lachneri 1 1 1 A. brunneus 1 3 1 2 N. leptacanthus L. sicculus F. olivaceus G. affinis L. auritus 2 2 3 2 3 L. cyanellus 3 L. gulosus L. macrochirus 6 5 1 1 1 L. megalotis 1 L. microlophus M. cataractae 1 1 M. punctulatus 1 M. salmoides P. nigromaculatus P nigrofasciata 20 9 6 4 Richness 9 4 9 3 6 4 9 6 Jaccard Index 0.40 0.20 0.22 0.23 41 Table 3. (continued) Site # 7S 7P 8S 8P 9S 9P 10S 10P Species L. oculatus 1 A. calva 1 A. rostrata D. cepedianum C. pauciradii 1 C. venusta 8 25 6 6 18 2 2 32 C. carpio E. buccata H. sp. winchelli 6 L. zonistius L. atrapiculus 1 N. leptocephalus N. baileyi N. hypsilepis N. longirosris N. texanus 2 3 3 2 3 O. emiliae S. thoreauianus 1 H. etowanum 6 1 1 M. melanops M. lachneri 1 1 A. brunneus 2 1 N. leptacanthus L. sicculus F. olivaceus G. affinis 5 L. auritus 2 3 5 2 2 3 1 L. cyanellus 7 L. gulosus 1 L. macrochirus 1 L. megalotis 1 1 L. microlophus M. cataractae 1 2 1 2 M. punctulatus 2 M. salmoides 1 P. nigromaculatus 1 P nigrofasciata 5 11 4 3 Richness 6 4 6 2 11 7 4 10 Jaccard Index 0.25 0.14 0.20 0.16 42 Table 4. Jaccard similarity values and richness for Wacoochee Creek pools and shoals sampled in 2005 (P = pool, S= shoal). Site # 18S 18P 19S 19P 20S 20P 21S 21P Species L. oculatus 1 A. calva A. rostrata D. cepedianum C. pauciradii 1 1 3 4 C. venusta 25 1 15 3 1 2 C. carpio E. buccata 1 3 1 H. sp. winchelli 1 3 4 3 3 L. zonistius L. atrapiculus 8 N. leptocephalus N. baileyi N. hypsilepis 3 N. longirosris N. texanus 2 2 1 4 O. emiliae 2 S. thoreauianus H. etowanum M. melanops M. lachneri 1 1 3 3 2 A. brunneus 1 5 1 5 5 N. leptacanthus L. sicculus 1 1 1 2 F. olivaceus 2 G. affinis L. auritus 1 3 4 1 10 2 2 1 L. cyanellus 2 2 2 1 L. gulosus L. macrochirus 1 1 4 3 L. megalotis 1 L. microlophus M. cataractae M. punctulatus 1 M. salmoides 1 1 P. nigromaculatus P nigrofasciata 13 1 12 Richness 9 5 11 9 11 5 7 6 Jaccard Index 0.40 0.53 0.23 0.18 43 Table 5. Jaccard similarity values and richness for Halawakee Creek pools and shoals sampled in 2005 Site # 22S 22P 27S 27P 28S 28P 29S 29P 30S 30P 32S 32P Species L. oculatus 1 A. calva A. rostrata D. cepedianum 1 C. pauciradii 11 4 5 2 1 C. venusta 5 5 2 2 10 6 1 4 C. carpio 2 E. buccata H. sp. winchelli 3 1 L. zonistius 1 L. atrapiculus N. leptocephalus 1 1 N. baileyi 1 4 1 4 1 N. hypsilepis 1 N. longirosris N. texanus 2 1 O. emiliae S. thoreauianus H. etowanum 1 1 3 1 M. melanops 1 M. lachneri 1 5 1 1 3 1 A. brunneus 1 1 N. leptacanthus 2 1 4 L. sicculus 1 F. olivaceus 2 2 2 G. affinis L. auritus 2 15 1 8 1 4 1 2 L. cyanellus L. gulosus 1 L. macrochirus 4 5 6 5 1 2 4 1 L. megalotis 6 1 1 L. microlophus 1 M. cataractae M. punctulatus 3 2 1 M. salmoides P. nigromaculatus 1 1 P nigrofasciata 2 6 8 2 2 1 Richness 6 3 11 8 10 4 9 4 10 5 8 3 Jaccard Index 0.00 0.26 0.27 0.08 0.25 0.10 44 Table 6. Paired t-test (n = 8) results for temporal variability in environmental variables in 2005 and 2006. Values marked in bold are significant at alpha = .05. Mean (+ SE) Mean (+ SE) 95% Confidence 2005 2006 Lower Upper t df p-value Depth (m) 0.52 (0.03) 0.23 (0.02) 0.23 0.34 12.07 7 p < .001 Thalweg depth (m) 1.15 (0.18) 0.58 (0.08) 0.19 0.94 3.56 7 p < .01 Volume (m 3 ) 2007.28 (566.29) 741.91 (260.04) 361.09 2169.65 3.31 7 p < .01 Current Velocity (m/s) .22 (.02) .12 (.01) 0.05 0.14 5.30 7 p < .001 Temperature (C?) 24.43 (.99) 26.00 (.25) -4.21 1.08 -1.40 7 p = .206 45 Table 7. Paired t-test (n = 8) results for temporal variability in biotic variables in 2005 and 2006. Values marked in bold are significant at alpha = .05. Mean (+ SE) Mean (+ SE) 95% Confidence t df p-value 2005 2006 Lower Upper Species Richness 6.75 (.52) 9.62 (.56) -0.22 -0.09 -5.49 7 p < .001 # of juveniles /100m 2 0.61 (.22) 1.69 (.25) -1.04 -0.29 -4.21 7 p < .01 # of adults /100m 2 1.36 (.64) 2.88 (1.21) -0.74 -0.13 -3.41 7 p < .01 # of all fishes /100m 2 1.97 (.83) 4.57 (1.37) -0.82 -0.23 -4.22 7 p < .01 46 Table 8. Jaccard similarity index and richness of replicated shoals in Little Uchee Creek in 2005 and 2005. Shoal # 1 1/06' 5 5/06' 8 8/06' 10 10/06' Species List Anguilla rostrata 1 Campostoma pauciradii 9 5 1 Cyprinella venusta 5 1 17 6 9 2 4 Ericymba buccata 1 1 Hybopsis sp. winchelli 1 7 1 Notropis texanus 1 5 2 Semotilus thoreauianus 3 Hypentelium etowanum 3 6 1 1 Moxostoma lachneri 1 1 Ameiurus brunneus 1 4 1 9 4 Lepomis auritus 2 5 2 3 5 10 3 4 Lepomis cyanellus 3 Lepomis gulosus 1 Lepomis macrochirus 6 1 1 2 Lepomis megalotis 1 2 2 Micropterus cataractae 1 1 2 3 2 1 Micropterus punctulatus 2 Percina nigrofasciata 20 30 6 22 11 22 3 15 Richness 9 12 6 7 6 10 4 9 Jaccard similarity index 0.50 0.44 0.60 0.30 47 Table 9. Jaccard similarity index and richness of replicated shoals in Wacoochee Creek in 2005 and 2006. Shoal # 18 18/06' 19 19/06' Species List Campostoma pauciradii 21 6 Cyprinella venusta 25 25 1 3 Ericymba buccata 1 Hybopsis sp. winchelli 23 Lythurus atrapiculus 8 Notropis texanus 2 1 Moxostoma lachneri 1 2 3 Ameiurus brunneus 1 3 5 8 Lepomis auritus 1 2 4 2 Lepomis cyanellus 2 1 2 Lepomis macrochirus 1 1 Micropterus punctulatus 1 1 Micropterus salmoides 1 Percina nigrofasciata 13 43 9 Richness 8 9 11 7 Jaccard similarity index 0.50 0.38 48 Table 10. Jaccard similarity index and richness of replicated shoals in Halawakee in 2005 and 2006. Site# 27 27/06' 32 32S/06' Species List Lepisosteus oculatus 1 Dorosoma cepedianum 1 Campostoma pauciradii 7 2 Cyprinella venusta 3 6 Hybopsis sp. winchelli 3 Notropis baileyi 1 Cyprinus carpio 2 1 Hypentelium etowanum 1 1 Minytrema melanops 2 Moxostoma lachneri 5 2 3 1 Ameiurus brunneus 7 4 11 Noturus leptacanthus 1 Lepomis auritus 15 7 3 6 Lepomis cyanellus 7 Lepomis macrochirus 5 4 2 8 Lepomis microlophus 1 Lepomis miniatus 4 Micropterus punctulatus 2 12 Micropterus salmoides 2 Pomoxis nigromaculatus 1 Perca flavescens 1 Percina nigrofasciata 2 23 29 Richness 11 10 8 11 Jaccard similarity index 0.23 0.35 49 Table 11. Eigenvalues, percent, and cumulative variance for principal components for 2005 Initial Eigenvalues PC Total % of Variance Cumulative % 1 5.29 31.12 31.12 2 2.70 15.91 47.03 3 2.22 13.07 60.11 4 1.81 10.64 70.75 5 1.66 9.77 80.52 6 1.05 6.21 86.74 7 .83 4.88 91.62 8 .51 3.01 94.64 9 .41 2.45 97.10 10 .23 1.40 98.50 11 .12 .73 99.24 12 .43 99.67 13 .23 99.90 14 99.99 15 99.99 16 100.00 17 100.00 50 Table 12. Eigenvalues, percent, and cumulative variance for principal components for 2006 Initial Eigenvalues PC Total % of Variance Cumulative % 1 5.390 31.70 31.70 2 3.444 20.25 51.96 3 2.189 12.87 64.83 4 1.687 9.92 74.76 5 1.170 6.88 81.64 6 .838 4.93 86.57 7 .806 4.73 91.31 8 .604 3.55 94.86 9 .315 1.85 96.72 10 .203 1.19 97.91 11 .145 .85 98.76 12 .120 .70 99.47 13 .35 99.82 14 .10 99.92 15 99.98 16 100.00 17 100.00 51 Table 13. Component loadings of environmental variables on principal components for 2005 and 2006. Variables in bold were used in regression analyses. Environmental 2005 2006 Variables PC1 PC2 PC3 PC4 PC1 PC2 PC3 PC4 volume 0.92 -0.12 0.15 0.21 0.97 0.21 depth 0.88 0.51 0.57 -0.12 0.21 area 0.84 -0.18 0.23 0.32 0.97 0.16 thalweg depth 0.81 0.25 -0.31 0.44 0.59 0.51 0.13 width 0.72 -0.35 -0.42 0.69 0.46 -0.33 -0.11 length 0.69 0.43 0.28 0.87 -0.16 0.31 velocity 0.68 0.36 0.38 -0.32 0.11 0.35 -0.35 -0.72 bedrock -0.95 0.15 -0.16 0.13 0.95 0.10 cobble -0.10 0.78 -0.27 -0.74 -0.12 CV velocity -0.35 0.88 0.23 0.91 CV width 0.11 0.84 -0.19 0.58 0.36 boulder 0.13 -0.15 0.91 0.31 -0.75 0.38 Simpson div. 0.18 0.52 0.13 0.76 -0.20 -0.90 0.13 0.17 Sand 0.24 -0.32 -0.33 -0.22 CV depth -0.17 0.44 -0.12 0.15 0.93 gravel -0.12 -0.15 -0.19 -0.28 temperature -0.38 0.22 0.12 0.30 -0.52 -0.26 0.30 52 Table 14. ANOVA of PC variables selected from the principal component analysis for Little Uchee, Wacoochee, and Halawakee Creek shoals. Values marked in boldface are significant at the alpha = .05 level. 2005 Sum of Squares df Mean Square F p Volume (PC1) Among Groups 0.74 2 0.37 1.094 0.36 Within Groups 5.09 15 0.33 Total 5.83 17 Bedrock (PC2) Among Groups 0.05 2 0.02 1.572 0.24 Within Groups 0.27 15 0.01 Total 0.33 17 CV Velocity (PC3) Among Groups 0.03 2 0.01 0.999 0.39 Within Groups 0.25 15 0.01 Total 0.28 17 Boulder (PC4) Among Groups 0.03 2 0.01 3.294 0.07 Within Groups 0.06 15 0.01 Total 0.09 17 2006 Volume (PC1) Among Groups 1.97 2 0.98 4.604 0.02 Within Groups 4.06 19 0.21 Total 6.03 21 Bedrock (PC2) Among Groups 0.05 2 0.02 0.964 0.40 Within Groups 0.49 19 0.02 Total 0.54 21 CV Depth (PC3) Among Groups 0.02 2 0.01 0.517 0.60 Within Groups 0.40 19 0.02 Total 0.42 21 CV Velocity (PC4) Among Groups 0.23 2 0.11 1.354 0.28 Within Groups 1.63 19 0.08 Total 1.87 21 53 Table 15.Bonferroni post-hoc analysis of selected principal components in 2006 Mean Difference (A-B) Std. Error p Dependent Variable (A) STREAM (B) STREAM Volume (PC1) Little Uchee Wacoochee .529 .21 .05 Halawakee .499 .21 .07 Wacoochee Little Uchee -.529 .21 .05 Halawakee -.030 .21 1.00 Halawakee Little Uchee -.499 .21 .07 Wacoochee .030 .21 1.00 Bedrock (PC2) Little Uchee Wacoochee .101 .05 .25 Halawakee .082 .05 .46 Wacoochee Little Uchee -.101 .05 .25 Halawakee -.018 .05 1.00 Halawakee Little Uchee -.082 .05 .46 Wacoochee .018 .05 1.00 CV Depth (PC3) Little Uchee Wacoochee .018 .07 1.00 Halawakee -.027 .07 1.00 Wacoochee Little Uchee -.018 .07 1.00 Halawakee -.045 .07 1.00 Halawakee Little Uchee .027 .07 1.00 Wacoochee .045 .07 1.00 CV Velocity (PC4) Little Uchee Wacoochee .125 .09 .54 Halawakee .031 .09 1.00 Wacoochee Little Uchee -.125 .09 .54 Halawakee -.093 .09 .97 Halawakee Little Uchee -.031 .09 1.00 Wacoochee .093 .09 .97 54 Table 16. ANOVA of 2006 Environmental variables for shoals in Little Uchee, Wacoochee, and Halawakee creeks Sum of Squares df Mean Square F p TEMP Among Groups .102 2 .051 .943 .407 Within Groups 1.023 19 .054 Total 1.124 21 DEPTH Among Groups .038 2 .019 1.168 .332 Within Groups .309 19 .016 Total .348 21 CVDEPTH Among Groups .022 2 .011 .517 .604 Within Groups .401 19 .021 Total .423 21 THALWEG Among Groups .083 2 .042 1.687 .212 Within Groups .470 19 .025 Total .554 21 VELOCITY Among Groups .010 2 .005 .230 .796 Within Groups .400 19 .021 Total .410 21 CVVELOCI Among Groups .233 2 .117 1.354 .282 Within Groups 1.637 19 .086 Total 1.870 21 WIDTH Among Groups .163 2 .082 2.037 .158 Within Groups .762 19 .040 Total .925 21 CVWI1TH Among Groups .014 2 .007 .227 .799 Within Groups .590 19 .031 Total .604 21 LENGTH Among Groups .730 2 .365 3.656 .045 Within Groups 1.897 19 .100 Total 2.627 21 AREA Among Groups 1.815 2 .907 4.978 .018 Within Groups 3.463 19 .182 Total 5.278 21 VOLUME Among Groups 1.970 2 .985 4.604 .023 Within Groups 4.065 19 .214 Total 6.035 21 BEDROCK Among Groups .050 2 .025 .964 .399 Within Groups .498 19 .026 Total .548 21 BOULDER Among Groups .013 2 .007 .816 .457 Within Groups .155 19 .008 Total .168 21 COBBLE Among Groups .043 2 .022 2.314 .126 Within Groups .177 19 .009 Total .220 21 GRAVEL Among Groups .004 2 .002 .482 .625 Within Groups .087 19 .005 Total .091 21 SAND Among Groups .010 2 .005 .641 .538 Within Groups .155 19 .008 Total .166 21 SUBDIVER Among Groups .061 2 .030 .459 .639 Within Groups 1.256 19 .066 Total 1.317 21 55 Table 17. ANOVA of 2005 Environmental variables for shoals in Little Uchee, Wacoochee, and Halawakee creeks. Sum of Squares df Mean Square F p TEMP Among Groups .200 2 .100 2.112 .156 Within Groups .709 15 .047 Total .908 17 DEPTH Among Groups .049 2 .024 .705 .510 Within Groups .518 15 .035 Total .567 17 CVDEPTH Among Groups .072 2 .036 .573 .576 Within Groups .939 15 .063 Total 1.011 17 THALWEG Among Groups .037 2 .018 .449 .647 Within Groups .612 15 .041 Total .648 17 VELOCITY Among Groups .002 2 .001 .024 .976 Within Groups .476 15 .032 Total .477 17 CVVELOCI Among Groups .034 2 .017 .999 .391 Within Groups .254 15 .017 Total .288 17 WIDTH Among Groups .020 2 .010 .418 .666 Within Groups .359 15 .024 Total .379 17 CVWIDTH Among Groups .029 2 .014 .633 .545 Within Groups .342 15 .023 Total .371 17 LENGTH Among Groups .283 2 .141 .950 .409 Within Groups 2.233 15 .149 Total 2.516 17 AREA Among Groups .385 2 .193 .915 .422 Within Groups 3.157 15 .210 Total 3.542 17 VOLUME Among Groups .743 2 .371 1.094 .360 Within Groups 5.090 15 .339 Total 5.833 17 BEDROCK Among Groups .058 2 .029 1.572 .240 Within Groups .276 15 .018 Total .333 17 BOULDER Among Groups .030 2 .015 3.294 .065 Within Groups .067 15 .004 Total .097 17 COBBLE Among Groups .177 2 .089 4.056 .039 Within Groups .328 15 .022 Total .505 17 GRAVEL Among Groups .015 2 .007 2.490 .116 Within Groups .045 15 .003 Total .059 17 SAND Among Groups .130 2 .065 12.424 .001 Within Groups .078 15 .005 Total .208 17 SUBDIVER Among Groups .008 2 .004 .116 .891 Within Groups .543 15 .036 Total .551 17 56 Table 18. Standardized coefficients, representing the change in a dependent variable that result from a change of one standard deviation in an independent variable, for multiple regression of species richness and fish density against environmental principal components in 2005 and 2006. Significant coefficients are marked in bold. Significance test at alpha = .05. PC1 from 2005 and 2006 represented volume/size. PC2 from 2005 and 2006 represented proportion of bedrock. In 2005, PC3 represented CV of current velocity. PC3 and PC4 in 2006 represented CV of depth and current velocity, respectively. In 2005, PC4 represented proportion of boulder. r 2 values given with corresponding figures. Dependent Standardized Coefficients Variables Year PC1 PC2 PC3 PC4 Species Richness 2005 0.08 -0.40 0.57 -0.57 2006 0.6 -0.31 0.18 0.45 Total # of fish /m 2 2005 -0.62 0.08 0.43 0.12 2006 -0.58 0.04 0.16 0.04 Total # of juveniles /m 2 2005 -0.6 0.01 0.24 0.30 2006 -0.49 -0.19 0.06 0.22 Total # of adults /m 2 2005 -0.57 0.18 0.48 -0.02 2006 -0.32 0.17 0.2 -0.09 # of C. pauciradii 2005 (<80mm) /m 2 2006 -0.64 -0.51 0.36 0.51 # of C. pauciradii 2005 -1.08 0.02 0.3 0.44 density (>80mm) /m 2 2006 -0.25 0.16 -0.53 0.09 # of C. venusta 2005 -0.04 0.77 0.1 -0.17 (>50mm) /m 2 2006 -0.34 0.59 0.09 -0.09 # of P. nigrofasciata 2005 -0.46 0.03 0.41 0.26 (<60mm) /m 2 2006 -0.53 0.09 -0.17 0.01 57 Table 19. Pearson correlations for shoal size (length/ area) and fish variables in 2005 and 2006. Significant coefficients are marked in bold. Linear regression significance test at alpha = .05. 2005 2006 Length Area Length Area Richness 0.06 0.00 0.56 0.61 # of juv. C. pauciradii /m 2 -0.52 -0.52 -0.23 -0.35 # of adult C. pauciradii /m 2 -0.51 -0.63 -0.36 -0.39 # of adult C. venusta /m 2 -0.30 -0.34 -0.12 -0.21 # of juv. L. auritus /m 2 -0.32 -0.33 -0.17 -0.30 # of adult L. auritus /m 2 -0.46 -0.40 -0.55 -0.55 # of juv. P. nigrofasciata /m 2 -0.06 -0.15 -0.55 -0.54 # of adult P. nigrofasciata /m 2 -0.39 -0.51 -0.43 -0.41 # of juveniles /m 2 -0.37 -0.39 -0.40 -0.42 # of adults /m 2 -0.38 -0.48 -0.24 -0.23 58 Table 20. Component loadings of spatial variables on principal components combined for 2005 and 2006. Variables in bold were used in regression analyses. Spatial variables PC1 PC2 Proximity Index 0.915 Distance to nearest neighbor -0.901 Distance to Chattahoochee 0.823 Link Magnitude -0.787 % of variance 41.66 32.6 cumulative % 41.66 74.26 59 Table 21. Standardized coefficients, representing the change in a dependent variable that result from a change of one standard deviation in an independent variable, for multiple regression of species richness and fish density against spatial principal components. Significant coefficients are marked in bold. Significance test at alpha = .05. PC1 represented proximity index. PC2 represented link magnitude. r 2 values given with corresponding figures. Dependent variables Standardized Coefficients Year PC1 PC2 Species Richness 2005 0.26 -0.41 2006 -0.57 0.12 Cyprinid density /m 2 2005 -0.06 -0.53 2006 0.28 -0.56 Centrarchid density /m 2 2005 -0.5 -0.05 2006 -0.24 0.48 60 Table 22. List of proximity ranges for species found in shoals in the Chattahoochee River Drainage. Species Mean Proximity Index SD Proximity Range Campostoma pauciradii 11.48 9.37 0.47 - 32.61 Cyprinella venusta 12.19 8.34 0.47 - 32.61 Ericymba buccata 12.14 8.89 1.75 - 22.82 Hybopsis sp. winchelli 15.12 9.27 0.96 - 32.61 Luxilus zonistius 14.12 3.47 7.79 - 17.98 Notropis baileyi 1.69 0.73 0.96 - 2.48 Notropis texanus 14.86 9.40 4.11 - 32.61 Semotilus thoreauianus 8.68 5.07 4.11 - 14.13 Hypentelium etowanum 11.16 9.83 4.11 - 32.61 Moxostoma lachneri 10.51 9.68 1.75 - 32.61 Ameiurus brunneus 13.29 8.38 1.18 - 32.61 Noturus leptacanthus 6.58 6.29 0.96 - 14.97 Lepomis auritus 11.60 8.93 0.47 - 32.61 Lepomis cyanellus 11.34 8.25 1.75 - 22.82 Lepomis macrochirus 8.08 6.79 1.18 - 22.82 Lepomis megalotis 9.68 8.42 0.96 - 21.50 Micropterus cataractae 14.05 8.74 7.05 - 32.61 Micropterus punctulatus 12.13 7.80 0.47 - 22.82 Percina nigrofasciata 12.26 8.78 0.96 - 32.61 61 Table 23. Longitudinal succession of fish families in shoals for 2005 and 2006. (Upper = headwater sections, Middle = middle reaches of streams, Lower = lower reaches of streams) Upper % Middle % Lower % Little Uchee Cyprinidae 43 Cyprinidae 36 Centrarcidae 43 Centrarcidae 29 Centrarcidae 27 Cyprinidae 29 Catostomidae 14 Catostomidae 18 Catostomidae 14 Ictaluridae 7 Ictaluridae 9 Ictaluridae 7 Percidae 7 Percidae 9 Percidae 7 Wacoochee Cyprinidae 46 Cyprinidae 43 Centrarchidae 27 Centrarchidae 36 Ictaluridae 13 Ictaluridae 7 Catostomidae 7 Catostomidae 7 Percidae 7 Percidae 7 Halawakee Cyprinidae 34 Cyprinidae 34 Cyprinidae 34 Catostomidae 20 Centrarchidae 33 Centrarchidae 33 Centrarchidae 20 Catostomidae 13 Catostomidae 13 Ictaluridae 13 Ictaluridae 13 Ictaluridae 13 Percidae 13 Percidae 7 Percidae 7 62 Fig.1. Shoal sites sampled in Little Uchee, Wacoochee, and Halawakee Creeks in Alabama during summer 2005 and 2006. 63 Fig. 2. Fish species composition from pool and shoals in Little Uchee Creek from 2005 and 2006. Centrarchidae 40% Cyprinidae 28% Catostomidae 8% Lepisostiodae 4% Amiidae 4% Anguillida e Ictalurida e Poeciliidae 4% Percidae 4% 64 Fig. 3. Fish species composition from pool and shoals in Wacoochee Creek from 2005 and 2006. Cyprinidae 47% Centrarchidae 22% Ictaluridae 11% Catostomidae 4% Fundulidae 4% Atherinopsidae 4% Percidae 4% Lepisostiodae 4% 65 Fig. 4. Fish species composition from pool and shoals in Halawakee Creek from 2005 and 2006. Centrarchidae 34% Cyprinidae 30% Catostomidae 9% Percidae 6% Ictalurida e Lepisostiodae 3% Fundulidae 3% Poeciliidae 3% Atherinopsidae 3%Dorosomidae 3% 66 Fig. 5. Fish species composition of pool habitats in Little Uchee Creek in 2005. Amiidae 4% Ictaluridae 4% Poeciliidae 4% Cyprinidae 31% Centrarchidae 40% Catostomidae 9% Lepisosteidae 4% Percidae 4% 67 Fig. 6. Fish species composition of pool habitats in Wacoochee Creek in 2005. Lepisosteidae 5% Fundulidae 5% Cyprinidae 43% Catostomida e Atherinopsidae 5% Percidae 5% Ictaluridae 11% Centrarchide 21% 68 Fig. 7. Fish species composition of pool habitats in Halawakee Creek in 2005. Ictaluridae 6% Fundulidae 6% Poeciliidae 6% Atherinopsidae 6% Percidae 6% Catostomidae 16% Cyprinidae 16% Centrarchidae 38% 69 Fig. 8. Fish species composition of shoal habitats in Little Uchee Creek from 2005 and 2006. Centrarchidae 44% Cyprinidae 33% Catostomidae 11% Ictaluridae 6% Percidae 6% 70 Fig. 9. Fish species composition of shoal habitats in Wacoochee Creek from 2005 and 2006. Cyprinidae 44% Cetrarchidae 28% Catostomidae 11% Ictaluridae 11% Percidae 6% 71 Fig. 10. Fish species composition of shoal habitats in Halawakee Creek from 2005 and 2006. Cyprinidae 44% Cetrarchidae 28% Catostomidae 11% Ictaluridae 11% Percidae 6% 72 Fig. 11. Uchee Creek gauge from July 2004 ? Jan 2007. 73 Fig. 12. Principal component analysis plots of environmental variables of shoals in 2005 length area volume cvveloci velocity cvwidth depth PC2 bedrock width 1.01.0 thalweg -.5 sand boulder subdiver 0.0 .5.5 .5 gravel 1.0 temp cobble cvdepth PC3PC1 0.00.0 -.5-.5 74 Fig. 13. Principal component analysis plots of environmental variables of shoals in 2006 length area cvdepth volume thalweg boul der cvwidth PC2 1.01.0 cobble subdiver -.5 width depth 0.0 .5.5 cvveloci temp bedrock .5 gravel 1.0 velocity PC3PC1 0.00.0 sand -.5-.5 75 Fig. 14. Liner relationship of species richness and CV of current velocity of shoals in 2005. Significant at alpha = 0.05 (r 2 = .15) 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0.60 0.70 0.80 0.90 1.00 1.10 1.20 Log of CV current velocity (m/s) 76 Fig. 15. Linear relationship between species richness and proportion of boulder in shoals in 2005. Significant at alpha = 0.05 (r 2 = 0.27) 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0.00 0.05 0.10 0.15 0.20 0.25 Arcsine of proportion of boulder 77 Fig. 16. Linear relationship of the total fish density/m 2 and shoal volume in 2005. Significant at alpha = 0.05 (r 2 = 0.33) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 1.50 2.00 2.50 3.00 3.50 4.00 Log of volume (m3) 78 Fig. 17. Linear relationship between juvenile fish density/m 2 and shoal volume in 2005. Significant at alpha = 0.05 (r 2 = 0.19) 0.00 0.50 1.00 1.50 2.00 2.50 1.25 1.75 2.25 2.75 3.25 3.75 4.25 Log of volume (m3) 79 Fig. 18. Linear relationship between adult fish density/m 2 and shoal volume in 2005. Significant at alpha = 0.05 (r 2 = 0.30) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 1.25 1.75 2.25 2.75 3.25 3.75 4.25 Log of volume (m3) 80 Fig. 19. Linear relationship between number of adult C. pauciradii/m 2 and shoal volume in 2005. Significant at alpha = 0.05 (r 2 = 0.66) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 1.50 2.00 2.50 3.00 3.50 4.00 Log of volume (m3) 81 Fig. 20. Linear relationship between number of adult C. venusta/m 2 and the proportion of bedrock in 2005. Significant at alpha = 0.05 (r 2 = 0.32) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 Arcsine of Proportion of bedrock 82 Fig. 21. Linear relationship between number of cyprinids/m 2 and shoal volume in 2005. Significant at alpha = 0.05 (r 2 = 0.41) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 1.50 2.00 2.50 3.00 3.50 4.00 Log of volume (m3) 83 Fig. 22. Linear relationship between species richness and shoal volume in 2006. Significant at alpha = 0.05 (r 2 = 0.30) 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20 1.00 1.50 2.00 2.50 3.00 3.50 Log of volume (m3) 84 Fig. 23. Linear relationship between number of juvenile P. nigrofasciata/m 2 and shoal volume in 2006. Significant at alpha = 0.05 (r 2 = 0.34) 1.00 1.50 2.00 2.50 3.00 3.50 1.00 1.50 2.00 2.50 3.00 3.50 Log of volume (m3) 85 Fig. 24. Linear relationship between number of cyprinids/m 2 and shoal volume in 2006. Significant at alpha = 0.05 (r 2 = 0.28) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 1.00 1.50 2.00 2.50 3.00 3.50 Log of volume (m3) 86 Fig. 25A. Species-area relationship for shoals in 2005. 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 2.00 2.50 3.00 3.50 4.00 Log of area (m2) 87 Fig. 25B. Species-area relationship for shoals in 2006. Significant at alpha = 0.05 (r 2 = 0.40) 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20 2.00 2.50 3.00 3.50 4.00 4.50 Log of area (m2) 88 Fig. 26. Linear relationship between density of C. pauciradii/m 2 and CV of current velocity in 2006. Significant at alpha = 0.05 (r 2 = 0.51) 0.50 0.70 0.90 1.10 1.30 1.50 1.70 1.90 2.10 2.30 0.25 0.45 0.65 0.85 1.05 1.25 1.45 Log of CV current velocity (m/s) 89 Fig. 27. Size and spatial distribution of shoal habitats in Little Uchee Creek. 90 Fig. 28. Size and spatial distribution of shoal habitats in Wacoochee Creek. 91 Fig. 29. Size and spatial distribution of shoal habitats in Halawakee Creek. 92 Fig. 30. Linear relationship between species richness and proximity index in 2006. Significant at alpha = 0.05 (r 2 = 0.31) 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 Proximity Index 93 Fig. 31. Linear relationship between the number of cyprinids/m 2 and link magnitude in 2005. Significant at alpha = 0.05 (r 2 = 0.28) 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00 2.50 3.50 4.50 5.50 6.50 7.50 Square-root of link magnitude 94 Fig. 32. Linear relationship between the number of cyprinids/m 2 and link magnitude in 2006. Significant at alpha = 0.05 (r 2 = 0.26) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 2.00 3.00 4.00 5.00 6.00 7.00 Square-root of link magnitude 95 Fig. 33. Linear relationship between the number of centrarchids and link magnitude in 2006. Significant at alpha = 0.05 (r 2 = 0.18) 0.00 0.50 1.00 1.50 2.00 2.50 2.50 3.50 4.50 5.50 6.50 7.50 Square-root of link magnitude