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Aquatic Macroinvertebrate Assemblages in Southwest Georgia Headwater Streams

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AQUATIC MACROINVERTEBRATE ASSEMBLAGES IN SOUTHWEST GEORGIA HEADWATER STREAMS By REBECCA TURNER WINN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Rebecca Turner Winn

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This document is dedicated to my parents.

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iv ACKNOWLEDGMENTS I thank my parents, whose support, guidance, and love have shaped the person I am today. They were a constant motivator for th is work. I would also like to thank my manager at International Paper for supporti ng the Dry Creek Long-term Watershed Study and approving my request for taking this st udy as my master’s research. Many coworkers at International Paper have assisted me with this research in enumerable ways, such as assistance with field work, technical advice, assistance with lab work, statistical help, and moral support to name a few. I am also grateful to the students in my committee chair’s lab who provided advice and a listening ear during my last semester. My committee also provided invaluable input th at has made this research something that I am very proud of and that I hope has laid a foundation for future research to be conducted as part of the Dry Creek study. This research would not have been possible without the following organizations that f unded or supported this study: International Paper, the National Council for Air and Stream Improvement, the National Fish and Wildlife Foundation, the J.W. Jones Ecological Research Center, and the H. T. Odom Center for Wetlands. Finally, I thank God who makes all things possible.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES...........................................................................................................ix ABSTRACT.....................................................................................................................xi ii 1 INTRODUCTION AND OBJECTIVES......................................................................1 Introduction................................................................................................................... 1 Headwater Streams................................................................................................1 Aquatic Fauna........................................................................................................2 Benthic Macroinvertebrates...................................................................................4 Biomonitoring........................................................................................................5 Objectives..................................................................................................................... 6 2 SITE DESCRIPTION...................................................................................................8 Study Site..................................................................................................................... .8 Vegetation...................................................................................................................11 Climate........................................................................................................................ 12 Site History.................................................................................................................12 3 METHODS.................................................................................................................18 Overview of Study......................................................................................................18 Data Collection...........................................................................................................19 Physical Measurements.......................................................................................19 Environmental Measurements.............................................................................21 Chemical and Hydrological Measurements.........................................................22 Macroinvertebrates..............................................................................................22 Data Analysis..............................................................................................................24 Physical Measurements.......................................................................................24 Environmental Measurements.............................................................................24 Chemical and Hydrological Measurements.........................................................25 Macroinvertebrates..............................................................................................26

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vi 4 RESULTS...................................................................................................................32 Physical Measurements..............................................................................................32 Environmental Measurements....................................................................................36 Chemical and Hydrological Measurements................................................................37 Macroinvertebrates.....................................................................................................43 Abundance...........................................................................................................45 Dominant Taxa....................................................................................................47 Total Taxa............................................................................................................49 EPT Taxa.............................................................................................................52 Chironomidae Taxa.............................................................................................53 Percent Chironomidae.........................................................................................56 Percent Diptera....................................................................................................58 Percent Elmidae...................................................................................................58 Feeding Type and Habitat Type..........................................................................62 Biotic Indices.......................................................................................................64 Multivariate Analysis..................................................................................................73 Regression Analysis....................................................................................................73 5 DISCUSSION AND CONCLUSIONS......................................................................84 Discussion...................................................................................................................84 Macroinvertebrate Assemb lages All Streams ..................................................84 Macroinvertebrate Assembla ges Within Streams.............................................87 Macroinvertebrate Assemblages Among Streams............................................87 Metrics Assessment.............................................................................................92 Conclusions.................................................................................................................97 APPENDIX SPECIES LIST AN D TOTAL ABUNDANCE FOR EACH SITE..........99 LIST OF REFERENCES.................................................................................................102 BIOGRAPHICAL SKETCH ...........................................................................................110

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vii LIST OF TABLES Table page 2-1 Site history events for th e study site and watersheds...............................................13 3-1 Stream Condition Index metric scoring formulae....................................................27 3-2 Category names, ranges of values fo r Stream Condition Index, and typical biological conditions................................................................................................28 3-3 Sample Ecological Condition Worksheet................................................................29 4-1 Tally of large woody debris (>10cm diameter)........................................................36 4-2 Mean periphyton chlorophyll a and dry weight. Mean macrophyte dry weight.....37 4-3 Mean, minimum, and maximu m in-situ water chemistry........................................40 4-4 Repeated measures analyses for effects of time and position (upstream vs. downstream) on macroinvertebrate metrics.............................................................48 4-5 Repeated measures analyses for e ffects of time (Dec 01, Feb 02, Dec 02, Feb 03) and stream (A, B, C, D) on macroinvertebrate metrics............................................50 4-6 Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and position (upstream vs. downstr eam) on macroinvertebrate metrics............60 4-7 Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and stream (A, B, C, D) on macroinvertebrate metrics......................................61 4-8 Sample comparison of sites (B1 vs. C1 for February 2002)....................................72 4-9 Percent comparability scores for year to year comparison of sites..........................72 4-10 Percent comparability scores for downs tream vs. upstream comparison of sites....72 4-11 Percent comparability scores for st ream to stream comparison of sites...................73 4-12 Adjusted R2 values (%) for five *models: 1) all samples pooled (n=31), 2) Dec 01 samples only (n=7), 3) Feb 02 sa mples only (n=8), 4) Dec 02 samples only (n=8), 5) Feb 03 samples only (n=8)................................................................75

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viii 4-13 Stepwise regression models of th e relationship between EPT taxa and abundance (response) with water ch emistry and hydrology parameters (predictors). ............................................................................................................78 4-14 Stepwise regression models of the re lationship between Georgia EPD index and Georgia AAS index (response) with wate r chemistry and hydrology parameters (predictors). ............................................................................................................79 4-15 Stepwise regression models of the re lationship between percent dominant taxa, percent filter feeders, total taxa, and percent Elmidae (response) and water chemistry and hydrology parameters (predictors). .................................................80

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ix LIST OF FIGURES Figure page 2-1 Location of study site in rela tion to physiographic regions.......................................8 2-2 Location of study area in rela tion to physiographic districts.....................................9 2-3 Topographic map of Dry Creek watershed and location of four headwater watersheds (A-D).....................................................................................................10 3-1 Topographic map and aerial photograph of location of four headwater watersheds (A-D).....................................................................................................18 3-2 Topographic map of location of four headwater watersheds (A-D) with eight sample reaches and schematic of an individual sample reach..................................19 3-3 Schematic of a representative sample reach with layout of litterfall traps...............21 4-1 Percent coverage of in-stream ha bitat units for each sampling site.........................33 4-2 Percent coverage of in-stream ch annel units for each sampling site........................34 4-3 Percent canopy cover for each sampling site (A-1 through D-2) as defined by GLA software...........................................................................................................35 4-4 Average dry weight of total litterfa ll (hardwood leaves, pine, woody debris, and mast) across sites with proportion of total litterfall as leaves (hardwood leaves) in grey.......................................................................................................................3 6 4-5 Periphyton ash fr ee dry weight.................................................................................38 4-6 Macrophyte dry weight (July 2003).........................................................................39 4-7 Monthly mean water temperature............................................................................39 4-8 Monthly mean dissolved oxygen..............................................................................40 4-9 Monthly mean pH.....................................................................................................41 4-10 Monthly mean inorganic nitrogen............................................................................42

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x 4-11 First and second axes of the principa l components analysis (PCA) for in-situ water chemistry data at all sites from September 2001-December 2003.................43 4-12 First and third axes of the principa l components analysis (PCA) for in-situ water chemistry data at all sites from September 2001-December 2003.................44 4-13 Partitioning of total abundance by inve rtebrate orders in study streams over the entire study period....................................................................................................46 4-14 Macroinvertebrate abundance (total number of individuals) for upstream and downstream sites of each stream (A-D) over the entire study period......................47 4-15 Mean macroinvertebrate abundance indi vidual sampling periods with standard error and repeated contrast results (alpha = 0.05)....................................................49 4-16 Means for macroinvertebrate abundance for all sites within each stream for all time periods with standard error...............................................................................51 4-17 Percent dominant taxon for upstream a nd downstream sites of each stream (A-D) over the entire study period...........................................................................51 4-18 Taxa richness for upstream and downstr eam sites of each stream (A-D) over the entire study period....................................................................................................52 4-19 Mean taxa richness for individual sa mpling periods with standard error and repeated contrast resu lts (alpha = 0.05)....................................................................53 4-20 Taxa richness for each stream for all time periods with standard error...................54 4-21 Total Ephemeroptera, Plecoptera, an d Trichoptera (EPT) taxa for upstream and downstream sites of individual streams (A-D) over the entire study period............54 4-22 Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa within each time period with standard error and repeated contrast resu lts (alpha = 0.05) across time........................................................................................................................... 55 4-23 Mean Ephemeroptera, Plecoptera, and Tr ichoptera (EPT) taxa fo r all sites within each stream for all time periods and pairwise multiple comparison test results (Tukey’s honestly significant diffe rence (HSD) test, alpha = 0.05)........................55 4-24 Mean subfamily composition of Chironom idae in individual streams (A-D) over the entire sampling period........................................................................................56 4-25 Number of Chironomidae taxa for upst ream and downstream sites of individual streams (A-D) over the entire study period..............................................................57 4-26 Percentage of total abundance cont ributed by Chironomidae for upstream and downstream sites of individual streams (A-D) over the entire study period............57

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xi 4-27 Percentage of total abundance c ontributed by Diptera for upstream and downstream sites of individual streams (A-D) over the entire study period............58 4-28 Percent of the total assemblage represented by Elmidae for upstream and downstream sites of individual streams (A-D) over the entire study period............59 4-29 Interaction plot (data means) for percent Elmidae. ................................................62 4-30 Percentage of the total assemblage c ontributed by individu al functional feeding groups for individual streams (A-D ) over the entire study period...........................63 4-31 Percentage of the total assemblage represented by filter feeders for upstream and downstream sites of individual str eams (A-D) over the entire study period.....63 4-32 Clinger taxa for upstream and downstr eam sites of individual streams (A-D) over the entire study period......................................................................................64 4-33 Florida Stream Condition Index (SCI) sc ores for upstream and downstream sites of each stream (A-D) over the entire study period...................................................65 4-34 Georgia EPD Biological Assessment scor es for upstream and downstream sites of each stream (A-D) over the entire study period...................................................66 4-35 Georgia EPD Biological Assessment scor es for upstream and downstream sites of each stream (A-D) over the entire study period...................................................67 4-36 Means for GA EPD Index for all stre ams combined during each time period with standard error and repeated contra st results (alpha = 0.05) across time..........68 4-37 Means for GA EPD Index for all sites combined (200 individual subsample) within each time period with standard error and repeated contrast results (alpha = 0.05) across time........................................................................................68 4-38 Means for GA EPD Index (individual str eams for the entire study) and pairwise multiple comparison test results (Tukey ’s honestly significant difference (HSD) test, alpha = 0.05).....................................................................................................69 4-39 Georgia Adopt-A-Stream Index scores for upstream and downstream sites of each stream (A-D) over the entire study period.......................................................70 4-40 Means for GA AAS Index for all sites combined within each time period with standard error and repeated contrast results (alpha = 0.05) across time...................70 4-41 Means for GA AAS Index (individual str eams for the entire study) and pairwise multiple comparison test results (Tukey ’s honestly significant difference (HSD) test, alpha = 0.05).....................................................................................................71 4-42 Principal components ordination for m acroinvertebrate metrics and indices..........74

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xii 4-43 Total annual rainfall from 1967-2003 at the Bainbridge, GA station (90586) at International Paper arranged from lowest to highest annual values.........................77 4-44 Abundance vs. average daily flow for all sites and time periods (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003)..........81 4-45 EPT taxa vs. average daily flow for all sites and time periods (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003)..........81 4-46 GA EPD Index vs. average daily flow for all sites and time periods (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003)..........82 4-47 Abundance vs. average daily flow for all sites and time pe riods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3December 2002, 4-February 2003)..........................................................................82 4-48 EPT taxa vs. average daily flow for all sites and time periods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003).......................................................................83 4-49 GA EPD Index vs. average daily flow fo r all sites and time periods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3December 2002, 4-February 2003)..........................................................................83

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xiii Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science AQUATIC MACROINVERTEBRATE ASSEMBLAGES IN SOUTHWEST GEORGIA HEADWATER STREAMS By Rebecca Turner Winn May 2005 Chair: Thomas L. Crisman Major Department: Environmental Engineering Sciences Headwater streams account for a significant portion of channel length in a stream network and strongly influen ce hydrological, water qualit y, and biological attributes downstream. Little biological monitoring or assessment has been conducted in headwater watersheds, especially in the Southeast coastal plain. Biological assessments must have a standard, or reference condition, against wh ich potentially impacted sites can be compared. The objective of this study was to compare aquatic macroinvertebrate assemblages in four headwater streams as part of the Dry Creek Long-term Watershed Study being conducted by multiple partners. Four headwater streams (designated A, B, C, D) in the Dry Creek watershed of the Southl ands Forest of International Paper were selected for this study. Benthic macroinve rtebrates were sampled in streams during December 2001, February and December 2002, a nd February 2003 within fixed distance sample reaches. Macroinvertebrates were identified to the lowe st taxonomic level and results were used in biotic indices. Data analysis incl uded using repeated measures

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xiv ANOVA to identify differences in macroi nvertebrate assemblages due to sampling period, position (upstream vs. downstream), and between streams. Stepwise regressions were used to correlate differences in hydrol ogy and water chemistry to relate with stream differences. ANOVA results for abundance, total taxa, Ephemeroptera Plecoptera Trichoptera (EPT) taxa, Georgi a Adopt-A-Stream (AAS) index indicated differences in macroinvertebrate assemblages due to samp ling period, with lower values for December 2001 relative to February 2003. A bundance, total taxa, EPT taxa, Georgia Environmental Protection Division (EPD) index, Georgia AAS index, and percent Elmidae displayed significant differences due to stream with comparisons between streams for EPT taxa, Georgia EPD index, and Georgia AAS index resulting in stream A having significantly lower values than stream C. Significant predictors in regres sions were average daily flow and specific conductance for sele cted macroinvertebrate metric s. Natural variability in hydrology, interannual and stream to stream wa s significantly different even within subwatersheds of a small catchment, which suggested that hydrology is an important environmental factor influencing stream ecology and should be considered in macroinvertebrate studies. Of all metrics examined in this study, abundance, EPT taxa, total taxa, GA AAS index, and GA EPD index de tected differences in macroinvertebrates due to time and stream, and therefore best de scribed differences in the macroinvertebrate assemblage. Differences in the macroinverteb rate assemblages between streams A and C, but not between A and B or C and D, support the overall Dry Creek Long-term Watershed Study design and suggest that A and D would be appropriate reference streams for B and C, respectively.

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1 CHAPTER 1 INTRODUCTION AND OBJECTIVES Introduction Headwater Streams First or second order streams comprise approximately 95% of all streams and represent 73% of total cha nnel length in North America (Leopold et al. 1992). For example, the Chattooga River watershed is ch aracterized by 59% of total stream length being first order streams (Hansen 2001). Guid elines for protecting water quality from anthropogenic activities are usually applied to streams designated as perennial (‘blue line’) or intermittent (dashed line) on United St ates Geological Survey topographic maps. For the Chattooga River watershed, only a pproximately 20% of total stream length (1st7th order) was represented as perennial streams on 1:24,000 topographic maps with essentially none of the intermittent or ephemeral streams identified (Hansen 2001). When compared with larger aquatic systems, th e small size but large numbers of headwater streams have led to underestimation of their functions within a watershed and subsequently inadequate management (Gomi et al. 2002). To ensure adequate protection of water quality and aquatic habitats through the use of Best Management Practices for various land management activities, land managers must recognize the location and importance of headwater streams (Hansen, 2001). The “edge” to “interior,” or perimeter to ar ea ratio (P/A), influences the importance of individual input to a habitat (e.g., watershe d to stream) whether the input is natural (e.g., litterfall) or anthropogenic (e.g., nutrients from fertiliz er). Headwater streams have

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2 a high P/A ratio compared to larger rivers, and as such, are more influenced by their stream-land interface (Polis et al. 1997). R ecognition of this conn ection between streams and the surrounding landscape (Hynes 1975, Va nnote et al. 1980) and between headwater streams and downstream systems (Vannote et al 1980) has guided recent studies related to headwater streams and their functions. Headwater streams have many functions im portant to downstream systems (Meyer et al. 2003). Such streams are often str ongly influenced by ripa rian vegetation, which contributes allochthonous detritus and limits autochthonous primary production by shading (Vannote et al. 1980). Wallace et al (1997) showed through a leaf litter exclusion study that terrestrial -aquatic linkages in headwater streams influenced diversity and productivity. Headwater streams store, tran sform (Webster et al. 1999), and export (Wallace et al. 1991) organic matter and nut rients. Invertebrates and diatoms (Allan 1995) are an important energy source for downstream ecosystems. For example, in forested headwater streams of southeastern Alaska, invertebrates and coarse organic detritus are exported downstream year-r ound (Wipfli and Gregovich 2002). These systems also retain (Dieterich and Anders on 1998) and export sediment (Zimmerman and Church 2001). Headwater streams maintain st reamflow by supplying a stable source of water to downstream systems through outflows fr om hillslopes, channel storage, riparian wetlands (Gomi et al. 2002) and groundw ater recharge (Meyer et al. 2003). Aquatic Fauna The southeastern United States harbors a rich and diverse aquatic fauna that is threatened by development, habitat fragment ation, chemical pollution, and exotic species introductions. The Southeast contains approxi mately 40% of the aquatic insect species found in North America (Morse et al. 1997); however, the rich fauna in the Southeast is

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3 poorly known, especially invertebrates (F olkerts 1997). Diversity of aquatic invertebrates is high in the Gulf Coasta l plain (Felley 1992). However, in the Apalachicola-Chattahoochee-Flint (ACF) river basin, there is limited information on the number and distribution of inve rtebrate species, except for ch ecklists of specific taxa in select portions of the basin (Couch et al. 1996). Due to their ge ographical isolation, headwater streams may support species gene tically isolated from those downstream (Gomi, et al. 2002), so these systems may be important for maintain ing local and regional biodiversity. Spatial significance, connection to the la ndscape, and many functions that maintain downstream ecosystems highlight the need for monitoring and assessing headwater streams. A great deal of research on macr oinvertebrates and headwater streams has been conducted in Montane regions, such as the sout hern Appalachians at the U. S. Forest Service’s Coweeta Hydrologic Laboratory in No rth Carolina, and to a lesser extent in the White Mountains at the Hubba rd Brook Experimental Forest in New Hampshire (Stone and Wallace 1998, Whiles and Wallace 1995, Noel et al. 1986). Research has been conducted in lower gradient Coastal Plain syst ems, including in four th-order streams and two rivers in Georgia (Benke et al. 1 984, Wallace and Benke 1984) and in low order streams of southeastern Virginia (e.g., Kedzierski and Smock 2001, Wright and Smock 2001, Smock et al. 1989). Generally, research ers and government agencies have given little attention to wadeable st reams of the coastal plain (Max ted et al. 2000). Therefore, additional information is needed to build on the work previously conducted in the ACF river basin (Muenz 2004, Davi s et al. 2003, Gregory 1996) an d further characterize the unique aquatic macroinvertebrate asse mblages of headwater streams.

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4 Benthic Macroinvertebrates Benthic macroinvertebrates are often used in biological assessments because: 1) they are found in many types of aquatic habita ts, 2) the variety of species that can be monitored offer a range of responses to envi ronmental changes, 3) they do not migrate widely compared to other groups like fish, so they indicate conditions (Barbour et al. 1999), 4) their long life cycles allow temporal assessments, and 5) individual species’ tolerance to pollution have b een established (Rosenberg and Resh, 1993). As a result, benthic macroinvertebrates are well suited fo r continuous monitoring of streams, which enables analysis of continuous and intermittent discharges, single or multiple pollutants, and cumulative effects of pollutants (Rosenberg and Resh, 1993). However, using macroinvertebrates in bioassessment also has a number of potential disadvantages: 1) macroinvertebrates do not respond to all impact s, 2) they can be affected by natural stressors and disturbances such as drought (Feminella 1996), 3) they display seasonal variation (Linke et al. 1999), which can pr esent constraints for timing of sampling and comparing samples, and 4) their drift behavior ca n be problematic if the intent is to detect localized pollution effects (Rosenberg and Resh 1993). This spatial and temporal variability must be accounted for in the sa mpling design (Hershey and Lamberti 2001). Analyzing macroinvertebrates for bioasse ssment can present challenges. Taxonomy for some groups such as the Chironomidae and Oligochaeta requires specialized training. Also, quantitative samp ling requires high numbers of samples for precision, and sample processing and identifi cation are time consuming and expensive, although rapid bioassessment methods can redu ce these concerns (Rosenberg and Resh, 1993).

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5 Biomonitoring In the late 1980’s, severa l state water resource monitoring programs were combined and expanded by the United States Environm ental Protection Agency (USEPA) and state biologists to create Rapid Bi oassessment Protocols (RBPs) as cost-effective biological survey techniques (Barbour et al. 1999). RBP s use an integrated approach to assess waterbody condition by comparing biotic, wate r quality, and habitat measures with reference conditions. The latter can be em pirically defined through historical data, modeling/extrapolation, and/or actual reference sites, but it is best determined by monitoring sites that represent natural ranges of variation, i. e. minimally disturbed with respect to biological condition, water quality, an d habitat (Gibson et al. 1996 as cited in Barbour et al. 1999). As a re sult, biomonitoring programs ha ve attempted to describe reference conditions from a wide range of sites rather than relying on one or two reference sites that could only be used for site specific comparisons. Field experiments in biomonitoring typi cally measure abundances and/or other characteristics of macroinvertebrates at diffe rent sites or times, each with associated environmental conditions. Detected differences in macroinvertebrate s are attributed to differences in environmental conditions of th at site or sample time (Cooper and Barmuta, 2000). Biomonitoring programs and field expe riments in biomonitoring must have a standard, or reference cond ition, by which other sites are evaluated. This provides a baseline (Karr and Chu 1999) for comparis on. Reynoldson et al. (1997) defines reference condition as “the condition that is representative of a group of minimally disturbed sites organized by selected physical, chemical, a nd biological characteristics.” A challenge in biological assessment is finding separate s ites with similar physical, chemical and biological characteristics to se rve as a reference. Field st udies have sought to decrease

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6 this variability by comparing an upstream site to an impacted downstream area (Kedzierski and Smock 2001), comparing near by streams draining watersheds with different land use or treatments (Davis et al. 2003, Richards and Minshall 1992, Gurtz and Wallace 1984), comparing before and after a disturbance, or a combination of before and after disturbance with watershed comp arisons (Stone and Wallace 1998, Wallace et al. 1996). Other studies have combined two of these approaches into a Before-AfterControl-Impact (BACI) design (Rosario and Resh, 2000). Pre-treatment or baseline data are esse ntial for characterizing responses to management (Hershey and Lamberti 2001, Karr and Chu 1999, Reynoldson et al. 1997), and robust baseline data can lessen the potential of natural variation obscuring identification of a treatment effect. In this study, a two-year pre-treatment characterization of benthic macroinvertebra tes in adjacent watersheds and lower and upper reaches of four streams in the Dry Cr eek watershed of southwestern Georgia was undertaken to determine natural variation in macroinvertebrate assemblages. Objectives The objective of this research was to compare aquatic macroinvertebrate assemblages in four headwater streams prior to an experimental evaluation of forestry best management practices. Major questions that were addressed included: 1. What are the macroinvertebrate assemblage s in eight sample reaches (two per study watershed)? 2. Are the assemblages (upstream vs. downstream, between watersheds, across time) similar in population attr ibutes, richness, composition, and functional feeding group composition? 3. If assemblages in reaches are not simila r, what are the primary environmental differences between reaches that may be responsible?

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7 4. How do different state assessment protocols score the biological condition of the eight sample reaches?

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8 CHAPTER 2 SITE DESCRIPTION Study Site The study was located in southwestern Georgia approximately 16 km south of Bainbridge in the Coastal Plain physiographi c province (Figure 2-1) specifically on the boundary of two physiographic districts, the Tifton Upland and Dougherty Plain (Figure 2-2). The steeply sloping Pelham Escarpmen t also forms the boundary or surface-water divide between the Flint River basin to the west and the Ochlockonee River basin to the east (Couch et al. 1996). St reams originating from the Pelham Escarpment are characterized by perennial headwaters that downstream become intermittent or drain directly into the Flint River. This trans itional area is characterized by bluffs and deep ravines that create cool microclimates s upporting rare plant species with northern affinities (Wharton 1978 as cite d in Entrekin et al. 1999). Figure 2-1. Location of study site in relation to physiographi c regions (modified from US Forest Service 1969).

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9 Figure 2-2. Location of study area in relation to physiographi c districts (modified from Torak 2003). The study site is located in the Dry Creek watershed, which discharges to the Flint River approximately 22.5 km up from the Ji m Woodruff Dam of Lake Seminole. The Flint River is part of the larger lower Apalachicola-Chattahoochee-Flint River (ACF) Basin. Late Eocene Ocala Limest one extends throughout this 17,600 km2 river basin. Oligocene Suwannee Limestone extends 26 km up the Flint River impoundment arm (Torak 2003). Soils of the study sites are domin ated by Ultisols, with the riparian area

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10 comprised of the Chiefland and Esto series, cl assified as well draine d fine sands over clay loams. The slopes are Eustis series soils, which are loamy sands over sandy loams and classified as somewhat excessively well dr ained. The upland soils are comprised of Wagram, Norfolk, Lakeland, Orangeburg, and Lucy, which are generally well drained loamy sands over sandy clay loams, with the exception of the Lakeland Unit, which has a sandy texture throughout and is characterized as excessively well drained (International Paper 1980). Streams draining the four study watersheds, A, B, C, and D (Figure 2-3) comprise part of the headwaters of Dry Creek. Figure 2-3. Topographic map of Dry Creek watershed and location of four headwater watersheds (A-D). Surface water flow in the ACF basin is lowest from September to November and peaks during January to Apr il due to higher rainfall and decreased evapotranspiration (Couch et al. 1996). Streams and rivers in th e Coastal Plain receive substantial amounts of groundwater because they ar e typically deeply incised in to underlying aquifers (Couch

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11 et al. 1996). The study streams are first orde r, groundwater-influen ced, low to medium gradient, and have sand-dominated substrate. In-stream habitat includes coarse woody debris, undercut banks, leaf packs, and fine roots. The four study watersheds average 39 ha, 1.5 L/s in average annual discharge, and 457 m in channel length (Summer et al. 2003 and Summer unpublished data). Watersheds A and B have gentle slopes and broader, meandering channels, whereas the remaining watersheds, C and D, have steeper slopes with well defined stream channels. Vegetation The overstory, midstory, and understory vegetation in riparian, midslope, and upslope areas of watersheds A, B, C, and D are generally similar with a few exceptions. The species dominating the overstory in ripari an areas were: Nyssa biflora, Liriodendron tulipifera, Pinus glabra, Magnol ia virginiana, Fagus grandifo lia, Liquidambar styraciflua, Quercus nigra, and Quercus michauxii. Ma gnolia grandiflora was found more frequently in watersheds C and D (International Pa per unpublished data). The upland of each watershed was dominated by Pinus taeda, whic h was established at varying times by hand planting. The midstory of all watersheds was generally composed of Carpinus caroliniana, Ostrya virginiana, Acer rubrum, Acer barbatum, and Oxydendrum arboretum. Magnolia pyramidata occurred in ri parian areas and midslopes of watersheds C and D. The understory composition and coverage varied from watersheds A and B dominated by riparian wetland species to wate rsheds C and D with understory similar to that of watersheds A and B, but less abunda nt. This is likely due to the mixed mesic hardwood forest type and drier soil conditions of watersheds C a nd D. Typical shrub species of the understory we re Ilex coriacea, Myrica ce rifera, Rhododendron canescens, Viburnum nudum, Alnus serrulata, Ilex glabra and Ilex opaca. Herbaceous species of

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12 the understory in watersheds A and B in cluded Boehmeria cylindrica, Woodwardia virginica, Woodwardia areolata, Panicum sp., Carex sp., Cyperus sp., Juncus effusus, and Smilax laurifolia. Typical herbaceous species in the understory of watersheds C and D were Arundinaria gigantea, Leucothoe axilla ris, Smilax pumila, and Mitchella repens (International Paper unpublished data). Climate Climate of the region is char acterized by warm, humid summ ers, and mild winters. Temperatures in January, the coldest month of the year, range from an average maximum of 16.3oC and a minimum of 2.8 oC. July is the hottest month of the year with an average maximum temperature of 33.5 oC and minimum of 21.5 oC (SERCC 2004). Mean annual precipitation is 1412 mm. June has the hi ghest mean rainfall (152.1 mm) and October lowest (77.5 mm) (SERCC 2004). Summer rains are usually s hort, with high intensity events giving way to low intensity frontal ev ents from late fall to early spring. Due to proximity of the Gulf of Mexico, heavy rainfa ll associated with hurricanes and tropical storms in late summer is not unusual. Drought conditions occurred during 1998-2002 and resulted in an accumulated rainfall de ficit of 711-1270 mm in some southwestern Georgia areas (Pam Knox, Assistant Georgia State Climatologist, oral communication as cited in Warner and Norton 2003). Site History Starting with small-scale disturbance by Native Americans who used fire to manage pinelands and prepare land for cultiv ation, the forest in many parts of the ACF river basin has been affected by human act ivity. This continued through European settlement, with pre-and post-Civil War ag riculture, and now the area is primarily characterized by second growth st ands and acreages of planted pine (Couch et al. 1996).

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13 Site history specific to the study area and when noted, the specific study sites, is as follows. Table 2-1. Site history events for the study site and watersheds. *S A A BCDSite History Event Date: 1837 X Site settled by Munnerlyn family Cattle grazing and sharecropped for cotton, corn, peanuts, and flax 1925 X Portable sawmill operations Riparian areas not likely harvested 1937 X Managed as a hunting preserve 1957 X Property aquired by International Paper 1968 X X Uplands of C (south side) and D (north side) hand planted with loblolly pine 1969 X X Uplands of B (south side) and C (north side) hand planted with loblolly pine 1986 X 5.67 ha portion was hand planted 1987 X 5.67 ha portion had herbicide applied by a skidder to control herbaceous vegetation 1988 1989 X X Uplands of A and B (northern half) hand planted with loblolly pine 1990 X X Uplands of B (south side) and C (northern portion) were control burned 1991 1992 X X Uplands of B (south side) and C (northern portion) were control burned X X Uplands of C (south side) and D (north side) were control burned X Uplands of D (south side) were control burned 1993 1994 X 5.67 ha portion was control burned 1995 X X Uplands of C (south side) and D (north side) were control burned 1996 X 5.67 ha portion was control burned X X Uplands of B (south side) and C (northern portion) were thinned X X Uplands of C (south side) and D (north side) were thinned 1997 1998 1999 2000 X 5.67 ha portion was control burned X X Aerial herbicide application and control bur n for uplands of A and B (northern half) 2001 X 5.67 ha portion was thinned *SA = activities occurred in study area Watersheds In 1837, the land known then as the Fow ltown tract was bought and settled by Charles Lewis Munnerlyn, originally from Georgetown, South Carolina. The 1,349 ha property was pineland at the time of purchase, which was thought to be of little value except for cattle grazing (International Pa per 1997). In the 1830’s and 1840’s the Munnerlyn slaves cleared all debris (i.e. moss, limbs, and leaves) out of the streams and spread this over the fields. This scatte ring of debris and another technique known as “cow pinning”, which consisted of allowing large herds of cattle to rest in the fields, was

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14 used to enrich the soils. This practice is thought to have occurred in the study streams and watersheds (J. Wingate, personal communication, 17 August 2004). In 1864, Munnerlyn’s only son, Charles James, was appo inted by Jefferson Davis as a Major with command of the First Battalion, Florida Special Cavalry. This batta lion, later named the Cow Cavalry, was organized to collect and dr ive cattle from Florid a to help supply the Confederate Army. Munnerlyn’s superior offi cer noted that he had operated his own large plantation with great success (Taylor 1986). The study area is thought to have been used as a resting and grazing place by M unnerlyn for cattle herds being moved from Florida to Columbus Georgia to supply Confederate troops (J. Wingate, personal communication, 17 August 2004). During the year s of Munnerlyn family ownership after the war, the property was sharec ropped for cotton, corn, peanut s, and flax (Table 2-1) (J. Wingate, personal communication, 17 August 2004). There is evidence of damming in an upstream portion of watershed C. This site was dammed, and a water “ram” was construc ted downstream. This ram supplied water to a house located upslope from the site, which is thought to be the first house built in 1822 or 1823 in Decatur County (J. Wingate personal communication, 17 August 2004). It is not known when this dam wa s installed, or how long it existed. In 1925, the property was sold to a partne rship of Ludwick Gaissert, O.M. Peden, H.R. Garrett, and W.R. Layson. This partne rship dissolved, and H.R. Garrett became sole owner and set up a lumber mill site. His operation had portable saws and moved from site to site on the property as needed (Table 2-1). Garrett apparently did not use oxen to move harvested timber, and this has led to the assumption that Garrett predominantly cut timber on the ridges and likel y did not harvest ripa rian areas at the

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15 bottom of steep slopes that are found in the study area (J. Wingate, personal communication, 17 August 2004). Due to better opportunities or possibly because most saleable timber had been cut, Garrett sold the property. Richard Tift, a prominent land speculator, and Herbert L. Stoddard, generally recognized as the “father” of prescribed burning in the S outh and for his work with bobwhite quail, began buying options for parc els of land along the Flint River. After approximately a year and a half, Tift and St oddard acquired options for 28 parcels of land comprising 10,522 ha. In 1937, Houghton P. Metcalf, a wealthy industrialist from Providence, Rhode Island, bought the parcels an d named his estate Southlands. Metcalf authorized removal of the remainder of Munne rlyn’s cattle herds and wild hogs from the property. The property on the east side of the Fl int River, where the study site is located, was managed as a hunting preserve (Table 21) and was specifically managed to attract quail, dove and turkeys. The property on the west side of the river had a hog farm and was planted in corn and peanuts. Metcalf wa s interested in refore station and wanted to preserve the natural beauty of the property. In 1947, the property was sold to Southern Kraft Timberland Corporation, a division of International Paper Company (International Paper 1997). On 14 November 1957, the property was dedicate d as a research center due, in part, that all four major southern pine species (i .e. loblolly, longleaf, shortleaf, and slash) naturally grew on site (Table 2-1). Also, the property had diverse terrain with upland loblolly sites on the east side of the river, sandy longleaf sites on th e west side of the river, river swamps, and bottomland ha rdwoods (International Paper 1997).

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16 Detailed information on each stand in th e study was obtained from International Paper stand inventory data (Table 2-1). Tr ees in riparian areas of each of the four study watersheds were aged by a timber cruise in 1987. Increment cores were taken on 2 or more trees per plot in the natural pine/h ardwood stands. An establishment date was estimated as 1935 (D. Morgan, personal communication, 3 August 2004), although the trees in riparian areas are thought to be older due to the manner of harvesting employed by H.R. Garrett (J. Wingate, personal comm unication, 17 August 2004). Riparian areas in all four watersheds, (A through D), (Figure 2.3) were not subject to any silvicultural activities due to Inte rnational Paper policy of maintaining forested buffers. A 5.67 ha portion of watershed A, north of the stream and south of the main road, was hand planted in 1986, and herbicide was applied by a skidde r in 1987 to control herbaceous vegetation. This area was control burned in 1994, 1996, and 2000 and thinned in March 2001. The majority of the uplands of watershed A and the northern half of watershed B were hand planted with loblolly pine in 1989. An aer ial herbicide applica tion and a control burn were completed in 2000. The uplands on the south side of watershed B and the northern portion of watershed C’s uplands were esta blished in 1969 by hand planting of loblolly pine. Control burns were completed in 1990 and 1992, then the area was thinned in 1996. Uplands on the south side of watershed C and the north side of watershed D were hand planted with loblolly pine in 1968. Control burns were completed in 1992 and 1995, and the area was thinned in 1996. Uplands on the south side of the stream in watershed D were allowed to naturally regene rate in 1950. A control burn of this area was completed in 1992.

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17 A private landowner owns 24% of waters hed B and 18% of watershed C (Figure 2.4). A cattle farm was operated in these areas from 1950 through 1994. Hogs were also kept on the property. Streams of watersheds B and C were the water source for the cattle and hogs. In 1968, pines were selectively re moved from riparian areas, but hardwoods were left (C. Lynn, personal communication, 17 August 2004).

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18 CHAPTER 3 METHODS Overview of Study Four headwater streams and their watersheds (A, B, C, and D) were selected for study (Figure 3-1). The overall Dry Creek Study (Streamside Management Zone Effectiveness on Hydrology, Water Quality, an d Aquatic Habitats in Southwestern Georgia Headwater Streams) design incl udes elements of before and after, upstream/downstream, and paired watersheds experimental designs. Figure 3-1. Topographic map and aerial photogr aph of location of four headwater watersheds (A-D).

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19 This study compared upstream vs. downs tream, between watersheds, and across time to evaluate macroinvertebrate assembla ges and primary environmental variables in the four adjacent study streams. This study established the pre-harvest condition and natural variability of the macroinvertebrate assemblage. This information will be used for post-harvest comparisons in the overa ll Dry Creek Study, being conducted by multiple partners. Data Collection Physical Measurements Eight fixed-distance sample reaches, tw o per watershed, were established 30.8 m upstream of flumes (Figure 3-2). Figure 3-2. Topographic map of location of four headwater watersheds (A-D) with eight sample reaches and schematic of an individual sample reach.

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20 Three transects were established perpendicu lar to the stream within each reach to serve as in-stream data collection points for physical measurements including channel cross-sections, canopy cover, a nd percent cover of in-stream habitat. At each transect, percent cover of in-stream habitat was dete rmined by extending a tape across the active channel and recording the le ngth of each habitat type (e.g., sand, small woody debris, roots, leaf pack, gravel). These lengths we re converted into percent cover, which was used to define the major habitat types to be sampled for macroinvertebrates. In August 2002, pictures of the canopy were taken at each transect with a digital camera fitted with an 180o hemispherical fisheye lens. A survey of habitat unit a nd channel characteristics wa s conducted longitudinally within established macroinvertebrate sample re aches. A 50 m fiberglass tape was placed in the thalweg of the stream, then divi sions between each hab itat unit type were determined and physical characteristics were recorded. Unit types included riffle, run, glide, pool, backwater pool, step, and undercut bank. A b ackwater pool was defined as slower and deeper than a glid e, but did not possess characte ristics of a pool, such as evidence of scouring, deposition, and having a d eep and shallow section (i.e. measurable residual pool depth). For each unit type, a unit end (length), channel width (active channel), and maximum water dept h were recorded. For step and pool unit types, a step height and residual pool dept h were taken. Primary obstruc tions (e.g., wood, roots), their length, and diameter, were recorded when th e object was primarily responsible for pool formation. A tally of functional and non-functio nal wood greater than 10 cm in diameter was taken. Functionality was based on the role wood played for changing morphology.

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21 Texture of the streambed (e.g., sand, silty-sand) was estimated by soil feel and appearance in each sample reach. Environmental Measurements Sixteen leaf litter trap s (surface area of 0.26 m2 each) were positioned within the riparian area: six along the streambank, six 10 m from the stream, and four 20 m from the stream (Figure 3-3). Litter samples were collected monthly, dried at 60oC for 24 hours, separated into pine and hardwood foliage woody debris, and mast, and weighed. Figure 3-3. Schematic of a representative samp le reach with layout of litterfall traps. Within each stream reach, ten randomly selected locations were sampled for periphyton and macrophytes in June, July, a nd August. Following the method of Tett et al. (1978), two petri dishes (17.34 cm2) were inserted into the sediment at each sampling location. Chlorophyll a concen trations of periphyton in the sediment sample were measured using an acetone ex traction procedure (American P ublic Health Association, 1995) followed by colorimetric analysis. The co ntents of the second petri dish were dried

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22 at 60oC, weighed, burned at 500oC, and reweighed for ash-free dry weight determination. Macrophytes were sampled by cutting all vegeta tion at the sediment surface that existed within a 0.25 m2 quadrat. Macrophyte samples were rinsed and dried at 60oC (Kedierski and Smock, 2001). Dry weight was determined for each sample. Chemical and Hydrological Measurements Water temperature was measured from October 2001 through December 2003 with an Onset HOBO temperature logger (Pocasset, MA), which was programmed to measure temperature every 15 minutes. Stream flow, water chemistry, and meteorological measurements have been collect ed by other investigat ors as part of the Dry Creek Study, and these data were availabl e for use in this study. Stream stage and discharge was recorded every 15 minutes by Is co Model 4320 Bubbler Flow Meters at six sites: one in the stream at the outlet of wa tersheds A, B, C, D and one in the upstream portion of watersheds B and C (Summer 2003) Monthly in-situ measurements for dissolved oxygen, specific conductance, temper ature, pH, and turbidity were made at eight sites (two per watershed) with portable meters. Grab samples were taken from a midstream location and analyzed for inor ganic nitrogen, inorganic phosphorus, and ammonium (Jones et al. 2003). Macroinvertebrates Benthic macroinvertebrates were collected within established sample reaches (Figure 3-2) with a 500-m-mesh D-frame ne t (0.3 m wide) in December 2001, February and December 2002, and February 2003 using a multi-habitat sampling procedure (Barbour et al. 1999). This procedure was te sted by the Mid-Atlantic Coastal Streams Workgroup and the Florida Department of Environmental Protection and deemed a scientifically valid sampling technique for lo w-gradient streams (Barbour et al. 1999).

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23 Fall and winter sampling periods were chosen because these seasons are prior to the emergence of most species and larvae are ge nerally easier to iden tify because of their larger size. Within each reach, 20 sampling sweeps (i.e. disturbing habitat for 0.5 m) were made through major habitat types such as sand, woody debris, fine roots, and leaf packs. This resulted in approximately 3.1 m2 of habitat sampled. The duration of sampling in each reach was timed to maintain a consistent sampling effort for all reaches. Material collected from each sampling sweep wa s deposited in a 19 L bucket. Material in the bucket was rapidly stirred to suspend or ganisms and poured into the 500-m-mesh Dframe sampling net. Material caught in th e net was placed in a 4 L glass jar and preserved with 70% ethyl alc ohol in the field. Rose Bengal biological stain was added to each sample in the laboratory. All samples we re processed by washing organic debris (leaves and woody debris) with water into a 500-m-mesh sieve. Invertebrates were handpicked from the sieve contents and identi fied to genus or species (when possible), under a low power (<50x) dissecting mi croscope (Richardson 2003, Gelhaus 2002, Pescador, Rasmussen, Richard 2000, Epler 1996, Merritt and Cumm ins 1996, Pescador, Rasmussen, Harris 1995, Peckarsky et al. 1990, Brigham, Brigham, and Gnilka, 1982). Genus or species-level taxonomy has been found to yield the greatest benefits for biological monitoring studies especially wh en results could influence management decisions (Lenat and Resh 2001). Ephemeropt era, Plecoptera, and Trichoptera generic identifications were verified, and species identifications were made when possible by M.L. Pescador and A.K. Rasmussen. Dytiscidae species identifications were made by Bill Wolfe. All Chironomidae samples were sent to a consultant, Penni ngton and Associates, for identification, generally to species. La rval Chironomidae were cleared with cold 10%

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24 KOH for 24 hours, then temporary slide mounts were made using glycerin. Permanent slide mounts were made in CMC mounting me dia for voucher specimens. Identifications were made to genus under a dissecting micr oscope using Merritt and Cummins (1996). Further identification to speci es was made using a compound microscope (Epler 2001). Functional feeding group and habitat/behav ior designations were determined using Merritt and Cummins (1996). Oligochaeta, Gastropoda, and Bivaliva were enumerated but not identified beyond Class and were not included in metric calculations or data analysis. Data Analysis Physical Measurements Percent cover of in-stream habitats was summarized for each site. Length multiplied by average width measurements for each channel unit was used to calculate the area of each channel unit. The percentage of the total area occupied by each channel unit was calculated by: % of Area = area of ch annel unit type / total area of reach x 100 (Bisson, and Montgomery, 1996). A digital camera was used to convert the hemispherical images of canopy cover into bitmaps, which were then analyzed us ing Gap Light Analyzer software (Frazer and Canham, 1999). This software transformed pixe l intensities into sky and non-sky classes, then these data were used to estimate per cent canopy cover. A ta lly of functional and non-functional wood > 10 cm in diameter was summarized for each site. Environmental Measurements Seasonal average dry-weight data were ca lculated from the six litterfall traps positioned along the stream bank for each site. Repeated measures analysis of variance (ANOVA) (SPSS Inc., Chicago IL) was used to determine whether there was a

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25 significant effect due to position (upstream ve rsus downstream, df =1,6), season (fall, winter, spring, summer, df =3,18), or the interaction of position and season (df =3,18). A second repeated measures ANOVA was run to determine effects due to season (fall, winter, spring, summer, df =3,12), stream (A, B, C, D, df = 3, 4), or the interaction of season and stream (df =9,12). The sample si ze for each stream was 2, which limited the power of the across stream comparisons. Periphyton chlorophyll a concentrations, periphyton ash-free dry-weight and macrophyte dry-weight were analyzed using one way ANOVA (alpha = 0.05), which tested the equality of site means. One way ANOVA was used because the samples for each si te were 10 independent random samples. Differences between time periods were not ex amined because samples were collected in one summer season, June, July, and Augus t of 2003. Fisher’s multiple comparison procedure was used for significant ANOVA result s, which generated confidence intervals for all pairwise differences between site m eans (individual error ra te = 0.05) (Minitab Inc., State College PA). Chemical and Hydrological Measurements Monthly dissolved oxygen, specific conduc tance, temperature, pH, turbidity, inorganic nitrogen, inorganic phosphorus, and ammonium values were summarized as averages for six months and three months prior to each macroinvertebrate sample. Average daily flow (Liters/second) was convert ed into minimum, average, and maximum daily flow for each month. Average zero-fl ow days were calculated and further summarized as averages for six months and th ree months prior to ea ch macroinvertebrate sample.

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26 Macroinvertebrates Data from each site were used to de velop numerical metrics to describe the macroinvertebrate assemblages of the study streams. Abundance and percent dominant taxon (i.e. dominance of the single most a bundant taxon) were tall ied and calculated to characterize the population in each stream. Taxa richness, EPT taxa, and number of Chironomidae taxa were calculated to determin e richness. Taxa richness was calculated as the number of unique taxa at the family, genus, or species level. For example, if a sample contained 5 Libellulidae, 4 Gomphidae, 5 Gomphus 5 Progomphus and 1 Boyeria vinosa this would result in 4 ta xa with 20 individuals. EPT taxa were calculated as the number of unique taxa at the genus or species level. Number of Chironomidae taxa was calculated as the num ber of unique taxa at the genus or species level. Percent Diptera and percent Chironomid ae were also calculated for each stream. Percent filter feeders and number of clinger taxa pr ovided information on partitioning feeding strategies and habitat preference of insects in the assemblages. Percent Elmidae was calculated as an experimental metric because percent Elmidae was found useful in describing perennial stream s within Georgia’s Fall Line Hills District (Muenz 2004), which is located in the adjace nt physiographic distri ct to the study site (Figure 2.2). Elmids prefer sw ifter parts of streams such as oxygen rich riffles (Merritt and Cummins 1996). Also, this family of bee tles were described by Epler (1996) to be the most truly aquatic of Florida water beet les because the larvae possess gills and adults utilize a plastron (cover ing of fine dense hydrofuge setae that holds a layer of air where gases can be exchanged), which enables them to remain submerged. Most other aquatic beetles must go to the surface. These characte ristics of the Elmidae make them the best candidates of the aquatic beetles as indi cators of water quality (Epler 1996).

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27 Data from each site were used to deve lop numerical metrics which were used to calculate Florida Department of Environmental Protecti on’s Stream Condition Index (SCI) (FDEP, 2004) and Georgia Department of Natural Resources’ (DNR) Freshwater Macroinvertebrate Biological Assessment (GA DNR, 2002). Oligochaeta, Gastropoda, and Bivaliva were excluded from analyses. Fo r Florida’s SCI, raw data from each site were sub-sampled for 100 individuals us ing Microsoft Excel’s random number generator. Metric values fo r total taxa, Ephemeroptera taxa Trichoptera taxa, long-lived taxa, percent filter feeders, number of clinge r taxa, number of Chironomidae taxa, percent Tanytarsini, sensitive taxa, and percent very-tolerant were calc ulated and converted into a metric score ranging from 0 to 10 usi ng formulae contained in Table 3-1. Table 3-1. Stream Condition Index metric scoring formulae. SCI metric Northeast Panhandle Peninsula Total taxa 10 (X–16)/26 10 (X–16)/33 10 (X–16)/25 Ephemeroptera taxa 10 X /3.5 10 X /6 10 X /5 Trichoptera taxa 10 X /6.5 10 X /7 10 X /7 % Filterer 10 (X–1)/41 10 (X–1)/44 10 (X–1)/39 Long-lived taxa 10 X /3 10 X /5 10 X /4 Clinger taxa 10 X /9 10 X /15.5 10 X /8 % Dominance 10 – ( 10 [ ( X–10)/44 ] ) 10 – ( 10 [ ( X–10)/33 ] ) 10 – ( 10 [ ( X–10)/44 ] ) % Tanytarsini 10 [ ln( X + 1) /3.3] 10 [ ln( X + 1) /3.3] 10 [ ln( X + 1) /3.3] Sensitive taxa 10 X /11 10 X /19 10 X /9 % Very tolerant 10 – (10 [ ln( X + 1)/4.4 ] )10 – (10 [ ln( X + 1)/3.6 ] ) 10 – (10 [ ln( X + 1)/4.1 ] ) (FDEP, 2004) Metric scores were summed and divided by a correction factor. The SCI category (good, fair, poor, very poor) for each site foll owed ranges provided in the index (Table 32).

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28 Table 3-2. Category names, ranges of values for Stream Condition Index, and typical biological conditions. SCI category SCI range Example Description 1 sample Good [73–100] Similar to natural conditions, up to 10% loss of taxa expected Fair [46–73) Significantly different from natural conditions; 20–30% loss of Ephemeroptera, Tric hoptera and long-lived taxa; 40% loss of clinger and sens itive taxa; percentage of very tolerant individuals doubles Poor [19–46) Very different from na tural conditions; 30% loss of total taxa; Ephemeroptera, Tric hoptera, long-lived, clinger and sensitive taxa uncomm on or rare; Filterer and Tanytarsini individuals decline by half; 25% of individuals are very tolerant Very poor [0–19) Extremely degrad ed; 50% loss of expected taxa; Ephemeroptera, Trichoptera long-lived, clinger, and sensitive taxa missing or ra re; 60% of individuals are very tolerant (FDEP, 2004) For Georgia’s Biological Assessment, the da ta from each site was used to calculate the following metrics: taxa richness, nu mber of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, number of Chironomid ae taxa, percent contri bution of dominant taxon, percent Diptera, Florida Index, and pe rcent filterers. These metrics measure the richness, composition, tolerance/ intolerance, and feeding stra tegies of the assemblage. Each metric value was converted into a scor e, and scores were summed. Georgia DNR reference stream data scores from the Sout heastern Plains Ecoregion, Tifton Upland subecoregion were averaged and compared to study sites. Percent comp arability of study to reference sites were calculated (study site score/reference site score x 100) to determine ecological condition (Table 3-3). A sec ond calculation of Georgia’s Biological assessment was performed for a 200 indivi dual sub-sample according to GA DNR’s Standard Operating Procedur es (GA DNR, 2002). Raw data from each site were sub-

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29 sampled for 200 individuals using Microsof t Excel’s random number generator, and scores were generated as outlined above. Table 3-3. Sample Ecological Condition Worksheet. 5310 Taxa Richness (Total # Taxa)>3030-16<16 EPT Index>66-4<4 # Chironomidae Taxa >88-5<5 % Contribution of Dominant Taxon<2323-61>61 % Diptera -----<51>50 Florida Index>1515-8<8 % Filterers >1111-6<6 Total Habitat Score:>89%89-75%74-60%<59% Total Points Earned 00 % of Reference Site Ecological Condition: Very Good > 82% Good 81-64% Fair 63-48% Poo r 47-35% Very Poo r < 35% (GA DNR 2002) METRIC: Study Site Data:Ref Site: SOUTHEASTERN PLAINS (65) SCORE RANGES Study Site Ref Site Score Expected species absent or in low abundance; few sensitive species present. Low species richness, with tolerant species predominant, sensitive species absent. Expected species absent, only tolerant organisms present, few or no EPT taxa. Comparable to best situation expected; species with endangered, threatened, or Balanced community with sensitive species present. Using the Georgia Biological Assessment method, study sites were compared to each other to assess year to year, between watersheds, and upstream vs. downstream percent comparability. An ecological c ondition score was not assigned to these comparisons. Georgia Adopt-A-Stream volunteer monito ring assessment methods were applied to the macroinvertebrate data. A presen ce/absence count of sensitive, somewhat sensitive, and tolerant insects, crustaceans, aquatic worms, gastropods, and bivalves were made for each site. All categories were su mmed and multiplied by a factor of 3 for sensitive, 2 for somewhat sensitive, and 1 fo r tolerant. The result for each category was summed for the total index value, and a wate r quality ranking (exc ellent, good, fair, and poor) was assigned (GA DNR 2000). All percent metrics were arcsine transf ormed and abundance was log transformed prior to statistical analysis Repeated measures ANOVA (SPSS Inc., Chicago IL) was

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30 used to determine any significant effect due to position (upstream versus downstream, df =1,6), time (Dec 01, Feb 02, Dec 02, Feb 03, df =3,18), or interaction of position and time (df =3,18) for all macroinvertebrate metr ics and index values. Within and between subjects means and standard error were calc ulated as part of the repeated measures ANOVA procedure (SPSS Inc., Chicago IL). When significant (P<0.05) differences were detected due to time, repeated contra sts (i.e. comparison of adjacent levels) was used to compare time periods. A sec ond repeated measures ANOVA was run when position was insignificant (P>0.05) for determ ining effects due to time (Dec 01, Feb 02, Dec 02, Feb 03, df =3,12), stream (A, B, C, D, df = 3, 4) or interacti on of time and stream (df =9,12). The power of this analysis was limited because the sample size for each stream was two. When ANOVA resulted in si gnificant (P<0.05) differences between means, a pairwise multiple comparison test (Tukey’s honestly significant difference (HSD) test, alpha = 0.05) was made between means of a factor. Principal components analysis (PCA) wa s used as an exploratory analysis (Golladay and Battle 2002, Karr and Wisseman 1996) to visualize broad trends in the chemical data, hydrological data, and macroi nvertebrate measures among sites. This technique reduces a data set with many variables into a smaller number of composite variables (axes) and indicates covariation among variables wi th a set of primary axes. Options for PCA included Euclidean distance and cutoff r2 (0.2) (McCune and Mefford 1995). For each PCA (i.e. chemical, hydrologi cal, and macroinvertebrates), the number of axes included in the analysis was determ ined using broken-stick eigenvalues. For the PCA graph, each stream was assigned a unique symbol and further identified with a position number (1-downstream, 2-upstream) and a time number (1-Dec 01, 2-Feb 02, 3-

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31 Dec 02, and 4-Feb 03). Interpretation of PCA results assumed that most variation is explained by variables furthest from the origin. Positively correlated variables are close together, whereas negatively correlated variable s are located at opposite ends of the axis. Data points close together are more simila r, and those far apar t are dissimilar. Stepwise multiple regressions (Alpha -to-Enter: 0.05, Alpha-to-Remove: 0.05) (Minitab Inc., State College PA) were used to quantify relationshi ps between predictor variables (abundance, EPT taxa, total taxa Georgia EPD index, Georgia AAS index, percent Elmidae, percent dominant taxa, and percent filtering colle ctors), with response variables (DO, pH, water temperature, specific conductance, inorganic nitrogen, inorganic phosphorus, ammonium, turbidity, maximum daily flow, average daily flow, minimum daily flow). Abundance, EPT taxa, total taxa, Georgia EPD index, Georgia AAS index, and percent Elmidae were sele cted as response variables because of significant ANOVA results. Five models were run for each response variable: 1) all samples pooled (n=31), 2) December 2001 samples only (n=7), 3) February 2002 samples only (n=8), 4) December 2002 samp les only (n=8), 5) February 2003 samples only (n=8). This procedure was run three tim es with mean values for water chemistry and hydrologic variables from one month, three months, and six months prior to macroinvertebrate sample collection.

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32 CHAPTER 4 RESULTS Physical Measurements Habitat units in the study streams include d sand (and other fine sediment), leaves, roots, undercut bank, gravel, and small woody debris (SWD, <10 cm in diameter). The percent coverage of these in-stream habita t types varied more among watersheds than within the same stream. Sand and leaf habitat was most abunda nt in watershed A. Site A-1 contained more undercut bank habitat, wher eas A-2 had a greater percentage of roots (Figure 4-1). Sand and leaves were dominant habitats in wa tershed B, with root habitat also represented. Site B-2 had gravel and undercut bank habitats re presented, while site B-1 did not (Figure 4-1). Wa tershed C, Sites C-1 and C-2 contained sand, leaf, root, and SWD habitats. Coarse bed material was observe d at C-1, but did not occur in a measured transect. Sites in watershed D (Figure 4-1) were characterized by sand, leaf, gravel and SWD habitats, with D-1 also having root hab itats. Although not measured in this survey, exposed areas of limestone were presen t in the streambed of watershed D. Channel units in the study streams included backwater pool glide, pool, riffle, run, and step. The percent aerial co verage of these channel units varied among watersheds and within the same stream. Site A-1 had a much greater percentage of run (49%) than A-2 (13%), but A-2 had 30% more backwater pool area than A-1 (Figure 4-2). Sites B-1 and B-2 (Figure 4-2) had similar areas of glide, pool, and run, but B-2 had a small area of riffle, and B-1 had a small area of backwater pool.

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33 Figure 4-1. Percent coverage of in-stream ha bitat units for each sampling site (A-1 through D-2).

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34 Figure 4-2. Percent coverage of in-stream ch annel units for each sampling site (A-1 through D-2).

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35 Sites within watershed C were dominated by runs and glides at C-1 and C-2, respectively. C-1 had areas with riffles, wh ereas C-2 had backwater pools (Figure 4-2). Sites within watershed D were the most sim ilar in channel unit area, with all unit types represented. Runs dominated the stream, with glide area s of secondary importance. Riffles were present at both D-1 and D-2 (Figure 4-2). Average canopy for all sites combined was 85% with maximum canopy cover of 87% at site B-1 and minimum (83%) at C-2. Canopy cover varied within sites, but percentages were similar among sites (Figure 4-3). Figure 4-3. Percent canopy cover for each sampli ng site (A-1 through D-2) as defined by GLA software. Data represented in box (interquartile range) and whiskers plot with median (horizontal line), m ean (circle), and outliers (star). Amounts of large woody debris (LWD) varied greatly among and within watersheds with no readily a pparent patterns (Table 4-1). A-1 and B-1 had the greatest number of total LWD. B-2, D-1, and D2 had lowest total numbers of LWD.

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36 Table 4-1. Tally of large woody debris (>10cm diameter). Environmental Measurements Repeated measures ANOVA for litter fall indicated significant (P<0.001) differences between the four sampling periods (time). There was no significant effect (P=0.92) due to sampling position (upstream/ downstream) or the interaction between position and time (P=0.62). There were no signif icant (P=0.50) differences among sites. Most litterfall in all streams occurred fr om September through January. Hardwood leaves comprised the greatest proportion of lit terfall during this time period (Figure 4-4). Figure 4-4. Average dry weight of total litterfa ll (hardwood leaves, pine, woody debris, and mast) across sites with proportion of total litterfall as leaves (hardwood leaves) in grey.

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37 There were no significant differences among sites for periphyton chlorophyll a mean concentrations in July (P=0.49) a nd August (P=0.59) samples (Table 4-2). June 2003 samples are not reported due to an analytical error. Table 4-2. Mean peri phyton chlorophyll a and dry weight. Mean macrophyte dry weight. Periphyton ash free dry wei ght was significantly diffe rent (P<0.001) among sites for June, July and August sampling dates. Generally, sites within the same watershed were similar, and mean weight decreased from watershed A to D (Figure 4-5). Macrophyte dry weights among sites were not si gnificantly different for June (P=0.07) and August (P=0.06) samples, but were di fferent (P=0.005) between July 03 samples (Figure 4-6). A1, B1, C1, D1 and D2’s mean biomass was very low (<3 g/m2) and were not significantly different, whereas A2, B2, and C2 had greater biomass of macrophytes (Figure 4-6 and Table 4-2). Chemical and Hydrological Measurements Average daily-flow for the study period (J uly 2001-February 2003) was highest in watershed C (2.66 L/s), followed by B (2.16 L/ s), D (1.29 L/s), and A (1.02 L/s). The number of days out of 638 days with zero flow was 161 (25%) for watershed A, 6 (1%) for watershed B, 2 (0.3%) for watershed C, and 206 (32%) for watershed D. Monthly mean water temperature displayed little variation among sites (Figure 4-7) with lowest values in January and February and highest from June through September.

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38 Figure 4-5. Periphyton ash free dry weight. A) June 2003, B) July 2003, C) August 2003. Data represented in box (interquartile ra nge) and whiskers plot with median (horizontal line), mean (c ircle), and outliers (star).

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39 SiteMacrophyte dry weight (g/m2) D-2 D-1 C-2 C-1 B-2 B-1 A-2 A-1 100 80 60 40 20 0 Figure 4-6. Macrophyte dry wei ght (July 2003). Data repres ented in box (interquartile range) and whiskers plot with median (horizontal line), mean (circle), and outliers (star). 5 10 15 20 25 30Oct-01 No v -01 De c -01 Ja n -02 Feb 02 Ma r02 Ap r02 M ay -0 2 J un -0 2 Ju l-0 2 Au g-0 2 Se p -02 O ct0 2 Nov-02 De c -02 Jan-03 Feb 03 Mar 03 Apr-03 M ay -0 3 J un -03 J u l-03 A u g-0 3 Se p-0 3 O ct03 Nov -0 3 Dec -0 3Water TemperatureoC A B C D Figure 4-7. Monthly mean water temperature. Dissolved oxygen values across sites ranged from 0.270 mg/L in September 2001 at A2 to 10.5 mg/L in January 2002 at D1 (Table 4-3). Average dissolved oxygen was lowest in watershed A (Figure 4-8).

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40 Table 4-3. Mean, minimum, and ma ximum in-situ water chemistry. MeanA-1 A -2B-1B-2C-1C-2D-1D-2(min-max) Temperature 18.118.118.318.618.318.718.518.5oC (10.2-23.9)(9.3-24.4)(10.4-24.4)(10.5-24.5)(11.1-24.4)(11.5-25.2)(10.7-24.5)(11.9-24.0) DO 4.113.994.795.016.646.266.695.29 mg/L (0.98-8.78)(0.27-7.60)(.97-8.17)(0.62-7.86)(1.59-9.68)(1.91-9.60)(2.20-10.56)(1.56-9.25) pH 4.94.55.85.96.76.66.96.7 (3.5-5.8)(3.3-5.6)(4.1-6.9)(4.3-6.6)(5.1-8.0)(5.1-7.5)(5.1-7.8)(5.1-7.3) Turbidity 2.141.546.136.926.778.484.974.78 NTU (0.35-7.70)(0.00-7.20)(2.20-19.00)(1.90-52.10)(2.30-16.00)(2.40-63.00)(2.60-15.00)(0.55-28.00) Specific Conductance 39.231.7106.595.698.986.4100.190.6 mS/cm (23.0-70.8)(24.0-80.2)(25.8-272.0)(26.0-360.0)(25.4-157.8)(26.6-154.2)(50.8-166.2)(25.4-179.4) NH40.0110.0070.0320.0370.0050.0200.0060.006 ug/L (0.000-0.097)(0.000-0.025)(0.000-0.150)(0.000-0.180)(0.000-0.032)(0.000-0.071)(0.000-0.023)(0.000-0.066) Inorganic N 0.0020.0010.4120.8500.8721.1880.0100.020 ug/L (0.000-0.018)(0.000-0.007)(0.000-1.245)(0.000-2.419)(0.029-1.414)(0.031-1.785)(0.000-0.219)(0.000-0.222) Inorganic P 0.0030.0060.0040.0030.0060.0040.0350.053 ug/L (0.001-0.005)(0.000-0.081)(0.000-0.014)(0.000-0.011)(0.003-0.012)(0.002-0.007)(0.015-0.073)(0.012-0.130) Figure 4-8. Monthly mean dissolved oxygen. A) Site A-1 and A-2. B) Site B-1 and B-2. C) Site C-1 and C-2. D) Site D-1 and D-2. indicates no data due to equipment malfunction. ** indicates no data due to a no flow period.

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41 Figure 4-9. Monthly mean pH. A) Site A-1 and A-2. B) Site B-1 and B-2. C) Site C-1 and C-2. D) Site D-1 and D-2. indicates no data due to equipment malfunction. ** indicates no data due to a no flow period. pH ranged from 3.3 recorded in February 2003 in A2 to 8.0 in December 2001 at C1 (Table 4-3, Figure 4-9). Mean pH increas ed from watershed A to D (Table 4-3). Average turbidity was lowest in watershed A, followed by watershed D, with watersheds B and C having highest values. Overall, mean turbidity at all sites was very low (<10 NTU) (Table 4-3). Mean specific conducta nce was lowest in watershed A, with watersheds B, C, and D having hi ghest mean values (Table 4-3). Inorganic nitrogen in watersheds A and D was consistently very low with average concentrations < 0.05 mg/L (Table 4-3). Wate rsheds B and C had average concentrations an order of magnitude higher. An additio nal monitoring site at the upstream boundary (B-B, C-B) between the study site and an adjoining landowner for watersheds B and C

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42 had consistently higher c oncentrations of inorganic N (Figure 4-10). Inorganic phosphorus average concentrations for wate rsheds A, B, and C were <0.0065 mg/L; however, concentrations in watershed D were an order of magnitude higher (Table 4-3). Figure 4-10. Monthly mean inorganic nitrogen. A) Site A-1 and A-2. B) Site B-1 and B2. C) Site C-1 and C-2. D) Site D-1 and D-2. indicates no data due to equipment malfunction. ** indicates no data due to a no flow period. The first two axes of the water chemis try PCA explained 56% of the variation (Figure 4-11), but inclusion of the third axis explained an additional 20% of the variation (Figure 4-12). Turbidity and specific conductance were positiv ely correlated with Axis 1 (r2 = 0.689 and 0.718, respectively). Dissolved oxygen was negativel y correlated with Axis 2 (r2 = 0.809). Inorganic phosphorus was po sitively correlated with Axis 3 (r2 = 0.773). Watershed A was characterized by lowe r turbidity, specific conductance, pH, and dissolved oxygen. Watershed D was char acterized by higher va lues of inorganic

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43 phosphorus. The PCA did not separate wate rshed B and C based on water chemistry variables. Figure 4-11. First and second ax es of the principal component s analysis (PCA) for in-situ water chemistry data at all sites from September 2001-December 2003. Macroinvertebrates A total of 17,034 individuals representing 126 taxa were collected from the four streams during the study (Appendix). Overall, dipterans were the most diverse insect order with 63 taxa, 44 of which were in the family Chironomidae. Coleoptera contributed 23 taxa, Trichoptera 12, Epheme roptera 11, Odonata 9, Plecoptera 4 and Megaloptera 2.

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44 Figure 4-12. First and third axes of the prin cipal components analys is (PCA) for in-situ water chemistry data at all sites from September 2001-December 2003. Dipterans dominated assemblages in all streams, comprising >60% of total abundance. The composition of orders in wate rsheds B and C were most similar with Diptera comprising 80% and 82% of individuals, and othe r orders at 20% and 18%, respectively. Watershed A had < 1% of total individuals from the most sensitive orders, Ephemeroptera, Plecoptera, and Trichoptera (E PT), while watershed D had the most at 23%. Amphipods and Isopods comprised 24% an d 10% of total individuals, respectively, in watershed A; whereas waters heds B, C, and D all had < 2% representation from these orders (Figure 4-13).

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45 The following taxa considered sensitive to human disturbance in Florida (Fore 2003, as cited in FDEP 2004) were collected: Crangonyx, Microtendipes, Parametriocnemus, Rheocricotopus, Tr ibelos juncundum, Acerpenna pygmaea, Ephemerella, Eurylophella, Stenonema, Habr ophlebiodes, Lept ophlebia, Caecidotea, Amphinemura, Ciloperla, Perl esta, Allocapnia, Triaenodes and Chimarra (Appendix A). These 18 taxa comprised 14 % of total taxa in the streams. Cordulegaster sayi which has been identified as a rare and vulnerable odonate of the southeastern Piedmont and Coastal Plain (Morse et al. 1997), was co llected in watersheds C and D. The following taxa were collected only at one site, with those considered sensitive to human disturbance in Florida (Fore 2003, as cited in FDEP 2004) designated with (s). Tribelos fuscicorne, Pseudosmitta sp ., and Smittia sp were only collected in watershed A. The isopod Caecidotea (s) was abundant only at site A2; however, one individual was also found at A1, B1, and D1. Paracladopelma sp., Odontomesa fulva, Rhyacophia carolina, and Polycentropus were unique to watershed B. Watershed C had the greatest number of site specific taxa: Brillia flavifrons, Baetis intercalaris, Eurylophella doris (s), Hexagenia, Cheumatopsyche, Triaenodes (s), and Agarodes Rheocricotopus tuberculatus (s), Eukiefferiella claripennis, Zavrelia sp., Molanna blenda and Allocapnia (s) were found only at watershed D. Abundance Mean abundance per sample for all s ites across all sampling periods was 436 individuals, and indivi dual values ranged from a maximum at C2 (1896) in February 2003 to a minimum at B1 (19) in December 2001 (Figure 4-14). Invertebrate abundance genera lly increased at each site across time. For example, abundance at B2 increased from 86 in December 2001 to 202 in February 2002, to 370 in

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46 Figure 4-13. Partitioning of to tal abundance by invertebrate orders in study streams over the entire study period. A) Stream A. B) St ream B. C) Stream C. D) Stream D.

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47 Figure 4-14. Macroinvertebrate abundance (tot al number of individuals) for upstream and downstream sites of each stream (A-D) over the entire study period. December 2002, and finally 693 in Februa ry 2003. Repeated measures ANOVA (Table 4-4) indicated sign ificant (P<0.001) differences between the four sampling periods. There was no significant effect due to sampling position, i.e. upstream/downstream (P=0.38) or the interaction between pos ition and time (P=0.72). The December 2001 sample had significantly lower abundance than February 2002 (P=0.03). December 2002 and February 2002 samples were not signi ficantly different. December 2002 had significantly lower abundance than February 2003 (P<0.001) (Figure 415). Differences among streams were marginally significant (P=0.05) (Tab le 4-5). Highest mean abundance was in watershed C followe d by D, B, and A (Figure 4-16). Dominant Taxa The dominant taxon (i.e. percent dominan ce of the single most abundant taxon) varied across sampling periods and between si tes. Single taxon dominance ranged from 54% at D2 in February 2002, to 8% at C2 in December 2001 (Figure 4-17). 21 of the 32

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48 Table 4-4. Repeated measures analyses for effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and position (upstream vs. downstr eam) on macroinvertebrate metrics. Significant results are highlighted. Metric Source of variation dfMSFp A bundanceBetween sub j ects Position10.0130.8920.38 error60.014 Within sub j ects Time 1.6382.46021.167<0.001 Position*Time1.6380.032120.2760.72 error ( time ) 9.8310.116% Dominant TaxonBetween sub j ects Position10.0000.0560.82 error60.006 Within sub j ects Time30.0110.5790.630 Position*Time30.0060.3010.820 error ( time ) 180.020Total TaxaBetween subjects Position10.9450.0490.83 error619.299 Within sub j ects Time 3380.94810.663<0.001 Position*Time315.1150.4230.73 error ( time ) 1835.726EPT TaxaBetween sub j ects Position13.1250.2210.65 error614.141 Within subjects Time 333.4587.860.001 Position*Time34.3331.0180.40 error ( time ) 184.257Chironomidae TaxaBetween sub j ects Position10.1950.0910.77 error62.154 Within sub j ects Time330.1982.8520.06 Position*Time319.5311.8450.17 error (time)1810.587% ChironomidaeBetween subjects Position10.0020.3590.57 error60.006 Within sub j ects Time30.0442.0590.14 Position*Time30.1265.9210.005 error ( time ) 180.021% DipteraBetween sub j ects Position10.0170.8390.39 error60.021 Within sub j ects Time30.0080.270.84 Position*Time30.010.3520.78 error ( time ) 180.028

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49 0 200 400 600 800 1000 1200 1400Dec 01Feb 02Dec 02Feb 03TimeNumber of individuals* **value is significantly different (P<0.05) from the previous time period Figure 4-15. Mean macroinvertebrate abunda nce individual sampling periods with standard error and repeated contrast results (alpha = 0.05). Letters above bars indicate statistical groupings. samples were dominated by Chironomidae with 7 of the 21 dominated by Parametriocnemus a taxon sensitive to disturbance in Florida (Fore 2003, as cited in FDEP 2004). In the February 2002 samples, 5 of 8 sites were dominated by the predator Conchapelopia sp .. Repeated measures ANOVA found no significant effects due to time of sampling, position, or an in teraction between position and time (Table 4-4). No significant differences were detect ed between streams (Table 4-5). Total Taxa Overall taxa richness displayed no clear trend between sites, but the December 2001 sampling period had the lowest values. D1 had the highest taxa richness (42) in December 2002, and B1 had the lowest (7) in December 2001 (Figure 4-18).

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50 Table 4-5. Repeated measures analyses for effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and stream (A, B, C, D) on macroinvertebrate metr ics. Significant results are highlighted. Metric Source of variation dfMSFp A bundanceBetween sub j ects Stream30.0276.4070.05 error40.004 Within sub j ects Time 31.34426.272<0.001 Time*Stream90.0651.2630.34 error ( time ) 120.051% Dominant TaxonBetween sub j ects Stream30.0061.5440.33 error40.004 Within sub j ects Time30.0111.3120.31 Time*Stream90.033.4250.02 error ( time ) 120.009Total TaxaBetween subjects Stream 335.25812.8580.01 error42.742 Within sub j ects Time 1.665686.4779.1860.010 Time*Stream4.99438.1990.5110.76 error ( time ) 6.65974.728EPT TaxaBetween sub j ects Stream 325.0527.8210.03 error43.203 Within subjects Time 333.4586.0150.01 Time*Stream92.5420.4570.87 error ( time ) 125.562Chironomidae TaxaBetween sub j ects Stream30.9870.3890.76 error42.539 Within sub j ects Time1.9446.6982.0720.19 Time*Stream5.8212.7630.5660.74 error (time)7.7622.535% ChironomidaeBetween subjects Stream30.0051.1720.42 error40.005 Within sub j ects Time30.0440.9680.44 Time*Stream90.0240.5350.82 error ( time ) 120.045% DipteraBetween sub j ects Stream30.0312.5370.19 error40.012 Within sub j ects Time1.5980.0140.4180.63 Time*Stream4.7930.0661.9390.21 error ( time ) 6.3910.034

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51 0 200 400 600 800 1000 1200ABCDStreamsNumber individuals Figure 4-16. Means for macroinvertebrate abun dance for all sites within each stream for all time periods with standard error. 0 10 20 30 40 50 60 70 80 90 100A1 A2B1B2C1C2D1D2% Dominant Taxon Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-17. Percent dominant taxon for upstr eam and downstream sites of each stream (A-D) over the entire study period.

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52 0 5 10 15 20 25 30 35 40 45A1 A2B1B2C1C2D1D2Taxa Richness Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-18. Taxa richness for upstream and do wnstream sites of each stream (A-D) over the entire study period. Significant (P<0.001) differences between four sampling periods (time) were detected by repeated measures ANOVA (Table 4-4). There was no significant effect due to sampling position (upstream/downstream) or the interaction between position and time. The December 2001 sample had significantly lower taxa richness than February 2002 (P=0.03). The remaining sampling periods were not significantly different (Figure 4-19). Differences (P=0.01) were detected between streams (Table 4-5); however, multiple comparisons between streams were not significant. Means showed highest total taxa in watershed C followed by D, B, then A (Figure 4-20). EPT Taxa The number of EPT taxa (Ephemeroptera, Trichoptera, and Plecoptera taxa) was consistently highest at C1. Bo th sites in watershed A had the lowest number of EPT taxa (Figure 3.22). Repeated measures ANOVA (Tab le 4-4) indicated si gnificant (P=0.001) differences between the four sampling periods (time), but there wa s no significant effect due to sampling position (upstream/downstream ) or the interaction between position and

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53 time. Differences between the Decemb er 2001 and February 2002 sample were marginally significant (P=0.1). The Decembe r 2002 sample had significantly lower EPT taxa than February 2003 (P=0.002). The remaining sampling periods were not significantly different (Figure 4-22). Differences (P=0.03) were detected between streams (Table 4-5), with A having significantly lowe r EPT taxa than C (P=0.03) (Figure 4-23). 0 5 10 15 20 25 30 35 40Dec 01Feb 02Dec 02Feb 03 TimeTaxa richness**value is significantly different (P<0.05) from the previous time period Figure 4-19. Mean taxa richness for individua l sampling periods with standard error and repeated contrast results (a lpha = 0.05). Letters above bars indicate statistical groupings. Chironomidae Taxa A total of 44 species of Chironomidae were identified from four subfamilies (Chironominae, Orthocladiinae, Prodiamesi nae, Tanypodinae). The subfamilies were represented at all sites with the exception of the Prodiamesinae (Figure 4-24), which was represented by a single species, Odontomesa fulva and was only found at site B1 on one occasion. B2 had the lowest Chironomidae taxa richness in December 2001 (3), and D2

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54 0 5 10 15 20 25 30 35 40ABCDStreamTaxa richness Figure 4-20. Taxa richness for each stream for all time periods with standard error. 0 2 4 6 8 10 12 14 16 18A1 A2B1B2C1C2D1D2EPT taxa Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-21. Total Ephemeroptera, Plecopter a, and Trichoptera (EPT) taxa for upstream and downstream sites of individual st reams (A-D) over the entire study period.

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55 0 2 4 6 8 10 12Dec 01Feb 02Dec 02Feb 03TimeEPT Taxa**value is significantly different (P<0.05) from the previous time period Figure 4-22. Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa within each time period with standard error and rep eated contrast results (alpha = 0.05) across time. Letters above bars indicate statistical groupings. 0 2 4 6 8 10 12ABCDStreamEPT Taxab a ab ab Figure 4-23. Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa for all sites within each stream for all time periods and pairwise multiple comparison test results (Tukey’s honestly significant difference (HSD) test, alpha = 0.05). Letters above bars indica te statistical groupings.

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56 had the greatest (17) in December 2002 (Figure 4-25). Tanytarsus sp., Tribelos sp., Parametriocnemus sp., Conchapelopia sp. and Zavrelimyia sp occurred at all sampling sites. Repeated measures ANOVA detected no differences due to time, position, or site (Table 4-4 and 4-5). 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%A1A2B1B2C1C2D1D2% Total Density Chironominae Orthocladiinae Prodiamesinae Tanypodinae Figure 4-24. Mean subfamily composition of Chironomidae in individual streams (A-D) over the entire sampling period. Percent Chironomidae The lowest and highest percentage of a sample composed of Chironomidae was found, respectively, at site D2 with 19% in December 2002 and 82% in December 2001 (Figure 4-26). Seventy-two percent of sa mples contained >50% Chironomidae. There were no significant effects due to time of sampling, sampling position, or interaction between position and time (Table 4-4 and 4-5).

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57 0 2 4 6 8 10 12 14 16 18A1 A2B1B2C1C2D1D2# Chironomidae taxa Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-25. Number of Ch ironomidae taxa for upstream and downstream sites of individual streams (A-D) over the entire study period. 0 10 20 30 40 50 60 70 80 90 100A1 A2B1B2C1C2D1D2% Chironomidae Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-26. Percentage of total abunda nce contributed by Chironomidae for upstream and downstream sites of individual st reams (A-D) over the entire study period.

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58 Percent Diptera Eighty-four percent of samp les had >50% Diptera, and 47% of samples had >75% Diptera. Minimum and maximum values for percent Diptera were December 2001 at A2 (29%) and D2 (96%) (Figure 4-27) Repeated measures ANOVA detected no differences due to time, position, or s ite (Table 4-4 and 4-5). 0 10 20 30 40 50 60 70 80 90 100A1 A2B1B2C1C2D1D2% Diptera Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-27. Percentage of total abundan ce contributed by Diptera for upstream and downstream sites of individual streams (A-D) over the en tire study period. Percent Elmidae All sites had <20% of the family Elmidae, which are a family of beetles which prefer swifter parts of str eams such as oxygen rich riffles (Merritt and Cummins 1996). Sites in A and B had no occurrences of el mids in the December 2001 and February 2002 sampling period with site A1 having no o ccurrences in any sample (Figure 4-28).

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59 Repeated measures ANOVA detected no si gnificant differences due to position (Table 4-6), but significant differences due to time (P< 0.001), site (P=0.003), and an interaction between time and si te (P=0.002) (Table 4-7). Figure 4-29 illustrates the interaction becau se the lines are not parallel, implying that the effect of site up on percent Elmidae depends upon the time period examined. This interaction seems to be the result of the December 2001 sampling period having highest mean percent Elmidae at C, where the rema ining sampling periods have highest mean percent Elmidae at D. The December 2002 sampling period had the highest mean percent Elmidae compared to the remaini ng sampling periods (Figure 4-29) and D had highest mean percent Elmidae, followed by C, B, and A. 0 2 4 6 8 10 12 14 16 18 20A1 A2B1B2C1C2D1D2% Elmidae Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-28. Percent of the total assembla ge represented by Elmidae for upstream and downstream sites of individual streams (A-D) over the en tire study period.

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60 Table 4-6. Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and position (upstream vs. downstream) on macroinvertebrate metrics. Significant results are highlighted. Clin g er TaxaBetween sub j ects Position123.2055.2240.06 error64.442 Within sub j ects Time31.8410.9450.44 Position*Time311.6545.980.005 error ( time ) 181.949% Filterin g CollectorsBetween subjects Position10.0062.710.15 error60.002 Within sub j ects Time30.0231.990.15 Position*Time30.0131.1470.35 error ( time ) 180.012% ElmidaeBetween sub j ects Position10.0000.0170.89 error60.004 Within sub j ects Time1.2180.0093.8540.08 Position*Time1.2180.0010.4960.53 error ( time ) 7.3070.002FL SCIBetween subjects Position1204.9050.4050.54 error6505.827 Within sub j ects Time375.2791.0310.40 Position*Time3208.1512.8520.06 error ( time ) 1872.992GA AASBetween sub j ects Position10.6330.0140.91 error645.82 Within sub j ects Time 3276.86519.850<0.001 Position*Time35.5310.3970.75 error ( time ) 1813.948EPDBetween subjects Position18.0000.0440.84 error6183.875 Within sub j ects Time 3327.1673.2200.04 Position*Time389.5000.8810.47 error ( time ) 18101.611EPD (200 individual subsample)Between sub j ects Position15.2810.0250.87 error6209.99 Within subjects Time 3323.2083.3570.04 Position*Time353.3750.5540.65 error ( time ) 1896.292

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61 Table 4-7. Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb 03) and stream (A, B, C, D) on m acroinvertebrate metrics. Significant results are highlighted. Clin g er TaxaBetween sub j ects Stream38.6011.430.35 error46.014 Within sub j ects Time31.8410.3670.77 Time*Stream91.0980.2190.98 error (time)125.013% Filterin g CollectorsBetween sub j ects Stream30.0041.7440.29 error40.002 Within sub j ects Time30.0231.970.17 Time*Stream90.0121.0260.47 error (time)120.012% ElmidaeBetween sub j ects Stream 30.00234.0750.003 error40.000 Within sub j ects Time 30.00313.88<0.001 Time*Stream 90.0026.4640.002 error (time)120.000FL SCIBetween sub j ects Stream3215.5185.2750.07 error440.853 Within sub j ects Time1.158194.9621.1370.35 Time*Stream3.475329.2291.9210.25 error (time)4.633171.406GA AASBetween sub j ects Stream 387.25825.3270.005 error43.445 Within sub j ects Time 3276.86527.149<0.001 Time*Stream916.1421.5830.22 error (time)1210.198EPDBetween sub j ects Stream 3329.18810.6460.02 error430.922 Within sub j ects Time 3327.1673.5010.50 Time*Stream9108.4721.1610.390 error (time)1293.437EPD (200 individual subsample)Between sub j ects Stream3328.8024.7170.08 error469.703 Within sub j ects Time 3323.2084.3890.02 Time*Site9112.1811.5230.24 error (time)1273.646

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62 Figure 4-29. Interaction plot (d ata means) for percent Elmidae. Site 1, 2, 3, 4, represents A, B, C, D, respectively and Time 1,2,3,4 represents Dec 01, Feb 02, Dec 02, and Feb 03, respectively. Feeding Type and Habitat Type The relative contribution of functional feed ing groups to the to tal assemblage of each stream varied. The assemblages of B, C, and D were co-dominated by shredders, predators, and collectors, while collectors we re dominant in A (Figure 4-30). Within the collector functional feeding group, collector-gat herers were dominant over filter feeders. Each site for all sampling periods had <15% filter feeders (Figure 4-31), which are thought to be sensitive in low gradient stream s with high percent filter feeders indicating healthy coastal plain streams (Barbour et al. 1996). Rep eated measures ANOVA detected no differences due to time, positi on, or site (Table 4-6 and Table 4-7). The number of clinger taxa generally in creased at each site from December 2001 through February 2003 (Figure 4-32); however there was no significant effect due to

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63 time of sampling, sampling position, or intera ction between position and time (Table 4-6 and Table 4-7). 4% 7% 9% 20% 22% 27% 27% 32% 34% 30% 39% 31% 5% 6% 4% 6% 4% 24% 66% 2%0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%ABCDFunctional Feeding Group (%) Unknown Scrapers Shredders Predators Collector-gatherers Filter feeders Figure 4-30. Percentage of th e total assemblage contribute d by individual functional feeding groups for individual stream s (A-D) over the entire study period. 0 5 10 15 20 25A1 A2B1B2C1C2D1D2% Filter Feeders Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-31. Percentage of the total assemblage represented by filter feeders for upstream and downstream sites of individual st reams (A-D) over the entire study period.

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64 0 2 4 6 8 10 12A1 A2B1B2C1C2D1D2# Clinger Taxa Dec-01 Feb-02 Dec-02 Feb-03 Figure 4-32. Clinger taxa for upstream and dow nstream sites of individual streams (A-D) over the entire study period. Biotic Indices The Florida Stream Condition Index (SCI) scored A1 as Very Poor for every sampling period (Figure 4-33). Decemb er 2001, February 2002, and February 2003 samples for A2 scored Poor, while the Decem ber 2002 sample fell within the Very Poor category. The earliest sample for B1, December 2001, scored Very Poor, with the remaining samples in the Poor category. December 2001, December 2002, and February 2003 samples for B2 scored Poor, while Febr uary 2002 was Fair. C1 had the greatest number of samples (December 2001 and Decembe r 2002) in the Fair category, with the remaining samples, February 2002 and Februa ry 2003, listed as Poor. All C2 samples scored Poor. December 2001, February 2002, and February 2003 samples for D1 scored Poor, while the December 2002 sample fell into the Fair category. All D2 samples scored Poor.

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65 0 10 20 30 40 50 60 70 80 90 100 A1 A2B1B2C1C2D1D2FL SCI Score Dec-01 Feb-02 Dec-02 Feb-03Very Poor Poor Fair Good Figure 4-33. Florida Stream Condition Index (SCI) scores for upstream and downstream sites of each stream (A-D ) over the entire study period. Repeated measures ANOVA did not detect significant differences due to time, position, or site (Table 4-6 a nd Table 4-7). Overall, the Fl orida SCI scored 9.4% of the samples for the eight sites as Fair, 59.3% Poor, and 31.3% Very Poor No sites were classified as Good. C1 and A1 had the highest and lowest average sc ore, respectively, for every sampling period. Results from the Georgia Environmenta l Protection Division (EPD) Biological Assessment were more favorable. 12.5% of sc ores for the four samples each at the eight sites were Very Good, 53.1% Good, 21.9% Fair 6.3% Poor, and 3.1% Very Poor when compared to the Georgia DNR reference str eam from the Southeastern Plains Ecoregion, Tifton Upland sub-ecoregion. A1 and A2 D ecember 2001 samples scored Poor, but the February 2002, December 2002, and February 2003 samples of both scored Fair (Figure 4-34). The December 2001 sample for B1wa s the only one in the study to score Very Poor. The remainder of B1 samples sc ored Good. December 2001 and February 2002

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66 samples for B2 scored Good, while the December 2002 sample fell into the Good condition, and the February 2003 was in the Ve ry Good category. C1 had the greatest number of samples (December 2002, February 2002, and February 2003) in the Very Good condition, with one sample (December 2001) in the Good category. All samples for C2 scored in the Good category. December 2001 and February 2003 samples for D1 scored Good, while the February 2002 sa mple scored Fair, and the December 2002 sample scored Very Good. All samples for D2 scored Good (Figure 4-34). 0 10 20 30 40 50 60 70 80 90 100 A1A2B1B2C1C2D1D2Ecological Condition Score 12/01 2/02 12/02 2/03 Very Poor Poor Fair Good Very Good Figure 4-34. Georgia EPD Biological Assessm ent scores for upstream and downstream sites of each stream (A-D ) over the entire study period. For the Georgia EPD Biological Assessment applied to a 200 individual subsample, as called for in Georgia EPD standard ope rating procedures, site condition scores changed slightly from results presented above, with 11 samples increasing by 10%, 11 samples decreasing by 10%, and 10 sites rema ining unchanged. Overall scores improved slightly with 15.6% listed as Very G ood, 56.2% Good, 18.8% Fair, 6.2% Poor, and 3.1% Very Poor (Figure 4-35). For both the complete and 200 individual subsample, the

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67 Georgia EPD Biological Assessment was simila r to the Florida SCI in scoring C1 the highest and A1 the lowest across all sampling periods. 0 10 20 30 40 50 60 70 80 90 100 A1A2B1B2C1C2D1D2Ecological Condition Score (200 individual subsample) 12/01 2/02 12/02 2/03 Very Poor Poor Fair Good Very Good Figure 4-35. Georgia EPD Biological Assessm ent scores (based on a 200 individual subsample) for upstream and downstream sites of each stream (A-D) over the entire study period. Repeated measures ANOVA detected weak but significant differe nces due to time (Table 4-6) for the Georgia EPD Biological Assessment scores calculated from both the complete sample (P=0.04) and 200 indi vidual subsample (P=0.04), with varying significance between specific time periods. For the complete sample (P=0.08) (Figure 436) and 200 individual subsample (P =0.04) (Figure 4-37), December 2002 had significantly higher scores than February 2002, although results from the complete sample were marginally significant. No diffe rences were detected due to position (Table 4.6). A significant difference (P=0.02) was found between sites for the Georgia EPD Biological Assessment scores calculated from the complete sample, but differences were not detected for the 200 indi vidual subsample (Table 4.7). For the complete sample, stream A had significantly lower scores than stream C (P=0.01) (Figure 4-38).

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68 0 10 20 30 40 50 60 70 80 90 100Dec 01Feb 02Dec 02Feb 03TimeGA EPD Index**value is significantly different (P<0.05) from the previous time period Figure 4-36. Means for GA EPD Index for all streams combined during each time period with standard error and repeated cont rast results (alpha = 0.05) across time. 0 10 20 30 40 50 60 70 80 90 100Dec 01Feb 02Dec 02Feb 03TimeGA EPD Index (200 individual subsample)**value is significantly different (P<0.05) from the previous time period Figure 4-37. Means for GA EPD Index for all sites combined (200 individual subsample) within each time period with standard error and repeated contrast results (alpha = 0.05) across time.

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69 0 10 20 30 40 50 60 70 80 90 100ABCDStreamGA EPD Indexa ab b abc Figure 4-38. Means for GA EPD Index (indiv idual streams for th e entire study) and pairwise multiple comparison test results (Tukey’s honestly significant difference (HSD) test, alpha = 0.05). Lette rs above bars indicate statistical groupings. The Georgia Adopt-A-Stream water quali ty rating was excellent for 50% of samples, good for 12.5%, fair for 12.5%, and poor for 25%. Five of eight sites collected in December 2001 were rated as having poor wa ter quality (Figure 4-39). Repeated measures ANOVA found signi ficant differences due to time (P<0.001) and site (P=0.005), but not for position (Table 4-6 a nd Table 4-7). The December 2001 samples had significantly (P=0.008) lower scores th an February 2002. February 2003 samples had significantly higher scores when compared to December 2002 (P=0.03) (Figure 4-40). Scores from stream A were significantly lower than scores for stream B (P=0.02), C (P=0.006), and D (P=0.006) (Figure 4-41).

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70 0 5 10 15 20 25 30 35 40 45A1A2B1B2C1C2D1D2GA AAS Index Value 12/01 2/02 12/02 2/03 Poor Fair Good Excellent Figure 4-39. Georgia Adopt-A-Stream Index scor es for upstream and downstream sites of each stream (A-D) over the entire study period. 0 5 10 15 20 25 30 35 40 45Dec 01Feb 02Dec 02Feb 03 TimeGA AAS Index* **value is significantly different (P<0.05) from the previous time period Figure 4-40. Means for GA AAS Index for all sites combined within each time period with standard error and repeated cont rast results (alpha = 0.05) across time.

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71 0 5 10 15 20 25 30 35 40 45 ABCDStreamGA AAS Indexa b b b Figure 4-41. Means for GA AAS Index (indiv idual streams for th e entire study) and pairwise multiple comparison test results (Tukey’s honestly significant difference (HSD) test, alpha = 0.05). Lette rs above bars indicate statistical groupings. The Georgia Ecological Condition Worksheet was used to compare among sites for year to year, downstream vs. upstream, and st ream to stream. Sites with lower percent comparability scores indicate greater similarity between sites, and higher scores indicate greater dissimilarity between sites. A score of 0 indicates 100% comparable assemblages, as shown in the comparison of B1 (study site) and C1 (reference) for the February 2002 samples (Table 4-8). Year to year site comparisons indicate generally higher percent comparability in year two (February 2002 to Fe bruary 2003) of the study compared to year one (December 2002 to December 2003) (Table 4-9). Downstream vs. upstream percent comparability varied more in watersheds B and C across time than watersheds A and D (Table 4-10).

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72 Table 4-8. Sample comparison of sites (B1 vs. C1 for February 2002) 5310 Taxa Richness (Total # Taxa) 3537 >3030-16<1655 EPT Index 514 >66-4<435 # Chironomidae Taxa1611 >88-5<555 % Contribution of Dominant Taxon 2823 <2323-61>6133 % Diptera9168 -----<51>5011 Florida Index1316>1515-8<8 55 % Filterers82 >1111-6<631 Total Habitat Score:>89%89-75%74-60%<59% Total Points Earned 2525 % of Difference 100 % of Difference 0ECOLOGICAL CONDITION WORKSH EET FOR B1 and C1 (2-02)C1 Data: SOUTHEASTERN PLAINS (65) SCORE RANGES C1 Score: 100 METRIC:B1 Data:B1 Score: Table 4-9. Percent comparability scores fo r year to year comparison of sites. A1 A 2B1B2C1C2D1D2 12-01 vs 12-021531156112698112-02 vs 2-030120320211010Year to Year Table 4-10. Percent comparability scores for downstream vs. upstream comparison of sites. 12-012-0212-022-03 A1 vs A21512120B1 vs B25321108C1 vs C2032269D1 vs D221191921Downstream vs Upstream Table 4-11 displays three wa tershed to watershed comparisons in grey or white boxes for each watershed for one sampling date The lowest percent comparability score for each sampling date is highlighted. Across sampling dates, there is no consistently lower percent comparability score for one site over another. However, when the data are viewed for year one (12-01 to 2-02) and y ear two (12-02 to 2-03) the format shows no consistent results. Year two scores showed lowest percent comparability between A1 and D1, B1 and D1, C1 and D1 and D1 and B1.

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73 Table 4-11. Percent comparability scores for stream to stream comparison of sites. 12-012-0212-022-03 A1 vs B122 353535A1 vs C152404840A1 vs D152 122935B1 vs A131 675353B1 vs C165 0 218B1 vs D16547 100C1 vs A117679367C1 vs B1188 0 269C1 vs D1847 79D1 vs A117 13 6753D1 vs B118832 90D1 vs C19 32148Stream to Stream Multivariate Analysis The first two PCA axes explained 57% of variability in macroinvertebrate data (Figure 4-42). Points in the plot repres ent individual sites for four time periods (e.g., B11= site B1, at December 2001). The Geor gia EPD index was highly correlated with Axis 1 for both the complete sample (r2=0.91) and 200 individual subsample (r2=0.89). EPT taxa, Georgia AAS index, and total taxa we re also strongly correlated with Axis 1 (r2=0.71, 0.71, and 0.62, respectively). Per cent filter feeders was correlated (r2=0.58) with Axis 2. Abundance and percent dominant taxa were negatively correlated (r2=0.54 and 0.41, respectively) with the same axis. Sa mples from watershed A tended to separate along Axis 1. Regression Analysis Five models were run with: 1) all sa mples pooled (n=31), 2) December 2001 samples only (n=7), 3) February 2002 samples only (n=8), 4) December 2002 samples

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74 Figure 4-42. Principal component s ordination for macroinvertebrate metrics and indices. only (n=8), and 5) February 2003 samples only (n =8). These five models were run with water chemistry and hydrology data from one, three, and six months prior to macroinvertebrate sampling (Table 4-12). The models run with pred ictor variable data from three months prior to macroinvertebr ate sampling cumulative ly explained 51.8% of variation, whereas one and six month prior da ta explained 50.5% a nd 50.9%, respectively (Table 4-12). As a result, the remaining discus sion will be restricted to the set of models run with predictor data from three months prior to macroinvertebrate sampling. The first predictive model using all sa mples pooled (n=31) explained 82.7% of variation (Georgia AAS) to 15.8% (percent filte r feeders). The remaining models with each time period as a separate model (n =8) generally had higher adjusted R2 than the

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75 Table 4-12. Adjusted R2 values (%) for five *models: 1) all samples pooled (n=31), 2) Dec 01 samples only (n=7), 3) Feb 02 sa mples only (n=8), 4) Dec 02 samples only (n=8), 5) Feb 03 samples only (n=8). (--) = no variables entered model at alpha=0.05. A. Predictor variables in models summarized for one month prior to macroinvertebrate sampling.12345 Response Variable Average GA EPD45.8589.2480.6698.179.8678.74 GA AAS79.267.885.6168.2980.1676.21 EPT taxa67.69--90.8179.3593.0266.17 Abundance55.66----55.3181.9238.58 Total taxa55.4785.6988.1947.87--55.444 % Elmidae66.2951.2872.9694.5386.7374.358 % Dominant taxon12.1149.18------12.26 % Filter feeders9.76--------1.95 Average49.042.952.355.452.7 50.46 B. Predictor variables in models summarized for three months prior to macroinvertebrate sampling.12345 Response Variable Average GA EPD54.4683.1680.6660.6390.3473.85 GA AAS82.6570.3185.6187.5680.1681.26 EPT taxa72.8363.9290.8197.1993.9783.74 Abundance74.53----53.2671.2639.81 Total taxa61.3993.8988.19----48.69 % Elmidae43.7854.1972.9691.1881.4268.71 % Dominant taxon16.7758.83------15.12 % Filter feeders15.79--------3.16 52.7853.0452.2848.7352.14 51.79 C. Predictor variables in models summarized for six months prior to macroinvertebrate sampling.12345 Response Variable Average GA EPD52.3486.0861.7582.1994.9875.47 GA AAS63.4668.9486.2375.4663.2471.47 EPT taxa59.1470.9251.4275.5391.1869.64 Abundance68.1748.72--74.3668.451.93 Total taxa51.4788.5576.948.94--53.17 % Elmidae49.8550.9885.0492.0984.9472.58 % Dominant taxon--51.68------10.34 % Filter feeders12.89--------2.58 44.6758.2345.1756.0750.34 50.90 *Models: 1) all samples pooled (n=31), 2) Dec 01 samples only (n=7), 3) Feb 02 samples only (n=8), 4) Dec 02 samples only (n=8), 5) Feb 03 samples only (n=8). (--) = no variables entered model at alpha 0.05 *Model (%) *Model (%) *Model (%) pooled models, especially for regressions with Georgia EPD, Georgia AAS, and EPT taxa. Percent Elmidae, dominant taxa and filter feeders had the lowest number of

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76 significant regressions (Table 4-12-B). EPT taxa had the highest cumulative adjusted R2 of the response variables (83.7%) with 72.8% (Model 1-Pooled), 63.9% (Model 2December 2001), 90.8% (Model 3-February 2002), 97.2% (Model 4-December 2002), and 94.0% (Model 5-February 2003) (Table 4-12-B). Predictor variables selected for Models 1 (samples pooled), 2 (December 2001), 3 (February 2002), 4 (December 2002), and 5 (Febru ary 2003) varied. This is likely due to ANOVA results that indicated differences between time periods for abundance, EPT taxa, total taxa, Georgia EPD index, Georgi a AAS index, and percent Elmidae. As a result, one time period, February 2003, was sele cted for discussion of predictor variable results because abundance, EPT taxa, total ta xa, and Georgia AAS index had the highest average values for this time period. Als o, annual rainfall data from 1967-2003 for the study site indicated that 2003 was closest to normal climatic conditions than 2001 or 2002 (Figure 4-43). Variation in abundance was explained by average daily flow (P=0.005) for the February 2003 model (adjusted R2=71.3%). The model for EPT taxa resulted in average daily flow (P<0.001) and inorganic phosphor us (P=0.03) explaini ng 94% (adjusted R2) of variation (Table 4-13). Variation in Georgia EPD index was explained (adjusted R2=90%) by specific conductance (P=0.002) and minimum daily flow (P=0.04), while specific conductance (P=0.002) alone explained variation (adjusted R2=80%) in Georgia AAS index values (Table 4-14). Inorga nic phosphorus (P=0.006) and dissolved oxygen (P=0.04) were significant predictors (adjusted R2=81%) for percent Elmidae. Total taxa, percent dominant taxon, and percent filtering collectors did not result in significant regressions for February 2003 (Table 4-15).

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77 0 200 400 600 800 1000 1200 1400 1600 1800 200019 6 8 19 67 1 9 90 2 0 00 1 9 77 19 7 8 19 8 6 19 7 1 19 81 20 01 1 9 88 1 9 74 1999 19 8 0 19 9 3 20 0 2 19 70 1 9 72 2 0 03 1 9 87 1985 19 9 5 19 7 6 19 96 19 73 1 9 98 1 9 89 1969 19 8 4 19 7 9 19 9 2 19 82 1 9 97 1 9 91 1 9 83 1994 19 7 5Annual rainfall (mm) 2003 2001 2002 2000 Av g annual: 1353mm 1999 Figure 4-43. Total annual rainfall from 19672003 at the Bainbridge, GA station (90586) at International Paper (S RCC 2004) arranged from lowe st to highest annual values. As a result of hydrology being a significant predictor for abundance, EPT taxa, and Georgia EPD index, for the February 2003 time period, the relationship between hydrology for the entire study period was exam ined. Plots of abundance (Figure 4-44), EPT taxa (Figure 4-45), and Ge orgia EPD index (Figure 4-46 ) with average daily flow for all sites and time periods (indicated with different symbols), showed an increasing positive relationship, partic ularly for abundance. For abundance (Figure 4-47), when a linear regression fit was applied to each time period, the December 2001 and February 2002 time period had no relationship with average daily flow, but the December 2002 time period was marginally significant (P=0.09) with an r2 of 40% and finally the February 2003 time period resulted in a highly significant relationship (P=0.005) with an r2 of 75%.

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78 Table 4-13. Stepwise regression models of the relationship between EPT taxa and abundance (response) with water ch emistry and hydrology parameters (predictors). Alpha to Enter/Remove: 0.05. Response: EPT TaxaResponse: Abundance StepPredictor(s)P value R2R2 (adj) PRESSStepPredictor(s)P value R2R2 (adj) PRESS (%)(%)(%)(%) PooledPooled 1DO<0.00159572481Maxdf<0.00150493.1 2DO<0.00174721632Maxdf<0.00169672.0 Turbidity<0.001Temp<0.001 3Maxdf<0.00177741.7 Temp<0.001 Min df0.007 Dec 01Dec 01 1Temperatur e 0.0169631091No variables entered or removed Feb 02Feb 02 1Turbidity0.016357911No variables entered or removed 2Turbidity<0.001939036 NH40.005 Dec 02Dec 02 1DO0.0028178321Inorg N0.0259530.3 2DO0.002939017 Turbidity0.03 3DO0.00198979 Turbidity0.005 Inorg P0.02 Feb 03Feb 03 1Avg df0.0018785201Avg df0.00575710.1 2Avg df<0.001959314 Inorg P0.030 EPT taxa (Figure 4-48) was slightly di fferent in that the December 2001 and time period had no relationship with average daily flow, but February 2002 and December 2002 had marginally significan t regressions (P=0.17 and r2= 28%, P=0.16 and r2= 30%, respectively). Finally, the February 2003 tim e period resulted in a highly significant regression (P=0.001) for EPT and av erage daily flow with an r2 of 87%. For Georgia EPD index (Figure 4-49), when a linear regression fit was applied to each time period, the December 2001 time period had no relationship with average daily flow. February 2002 and December 2002 displayed similar trends with EPT index in that both time periods had marginally si gnificant regressions (P=0.15 and r2= 30%, P=0.09 and r2= 40%, respectively). Finally, the Februa ry 2003 time period resulted in a highly

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79 significant regression (P=0.005) for Georgia EPD index and average daily flow with an r2 of 75%. For each metric, overall the increasing positive relationship improves with each time period with a marked difference in re lationship between the December 2001 time period and February 2003. Table 4-14. Stepwise regression models of the relationship between Georgia EPD index and Georgia AAS index (response) with water chemistry and hydrology parameters (predictors). Alpha to Enter/Remove: 0.05. Response: GA EPD IndexResponse: GA AAS Index StepPredictor(s)P value R2R2 (adj) PRESSStepPredictor(s)P value R2R2 (adj) PRESS (%)(%)(%)(%) PooledPooled 1DO<0.001353354071DO<0.0016058978 2DO<0.001575441012DO<0.0018180500 SC0.001Turbidity<0.001 3DO<0.0018482463 Turbidity<0.001 InorgN0.03 Dec 01Dec 01 1Inorg N0.03645614601Inorg N0.01757046 2Inorg N0.00688832250 Inorg P0.04 Feb 02Feb 02 1SC0.0259526221pH0.001878583 2SC0.0038680347 NH40.02 Dec 02Dec 02 1SC0.0166609381Turbidity0.0037875193 2Turbidity0.0019187118 Inorg P0.04 Feb 03Feb 03 1SC0.00282793191SC0.002838095 2SC0.0029390254 Mindf0.04

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80 Table 4-15. Stepwise regression models of the relationship between percent dominant taxa, percent filter feeders, total ta xa, and percent Elmidae (response) and water chemistry and hydrology parameters (predictors). Alpha to Enter/Remove: 0.05. Response: % Dominant taxonResponse: % Filter feeders StepPredictor(s)P value R2R2 (adj) PRESSStepPredictor(s)P value R2R2 (adj) PRESS (%)(%)(%)(%) PooledPooled 1SC0.0216130.51SC0.0118150.3 Dec 01Dec 01 1pH0.0458500.21No variables entered or removed Feb 02Feb 02 1No variables entered or removed1No variables entered or removed Dec 02Dec 02 1No variables entered or removed1No variables entered or removed Feb 03Feb 03 1No variables entered or removed1No variables entered or removed Response: Total taxaResponse: % Elmidae StepPredictor(s)P value R2R2 (adj) PRESSStepPredictor(s)P value R2R2 (adj) PRESS (%)(%)(%)(%) PooledPooled 1DO<0.001514912531Inorg P0.00228260.06 2DO<0.00163619892Inorg P<0.00147430.04 Maxdf0.004Max df0.004 Dec 01Dec 01 1Inorg N0.0267611381Inorg N0.0361540.00 2Inorg N0.001959325 Turbidity0.006 Feb 02Feb 02 1SC0.0168631791Inorg P0.00476720.00 2SC0.001918893 NH40.01 Dec 02Dec 02 1No variables entered or removed1Inorg P0.00185.00820.01 2Inorg P0.00193910.01 DO0.04 Feb 03Feb 03 1No variables entered or removed1Inorg P0.0168620.01 2Inorg P0.00686810.01 DO0.04

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81 Figure 4-44. Abundance vs. average daily flow for all sites and time periods (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003). Figure 4-45. EPT taxa vs. average daily flow for all sites and time periods (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003).

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82 Figure 4-46. GA EPD Index vs. average daily flow for all sites and time periods (1December 2001, 2-February 2002, 3-December 2002, 4-February 2003). Figure 4-47. Abundance vs. average daily flow for all sites and time periods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3December 2002, 4-February 2003).

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83 Figure 4-48. EPT taxa vs. average daily flow for all sites and time periods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3December 2002, 4-February 2003). Figure 4-49. GA EPD Index vs. average daily flow for all sites and time periods with linear regression fit for each time period (1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003).

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84 CHAPTER 5 DISCUSSION AND CONCLUSIONS Discussion Macroinvertebrate Assemblages All Streams Although Diptera comprised >60% of the to tal macroinvertebrate assemblages in the sand dominated study streams, they were st ill quite diverse with EPT taxa and other taxa sensitive to disturbance being well represented. Sand is generally considered a poor substrate for macroinvertebrates because of its instability and lack of interstitial oxygen, but some macroinvertebrates are specialists of this habitat. For example, the ephemeropteran, Hexagenia limbata found in this study creates a U-shaped burrow in fine sediments, then beats it s gills to create a current through its bu rrow (Allan 1995). A study of three steephead stream s adjacent to the Dry Creek wa tershed in the International Paper Southlands Forest found that macroinvertebrate asse mblages in all streams had high diversity with some taxa typically found in the southern Appalachians (Entrekin et al. 1999). The total number of EPT taxa (genus level) from all streams of the current study (26) was greater than reported for ot her streams in southwestern Georgia, 20 (Muenz 2004), 11 (Gregory 1996), and 15 (Davis 2000). A study of low gradient, higher order streams in Georgia had 31 taxa (Be nke et al. 1984), a low gradient, low order stream in southeastern Virginia had 34 (W right and Smock 2001), and in high gradient, low order streams of North Carolina, 29 EP T taxa were present (Stone and Wallace 1998).

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85 Repeated measures ANOVA results for abundance, total taxa, EPT taxa, Georgia AAS index, Georgia EPD index, and percen t Elmidae indicated that there were differences in the macroinvertebrate a ssemblages due to sampling period. More specifically, ANOVA results for Georgia EPD index and percent Elmidae were similar with the December 2002 sampling period having significantly greater average values than December 2001 and February 2002. The reason for the similarity in higher average values for December 2002 is not apparent a nd may be coincidental because the EPD index is composed of seven metrics (taxa richness, EPT index, nu mber of Chironomidae taxa, percent contribution of dominant taxon, percent Diptera, Florida Index, and percent filterers), and Elmidae would only influence one of these metrics, taxa richness. Abundance, total taxa, EPT taxa, and GA AAS index consistently indicated that the December 2001 sampling period had significantly lower values than February 2003 and that February 2002 did not differ from Dece mber 2002. Macroinvertebrate assemblages respond to temporal variability, whether seas onal (Gibbins et al 2001, Hutchens et al. 1998) or interannual (Hutchens et al. 1998). Seasonal variation is expected in macroinvertebrate communities due to life hi story patterns, especially for taxa that complete their life cycle within one y ear. The aforementioned ANOVA results for abundance, total taxa, EPT taxa, and GA AAS i ndex indicate that se asonal variation was not the controlling factor for differences b ecause the two seasons collected in 2002 did not differ, while the same two seasons from different years, 2001 and 2003, were significantly different. Interannual variation in macroinvertebra te communities can be influenced by drought (Feminella 1996), although Hutchens et al. (1998) reported th at no consistent

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86 drought-induced pattern in macroinvertebrate assemblages was apparent. This apparent contradiction of results may be due to the substrate sampled. Hutchens et al. (1998) suggested that drought-induced effects we re possibly not detected because mixed substrates, in this case red maple litter bags, were less sensitive to disturbance than other habitats, such as bedrock outcrops. In th e study of macroinvertebrate assemblages in small streams of Alabama along a gradient of flow permanence, riffles were the substrate sampled and total taxa was found to significan tly differ between years; 1994, a wet year preceded by a dry year and 1995 a normal year preceded by a wet year (Feminella 1996). EPT taxa were not significantly different be tween years, but showed a strong positive relationship with stream perm anence (Feminella 1996). In southwestern Georgia, drought conditions occurred during 1998-2002 and resulted in an accumulated rainfall defic it of 711-1270 mm in some areas (Pam Knox, Assistant Georgia State Clim atologist, oral communication as cited in Warner and Norton, 2003). The depressed rainfall totals resulted in low average daily flows (all streams combined) that were most severe in December 2001 (1.25 L/s), then steadily increased through February 2002 (1.40 L/s) and December 2002 (1.57 L/s), to February 2003 (2.78 L/s). The biota was affected by these conditions as evidenced by the generally increasing positive relationship th rough time between average daily flow and abundance, EPT taxa, and Georgia EPD index. Poff and Ward (1989) analyzed long-term discharge records for 78 streams across the US to develop quantitative characteri zations of streamflow variability and predictability. Acknowledging that there is ge nerally a lack of empirical data on stream organisms relative to long-term flow data, this characterization was used to suggest

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87 relationships between hydrology and ecological processes. Fo r streams that have some degree of intermittency, they hypothesized th at the biological community would be trophically simple with high predictability of successi onal patterns upon resumption of flow. The results of this study support Poff and Wards hypothesis because samples collected during December 2001 (higher degree of intermittency) had lower abundance, total taxa, and EPT taxa than subsequent periods (lower degree of intermittency). Also, as streams recovered from drought conditions an d flow increased, the predictive power of the relationship between flow and metrics improved. Macroinvertebrate Assemblages Within Streams ANOVA was also used to dete ct effects due to sampling position (i.e. upstream vs. downstream), but none were detected for the metrics and indices tested. The River Continuum Concept (Vannote et al. 1980) suggests that faun al changes will occur along the length of a river due to changes in the amount and type of production along that gradient. In this study, upstream and downstream sampling positions ranged from approximately 50-250 meters apart, which is not a large enough distance to incur substantial differences in a llochthonous inputs or differen ces in primary production that would result in faunal changes. Stream or der did not change between sites sampled within each stream which also lowered the potential for instream variation. Macroinvertebrate Assemblages Among Streams Abundance, total taxa, EPT taxa, Georgia EPD index, Georgia AAS index, and percent Elmidae displayed significant differe nces among streams; however the power of these analyses was very low due to a sa mple number of two, which could have underestimated the among-stream variation. Comparisons between streams for EPT taxa,

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88 Georgia EPD index, Georgia AAS index, and pe rcent Elmidae demonstrated that stream A had significantly lower values than stream C. In general, water chemistry was different in stream A versus C, with mean specifi c conductance, pH, disso lved oxygen, turbidity, and inorganic nitrogen being lower in A. Inorganic phosphorus and dissolved oxygen we re significant predictors for percent Elmidae. Percent Elmidae ANOVA results indicated that A had significantly lower percent Elmidae than C, but that C had si gnificantly lower percent Elmidae than D. Average inorganic phosphorus concentrations (for the entire study period, upstream and downstream positions) in D (0.044 ug/L) were an order of magnitude greater than concentrations in A (0.0045 ug/L), B (0.0035 ug/L), and C (0.0053ug/L). The source of the elevated phosphorus in D is unknown, but po ssibly reflects dissolution of limestone, because D is in a relatively undisturbed condition with no fertilization or other treatments. Average dissolved oxygen (for the entire study period, upstream and downstream positions) was highest in C (6.45 mg/L), followed by D (5.99 mg/L), B (4.90 mg/L), A (4.05 mg/L). Inorganic phosphorus is often the limiting nutr ient for growth of algae and macrophytes (Allan 1995). Since 95% of individuals collected were Elmidae of the genus Stenelmis which is a scraper (Merritt and Cummins 1996) that feeds on decayed plant materials and algae (Epler 1996) the significantly higher percent Elmidae in D versus other streams is pl ausible. Mean pe riphyton chlorophyll a concentrations collected during the summer of 2003 were not significantly different among sites, but these samples only quantified the periphyton co mmunity of the sediment, not of stable substrates such as exposed rock. Since Stenelmis is also a clinger (Merritt and Cummins 1996), they would more likely be associ ated with more stable substrate.

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89 EPT taxa, Georgia EPD index, Georgia AAS index had significantly lower values in A than C. Significant predictors in regr essions for EPT taxa were average daily flow and inorganic phosphorus, specific conductan ce and minimum daily flow for Georgia EPD index, and specific conductance for the Ge orgia AAS index. Average daily flow for three months prior to the February 2003 sampling period was 2.04 L/s in A and 3.50 L/s in C. For February 2003, Pearson correlati ons indicated that specific conductance was highly correlated (0.846, P=0.008) with average daily flow. C receives flow primarily from groundwater seepage, while A receives groundwater seepage and discharge from a small headwater pond. Specific conductance can be used as an indicator of baseflow (i.e. groundwater) input to a stream (Kuwabara 1992, Pilgrim et al. 1979, as cited in Black 1996) because groundwater has elevated conduc tivity relative to the water column. Streams with very low ionic concentrat ions generally have a flora and fauna characterized by low abundance and richness (Allan, 1995). However, this relationship has not been adequately established for aqua tic insects. In a study that identified the abiotic factors best predicting species ric hness and abundance of m acroinvertebrates from Patagonian streams and rivers, current spee d, conductivity, substrate type, and abundance of aquatic plants were the ma in factors (Miserendino 2001). These predictors are similar to the four primary factors controlling rive r fauna (Hynes 1966): 1) dissolved salts, 2) current, 3) temperature, and 4) dissolved oxygen. Hynes also stressed the importance of plants that influence biota by providing sh elter, food, and surface area for growth of attached algae, which are later grazed by invertebrates. Significant predictors for EPT taxa, Ge orgia EPD index, and Georgia AAS index were either related to flow or specific conducta nce, which were highly correlated to flow.

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90 Flow controls many structural at tributes of streams, such as current veloc ity, substratum stability, channel geomorphology, and habita t volume (Poff and Ward 1989), which in turn influence factors of critical importance to macroinvertebrates such as routing and retention of organic matter (Gomi et al. 2002). Water velocity, coup led with the abiotic and biotic factors that it in fluences, may be the most important environmental factor influencing stream ecology (Allan 1995, Po ff and Ward 1989, Hynes 1970). Hydrologic disturbances such as flood and drought can affect biota because fr equency, duration, and intensity of such disturbances influence the response and recovery time of communities (Gomi et al. 2002). Differences in streamflow magnitude a nd origin between st reams A and C may explain why these streams woul d be different in terms of EPT taxa, Georgia EPD index, Georgia AAS index, and percent Elmidae, but D also had low flow compared to C. Over a 638 day period, D had a higher number of zero flow days (206) compared to A (161). What is not expressed in this metric of inte rmittent conditions is the amount of water still present in the channel but not detected at the flume. Zero flow conditions at A versus D were very different. The downstream reaches of A were sometimes completely dry, whereas those of D always had water and could have provided a hyporheic refuge. Griffin and Perry (1993) noted that the hypor heic zone may provide a refuge from a longer-term disturbance, such as drought. Th is may partially explain why the lower flow conditions in D did not result in a de pressed fauna as detected in A. Another difference between A and D lies in dissolved oxygen concentrations. For the entire study period, average dissolved oxyge n in A was 4.05 mg/L (42% saturation of dissolved oxygen), while D was 6.00 mg/L ( 64% saturation of dissolved oxygen).

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91 Georgia Department of Natural Resources ( 2004) water quality regulations specify a daily average of 5.0 mg/L and no less than 4.0 mg/L for waters supporting warm water species of fish, which indicates that dissolv ed oxygen conditions in A are considered low for warm water fish species. Crisman et al. (1998) investigated the relationship of oxygen concentrations in shallow Florida lake s to humic color, trophic state, and lake size. Percent oxygen saturation was nega tively correlated with color. Although quantitative measurements of humic color we re not done in the current study, qualitative observations indicate that A is highly colored relative to D. The source of color for A is likely export of organic matter from a small, headwater pond that contributes flow to A during wet periods. Decomposition of dissolv ed organic matter consumes oxygen. Allan (1995) indicated that the biota of flowing waters is highly dependent on availability of oxygen, but low dissolved oxygen is usually not limiting. However, under certain conditions, such as drought, it can be impor tant. The low dissolved oxygen potentially influenced by color in A coupled with low flow conditions may have restricted the fauna. Another indication of the influence of the headwater pond in watershed A is the representation of functional feeding groups for stream A relative to B, C, and D. The assemblages of streams B, C, and D had f unctional feeding groups similar to headwater streams described in the River Continuum Concept (RCC) (Vannote et al. 1980), with shredders and collectors being co-dominant. However, predators were equally dominant in these streams. Collector s dominated stream A, which according to the RCC is an assemblage typical of large rivers with sma ller detrital particle size distribution. The small headwater pond is likely the primary sour ce of detritus for stream A because leaf litter inputs to each stream were not signi ficantly different, and the pond would provide

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92 the required residence time for large organi c matter to be broken down into smaller particle sizes. Metrics Assessment Many metrics were calculated both to describe individual macroinvertebrate assemblages and to compare assemblages be tween upstream and downstream, stream to stream, and year to year. The effectiveness of each metric in describing the study streams varied. Percent dominant taxa, number of Ch ironomidae taxa, percent Diptera, percent Chironomidae, percent filter f eeders, and number of clinge r taxa were not different between sampling periods, position, or stream s. Percent dominant taxa, number of Chironomidae taxa, percent Diptera, and pe rcent Chironomidae generally described the importance of Chironomidae in the assemblage. The percent dominant taxa was greatly influenced by Chironomidae because 21 of th e 32 total samples were dominated by this group. Percent Diptera was also heavily in fluenced by the Chironomidae because 44 of 63 total dipteran taxa were Chironomidae. Metrics should have a specific range of variability in order to discriminate between sites (Barbour et al. 1999), but Chironomidae were simply ubiquitous at all sites; theref ore, the methods of comparison employed in this study did not detect differences in metrics that described this group. Percent filter feeders and number of clinge r taxa also were not different between sampling periods, position, or streams. When pr esent, filter feeders and clinger taxa were not abundant. Barbour et al (1999) suggested that metric s with too many zero values should be eliminated from a pool of potential metrics, suggesting that these metrics may not be useful for evaluating the describing the macroinvertebrate assemblage of study streams. Furthermore, Karr (1999) indica ted that metrics base d on functional feeding groups can respond differently to dist urbance in different streams.

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93 Abundance, EPT taxa, and total taxa showed significant differences due to time and stream and consistently indicated that Decem ber 2001 had significantly lower values than February 2003. February 2002 did not differ from December 2002. Abundance can vary greatly naturally (Karr 1999). In a study of macroinvertebrate assemblages in small streams of Alabama, total taxa was signifi cantly different between years with varying degrees of flow permanence, and EPT taxa s howed the strongest relationship with stream permanence (Feminella 1996). Of abundance, to tal taxa, and EPT taxa, the latter had the strongest relationship with flow in the curren t study as there was si gnificantly lower EPT taxa in stream A versus C. The number of EPT taxa is often lower in headwater reaches relative to larger downstream reaches and this may limit the usefulness of this metric in biological monitoring unless it is used in comparisons of streams with similar size (Wallace et al. 1996). As mentioned previously, streams in this study have numbers of EPT taxa comparable with studies of low and higher orde r streams; however, it is still advisable to compare streams of similar size and characte ristics in biological monitoring studies. EPT taxa, a single metric, can detect changes in macroinvertebrate assemblages as can biotic indices that integrate several metrics toge ther to determine condition (Karr and Chu 1999). Wallace et al. (1996) investigated the ability of the North Carolina Biotic Index (NCBI) (Lenat 1993) and EPT taxa to tr ack manipulation of macroinvertebrate communities in headwater streams due to insecticide treatments. NCBI and EPT taxa reflected changes due to treatment and eff ectively indicated improved conditions during recovery, with EPT taxa being the easier to use (time for sample processing and ease of application). EPT taxa were sensitive to disturbance but relatively insensitive to natural

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94 disturbances such as extreme discharges. However, Stone and Wallace (1998) found that EPT taxa increased and NCBI decreased in headwater streams that had undergone forest harvesting, suggesting that more than one metr ic or index should be used in biological monitoring studies. Percent Elmidae was a metric that was utilized in southwestern Georgia to differentiate between fenced and unfenced ag ricultural streams (Muenz 2004). It was effective in detecting interannua l variation and was sensitive to influences of inorganic phosphorus. In biomonitoring, a metric is select ed because it reflects some aspect of the system biological condition (Karr and Chu 1999). Percent Elmidae reflects the range of conditions that affect one family of aquatic beetles. While these conditions may have similarities with other groups of insects, the metric may be too specific for use as an indicator of the assemblage as a whole. Ho wever, this metric may have utility when combined with other metrics. Three indices were calculated to describe the macroinvertebrate assemblage and to compare assemblages between upstream and down stream, stream to stream, and year to year. The effectiveness of each index in describing the study streams varied. The Georgia EPD index and Georgia AAS i ndex detected differences in the macroinvertebrate assemblages due to time and stream, but the Florida SCI did not. Also, the Georgia EPD index and Georgia AAS index scored most streams as Good or Excellent, respectively, whereas Fl SCI scored the majority of samples as Poor. There are similarities and inherent di fferences among these indices. Georgia EPD index and Florida SCI both combine results from selected metr ics that are weighted based on regional differences, then summed to provide a final score. For the Georgia EPD, the score is

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95 compared to a regional reference stream scor e, and this score is converted into a final assessment of ecological condition (GA DNR 20 02). The Florida SC I converts the score for the stream in question into a final asse ssment of ecological condition by determining where it falls within certain ranges of values that were established by statistical analysis of FDEP reference stream data from nor thwestern Florida (FDEP 2004). The Georgia EPD index scored most streams Good in their undisturbed condition, which was somewhat surprising given that the average ar ea of the watersheds in the study was 0.40 km2 compared to 38.4 km2 for reference watershed used for comparisons. The number of species is generally thought to increase from headwaters to mid-order streams, then to decrease again in larger rivers (Allan 1995, Vannote et al. 1980). Overall, Georgia EPD index scores might improve if compared to a reference stream closer to the size of the study streams. Florida SCI scores were low for the study st reams. The Florida SCI scores were calculated based on a 100 individual subs ample required as a standard operating procedure (FDEP 2004). In general, when a 100 individual subsample was randomly generated from the entire list of species pres ent in a sample, dominant taxa tended to displace more sensitive taxa such as EPT taxa that had a detrimenta l effect on the overall SCI score. Doberstein et al. (2000) analyzed 500 random 100-individual subsamples from a stream in the Puget Sound area of Washington that was minimally disturbed. They found that the ability to discern biological conditi on was reduced to a point where the potential for an ill-informed water resource decisi on was high when a 100-individual subsample was used. Additional subsamples at different intervals (100, 200, 500-individual

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96 subsamples) and subsequent calculations of the SCI may be warrant ed to determine if subsampling was the cause of the depre ssed SCI scores in the current study. Subsampling did not seem to have as drasti c an effect on Georgia EPD index scores, as overall condition of streams actually increased slightly as a result of calculating the index with a 200-individual subsample versus the entire sample. The Georgia AAS index is calculated as presence/absence of invertebrates at the order level (GA DNR 2000) versus genus and species levels, which are used in calculation of Georgia EPD inde x and Fl SCI. Genus or species-level taxonomy can yield the greatest benefits fo r biological monitoring studies es pecially when results could influence management decisions (Lenat and Resh 2001). However, studies utilizing higher taxonomic levels (e.g., family, order) discriminate among ecoregions (Feminella 2000) and describe community patterns (Bow man and Bailey 1997) equally as well as lower taxonomic levels (e.g., genus, species ). One argument against using lower taxonomic levels is that genus and/or sp ecies information increases the cost and ecological noise of bioassessment (Bailey et al. 2001). Feminella (2000) also proposed that coarser taxonomic levels may provide ad equate resolution for relatively unimpaired streams that may differ due to natural within -catchment variation. Analysis of Georgia AAS index and Georgia EPD values indicated th at there were signifi cant differences due to time and stream. However, comparisons between time for AAS and EPD varied in that December 2001 had significantly lower AAS index values than February 2003. February 2002 and December 2002 were not significantly different. December 2002 EPD index values were signi ficantly higher than the rema ining sampling periods, which were not significantly different. Georgi a AAS results for differences between time

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97 periods agreed with the resu lts for abundance, total taxa, and EPT taxa, whereas EPD index results only agreed with percent Elmidae. For differences due to stream, Georgia AAS index and Georgia EPD index had similar results as EPT taxa and percent Elmidae in that A had significantly lower values than C. These results do not suggest that the Georgia AAS index is better at describing differences in this study than the Georgia EPD, but they do suggest that a gr eat deal of information is not lost due to the coarser taxonomic resolution employed in Georgia AAS index. Conclusions The biota of small, sandy substrate headwate r streams in the Gulf coastal plain are dominated by Diptera, but they are not low in taxa richness and have taxa from the orders, Ephemeroptera, Plecoptera, and Tr ichoptera, considered sensitive to human disturbance. Since all sites in this study were in a relatively undisturbe d condition and were similar in location and physical characteristic s, the macroinvertebrate fauna was expected to be comparable between sites. However, there was variation in abundance, EPT taxa, total taxa, Georgia AAS index, and Georgi a EPD index between the four undisturbed adjacent headwater streams and from year to year. Natural variability, year-to-year and stream to stream variance can be significan t, even within sub-watersheds of a small catchment. Hydrology may be the controlli ng variable for the natural variability displayed in this study. However, due to small sample size, additional data are needed to strengthen this relationship. Hydrology should be monitored and considered in manipulative studies where macroinvertebrates are used as a response variable, because even small interannual differences in hydrology can have a significant effect on organisms. Establishing this natural variability is important to consider in manipulative

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98 studies; however, a robust base line dataset can lessen the potential of natural variation clouding identification of a treatment effect. Of all metrics examined in this study, abundance, EPT taxa, total taxa, GA AAS index, and GA EPD index detect ed differences in macroinve rtebrates due to time and stream, and therefore best described differe nces in the macroinvertebrate assemblage. Differences in the macroinvertebrate assemblages between A and C, but not between A and B or C and D, support the ove rall Dry Creek study design and suggest that A and D would be appropriate reference st reams for B and C, respectively. No differences were detected between upstream and downstream sampling locations within each stream suggesting that upstream reaches w ithin the same stream will be appropriate references for manipulations occurring on downstream reaches.

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99 APPENDIX SPECIES LIST AND TOTAL ABUNDANCE FOR EACH SITE OrderFamilySubfamilyGenusSpecies A 1 A 2B1B2C1C2D1D2 Diptera Chironomidae Chironominae Chironomussp. 151200902 Chironominae Cryptochironomussp. 0118455450 Chironominae Microtendipespedellus gp. 0157631640 Chironominae Paracladopelmasp. 001010000 Chironominae Paralauterborniellanigrohalterales 00200032 Chironominae Paratendipessp. 1293777101 Chironominae Polypedilumfallax 0034991651 Chironominae Polypedilumflavum 033805816892863109 Chironominae Polypedilumhalterale 003107001 Chironominae Polypedilumillinoense 32852291212 Chironominae Rheotanytarsussp. 002234325450 Chironominae Stenochironomussp. 012001512 Chironominae Tanytarsussp. 104531222403819 Chironominae Tribelosfuscicorne 70000000 Chironominae Tribelosjucundum 122383184333800 Chironominae Tribelossp. 161591482 Chironominae Zavreliasp. 00000041 Orthocladiinae Brilliaflavifrons 00002000 Orthocladiinae Corynoneurasp. 261980769 Orthocladiinae Eukiefferiellaclaripennis gp. 00000030 Orthocladiinae Heterotrissocladiusmarcidus 8350160000 Orthocladiinae Limnophyessp. 01000100 Orthocladiinae Nanocladiusdistinctus 070111017012296 Orthocladiinae Orthocladiinae 114040000 Orthocladiinae Orthocladiuslignicola 0001571830 Orthocladiinae Parachaetocladiussp. 116333072429 Orthocladiinae Parametriocnemussp. 10144018758171518375 Orthocladiinae Pseudorthocladiussp. 300803000 Orthocladiinae Pseudosmittasp. 14000000 Orthocladiinae Rheocricotopustuberculatus 00000030 Orthocladiinae Smittiasp. 60000000 Orthocladiinae Thienemanniellaxena 00430011 Orthocladiinae Xylotopuspar 0000048115 Prodiamesinae Odontomesafulva 00300000 Tanypodinae Ablabesmyiamallochi 007595200 Tanypodinae Alotanypussp. 268010407211 Tanypodinae Cantopelopiagesta 14011048011 Tanypodinae Clinotanypuspinguis 01000101 Tanypodinae Conchapelopiasp. 131027965186213108271 Tanypodinae Labrundiniapilosella 025503822405 Tanypodinae Larsiasp. 0002723600 Tanypodinae Procladiussp. 0251021551 Tanypodinae Tanypodinae 02804601200142 Tanypodinae Zavrelimyiasp. 252235119352557550 Tipulidae01133011 Tipula/Nippotipula 00161212232011 Pseudolimnophila 1324139517432109 Pilaria 33544318 Dicranota 00000000 Hexatoma 0225113233 Erioptera 15200100 Austrolimnophilasp. 00000010 Limnophila 01000000 Ceratopogonidae Bezzia/Palpomyia 1001041691259826689117 Alluaudomyia 60000000 Dasyhelea 00000010Site

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100 OrderFamilySubfamilyGenusSpecies A 1 A 2B1B2C1C2D1D2 Ptychopteridae Bittacomorpha 407180702 Simulidae8367347310218913123 Tabanidae40101329175 Culicidae95030710 Dixidae000020011 Psychodidae Pericoma 00001100 Psychoda 20000000 Dolichopodidae20000610 Isopoda Asellidae Caecidotea 1220100010 Amphipoda Crangonyctidae Cragonyx 3101942137432550 Odonata Gomphidae00100010 Ophiogomphus 00002000 Gomphus 00001300 Progomphus 00009001 Cordulegastridae01000000 Cordulegaster 00222280 sayi 00000311 Aeshnidae Boyeriavinosa 00001000 Libellulidae01240002 Libellulinae00000200 Corduliinae00210000 Calopterygidae Calopteryx 00010420 Plecoptera Nemouridae Amphinemura 011176522955228126 Perlodidae Ciloperlacilo 004311375 Perlidae Perlesta 00028100 Capniidae Allocapnia 00000070189 Ephemeroptera Baetidae Acerpennapygmaea 00212619800 Baetisintercalaris 00001000 Diphetorhageni 00002030 Pseudocloeonsp. 00010110 Ephemerelliae Ephemerellasp. 00214000 Eurylophelladoris 00000100 Ephemeridae Hexageniasp. 00007700 Hexagenialimbata 00000500 Heptageniidae Stenonemasmithae 000013010 Leptophlebiidae Habrophlebiodessp. 001625170193435 Leptophlebiasp. 002121193610 Trichoptera Calamoceratidae Anisocentropuspyraloides 0010275910 Odontoceridae Psilotretafrontalis 00008048 Hydropsychidae Diplectronamodesta 00411900 Cheumatopsyche 000071200 Philopotamidae Chimarra 0000242230 Limnephilidae Pycnopsyche 25121618232414 Molannidae Molanna blenda 00000001 Leptoceridae Triaenodes 00001200 Sericostomatidae Agarodes 00001000 Dipseudopsidae Phylocentropus 01000200 Rhyacophilidae Rhyacophilacarolina 00140000 Polycentropodidae Polycentropus 00010000Site

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101 OrderFamilySubfamilyGenusSpecies A 1 A 2B1B2C1C2D1D2 Coleoptera Dryopidae Helichus 005929291030 Pelonomus 00000001 Dytiscidae201210030 Thermonectusbasilaris 10000000 Agabussp. 20000000 Agabusastrictovittatus 10000000 Copelatusglyphicus 00000010 Rhantussp. 00000000 Rhantuscalidus 10100100 Coptotomusloticus 00000100 Hydaticusbimarginatus 00000100 Neoporussp. 01132411634 Neoporusstriatopunctatus 009701107 Neoporusblanchardi 04001000 Neoporusundulatus 00050000 Elmidae00000000 Stenelmis 0518679162156134 Dubiraphia 00008458 Macronychus 00002000 Scirtidae310306110 Hydrophilidae00000002 Helocombus 30100200 Lampyridae11010000 Ptilodactylidae Anchytarsus 00001401 Hemiptera Notonectidae Notonecta 10000000 Megaloptera Chauliodinae Nigronia 00002032 Chauliodes 10010100Site

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108 Rosario, R.B. and V.H.Resh. 2000. Invertebrates in intermittent and pe rennial streams: is the hyporheic zone a refuge from dryi ng? Journal of the North American Benthological Society. 19 (4): 680-696. Rosenberg, D.M. and V.H. Resh. 1993. Intr oduction to Freshwater Biomonitoring and Benthic Macroinvertebrates. In: Rosenberg, D.M. and V.H. Resh (ed.), Freshwater Biomonitoring and Benthic Macroinvertebr ates. Chapman and Hall, New York. 19. Smock, L.A., G.M. Metzler, and J.E. Gladden. 1989. Role of debris dams in the structure and functioning of low-gradient head water streams. Ecology. 70(3): 764-775. Southeast Regional Climate Center. Bai nbridge, Georgia Climate Information. http://climate.engr.uga.edu/bainbridge/index.html last accessed August 8, 2004. SPSS Inc. 2002. SPSS Base 10 for Windows User's Guide. SPSS Inc., Chicago IL. Stone, M.K. and J.B. Wallace. 1998. Long-term recovery of a mountain stream from clearcut logging: the effects of fo rest succession on benthic invertebrate community structure. Freshwater Biology. 39, 151-169. Summer, W.B., C.R. Jackson, D.G. Jones, and M. Miwa. 2003. Characterization of hydrologic and sediment transport behavior of forested headwater streams in southwest Georgia. In: Proceedings of the 2003 Georgia Water Resources Conference, Athens, GA. 23-24 April 2003. The Institute of Ecology: The University of Georgia, Athens, GA. 157-160. Tett, P., C. Gallegos, M.G. Kelly, G.M.Hor nberger, and B.J. Cosby. 1978. Relationships among substrate, flow, and benthic microa lgal pigment density in the Mechums River, Virginia. Limnology and Oceanography 23(4): 785-797. Torak, L.J. 2003. Assessment of karst features underlying Lake Seminole, southwestern Georgia and northwestern Florida, using orthorectified photographs of preimpoundment conditions and hydrographic maps. In: Proceedings of the 2003 Georgia Water Resources Conference, held April 23-24, 2003, at University of Georgia. Kathryn J. Hatcher, editor, Institute of Ecology, The University of Georgia, Athens, Georgia. 165-171. Taylor, R. A. 1986. Cow Cavalry: Munne rlyns Battalion in Florida, 1864-1865. The Florida Historical Quarterly. 55(2): 196-214. United States Forest Service. 1969. A Forest Atlas of the South. Southern Forest Experiment Station and Southeastern Fore st Experiment Station Publication. 27 pp. Vannote, R. L., G.W. Minshall, K. W.Cumm ins, J.R. Sedell, and C.E.Cushing, 1980. The river continuum concept. Canadian Journa l of Fisheries and Aquatic Sciences. 37: 130-137.

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109 Wallace, J. B. and A.C. Benke.1984. Quantifi cation of wood habitat in subtropical coastal plain streams. Canadian Journal of Fisheries and Aquatic Sciences. 41: 1643-1652. Wallace, J.B., T.F. Cuffney, J.R. Webster, G.J. Lugthart, K. Chung, and B.S. Goldowitz. 1991. Export of fine organic particles from headwater streams: Effects of season, extreme discharges, and invertebrate manipulation. Limnology and Oceanography. 36(4): 670-682. Wallace, J. B., J.W. Grubaugh, and M.R. Whiles. 1996. Biotic indices and stream ecosystem processes: results from an experimental study. 1996. Ecological Applications. 6(1): 140-151. Wallace, J.B., S.L. Eggert, J.L. Meyer, and J.R. Webster. 1997. Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Sc ience. 277: 102-104. Warner, D. and V. Norton. 2003. An overview of water-resource issues in the middle and lower Flint River subbasins, southwest Georgia. In: Proceedings of the 2003 Georgia Water Resources Conference, held April 23-24, 2003, at University of Georgia. Kathryn J. Hatcher, editor, Institute of Ecology, The University of Georgia, Athens, Georgia. 8-10. Webster, J.R., E.F. Benfield, T.P. Ehrman, M.A. Schaeffer, J.L. Tank, J.J. Hutchens, and D.J. DAngelo. 1999. What happens to al lochthonous material that falls into streams? A synthesis of new and published information from Coweeta. Freshwater Biology. 41: 687-705. Whiles M. R., and J. B. Wallace. 1995. M acroinvertebrate production in a headwater stream during recovery from anthropogeni c disturbance and hydrologic extremes. Canadian Journal of Fisheries and Aquatic Sciences. 52: 2402-2422. Wipfli, M. S. and D.P. Gregovich. 2002. E xport of invertebrates and detritus from fishless headwater streams in southeastern Alaska: implications for downstream salmonid production. Freshwater Biology. 47: 957-969. Wright, A.B., and L.A. Smock. 2001. Macroi nvertebrate community structure and production in a low-gradient stream in an undisturbed watershed. Archiv fuer Hydrobiologie. 152(2): 297-313. Zimmerman, A. and M. Church. 2001. Channe l Morphology, gradient profiles and bed stresses during flood in a step-poo l channel. Geomorphology. 40: 311-327.

PAGE 124

110 BIOGRAPHICAL SKETCH I graduated from Clemson Univ ersity with a B.S. in bi ological sciences in 1997. After graduation I took an in ternship position with Intern ational Paper to work on a forestry best management prac tices effectiveness-monitoring pr oject. It was during this project that I first began work ing with benthic macroinvertebr ates. In the past 6 years with International Paper I have had various responsibilities for the company, such as providing technical support to company foresters and other em ployees on matters related to water quality and water resource mana gement; leading or assisting in study installation, data collection, analysis, reporting, and pursuit of funding for internal and external research projects; leading or assisti ng in the development of and presentation of training on company environmental management policies; and repres enting International Paper at technical, policy meeti ngs/activities. I have also pa rticipated in state and local programs such as Georgia Adopt-A-Stream, Ge orgia Rivers Alive, and Keep America Beautiful. While in graduate school I rema ined employed by Inte rnational Paper as a Watershed Specialist, then later as the Coordinator of Partnerships.


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Title: Aquatic Macroinvertebrate Assemblages in Southwest Georgia Headwater Streams
Physical Description: Mixed Material
Copyright Date: 2008

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AQUATIC MACROINVERTEBRATE ASSEMBLAGES IN SOUTHWEST
GEORGIA HEADWATER STREAMS

















By

REBECCA TURNER WINN


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2005

































Copyright 2005

by

Rebecca Turner Winn

































This document is dedicated to my parents.















ACKNOWLEDGMENTS

I thank my parents, whose support, guidance, and love have shaped the person I am

today. They were a constant motivator for this work. I would also like to thank my

manager at International Paper for supporting the Dry Creek Long-term Watershed Study

and approving my request for taking this study as my master's research. Many co-

workers at International Paper have assisted me with this research in enumerable ways,

such as assistance with field work, technical advice, assistance with lab work, statistical

help, and moral support to name a few. I am also grateful to the students in my

committee chair's lab who provided advice and a listening ear during my last semester.

My committee also provided invaluable input that has made this research something that

I am very proud of and that I hope has laid a foundation for future research to be

conducted as part of the Dry Creek study. This research would not have been possible

without the following organizations that funded or supported this study: International

Paper, the National Council for Air and Stream Improvement, the National Fish and

Wildlife Foundation, the J.W. Jones Ecological Research Center, and the H. T. Odom

Center for Wetlands. Finally, I thank God who makes all things possible.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES ............................................. ................ ........... vii

LIST OF FIGURES ......... ....... .................... .......... ....... ............ ix

A B S T R A C T ......... .................................. ...................................................x iii

1 INTRODUCTION AND OBJECTIVES ........................................... .................

In tro d u ctio n ...................................... .................................. .................. .
H eadw ater Stream s ...................................................... .. .... .... ............
A qu atic F auna.................................................. 2
Benthic Macroinvertebrates.................. .......... ............................ 4
Biom monitoring .................................................................. ............... 5
O bjectiv e s ..................................................................................................... . 6

2 SIT E D E SC R IP T IO N .......................................................................... .......... ..........8

S tu d y S ite .................................................................................. 8
V e g e ta tio n .............................................................................................. 1 1
C lim ate ................................................. 12
S ite H isto ry .......................................................................................................1 2

3 M E T H O D S .......................................................................................................1 8

O overview of Study ................................. .................................. 18
D ata C collection ................................................................................................ ........ 19
P hy sical M easurem ents .................................................................................. 19
Environm mental M easurem ents .................................................................... ..21
Chemical and Hydrological Measurements .................................................. 22
M acroinvertebrates ................................................................................ 22
D ata A naly sis..................................................24
P hy sical M easurem ents .................................................................................. 24
Environm mental M easurem ents .................................................................... ..24
Chemical and Hydrological Measurements .................................................. 25
M acroinvertebrates ................................................................................ 26



v









4 R E SU L T S ....................................................... 32

P hy sical M easurem ents ...................................................................... ...................32
Environm ental M easurem ents .............................................................................. 36
Chemical and Hydrological Measurements ............................................................37
M acroinvertebrates ......................... ..... .......... ........ ..... ..... 43
A b u n d a n c e ..................................................................................................4 5
Dominant Taxa ........................................................................................................47
T o ta l T a x a ....................................................................................................... 4 9
E P T T a x a ........................................................................................................ 5 2
Chironom idae Taxa ..................................................... ............ 53
P percent C hironom idae .......................................................................... 56
P percent D iptera ........................................................................................ .. ......... .... 58
P percent E lm idae ................................................... ................ ... ...............58
Feeding Type and H habitat Type ........................................ ........................ 62
B io tic In d ic e s .................................................................................................. 6 4
M u ltiv ariate A n aly sis........... ................................................................... ..... ... .... 73
R egression A naly sis.......... ..... ........................................................................ .... 73

5 DISCU SSION AND CON CLU SION S ............................................. ....................84

D iscu ssio n ................... .... ........................................... ................ 8 4
Macroinvertebrate Assemblages All Streams ................................................84
Macroinvertebrate Assemblages Within Streams..........................................87
Macroinvertebrate Assemblages Among Streams .........................................87
M etrics A ssessm ent .............................................................. ............... 92
C o n clu sio n s..................................................... ................ 9 7

APPENDIX SPECIES LIST AND TOTAL ABUNDANCE FOR EACH SITE..........99

L IST O F R E F E R E N C E S ........................................................................ .................... 102

BIOGRAPH ICAL SKETCH ........................................................................110















LIST OF TABLES


Table page

2-1 Site history events for the study site and watersheds. ...................... ...............13

3-1 Stream Condition Index metric scoring formulae ..................................................27

3-2 Category names, ranges of values for Stream Condition Index, and typical
biological conditions. ......................................... .......................... 28

3-3 Sample Ecological Condition W orksheet. .................................... .................29

4-1 Tally of large woody debris (>10cm diameter)......................................................36

4-2 Mean periphyton chlorophyll a and dry weight. Mean macrophyte dry weight.....37

4-3 Mean, minimum, and maximum in-situ water chemistry. .....................................40

4-4 Repeated measures analyses for effects of time and position (upstream vs.
downstream) on macroinvertebrate metrics. ................................. .................48

4-5 Repeated measures analyses for effects of time (Dec 01, Feb 02, Dec 02, Feb 03)
and stream (A, B, C, D) on macroinvertebrate metrics................ ..................50

4-6 Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb
03) and position (upstream vs. downstream) on macroinvertebrate metrics............60

4-7 Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02, Feb
03) and stream (A, B, C, D) on macroinvertebrate metrics.............................. 61

4-8 Sample comparison of sites (B1 vs. Cl for February 2002) .................................72

4-9 Percent comparability scores for year to year comparison of sites........................72

4-10 Percent comparability scores for downstream vs. upstream comparison of sites. ...72

4-11 Percent comparability scores for stream to stream comparison of sites .................73

4-12 Adjusted R2 values (%) for five *models: 1) all samples pooled (n=31), 2)
Dec 01 samples only (n=7), 3) Feb 02 samples only (n=8), 4) Dec 02 samples
only (n=8), 5) Feb 03 samples only (n=8)......................................... ............... 75









4-13 Stepwise regression models of the relationship between EPT taxa and
abundance (response) with water chemistry and hydrology parameters
(predictors) .......... ..................... ................................................78

4-14 Stepwise regression models of the relationship between Georgia EPD index and
Georgia AAS index (response) with water chemistry and hydrology parameters
(predictors) .......... ..................... ................................................79

4-15 Stepwise regression models of the relationship between percent dominant taxa,
percent filter feeders, total taxa, and percent Elmidae (response) and water
chemistry and hydrology parameters (predictors). ............................................80
















LIST OF FIGURES


Figure p

2-1 Location of study site in relation to physiographic regions. ......................................8

2-2 Location of study area in relation to physiographic districts. ...................................9

2-3 Topographic map of Dry Creek watershed and location of four headwater
watersheds (A-D). ................................... ... .. ....... .......... .... 10

3-1 Topographic map and aerial photograph of location of four headwater
watersheds (A-D). ................................... .. ... ....... .......... .... 18

3-2 Topographic map of location of four headwater watersheds (A-D) with eight
sample reaches and schematic of an individual sample reach................................19

3-3 Schematic of a representative sample reach with layout of litterfall traps...............21

4-1 Percent coverage of in-stream habitat units for each sampling site .......................33

4-2 Percent coverage of in-stream channel units for each sampling site......................34

4-3 Percent canopy cover for each sampling site (A-l through D-2) as defined by
G L A softw are. ..................................................................... ... 35

4-4 Average dry weight of total litterfall (hardwood leaves, pine, woody debris, and
mast) across sites with proportion of total litterfall as leaves (hardwood leaves)
in grey ............. ................................................ ................. 36

4-5 Periphyton ash free dry weight .......... ..... ................ .................. 38

4-6 M acrophyte dry weight (July 2003) ....................................................................... 39

4-7 M monthly mean water temperature. ........................................ ....................... 39

4-8 M monthly m ean dissolved oxygen........................................ .......................... 40

4-9 M monthly m ean pH ........................................ ........ ... .. ........ .... 41

4-10 M monthly mean inorganic nitrogen. .......................................................................... 42









4-11 First and second axes of the principal components analysis (PCA) for in-situ
water chemistry data at all sites from September 2001-December 2003.................43

4-12 First and third axes of the principal components analysis (PCA) for in-situ
water chemistry data at all sites from September 2001-December 2003 ...............44

4-13 Partitioning of total abundance by invertebrate orders in study streams over the
entire study period ..................................... .. ... .. ....... .............. 46

4-14 Macroinvertebrate abundance (total number of individuals) for upstream and
downstream sites of each stream (A-D) over the entire study period ....................47

4-15 Mean macroinvertebrate abundance individual sampling periods with standard
error and repeated contrast results (alpha = 0.05). ............. .................................... 49

4-16 Means for macroinvertebrate abundance for all sites within each stream for all
tim e periods w ith standard error..................................... ............................ ........ 51

4-17 Percent dominant taxon for upstream and downstream sites of each stream
(A -D ) over the entire study period. ......................................................................... 51

4-18 Taxa richness for upstream and downstream sites of each stream (A-D) over the
entire study period ..................................... .. ... .. ....... .............. 52

4-19 Mean taxa richness for individual sampling periods with standard error and
repeated contrast results (alpha = 0.05)......................................... ............... 53

4-20 Taxa richness for each stream for all time periods with standard error .................54

4-21 Total Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa for upstream and
downstream sites of individual streams (A-D) over the entire study period............ 54

4-22 Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa within each time
period with standard error and repeated contrast results (alpha = 0.05) across
tim e. ........ ...... ........... ....... .. ........... ......... .......... ........... 55

4-23 Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa for all sites within
each stream for all time periods and pairwise multiple comparison test results
(Tukey's honestly significant difference (HSD) test, alpha = 0.05). .....................55

4-24 Mean subfamily composition of Chironomidae in individual streams (A-D) over
the entire sam pling period. ..... ........................... .......................................56

4-25 Number of Chironomidae taxa for upstream and downstream sites of individual
stream s (A-D) over the entire study period ........................................ ............... 57

4-26 Percentage of total abundance contributed by Chironomidae for upstream and
downstream sites of individual streams (A-D) over the entire study period............ 57









4-27 Percentage of total abundance contributed by Diptera for upstream and
downstream sites of individual streams (A-D) over the entire study period............ 58

4-28 Percent of the total assemblage represented by Elmidae for upstream and
downstream sites of individual streams (A-D) over the entire study period............ 59

4-29 Interaction plot (data means) for percent Elmidae. ..............................................62

4-30 Percentage of the total assemblage contributed by individual functional feeding
groups for individual streams (A-D) over the entire study period .........................63

4-31 Percentage of the total assemblage represented by filter feeders for upstream
and downstream sites of individual streams (A-D) over the entire study period.....63

4-32 Clinger taxa for upstream and downstream sites of individual streams (A-D)
over the entire study period .............................................. ............................ 64

4-33 Florida Stream Condition Index (SCI) scores for upstream and downstream sites
of each stream (A-D) over the entire study period .............................................65

4-34 Georgia EPD Biological Assessment scores for upstream and downstream sites
of each stream (A-D) over the entire study period .............................................66

4-35 Georgia EPD Biological Assessment scores for upstream and downstream sites
of each stream (A-D) over the entire study period .............................................67

4-36 Means for GA EPD Index for all streams combined during each time period
with standard error and repeated contrast results (alpha = 0.05) across time. .........68

4-37 Means for GA EPD Index for all sites combined (200 individual subsample)
within each time period with standard error and repeated contrast results
(alpha = 0.05) across tim e. ............................................. .............................. 68

4-38 Means for GA EPD Index (individual streams for the entire study) and pairwise
multiple comparison test results (Tukey's honestly significant difference (HSD)
test, alpha = 0.05). .....................................................................69

4-39 Georgia Adopt-A-Stream Index scores for upstream and downstream sites of
each stream (A-D) over the entire study period. ............. ......................... ......... 70

4-40 Means for GA AAS Index for all sites combined within each time period with
standard error and repeated contrast results (alpha = 0.05) across time...................70

4-41 Means for GA AAS Index (individual streams for the entire study) and pairwise
multiple comparison test results (Tukey's honestly significant difference (HSD)
test, alpha = 0.05). .....................................................................71

4-42 Principal components ordination for macroinvertebrate metrics and indices..........74









4-43 Total annual rainfall from 1967-2003 at the Bainbridge, GA station (90586) at
International Paper arranged from lowest to highest annual values.........................77

4-44 Abundance vs. average daily flow for all sites and time periods
(1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003). .........81

4-45 EPT taxa vs. average daily flow for all sites and time periods
(1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003). .........81

4-46 GA EPD Index vs. average daily flow for all sites and time periods
(1-December 2001, 2-February 2002, 3-December 2002, 4-February 2003). .........82

4-47 Abundance vs. average daily flow for all sites and time periods with linear
regression fit for each time period (1-December 2001, 2-February 2002, 3-
December 2002, 4-February 2003). .............................................. ............... 82

4-48 EPT taxa vs. average daily flow for all sites and time periods with linear
regression fit for each time period (1-December 2001, 2-February 2002,
3-December 2002, 4-February 2003). .............. .................. ......................... 83

4-49 GA EPD Index vs. average daily flow for all sites and time periods with linear
regression fit for each time period (1-December 2001, 2-February 2002, 3-
December 2002, 4-February 2003). .............................................. ............... 83















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

AQUATIC MACROINVERTEBRATE ASSEMBLAGES IN SOUTHWEST
GEORGIA HEADWATER STREAMS

By

Rebecca Turner Winn

May 2005

Chair: Thomas L. Crisman
Major Department: Environmental Engineering Sciences

Headwater streams account for a significant portion of channel length in a stream

network and strongly influence hydrological, water quality, and biological attributes

downstream. Little biological monitoring or assessment has been conducted in headwater

watersheds, especially in the Southeast coastal plain. Biological assessments must have a

standard, or reference condition, against which potentially impacted sites can be

compared. The objective of this study was to compare aquatic macroinvertebrate

assemblages in four headwater streams as part of the Dry Creek Long-term Watershed

Study being conducted by multiple partners. Four headwater streams (designated A, B, C,

D) in the Dry Creek watershed of the Southlands Forest of International Paper were

selected for this study. Benthic macroinvertebrates were sampled in streams during

December 2001, February and December 2002, and February 2003 within fixed distance

sample reaches. Macroinvertebrates were identified to the lowest taxonomic level and

results were used in biotic indices. Data analysis included using repeated measures









ANOVA to identify differences in macroinvertebrate assemblages due to sampling

period, position (upstream vs. downstream), and between streams. Stepwise regressions

were used to correlate differences in hydrology and water chemistry to relate with stream

differences. ANOVA results for abundance, total taxa, Ephemeroptera Plecoptera

Trichoptera (EPT) taxa, Georgia Adopt-A-Stream (AAS) index indicated differences in

macroinvertebrate assemblages due to sampling period, with lower values for December

2001 relative to February 2003. Abundance, total taxa, EPT taxa, Georgia Environmental

Protection Division (EPD) index, Georgia AAS index, and percent Elmidae displayed

significant differences due to stream with comparisons between streams for EPT taxa,

Georgia EPD index, and Georgia AAS index resulting in stream A having significantly

lower values than stream C. Significant predictors in regressions were average daily flow

and specific conductance for selected macroinvertebrate metrics. Natural variability in

hydrology, interannual and stream to stream was significantly different even within sub-

watersheds of a small catchment, which suggested that hydrology is an important

environmental factor influencing stream ecology and should be considered in

macroinvertebrate studies. Of all metrics examined in this study, abundance, EPT taxa,

total taxa, GA AAS index, and GA EPD index detected differences in macroinvertebrates

due to time and stream, and therefore best described differences in the macroinvertebrate

assemblage. Differences in the macroinvertebrate assemblages between streams A and C,

but not between A and B or C and D, support the overall Dry Creek Long-term

Watershed Study design and suggest that A and D would be appropriate reference

streams for B and C, respectively.














CHAPTER 1
INTRODUCTION AND OBJECTIVES

Introduction

Headwater Streams

First or second order streams comprise approximately 95% of all streams and

represent 73% of total channel length in North America (Leopold et al. 1992). For

example, the Chattooga River watershed is characterized by 59% of total stream length

being first order streams (Hansen 2001). Guidelines for protecting water quality from

anthropogenic activities are usually applied to streams designated as perennial ('blue

line') or intermittent (dashed line) on United States Geological Survey topographic maps.

For the Chattooga River watershed, only approximately 20% of total stream length (1st-

7th order) was represented as perennial streams on 1:24,000 topographic maps with

essentially none of the intermittent or ephemeral streams identified (Hansen 2001). When

compared with larger aquatic systems, the small size but large numbers of headwater

streams have led to underestimation of their functions within a watershed and

subsequently inadequate management (Gomi et al. 2002). To ensure adequate protection

of water quality and aquatic habitats through the use of Best Management Practices for

various land management activities, land managers must recognize the location and

importance of headwater streams (Hansen, 2001).

The "edge" to "interior," or perimeter to area ratio (P/A), influences the importance

of individual input to a habitat (e.g., watershed to stream) whether the input is natural

(e.g., litterfall) or anthropogenic (e.g., nutrients from fertilizer). Headwater streams have









a high P/A ratio compared to larger rivers, and as such, are more influenced by their

stream-land interface (Polis et al. 1997). Recognition of this connection between streams

and the surrounding landscape (Hynes 1975, Vannote et al. 1980) and between headwater

streams and downstream systems (Vannote et al. 1980) has guided recent studies related

to headwater streams and their functions.

Headwater streams have many functions important to downstream systems (Meyer

et al. 2003). Such streams are often strongly influenced by riparian vegetation, which

contributes allochthonous detritus and limits autochthonous primary production by

shading (Vannote et al. 1980). Wallace et al. (1997) showed through a leaf litter

exclusion study that terrestrial-aquatic linkages in headwater streams influenced diversity

and productivity. Headwater streams store, transform (Webster et al. 1999), and export

(Wallace et al. 1991) organic matter and nutrients. Invertebrates and diatoms (Allan

1995) are an important energy source for downstream ecosystems. For example, in

forested headwater streams of southeastern Alaska, invertebrates and coarse organic

detritus are exported downstream year-round (Wipfli and Gregovich 2002). These

systems also retain (Dieterich and Anderson 1998) and export sediment (Zimmerman and

Church 2001). Headwater streams maintain streamflow by supplying a stable source of

water to downstream systems through outflows from hillslopes, channel storage, riparian

wetlands (Gomi et al. 2002) and groundwater recharge (Meyer et al. 2003).

Aquatic Fauna

The southeastern United States harbors a rich and diverse aquatic fauna that is

threatened by development, habitat fragmentation, chemical pollution, and exotic species

introductions. The Southeast contains approximately 40% of the aquatic insect species

found in North America (Morse et al. 1997); however, the rich fauna in the Southeast is









poorly known, especially invertebrates (Folkerts 1997). Diversity of aquatic

invertebrates is high in the Gulf Coastal plain (Felley 1992). However, in the

Apalachicola-Chattahoochee-Flint (ACF) river basin, there is limited information on the

number and distribution of invertebrate species, except for checklists of specific taxa in

select portions of the basin (Couch et al. 1996). Due to their geographical isolation,

headwater streams may support species genetically isolated from those downstream

(Gomi, et al. 2002), so these systems may be important for maintaining local and regional

biodiversity.

Spatial significance, connection to the landscape, and many functions that maintain

downstream ecosystems highlight the need for monitoring and assessing headwater

streams. A great deal of research on macroinvertebrates and headwater streams has been

conducted in Montane regions, such as the southern Appalachians at the U. S. Forest

Service's Coweeta Hydrologic Laboratory in North Carolina, and to a lesser extent in the

White Mountains at the Hubbard Brook Experimental Forest in New Hampshire (Stone

and Wallace 1998, Whiles and Wallace 1995, Noel et al. 1986). Research has been

conducted in lower gradient Coastal Plain systems, including in fourth-order streams and

two rivers in Georgia (Benke et al. 1984, Wallace and Benke 1984) and in low order

streams of southeastern Virginia (e.g., Kedzierski and Smock 2001, Wright and Smock

2001, Smock et al. 1989). Generally, researchers and government agencies have given

little attention to wadeable streams of the coastal plain (Maxted et al. 2000). Therefore,

additional information is needed to build on the work previously conducted in the ACF

river basin (Muenz 2004, Davis et al. 2003, Gregory 1996) and further characterize the

unique aquatic macroinvertebrate assemblages of headwater streams.









Benthic Macroinvertebrates

Benthic macroinvertebrates are often used in biological assessments because: 1)

they are found in many types of aquatic habitats, 2) the variety of species that can be

monitored offer a range of responses to environmental changes, 3) they do not migrate

widely compared to other groups like fish, so they indicate conditions (Barbour et al.

1999), 4) their long life cycles allow temporal assessments, and 5) individual species'

tolerance to pollution have been established (Rosenberg and Resh, 1993). As a result,

benthic macroinvertebrates are well suited for continuous monitoring of streams, which

enables analysis of continuous and intermittent discharges, single or multiple pollutants,

and cumulative effects of pollutants (Rosenberg and Resh, 1993). However, using

macroinvertebrates in bioassessment also has a number of potential disadvantages: 1)

macroinvertebrates do not respond to all impacts, 2) they can be affected by natural

stressors and disturbances such as drought (Feminella 1996), 3) they display seasonal

variation (Linke et al. 1999), which can present constraints for timing of sampling and

comparing samples, and 4) their drift behavior can be problematic if the intent is to detect

localized pollution effects (Rosenberg and Resh 1993). This spatial and temporal

variability must be accounted for in the sampling design (Hershey and Lamberti 2001).

Analyzing macroinvertebrates for bioassessment can present challenges.

Taxonomy for some groups such as the Chironomidae and Oligochaeta requires

specialized training. Also, quantitative sampling requires high numbers of samples for

precision, and sample processing and identification are time consuming and expensive,

although rapid bioassessment methods can reduce these concerns (Rosenberg and Resh,

1993).









Biomonitoring

In the late 1980's, several state water resource monitoring programs were combined

and expanded by the United States Environmental Protection Agency (USEPA) and state

biologists to create Rapid Bioassessment Protocols (RBPs) as cost-effective biological

survey techniques (Barbour et al. 1999). RBPs use an integrated approach to assess

waterbody condition by comparing biotic, water quality, and habitat measures with

reference conditions. The latter can be empirically defined through historical data,

modeling/extrapolation, and/or actual reference sites, but it is best determined by

monitoring sites that represent natural ranges of variation, i.e. minimally disturbed with

respect to biological condition, water quality, and habitat (Gibson et al. 1996 as cited in

Barbour et al. 1999). As a result, biomonitoring programs have attempted to describe

reference conditions from a wide range of sites rather than relying on one or two

reference sites that could only be used for site specific comparisons.

Field experiments in biomonitoring typically measure abundances and/or other

characteristics of macroinvertebrates at different sites or times, each with associated

environmental conditions. Detected differences in macroinvertebrates are attributed to

differences in environmental conditions of that site or sample time (Cooper and Barmuta,

2000). Biomonitoring programs and field experiments in biomonitoring must have a

standard, or reference condition, by which other sites are evaluated. This provides a

baseline (Karr and Chu 1999) for comparison. Reynoldson et al. (1997) defines reference

condition as "the condition that is representative of a group of minimally disturbed sites

organized by selected physical, chemical, and biological characteristics." A challenge in

biological assessment is finding separate sites with similar physical, chemical and

biological characteristics to serve as a reference. Field studies have sought to decrease









this variability by comparing an upstream site to an impacted downstream area

(Kedzierski and Smock 2001), comparing nearby streams draining watersheds with

different land use or treatments (Davis et al. 2003, Richards and Minshall 1992, Gurtz

and Wallace 1984), comparing before and after a disturbance, or a combination of before

and after disturbance with watershed comparisons (Stone and Wallace 1998, Wallace et

al. 1996). Other studies have combined two of these approaches into a Before-After-

Control-Impact (BACI) design (Rosario and Resh, 2000).

Pre-treatment or baseline data are essential for characterizing responses to

management (Hershey and Lamberti 2001, Karr and Chu 1999, Reynoldson et al. 1997),

and robust baseline data can lessen the potential of natural variation obscuring

identification of a treatment effect. In this study, a two-year pre-treatment

characterization of benthic macroinvertebrates in adjacent watersheds and lower and

upper reaches of four streams in the Dry Creek watershed of southwestern Georgia was

undertaken to determine natural variation in macroinvertebrate assemblages.

Objectives

The objective of this research was to compare aquatic macroinvertebrate

assemblages in four headwater streams prior to an experimental evaluation of forestry

best management practices.

Major questions that were addressed included:

1. What are the macroinvertebrate assemblages in eight sample reaches (two per study
watershed)?

2. Are the assemblages (upstream vs. downstream, between watersheds, across time)
similar in population attributes, richness, composition, and functional feeding
group composition?

3. If assemblages in reaches are not similar, what are the primary environmental
differences between reaches that may be responsible?






7


4. How do different state assessment protocols score the biological condition of the
eight sample reaches?














CHAPTER 2
SITE DESCRIPTION

Study Site

The study was located in southwestern Georgia approximately 16 km south of

Bainbridge in the Coastal Plain physiographic province (Figure 2-1) specifically on the

boundary of two physiographic districts, the Tifton Upland and Dougherty Plain (Figure

2-2). The steeply sloping Pelham Escarpment also forms the boundary or surface-water

divide between the Flint River basin to the west and the Ochlockonee River basin to the

east (Couch et al. 1996). Streams originating from the Pelham Escarpment are

characterized by perennial headwaters that downstream become intermittent or drain

directly into the Flint River. This transitional area is characterized by bluffs and deep

ravines that create cool microclimates supporting rare plant species with northern

affinities (Wharton 1978 as cited in Entrekin et al. 1999).












-----^ .---r



Figure 2-1. Location of study site in relation to physiographic regions (modified from US
Forest Service 1969).

















OrS-
,E, ,, N-






LOE I AP IA ER
^ i V rl/1 h^ /L-















S COASTAL', LON'-
"-E IIF' -F-.
C,," \ 1 F

\- ~ "-' 0 10 0 MILES"
S0 10 20 KILOMETERS
I ]7
Base modified from U.S. Geological Surwy
l: 100,OO-sc ale digital data Apatach ola-
s \ lowr AChatlahoochee-
EXPLANATION / Flint R ver Basin
LOWER APALACHICOLA- o ALABAMA \ EORGIA
CHATTAHOOOHE E- FLINT L
RIVER BASIN -^-
SPHYSIOGRAPHIC DISTRICT
BOUNDARY



Figure 2-2. Location of study area in relation to physiographic districts (modified from
Torak 2003).

The study site is located in the Dry Creek watershed, which discharges to the Flint


River approximately 22.5 km up from the Jim Woodruff Dam of Lake Seminole. The

Flint River is part of the larger lower Apalachicola-Chattahoochee-Flint River (ACF)


Basin. Late Eocene Ocala Limestone extends throughout this 17,600 km2 river basin.

Oligocene Suwannee Limestone extends 26 km up the Flint River impoundment arm


(Torak 2003). Soils of the study sites are dominated by Ultisols, with the riparian area









comprised of the Chiefland and Esto series, classified as well drained fine sands over clay

loams. The slopes are Eustis series soils, which are loamy sands over sandy loams and

classified as somewhat excessively well drained. The upland soils are comprised of

Wagram, Norfolk, Lakeland, Orangeburg, and Lucy, which are generally well drained

loamy sands over sandy clay loams, with the exception of the Lakeland Unit, which has a

sandy texture throughout and is characterized as excessively well drained (International

Paper 1980).

Streams draining the four study watersheds, A, B, C, and D (Figure 2-3) comprise

part of the headwaters of Dry Creek.









(C c a. 1 k7rsinhC st i v
o g d b e.:
S | I I .** .






7f -.
". "-












Figure 2-3. Topographic map of Dry Creek watershed and location of four headwater
watersheds (A-D).

Surface water flow in the ACF basin is lowest from September to November and

peaks during January to April due to higher rainfall and decreased evapotranspiration

(Couch et al. 1996). Streams and rivers in the Coastal Plain receive substantial amounts

of groundwater because they are typically deeply incised into underlying aquifers (Couch
: ;.o ....














'f "rudae eas hyaetpclydel nie noudryn qies(oc









et al. 1996). The study streams are first order, groundwater-influenced, low to medium

gradient, and have sand-dominated substrate. In-stream habitat includes coarse woody

debris, undercut banks, leaf packs, and fine roots. The four study watersheds average 39

ha, 1.5 L/s in average annual discharge, and 457 m in channel length (Summer et al. 2003

and Summer unpublished data). Watersheds A and B have gentle slopes and broader,

meandering channels, whereas the remaining watersheds, C and D, have steeper slopes

with well defined stream channels.

Vegetation

The overstory, midstory, and understory vegetation in riparian, midslope, and

upslope areas of watersheds A, B, C, and D are generally similar with a few exceptions.

The species dominating the overstory in riparian areas were: Nyssa biflora, Liriodendron

tulipifera, Pinus glabra, Magnolia virginiana, Fagus grandifolia, Liquidambar styraciflua,

Quercus nigra, and Quercus michauxii. Magnolia grandiflora was found more frequently

in watersheds C and D (International Paper unpublished data). The upland of each

watershed was dominated by Pinus taeda, which was established at varying times by hand

planting. The midstory of all watersheds was generally composed of Carpinus

caroliniana, Ostrya virginiana, Acer rubrum, Acer barbatum, and Oxydendrum

arboretum. Magnolia pyramidata occurred in riparian areas and midslopes of watersheds

C and D. The understory composition and coverage varied from watersheds A and B

dominated by riparian wetland species to watersheds C and D with understory similar to

that of watersheds A and B, but less abundant. This is likely due to the mixed mesic

hardwood forest type and drier soil conditions of watersheds C and D. Typical shrub

species of the understory were Ilex coriacea, Myrica cerifera, Rhododendron canescens,

Viburnum nudum, Alnus serrulata, Ilex glabra, and Ilex opaca. Herbaceous species of









the understory in watersheds A and B included Boehmeria cylindrica, Woodwardia

virginica, Woodwardia areolata, Panicum sp., Carex sp., Cyperus sp., Juncus effusus, and

Smilax laurifolia. Typical herbaceous species in the understory of watersheds C and D

were Arundinaria gigantea, Leucothoe axillaris, Smilax pumila, and Mitchella repens

(International Paper unpublished data).

Climate

Climate of the region is characterized by warm, humid summers, and mild winters.

Temperatures in January, the coldest month of the year, range from an average maximum

of 16.3C and a minimum of 2.8 C. July is the hottest month of the year with an average

maximum temperature of 33.5 C and minimum of 21.5 C (SERCC 2004). Mean annual

precipitation is 1412 mm. June has the highest mean rainfall (152.1 mm) and October

lowest (77.5 mm) (SERCC 2004). Summer rains are usually short, with high intensity

events giving way to low intensity frontal events from late fall to early spring. Due to

proximity of the Gulf of Mexico, heavy rainfall associated with hurricanes and tropical

storms in late summer is not unusual. Drought conditions occurred during 1998-2002

and resulted in an accumulated rainfall deficit of 711-1270 mm in some southwestern

Georgia areas (Pam Knox, Assistant Georgia State Climatologist, oral communication as

cited in Warner and Norton 2003).

Site History

Starting with small-scale disturbance by Native Americans who used fire to

manage pinelands and prepare land for cultivation, the forest in many parts of the ACF

river basin has been affected by human activity. This continued through European

settlement, with pre-and post-Civil War agriculture, and now the area is primarily

characterized by second growth stands and acreages of planted pine (Couch et al. 1996).







13


Site history specific to the study area and when noted, the specific study sites, is as


follows.


Table 2-1. Site history events for the study site and watersheds.
Watersheds
*SA A B C D Site History Event
Date:
1837 X Site settled by Munnerlyn family
Cattle grazing and sharecropped for cotton, corn, peanuts, and flax

1925 X Portable sawmill operations
Riparian areas not likely harvested

1937 X Managed as a hunting preserve

1957 X Property acquired by International Paper

1968 X X Uplands of C (south side) and D (north side) hand planted with loblolly pine
1969 X X Uplands of B (south side) and C (north side) hand planted with loblolly pine

1986 X 5.67 ha portion was hand planted
1987 X 5.67 ha portion had herbicide applied by a skidder to control herbaceous vegetation
1988
1989 X X Uplands of A and B (northern half) hand planted with loblolly pine
1990 X X Uplands of B (south side) and C (northern portion) were control burned
1991
1992 X X Uplands of B (south side) and C (northern portion) were control burned
X X Uplands of C (south side) and D (north side) were control burned
X Uplands of D (south side) were control burned
1993
1994 X 5.67 ha portion was control burned
1995 X X Uplands of C (south side) and D (north side) were control burned
1996 X 5.67 ha portion was control burned
X X Uplands of B (south side) and C (northern portion) were thinned
X X Uplands of C (south side) and D (north side) were thinned
1997
1998
1999
2000 X 5.67 ha portion was control burned
X X Aerial herbicide application and control burn for uplands of A and B (northern half)
2001 X 5.67 ha portion was thinned

*SA = activities occurred in study area


In 1837, the land known then as the Fowltown tract was bought and settled by


Charles Lewis Munnerlyn, originally from Georgetown, South Carolina. The 1,349 ha


property was pineland at the time of purchase, which was thought to be of little value


except for cattle grazing (International Paper 1997). In the 1830's and 1840's the


Munnerlyn slaves cleared all debris (i.e. moss, limbs, and leaves) out of the streams and


spread this over the fields. This scattering of debris and another technique known as


"cow pinning", which consisted of allowing large herds of cattle to rest in the fields, was









used to enrich the soils. This practice is thought to have occurred in the study streams and

watersheds (J. Wingate, personal communication, 17 August 2004). In 1864,

Munnerlyn's only son, Charles James, was appointed by Jefferson Davis as a Major with

command of the First Battalion, Florida Special Cavalry. This battalion, later named the

Cow Cavalry, was organized to collect and drive cattle from Florida to help supply the

Confederate Army. Munnerlyn's superior officer noted that he had operated his own

large plantation with great success (Taylor 1986). The study area is thought to have been

used as a resting and grazing place by Munnerlyn for cattle herds being moved from

Florida to Columbus Georgia to supply Confederate troops (J. Wingate, personal

communication, 17 August 2004). During the years of Munnerlyn family ownership after

the war, the property was sharecropped for cotton, corn, peanuts, and flax (Table 2-1) (J.

Wingate, personal communication, 17 August 2004).

There is evidence of damming in an upstream portion of watershed C. This site

was dammed, and a water "ram" was constructed downstream. This ram supplied water

to a house located upslope from the site, which is thought to be the first house built in

1822 or 1823 in Decatur County (J. Wingate, personal communication, 17 August 2004).

It is not known when this dam was installed, or how long it existed.

In 1925, the property was sold to a partnership ofLudwick Gaissert, O.M. Peden,

H.R. Garrett, and W.R. Layson. This partnership dissolved, and H.R. Garrett became

sole owner and set up a lumber mill site. His operation had portable saws and moved

from site to site on the property as needed (Table 2-1). Garrett apparently did not use

oxen to move harvested timber, and this has led to the assumption that Garrett

predominantly cut timber on the ridges and likely did not harvest riparian areas at the









bottom of steep slopes that are found in the study area (J. Wingate, personal

communication, 17 August 2004). Due to better opportunities or possibly because most

saleable timber had been cut, Garrett sold the property.

Richard Tift, a prominent land speculator, and Herbert L. Stoddard, generally

recognized as the "father" of prescribed burning in the South and for his work with

bobwhite quail, began buying options for parcels of land along the Flint River. After

approximately a year and a half, Tift and Stoddard acquired options for 28 parcels of land

comprising 10,522 ha. In 1937, Houghton P. Metcalf, a wealthy industrialist from

Providence, Rhode Island, bought the parcels and named his estate Southlands. Metcalf

authorized removal of the remainder of Munnerlyn's cattle herds and wild hogs from the

property. The property on the east side of the Flint River, where the study site is located,

was managed as a hunting preserve (Table 2-1) and was specifically managed to attract

quail, dove and turkeys. The property on the west side of the river had a hog farm and

was planted in corn and peanuts. Metcalf was interested in reforestation and wanted to

preserve the natural beauty of the property. In 1947, the property was sold to Southern

Kraft Timberland Corporation, a division of International Paper Company (International

Paper 1997).

On 14 November 1957, the property was dedicated as a research center due, in part,

that all four major southern pine species (i.e. loblolly, longleaf, shortleaf, and slash)

naturally grew on site (Table 2-1). Also, the property had diverse terrain with upland

loblolly sites on the east side of the river, sandy longleaf sites on the west side of the

river, river swamps, and bottomland hardwoods (International Paper 1997).









Detailed information on each stand in the study was obtained from International

Paper stand inventory data (Table 2-1). Trees in riparian areas of each of the four study

watersheds were aged by a timber cruise in 1987. Increment cores were taken on 2 or

more trees per plot in the natural pine/hardwood stands. An establishment date was

estimated as 1935 (D. Morgan, personal communication, 3 August 2004), although the

trees in riparian areas are thought to be older due to the manner of harvesting employed

by H.R. Garrett (J. Wingate, personal communication, 17 August 2004). Riparian areas

in all four watersheds, (A through D), (Figure 2.3) were not subject to any silvicultural

activities due to International Paper policy of maintaining forested buffers. A 5.67 ha

portion of watershed A, north of the stream and south of the main road, was hand planted

in 1986, and herbicide was applied by a skidder in 1987 to control herbaceous vegetation.

This area was control burned in 1994, 1996, and 2000 and thinned in March 2001. The

majority of the uplands of watershed A and the northern half of watershed B were hand

planted with loblolly pine in 1989. An aerial herbicide application and a control burn

were completed in 2000. The uplands on the south side of watershed B and the northern

portion of watershed C's uplands were established in 1969 by hand planting of loblolly

pine. Control burns were completed in 1990 and 1992, then the area was thinned in

1996. Uplands on the south side of watershed C and the north side of watershed D were

hand planted with loblolly pine in 1968. Control burns were completed in 1992 and

1995, and the area was thinned in 1996. Uplands on the south side of the stream in

watershed D were allowed to naturally regenerate in 1950. A control burn of this area

was completed in 1992.






17


A private landowner owns 24% of watershed B and 18% of watershed C (Figure

2.4). A cattle farm was operated in these areas from 1950 through 1994. Hogs were also

kept on the property. Streams of watersheds B and C were the water source for the cattle

and hogs. In 1968, pines were selectively removed from riparian areas, but hardwoods

were left (C. Lynn, personal communication, 17 August 2004).















CHAPTER 3
METHODS

Overview of Study

Four headwater streams and their watersheds (A, B, C, and D) were selected for

study (Figure 3-1). The overall Dry Creek Study (Streamside Management Zone

Effectiveness on Hydrology, Water Quality, and Aquatic Habitats in Southwestern

Georgia Headwater Streams) design includes elements of before and after,

upstream/downstream, and paired watersheds experimental designs.

I-1~,~~1, 'j;' -~`'


Figure 3-1. Topographic map and aerial photograph of location of four headwater
watersheds (A-D).









This study compared upstream vs. downstream, between watersheds, and across

time to evaluate macroinvertebrate assemblages and primary environmental variables in

the four adjacent study streams. This study established the pre-harvest condition and

natural variability of the macroinvertebrate assemblage. This information will be used

for post-harvest comparisons in the overall Dry Creek Study, being conducted by

multiple partners.

Data Collection

Physical Measurements

Eight fixed-distance sample reaches, two per watershed, were established 30.8 m

upstream of flumes (Figure 3-2).


Figure 3-2. Topographic map of location of four headwater watersheds (A-D) with eight
sample reaches and schematic of an individual sample reach.









Three transects were established perpendicular to the stream within each reach to

serve as in-stream data collection points for physical measurements including channel

cross-sections, canopy cover, and percent cover of in-stream habitat. At each transect,

percent cover of in-stream habitat was determined by extending a tape across the active

channel and recording the length of each habitat type (e.g., sand, small woody debris,

roots, leaf pack, gravel). These lengths were converted into percent cover, which was

used to define the major habitat types to be sampled for macroinvertebrates. In August

2002, pictures of the canopy were taken at each transect with a digital camera fitted with

an 180 hemispherical fisheye lens.

A survey of habitat unit and channel characteristics was conducted longitudinally

within established macroinvertebrate sample reaches. A 50 m fiberglass tape was placed

in the thalweg of the stream, then divisions between each habitat unit type were

determined and physical characteristics were recorded. Unit types included riffle, run,

glide, pool, backwater pool, step, and undercut bank. A backwater pool was defined as

slower and deeper than a glide, but did not possess characteristics of a pool, such as

evidence of scouring, deposition, and having a deep and shallow section (i.e. measurable

residual pool depth). For each unit type, a unit end (length), channel width (active

channel), and maximum water depth were recorded. For step and pool unit types, a step

height and residual pool depth were taken. Primary obstructions (e.g., wood, roots), their

length, and diameter, were recorded when the object was primarily responsible for pool

formation. A tally of functional and non-functional wood greater than 10 cm in diameter

was taken. Functionality was based on the role wood played for changing morphology.










Texture of the streambed (e.g., sand, silty-sand) was estimated by soil feel and

appearance in each sample reach.

Environmental Measurements

Sixteen leaf litter traps (surface area of 0.26 m2 each) were positioned within the

riparian area: six along the streambank, six 10 m from the stream, and four 20 m from the

stream (Figure 3-3). Litter samples were collected monthly, dried at 600C for 24 hours,

separated into pine and hardwood foliage, woody debris, and mast, and weighed.

U Ip F IEp r IlIEalHp AMDa.to, MII t tn.I


1P 1 020 ihppe rD p


q
T II ul, ilt
5Up Or*m bI ii iJ




periphyton and macrophytes in June, July, and August. Following the method of Tett et

pmo M




SuIhrul NorI


Figure 3-3. Schematic of a representative sample reach with layout of litterfall traps.

Within each stream reach, ten randomly selected locations were sampled for

periphyton and macrophytes in June, July, and August. Following the method of Tett et

al. (1978), two petri dishes (17.34 cm2) were inserted into the sediment at each sampling

location. Chlorophyll a concentrations of periphyton in the sediment sample were

measured using an acetone extraction procedure (American Public Health Association,

1995) followed by colorimetric analysis. The contents of the second petri dish were dried









at 60C, weighed, burned at 5000C, and reweighed for ash-free dry weight determination.

Macrophytes were sampled by cutting all vegetation at the sediment surface that existed

within a 0.25 m2 quadrat. Macrophyte samples were rinsed and dried at 600C (Kedierski

and Smock, 2001). Dry weight was determined for each sample.

Chemical and Hydrological Measurements

Water temperature was measured from October 2001 through December 2003 with

an Onset HOBO 9 temperature logger (Pocasset, MA), which was programmed to

measure temperature every 15 minutes. Stream flow, water chemistry, and

meteorological measurements have been collected by other investigators as part of the

Dry Creek Study, and these data were available for use in this study. Stream stage and

discharge was recorded every 15 minutes by Isco Model 4320 Bubbler Flow Meters at six

sites: one in the stream at the outlet of watersheds A, B, C, D and one in the upstream

portion of watersheds B and C (Summer 2003). Monthly in-situ measurements for

dissolved oxygen, specific conductance, temperature, pH, and turbidity were made at

eight sites (two per watershed) with portable meters. Grab samples were taken from a

midstream location and analyzed for inorganic nitrogen, inorganic phosphorus, and

ammonium (Jones et al. 2003).

Macroinvertebrates

Benthic macroinvertebrates were collected within established sample reaches

(Figure 3-2) with a 500-[tm-mesh D-frame net (0.3 m wide) in December 2001, February

and December 2002, and February 2003 using a multi-habitat sampling procedure

(Barbour et al. 1999). This procedure was tested by the Mid-Atlantic Coastal Streams

Workgroup and the Florida Department of Environmental Protection and deemed a

scientifically valid sampling technique for low-gradient streams (Barbour et al. 1999).









Fall and winter sampling periods were chosen because these seasons are prior to the

emergence of most species and larvae are generally easier to identify because of their

larger size. Within each reach, 20 sampling sweeps (i.e. disturbing habitat for 0.5 m)

were made through major habitat types such as sand, woody debris, fine roots, and leaf

packs. This resulted in approximately 3.1 m2 of habitat sampled. The duration of

sampling in each reach was timed to maintain a consistent sampling effort for all reaches.

Material collected from each sampling sweep was deposited in a 19 L bucket. Material in

the bucket was rapidly stirred to suspend organisms and poured into the 500-tm-mesh D-

frame sampling net. Material caught in the net was placed in a 4 L glass jar and

preserved with 70% ethyl alcohol in the field. Rose Bengal biological stain was added to

each sample in the laboratory. All samples were processed by washing organic debris

(leaves and woody debris) with water into a 500-[tm-mesh sieve. Invertebrates were

handpicked from the sieve contents and identified to genus or species (when possible),

under a low power (<50x) dissecting microscope (Richardson 2003, Gelhaus 2002,

Pescador, Rasmussen, Richard 2000, Epler 1996, Merritt and Cummins 1996, Pescador,

Rasmussen, Harris 1995, Peckarsky et al. 1990, Brigham, Brigham, and Gnilka, 1982).

Genus or species-level taxonomy has been found to yield the greatest benefits for

biological monitoring studies especially when results could influence management

decisions (Lenat and Resh 2001). Ephemeroptera, Plecoptera, and Trichoptera generic

identifications were verified, and species identifications were made when possible by

M.L. Pescador and A.K. Rasmussen. Dytiscidae species identifications were made by Bill

Wolfe. All Chironomidae samples were sent to a consultant, Pennington and Associates,

for identification, generally to species. Larval Chironomidae were cleared with cold 10%









KOH for 24 hours, then temporary slide mounts were made using glycerin. Permanent

slide mounts were made in CMC mounting media for voucher specimens. Identifications

were made to genus under a dissecting microscope using Merritt and Cummins (1996).

Further identification to species was made using a compound microscope (Epler 2001).

Functional feeding group and habitat/behavior designations were determined using

Merritt and Cummins (1996). Oligochaeta, Gastropoda, and Bivaliva were enumerated

but not identified beyond Class and were not included in metric calculations or data

analysis.

Data Analysis

Physical Measurements

Percent cover of in-stream habitats was summarized for each site. Length

multiplied by average width measurements for each channel unit was used to calculate

the area of each channel unit. The percentage of the total area occupied by each channel

unit was calculated by: % of Area = area of channel unit type / total area of reach x 100

(Bisson, and Montgomery, 1996).

A digital camera was used to convert the hemispherical images of canopy cover

into bitmaps, which were then analyzed using Gap Light Analyzer software (Frazer and

Canham, 1999). This software transformed pixel intensities into sky and non-sky classes,

then these data were used to estimate percent canopy cover. A tally of functional and

non-functional wood > 10 cm in diameter was summarized for each site.

Environmental Measurements

Seasonal average dry-weight data were calculated from the six litterfall traps

positioned along the stream bank for each site. Repeated measures analysis of variance

(ANOVA) (SPSS Inc., Chicago IL) was used to determine whether there was a









significant effect due to position (upstream versus downstream, df =1,6), season (fall,

winter, spring, summer, df =3,18), or the interaction of position and season (df =3,18). A

second repeated measures ANOVA was run to determine effects due to season (fall,

winter, spring, summer, df =3,12), stream (A, B, C, D, df = 3, 4), or the interaction of

season and stream (df =9,12). The sample size for each stream was 2, which limited the

power of the across stream comparisons. Periphyton chlorophyll a concentrations,

periphyton ash-free dry-weight, and macrophyte dry-weight were analyzed using one

way ANOVA (alpha = 0.05), which tested the equality of site means. One way ANOVA

was used because the samples for each site were 10 independent random samples.

Differences between time periods were not examined because samples were collected in

one summer season, June, July, and August of 2003. Fisher's multiple comparison

procedure was used for significant ANOVA results, which generated confidence intervals

for all pairwise differences between site means (individual error rate = 0.05) (Minitab

Inc., State College PA).

Chemical and Hydrological Measurements

Monthly dissolved oxygen, specific conductance, temperature, pH, turbidity,

inorganic nitrogen, inorganic phosphorus, and ammonium values were summarized as

averages for six months and three months prior to each macroinvertebrate sample.

Average daily flow (Liters/second) was converted into minimum, average, and maximum

daily flow for each month. Average zero-flow days were calculated and further

summarized as averages for six months and three months prior to each macroinvertebrate

sample.









Macroinvertebrates

Data from each site were used to develop numerical metrics to describe the

macroinvertebrate assemblages of the study streams. Abundance and percent dominant

taxon (i.e. dominance of the single most abundant taxon) were tallied and calculated to

characterize the population in each stream. Taxa richness, EPT taxa, and number of

Chironomidae taxa were calculated to determine richness. Taxa richness was calculated

as the number of unique taxa at the family, genus, or species level. For example, if a

sample contained 5 Libellulidae, 4 Gomphidae, 5 Gomphus, 5 Progomphus, and 1

Boyeria vinosa, this would result in 4 taxa with 20 individuals. EPT taxa were calculated

as the number of unique taxa at the genus or species level. Number of Chironomidae

taxa was calculated as the number of unique taxa at the genus or species level. Percent

Diptera and percent Chironomidae were also calculated for each stream. Percent filter

feeders and number of clinger taxa provided information on partitioning feeding

strategies and habitat preference of insects in the assemblages.

Percent Elmidae was calculated as an experimental metric because percent Elmidae

was found useful in describing perennial streams within Georgia's Fall Line Hills District

(Muenz 2004), which is located in the adjacent physiographic district to the study site

(Figure 2.2). Elmids prefer swifter parts of streams such as oxygen rich riffles (Merritt

and Cummins 1996). Also, this family of beetles were described by Epler (1996) to be

the most truly aquatic of Florida water beetles because the larvae possess gills and adults

utilize a plastron (covering of fine dense hydrofuge setae that holds a layer of air where

gases can be exchanged), which enables them to remain submerged. Most other aquatic

beetles must go to the surface. These characteristics of the Elmidae make them the best

candidates of the aquatic beetles as indicators of water quality (Epler 1996).









Data from each site were used to develop numerical metrics which were used to

calculate Florida Department of Environmental Protection's Stream Condition Index

(SCI) (FDEP, 2004) and Georgia Department of Natural Resources' (DNR) Freshwater

Macroinvertebrate Biological Assessment (GA DNR, 2002). Oligochaeta, Gastropoda,

and Bivaliva were excluded from analyses. For Florida's SCI, raw data from each site

were sub-sampled for 100 individuals using Microsoft Excel's random number

generator. Metric values for total taxa, Ephemeroptera taxa, Trichoptera taxa, long-lived

taxa, percent filter feeders, number of clinger taxa, number of Chironomidae taxa, percent

Tanytarsini, sensitive taxa, and percent very-tolerant were calculated and converted into a

metric score ranging from 0 to 10 using formulae contained in Table 3-1.

Table 3-1. Stream Condition Index metric scoring formulae.
SCI metric Northeast Panhandle Peninsula
Total taxa 10 (X-16)/26 10 (X-16)/33 10 (X-16)/25
Ephemeroptera taxa 10 X /3.5 10 X /6 10 X /5
Trichoptera taxa 10 X /6.5 10 X /7 10 X /7
% Filterer 10 (X-1)/41 10 (X-1)/44 10 (X-1)/39
Long-lived taxa 10 x/3 10 X /5 10 X /4
Clinger taxa 10 X/9 10 *X /15.5 10 X /8
% Dominance 10 ( 10 [ (X-10)/44 ) 10 ( 10 [ (X-10)/33 ] ) 10 (10 [ (X-10)/44 )
% Tanytarsini 10 [ ln(X+ 1)/3.3] 10 [In( X + 1)/3.3] 10 [ ln(X + 1)/3.3]
Sensitive taxa 10 X/11 10 X /19 10 X /9
% Very tolerant 10 (10 [ln(X + 1)/4.4 )10 (10 [ln(X + 1)/3.6 )10 (10 [ln(X + 1)/4.1 )
(FDEP, 2004)

Metric scores were summed and divided by a correction factor. The SCI category

(good, fair, poor, very poor) for each site followed ranges provided in the index (Table 3-

2).









Table 3-2. Category names, ranges of values for Stream Condition Index, and typical
biological conditions.
SCI category SCI range Example Description
1 sample
Good [73-100] Similar to natural conditions, up to 10% loss of taxa
expected
Fair [46-73) Significantly different from natural conditions; 20-30%
loss of Ephemeroptera, Trichoptera and long-lived taxa;
40% loss of clinger and sensitive taxa; percentage of
very tolerant individuals doubles
Poor [19-46) Very different from natural conditions; 30% loss of total
taxa; Ephemeroptera, Trichoptera, long-lived, clinger
and sensitive taxa uncommon or rare; Filterer and
Tanytarsini individuals decline by half; 25% of
individuals are very tolerant
Very poor [0-19) Extremely degraded; 50% loss of expected taxa;
Ephemeroptera, Trichoptera, long-lived, clinger, and
sensitive taxa missing or rare; 60% of individuals are
very tolerant
(FDEP, 2004)

For Georgia's Biological Assessment, the data from each site was used to calculate

the following metrics: taxa richness, number of Ephemeroptera, Plecoptera, and

Trichoptera (EPT) taxa, number of Chironomidae taxa, percent contribution of dominant

taxon, percent Diptera, Florida Index, and percent filterers. These metrics measure the

richness, composition, tolerance/intolerance, and feeding strategies of the assemblage.

Each metric value was converted into a score, and scores were summed. Georgia DNR

reference stream data scores from the Southeastern Plains Ecoregion, Tifton Upland sub-

ecoregion were averaged and compared to study sites. Percent comparability of study to

reference sites were calculated (study site score/reference site score x 100) to determine

ecological condition (Table 3-3). A second calculation of Georgia's Biological

assessment was performed for a 200 individual sub-sample according to GA DNR's

Standard Operating Procedures (GA DNR, 2002). Raw data from each site were sub-











sampled for 200 individuals using Microsoft Excel's random number generator, and


scores were generated as outlined above.


Table 3-3. Sample Ecological Condition Worksheet.
SOUTHEASTERN PLAINS (65)
Study Site SCORE RANGES Study Ref Site
METRIC: Data: Ref Site: 5 3 1 0 Site Score
Taxa Richness (Total # Taxa) >30 30-16 <16
EPT Index >6 6-4 <4
# Chironomidae Taxa >8 8-5 <5

% Contribution of Dominant Taxon <23 23-61 >61
% Diptera ----- <51 >50
Florida Index >15 15-8 <8
% Filterers >11 11-6 <6
Total Habitat Score: >89% 89-75% 74-60% <59%
Total Points Earned 0 0
% of Reference Site
Ecological Condition:
Very Good Comparable to best situation expected; species with endangered, threatened, or > 82%
Good Balanced community with sensitive species present. 81-64%
Fair Expected species absent or in low abundance; few sensitive species present. 63-48%
Poor Low species richness, with tolerant species predominant, sensitive species absent. 47-35%
Very Poor Expected species absent, only tolerant organisms present, few or no EPT taxa. < 35%
(GA DNR 2002)


Using the Georgia Biological Assessment method, study sites were compared to


each other to assess year to year, between watersheds, and upstream vs. downstream


percent comparability. An ecological condition score was not assigned to these


comparisons.


Georgia Adopt-A-Stream volunteer monitoring assessment methods were applied


to the macroinvertebrate data. A presence/absence count of sensitive, somewhat


sensitive, and tolerant insects, crustaceans, aquatic worms, gastropods, and bivalves were


made for each site. All categories were summed and multiplied by a factor of 3 for


sensitive, 2 for somewhat sensitive, and 1 for tolerant. The result for each category was


summed for the total index value, and a water quality ranking (excellent, good, fair, and


poor) was assigned (GA DNR 2000).


All percent metrics were arcsine transformed and abundance was log transformed


prior to statistical analysis. Repeated measures ANOVA (SPSS Inc., Chicago IL) was









used to determine any significant effect due to position (upstream versus downstream, df

=1,6), time (Dec 01, Feb 02, Dec 02, Feb 03, df =3,18), or interaction of position and

time (df =3,18) for all macroinvertebrate metrics and index values. Within and between

subjects means and standard error were calculated as part of the repeated measures

ANOVA procedure (SPSS Inc., Chicago IL). When significant (P<0.05) differences

were detected due to time, repeated contrasts (i.e. comparison of adjacent levels) was

used to compare time periods. A second repeated measures ANOVA was run when

position was insignificant (P>0.05) for determining effects due to time (Dec 01, Feb 02,

Dec 02, Feb 03, df =3,12), stream (A, B, C, D, df = 3, 4) or interaction of time and stream

(df =9,12). The power of this analysis was limited because the sample size for each

stream was two. When ANOVA resulted in significant (P<0.05) differences between

means, a pairwise multiple comparison test (Tukey's honestly significant difference

(HSD) test, alpha = 0.05) was made between means of a factor.

Principal components analysis (PCA) was used as an exploratory analysis

(Golladay and Battle 2002, Karr and Wisseman 1996) to visualize broad trends in the

chemical data, hydrological data, and macroinvertebrate measures among sites. This

technique reduces a data set with many variables into a smaller number of composite

variables (axes) and indicates covariation among variables with a set of primary axes.

Options for PCA included Euclidean distance and cutoff r2 (0.2) (McCune and Mefford

1995). For each PCA (i.e. chemical, hydrological, and macroinvertebrates), the number

of axes included in the analysis was determined using broken-stick eigenvalues. For the

PCA graph, each stream was assigned a unique symbol and further identified with a

position number (1-downstream, 2-upstream) and a time number (1-Dec 01, 2-Feb 02, 3-









Dec 02, and 4-Feb 03). Interpretation of PCA results assumed that most variation is

explained by variables furthest from the origin. Positively correlated variables are close

together, whereas negatively correlated variables are located at opposite ends of the axis.

Data points close together are more similar, and those far apart are dissimilar.

Stepwise multiple regressions (Alpha-to-Enter: 0.05, Alpha-to-Remove: 0.05)

(Minitab Inc., State College PA) were used to quantify relationships between predictor

variables (abundance, EPT taxa, total taxa, Georgia EPD index, Georgia AAS index,

percent Elmidae, percent dominant taxa, and percent filtering collectors), with response

variables (DO, pH, water temperature, specific conductance, inorganic nitrogen,

inorganic phosphorus, ammonium, turbidity, maximum daily flow, average daily flow,

minimum daily flow). Abundance, EPT taxa, total taxa, Georgia EPD index, Georgia

AAS index, and percent Elmidae were selected as response variables because of

significant ANOVA results. Five models were run for each response variable: 1) all

samples pooled (n=31), 2) December 2001 samples only (n=7), 3) February 2002

samples only (n=8), 4) December 2002 samples only (n=8), 5) February 2003 samples

only (n=8). This procedure was run three times with mean values for water chemistry

and hydrologic variables from one month, three months, and six months prior to

macroinvertebrate sample collection.














CHAPTER 4
RESULTS

Physical Measurements

Habitat units in the study streams included sand (and other fine sediment), leaves,

roots, undercut bank, gravel, and small woody debris (SWD, <10 cm in diameter). The

percent coverage of these in-stream habitat types varied more among watersheds than

within the same stream. Sand and leaf habitat was most abundant in watershed A. Site

A-1 contained more undercut bank habitat, whereas A-2 had a greater percentage of roots

(Figure 4-1). Sand and leaves were dominant habitats in watershed B, with root habitat

also represented. Site B-2 had gravel and undercut bank habitats represented, while site

B-l did not (Figure 4-1). Watershed C, Sites C-l and C-2 contained sand, leaf, root, and

SWD habitats. Coarse bed material was observed at C-l, but did not occur in a measured

transect. Sites in watershed D (Figure 4-1) were characterized by sand, leaf, gravel and

SWD habitats, with D-1 also having root habitats. Although not measured in this survey,

exposed areas of limestone were present in the streambed of watershed D.

Channel units in the study streams included backwater pool, glide, pool, riffle, run,

and step. The percent aerial coverage of these channel units varied among watersheds and

within the same stream. Site A-i had a much greater percentage of run (49%) than A-2

(13%), but A-2 had 30% more backwater pool area than A-i (Figure 4-2). Sites B-l and

B-2 (Figure 4-2) had similar areas of glide, pool, and run, but B-2 had a small area of

riffle, and B-l had a small area of backwater pool.















-s r
A,


9-2









8-2 ab


4In


,,U,










C-I

I -.. . .
.
- -


. .


1 -



















Figure 4-1. Percent coverage of in-stream habitat units for each sampling site (A-1

through D-2).


I-
.5
C- T






wnmkm~




.











.- a w






PO

















a
.


. s


-sn
a .
wwe
. . ..











V


B-i















c;-i















fl-I


Figure 4-2. Percent coverage of in-stream channel units for each sampling site (A-l
through D-2).


EL
Sc n









Sites within watershed C were dominated by runs and glides at C-l and C-2,

respectively. C-l had areas with riffles, whereas C-2 had backwater pools (Figure 4-2).

Sites within watershed D were the most similar in channel unit area, with all unit types

represented. Runs dominated the stream, with glide areas of secondary importance.

Riffles were present at both D-1 and D-2 (Figure 4-2).

Average canopy for all sites combined was 85% with maximum canopy cover of

87% at site B-l and minimum (83%) at C-2. Canopy cover varied within sites, but

percentages were similar among sites (Figure 4-3).

95


90


85-

S0
S80


75


70-
A-1 A-2 B-1 B-2 C-1 C-2 0-1 D-2
Site

Figure 4-3. Percent canopy cover for each sampling site (A-l through D-2) as defined by
GLA software. Data represented in box (interquartile range) and whiskers plot
with median (horizontal line), mean (circle), and outliers (star).

Amounts of large woody debris (LWD) varied greatly among and within

watersheds with no readily apparent patterns (Table 4-1). A-1 and B-l had the greatest

number of total LWD. B-2, D-1, and D-2 had lowest total numbers of LWD.











Table 4-1. Tally of large woody debris (>10cm diameter).
Al A2 01 02 C1
Functoanio 8 1 3 0 4
ian.funrtihanul I 2 3 7 1 1


Environmental Measurements

Repeated measures ANOVA for litterfall indicated significant (P<0.001)

differences between the four sampling periods (time). There was no significant effect

(P=0.92) due to sampling position (upstream/downstream) or the interaction between


position and time (P=0.62). There were no significant (P=0.50) differences among sites.

Most litterfall in all streams occurred from September through January. Hardwood

leaves comprised the greatest proportion of litterfall during this time period (Figure 4-4).


IBM

1WD
E






111o
e2
a







1'a.


1K


Am De. Jai Flb Mal r Apr lMar in ill Aug SEp Ot KI EEr Jim Feb H l ar rApr ;r Jg i l A gi SEp
I DI I m 2 D 2 02 02 2 2 D2 D2 02 2 D3 D El D D0 3 D 0a3



Figure 4-4. Average dry weight of total litterfall (hardwood leaves, pine, woody debris,
and mast) across sites with proportion of total litterfall as leaves (hardwood
leaves) in grey.


C? DI D0


5 0 1
1 2 0


tfl r Otitr t I






nIbsl n~k









There were no significant differences among sites for periphyton chlorophyll a

mean concentrations in July (P=0.49) and August (P=0.59) samples (Table 4-2). June

2003 samples are not reported due to an analytical error.

Table 4-2. Mean periphyton chlorophyll a and dry weight. Mean macrophyte dry weight.
P eriphyton Macrophytes
Chlotophyll a frnmi Dr Weight (amt Dr Weiqht ( rm
June 03 July 03 Auqust 03 June 03 July 03 August 03 June 03 July 03 August 03
.t -. 5.39 9.28 38937 525.33 423 20 421 1.82 014
-2 -- 6.12 5.08 345.60 613.72 354.63 6.36 13.28 3.06
B-1 -- 2.58 8.78 216.93 69.37 284.18 6.42 2.95 6.98
B-2 -- 1717 3.89 17513 216.92 26431 18.01 8.35 10.24
C-1 -- 4.47 3.23 102.96 110.27 100.61 0.28 0.04 0.71
C-2 .. 6.24 10.43 11531 147.89 19429 288 4.20 10.46
D-1 -- 5.62 3.16 21.55 59.07 75.15 0.07 0.04 2.54
0-2 -- 1016 6.74 28.24 96.95 110.32 000 0.00 000
Pwlue -- 0.490 0.59 <0.000 <0.000 O0.000 0079 0.005 0066

Periphyton ash free dry weight was significantly different (P<0.001) among sites

for June, July and August sampling dates. Generally, sites within the same watershed

were similar, and mean weight decreased from watershed A to D (Figure 4-5).

Macrophyte dry weights among sites were not significantly different for June (P=0.07)

and August (P=0.06) samples, but were different (P=0.005) between July 03 samples

(Figure 4-6). Al, B1, Cl, Dl and D2's mean biomass was very low (<3 g/m2) and were

not significantly different, whereas A2, B2, and C2 had greater biomass of macrophytes

(Figure 4-6 and Table 4-2).

Chemical and Hydrological Measurements

Average daily-flow for the study period (July 2001-February 2003) was highest in

watershed C (2.66 L/s), followed by B (2.16 L/s), D (1.29 L/s), and A (1.02 L/s). The

number of days out of 638 days with zero flow was 161 (25%) for watershed A, 6 (1%)

for watershed B, 2 (0.3%) for watershed C, and 206 (32%) for watershed D.

Monthly mean water temperature displayed little variation among sites (Figure 4-7)

with lowest values in January and February and highest from June through September.

































120-


120-


A-1 A-2 8-1 B-2 G1 0-1 D-2
A-1 A-? e-1 B-2 C-i C-2 D-1 D-2
Ste



















A-l A-2 B-l B-2 C-1 C-2 D-1 D-2
Se



*















A-i A- B-l 6-2 C- cz D-l D-2
Ste


Figure 4-5. Periphyton ash free dry weight. A) June 2003, B) July 2003, C) August 2003.
Data represented in box (interquartile range) and whiskers plot with median
(horizontal line), mean (circle), and outliers (star).













100-


S 2 B- 2 -2 D D

A-1 A-2 B-1 B-2 C-l C-2 D-1 D2


Figure 4-6. Macrophyte dry weight (July 2003). Data represented in box (interquartile
range) and whiskers plot with median (horizontal line), mean (circle), and
outliers (star).

30
--A
.. B

-0-- D
25




,20


E
15-




10- 'AV,


Figure 4-7. Monthly mean water temperature.


Dissolved oxygen values across sites ranged from 0.270 mg/L in September 2001


at A2 to 10.5 mg/L in January 2002 at Dl (Table 4-3). Average dissolved oxygen was


lowest in watershed A (Figure 4-8).













Table 4-3. Mean, minimum, and maximum in-situ water chemistry.
Mean A-1 A-2 B-1 B-2 C-1 C-2
(min-max)

Temperature 181 181 183 186 183 187
C (102-239) (93-244) (104-244) (105-245) (11 1-244) (11 5-252)

DO 411 399 479 501 664 626
mg/L (098-878) (027-760) (97-8 17) (062-786) (1 59-968) (1 91-960)

pH 49 45 58 59 67 66
(3 5-58) (3 3-56) (4 1-69) (4 3-66) (51-8 0) (5 1-75)

Turbidity 214 154 613 692 677 848
NTU (0 35-7 70) (0 00-7 20) (220-1900) (1 90-5210) (230-1600) (240-6300)

Specific Conductance 392 31 7 1065 956 989 864
mS/cm (230-708) (240-802) (258-2720) (260-3600) (254-1578) (266-1542)

NH4 0011 0007 0032 0037 0005 0020
ug/L (0000-0097) (0000-0025) (0000-0 150) (0000-0 180) (0000-0032) (0000-0071)

Inorganic N 0002 0001 0412 0850 0872 1 188
ug/L (0000-0018) (0 000-0 007) (0000-1 245) (0000-2419) (0029-1 414) (0031-1 785)

Inorganic P 0 003 0 006 0 004 0 003 0 006 0 004
ug/L (0001-0005) (0000-0081) (0000-0014) (0000-0011) (0003-0012) (0002-0007)



A. B.





II-
A A

!rt i i"


.' ..
A A














Figure 4-8. Monthly mean dissolved oxygen. A) Site A-1 and A-2. B) Site B-l and B-2.
C Site C-l and C-2. D) Site D-1 and D-2. indicates no data due to

equipment malfunction. ** indicates no data due to a no flow period.
equipment malfunction. ** indicates no data due to a no flow period.


D-1


185
(10 7-24 5)

669
(220-1056)

69
(51-7 8)

497
(260-1500)

1001
(50 8-1662)

0006
(0 000-0 023)

0010
(0 000-0 219)

0035
(0 015-0 073)


D-2


185
(11 9-24 0)

529
(1 56-9 25)

67
(5 1-7 3)

478
(0 55-28 00)

906
(254-1794)

0006
(0 000-0 066)

0020
(0 000-0 222)

0053
(0 012-0 130)


II







41


















Figure 4-9. Monthly mean pH. A) Site A- and A-2. B) Site B- and B-2. Site C- and











C-2. D) Site D-1 and D-2. indicates no data due to equipment malfunction.
** indicates no data due to a no flow period.
.
m4














watersheds B, C, and D having highest mean values (Table 4-3).
I. I.








Figure 4-9. Monthly mean pH. A) Site A-i and A-2. B) Site B-l and B-2. C) Site C-l and
C-2. D) Site D-m and D-2. indicates no data due to equipment malfunction.
** indicates no data due to a no flow period.

pH ranged from 3.3 recorded in February 2003 in A2 to 8.0 in December 2001 at

C1 (Table 4-3, Figure 4-9). Mean pH increased from watershed A to D (Table 4-3).

Average turbidity was lowest in watershed A, followed by watershed D, with watersheds

B and C having highest values. Overall, mean turbidity at all sites was very low (<10

NTU) (Table 4-3). Mean specific conductance was lowest in watershed A, with

watersheds B, C, and D having highest mean values (Table 4-3).

Inorganic nitrogen in watersheds A and D was consistently very low with average

concentrations < 0.05 mg/L (Table 4-3). Watersheds B and C had average concentrations

an order of magnitude higher. An additional monitoring site at the upstream boundary

(B-B, C-B) between the study site and an adjoining landowner for watersheds B and C






42


had consistently higher concentrations of inorganic N (Figure 4-10). Inorganic

phosphorus average concentrations for watersheds A, B, and C were <0.0065 mg/L;

however, concentrations in watershed D were an order of magnitude higher (Table 4-3).

A. :. B. '.



: U O.




















Figure 4-10. Monthly mean inorganic nitrogen. A) Site A-1 and A-2. B) Site B-1 and B-
Sand C-2. D) Site D-. indicates no data due to

.: .





















The first two axes of the water chemistry PCA explained 56% of the variation

(Figure 4-11), but inclusion of the third axis explained an additional 20% of the variation

(Figure 4-12). Turbidity and specific conductance were positively correlated with Axis 1
(r = 0.689 and 0.718, respectively). Dissolved oxygen was negatively correlated with













Axis 2 (r2 = 0.809). Inorganic phosphorus was positively correlated with Axis 3 (r2=
2 I -. 2 ..


























0.773). Watershed A was characterized by lower turbidity, specific conductance, pH, and
dissolved oxygen. Watershed D was characterized by higher values of inorganic
Figure 4-10. Monthly mean inorganic nitrogen. A) Site A-i and A-2. B) Site B-i and B-
2. C) Site C-i and C-2. D) Site D-i and D-2. indicates no data due to
equipment malfunction. ** indicates no data due to a no flow period.

The first two axes of the water chemistry PCA explained 56% of the variation

(Figure 4-11), but inclusion of the third axis explained an additional 20% of the variation

(Figure 4-12). Turbidity and specific conductance were positively correlated with Axis 1

(r2 = 0.689 and 0.718, respectively). Dissolved oxygen was negatively correlated with

Axis 2 (r2 = 0.809). Inorganic phosphorus was positively correlated with Axis 3 (r2 =

0.773). Watershed A was characterized by lower turbidity, specific conductance, pH, and

dissolved oxygen. Watershed D was characterized by higher values of inorganic











phosphorus. The PCA did not separate watershed B and C based on water chemistry


variables.




C10



*C
iD




I --------
i' i i







P NIH4
S1 M Axis 1 I,-,









Sp Fciic Conduct iee

C*
A A'
Te mp.n A. *
























Dis0hre d ygen


Figure 4-11. First and second axes of the principal components analysis (PCA) for in-situ
water chemistry data at all sites from September 2001-December 2003.


Macroinvertebrates

A total of 17,034 individuals representing 126 taxa were collected from the four


streams during the study (Appendix). Overall, dipterans were the most diverse insect


order with 63 taxa, 44 of which were in the family Chironomidae. Coleoptera


contributed 23 taxa, Trichoptera 12, Ephemeroptera 11, Odonata 9, Plecoptera 4 and


Megaloptera 2.














w ceit Strtmb
LC

3K'
Incra ni. P h-sp h.n














i Speciic Condud,,oe Axis 1
A A &A














Figure 4-12. First and third axes of the principal components analysis (PCA) for in-situ











respectively. Watershed A had < 10 of total individuals from the most sensitive orders,




23%. Amphipods and Isopods comprised 24% and 10% of total individuals, respectively,


in watershed A; whereas watersheds B, C, and D all had < 2% representation from these


orders (Figure 4-13).
+

abundan.e. .,,-.. o ,,... |* .j^^^ B G C we nd uost +i+ A i t









The following taxa considered sensitive to human disturbance in Florida (Fore

2003, as cited in FDEP 2004) were collected: Crangonyx, Microtendipes,

Parametriocnemus, Rheocricotopus, Tribelos juncundum, Acerpenna pygmaea,

Ephemerella, Eurylophella, Stenonema, Habrophlebiodes, Leptophlebia, Caecidotea,

Amphinemura, Ciloperla, Perlesta, Allocapnia, Triaenodes, and Chimarra (Appendix A).

These 18 taxa comprised 14 % of total taxa in the streams. Cordulegaster sayi, which has

been identified as a rare and vulnerable odonate of the southeastern Piedmont and Coastal

Plain (Morse et al. 1997), was collected in watersheds C and D.

The following taxa were collected only at one site, with those considered sensitive

to human disturbance in Florida (Fore 2003, as cited in FDEP 2004) designated with (s).

Tribelosfuscicorne, Pseudosmitta sp., and Smittia sp. were only collected in watershed

A. The isopod Caecidotea (s) was abundant only at site A2; however, one individual was

also found at Al, B1, and D1. Paracladopelma sp., Odontomesafulva, Rhyacophia

carolina, and Polycentropus were unique to watershed B. Watershed C had the greatest

number of site specific taxa: Brilliaflavifrons, Baetis intercalaris, Eurylophella doris (s),

Hexagenia, Cheumatopsyche, Triaenodes (s), and Agarodes. Rheocricotopus

tuberculatus (s), Eukiefferiella claripennis, Zavrelia sp., Molanna blend, and Allocapnia

(s) were found only at watershed D.

Abundance

Mean abundance per sample for all sites across all sampling periods was 436

individuals, and individual values ranged from a maximum at C2 (1896) in February

2003 to a minimum at B1 (19) in December 2001 (Figure 4-14).

Invertebrate abundance generally increased at each site across time. For example,

abundance at B2 increased from 86 in December 2001 to 202 in February 2002, to 370 in













Impish
'SC


flu


Ir sii ii
II iii I I
Ir ail ii
ii i II i i
II iii
I ~ I I

~8~81






e~a~a






mmmmm




PUUIl1I~UllllfS


kumEmphlm





11lm1Am


Irmlllha



1%


Ir
..,--- n


hIumimlhm






* ill^
i' Bu

,lphip ir
a|iJ
*qHupb
urn
,jmpuiul~
'Ull~
1I9pspM


Minupil


Figure 4-13. Partitioning of total abundance by invertebrate orders in study streams over

the entire study period. A) Stream A. B) Stream B. C) Stream C. D) Stream D.


kmhinpim






INFilpm
1E






MJ










I impos
1%
Am
IM






i r.mphaM
b'.pfer




i' dU
**Ilttr


rl









2000
1800 -
1600
1400
I 1200 -
S1000
GiD




400 |
200

Al A2 91 B2 C1 C2 D1 D2

LDec-01 *Feb-02 Dec-02 *Feb-03


Figure 4-14. Macroinvertebrate abundance (total number of individuals) for upstream and
downstream sites of each stream (A-D) over the entire study period.

December 2002, and finally 693 in February 2003. Repeated measures ANOVA

(Table 4-4) indicated significant (P<0.001) differences between the four sampling

periods.

There was no significant effect due to sampling position, i.e. upstream/downstream

(P=0.38) or the interaction between position and time (P=0.72). The December 2001

sample had significantly lower abundance than February 2002 (P=0.03). December 2002

and February 2002 samples were not significantly different. December 2002 had

significantly lower abundance than February 2003 (P<0.001) (Figure 4-15). Differences

among streams were marginally significant (P=0.05) (Table 4-5). Highest mean

abundance was in watershed C followed by D, B, and A (Figure 4-16).

Dominant Taxa

The dominant taxon (i.e. percent dominance of the single most abundant taxon)

varied across sampling periods and between sites. Single taxon dominance ranged from

54% at D2 in February 2002, to 8% at C2 in December 2001 (Figure 4-17). 21 of the 32








48



Table 4-4. Repeated measures analyses for effects of time (Dec 01, Feb 02, Dec 02, Feb
03) and position (upstream vs. downstream) on macroinvertebrate metrics.
Significant results are highlighted.
Source of


Metric variation df MS


F p


Abundance
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
% Dominant Taxon
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
Total Taxa
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
EPT Taxa
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
Chironomidae Taxa
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
% Chironomidae
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
% Diptera
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)


1 0.013
6 0.014

1.638 2.460
1.638 0.03212
9.831 0.116


1 0.000
6 0.006


0.011
0.006
0.020


1 0.945
6 19.299


380.948
15.115
35.726


1 3.125
6 14.141


33.458
4.333
4.257


1 0.195
6 2.154


30.198
19.531
10.587


1 0.002
6 0.006


0.044
0.126
0.021


1 0.017
6 0.021


0.008
0.01
0.028


0.892 0.38


21.167 <0.001
0.276 0.72



0.056 0.82


0.579 0.630
0.301 0.820



0.049 0.83


10.663 <0.001
0.423 0.73



0.221 0.65


7.86 0.001
1.018 0.40



0.091 0.77


2.852 0.06
1.845 0.17



0.359 0.57


2.059 0.14
5.921 0.005



0.839 0.39


0.27 0.84
0.352 0.78










1400


1200


1000


3 800


S600
E
z
400 *


200 -


0
Dec 01 Feb 02 Dec 02 Feb 03
Time *value is significantly different (P<0 05) from the
previous time period


Figure 4-15. Mean macroinvertebrate abundance individual sampling periods with
standard error and repeated contrast results (alpha = 0.05). Letters above bars
indicate statistical groupings.

samples were dominated by Chironomidae with 7 of the 21 dominated by

Parametriocnemus, a taxon sensitive to disturbance in Florida (Fore 2003, as cited in

FDEP 2004). In the February 2002 samples, 5 of 8 sites were dominated by the predator

Conchapelopia sp.. Repeated measures ANOVA found no significant effects due to time

of sampling, position, or an interaction between position and time (Table 4-4). No

significant differences were detected between streams (Table 4-5).

Total Taxa

Overall taxa richness displayed no clear trend between sites, but the December

2001 sampling period had the lowest values. Dl had the highest taxa richness (42) in

December 2002, and B1 had the lowest (7) in December 2001 (Figure 4-18).








50



Table 4-5. Repeated measures analyses for effects of time (Dec 01, Feb 02, Dec 02, Feb
03) and stream (A, B, C, D) on macroinvertebrate metrics. Significant results
are highlighted.
Source of

Metric variation df MS F p

Abundance


Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
% Dominant Taxon
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
Total Taxa
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
EPT Taxa
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
Chironomidae Taxa
Between subjects
Stream
error


3 0.027 6.407 0.05
4 0.004

3 1.344 26.272 <0.001
9 0.065 1.263 0.34
12 0.051


3 0.006 1.544 0.33
4 0.004


0.011 1.312 0.31
0.03 3.425 0.02
0.009


3 35.258 12.858 0.01
4 2.742

1.665 686.477 9.186 0.010
4.994 38.199 0.511 0.76
6.659 74.728


3 25.052 7.821 0.03
4 3.203

3 33.458 6.015 0.01
9 2.542 0.457 0.87
12 5.562


3 0.987 0.389 0.76
4 2.539


Within subjects
Time 1.94 46.698 2.072 0.19
Time*Stream 5.82 12.763 0.566 0.74
error (time) 7.76 22.535


% Chironomidae
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
% Diptera
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)


3 0.005 1.172 0.42
4 0.005

3 0.044 0.968 0.44
9 0.024 0.535 0.82
12 0.045


3 0.031 2.537 0.19
4 0.012

1.598 0.014 0.418 0.63
4.793 0.066 1.939 0.21
6.391 0.034











1200



1000



S800



S600

.Q
E
z 400



200



0
A B C D
Streams


Figure 4-16. Means for macroinvertebrate abundance for all sites within each stream for
all time periods with standard error.

100

90

80

70

x 60
I-
50 -
E
0
o
o 40

30

20

10



Al A2 B1 B2 C1 C2 D1 D2

O Dec-01 U Feb-02 O Dec-02 U Feb-03



Figure 4-17. Percent dominant taxon for upstream and downstream sites of each stream
(A-D) over the entire study period.










45
40
35
30
25
20
I.-
15 -
10
5-
0
Al A2 B1 B2 C1 C2 D1 D2
D Dec-01 Feb-02 0 Dec-02 Feb-03


Figure 4-18. Taxa richness for upstream and downstream sites of each stream (A-D) over
the entire study period.

Significant (P<0.001) differences between four sampling periods (time) were

detected by repeated measures ANOVA (Table 4-4). There was no significant effect due

to sampling position (upstream/downstream) or the interaction between position and

time. The December 2001 sample had significantly lower taxa richness than February

2002 (P=0.03). The remaining sampling periods were not significantly different (Figure

4-19). Differences (P=0.01) were detected between streams (Table 4-5); however,

multiple comparisons between streams were not significant. Means showed highest total

taxa in watershed C followed by D, B, then A (Figure 4-20).

EPT Taxa

The number of EPT taxa (Ephemeroptera, Trichoptera, and Plecoptera taxa) was

consistently highest at C1. Both sites in watershed A had the lowest number of EPT taxa

(Figure 3.22). Repeated measures ANOVA (Table 4-4) indicated significant (P=0.001)

differences between the four sampling periods (time), but there was no significant effect

due to sampling position (upstream/downstream) or the interaction between position and







53


time. Differences between the December 2001 and February 2002 sample were

marginally significant (P=0.1). The December 2002 sample had significantly lower EPT

taxa than February 2003 (P=0.002). The remaining sampling periods were not

significantly different (Figure 4-22). Differences (P=0.03) were detected between streams

(Table 4-5), with A having significantly lower EPT taxa than C (P=0.03) (Figure 4-23).


40

35

30 -


25 -
c
.U 20
x

lO
15

10 -

5 -

0
Dec 01 Feb02 Dec 02 Feb 03
Tim e *value is significantly different (P<0 05) from the
previous time penod

Figure 4-19. Mean taxa richness for individual sampling periods with standard error and
repeated contrast results (alpha = 0.05). Letters above bars indicate statistical
groupings.

Chironomidae Taxa

A total of 44 species of Chironomidae were identified from four subfamilies

(Chironominae, Orthocladiinae, Prodiamesinae, Tanypodinae). The subfamilies were

represented at all sites with the exception of the Prodiamesinae (Figure 4-24), which was

represented by a single species, Odontomesafulva, and was only found at site B 1 on one

occasion. B2 had the lowest Chironomidae taxa richness in December 2001 (3), and D2


















4,
u 20
I-
1
15


-I


-I


I-


-I-


Stream

Figure 4-20. Taxa richness for each stream for all time periods with standard error.

18

16


14

12

S10
I-
. 8
LU
6

4

2

0


Al A2 B1 B2 C1 C2 D1 D2


O Dec-01 U Feb-02 O Dec-02


U Feb-03


Figure 4-21. Total Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa for upstream
and downstream sites of individual streams (A-D) over the entire study period.





















Dec 01


Feb02


=4


Dec 02


Time


9


Feb 03


*value is significantly different (P previous time period


Figure 4-22. Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa within each
time period with standard error and repeated contrast results (alpha = 0.05)
across time. Letters above bars indicate statistical groupings.
12


A B C D
Stream


Figure 4-23. Mean Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa for all sites
within each stream for all time periods and pairwise multiple comparison test
results (Tukey's honestly significant difference (HSD) test, alpha = 0.05).
Letters above bars indicate statistical groupings.











had the greatest (17) in December 2002 (Figure 4-25). Tanytarsus sp., Tribelos sp.,

Parametriocnemus sp., Conchapelopia sp., and Zavrelimyia sp. occurred at all sampling


sites. Repeated measures ANOVA detected no differences due to time, position, or site

(Table 4-4 and 4-5).

100% -

90%

80%

70%

60%
c-
50%
0
40% -

30%

20%

10%

0%
Al A2 B1 B2 C1 C2 D1 D2

O Chironominae U Orthocladiinae E3 Prodiamesinae O Tanypodinae


Figure 4-24. Mean subfamily composition of Chironomidae in individual streams (A-D)
over the entire sampling period.

Percent Chironomidae

The lowest and highest percentage of a sample composed of Chironomidae was


found, respectively, at site D2 with 19% in December 2002 and 82% in December 2001

(Figure 4-26). Seventy-two percent of samples contained >50% Chironomidae. There

were no significant effects due to time of sampling, sampling position, or interaction

between position and time (Table 4-4 and 4-5).

















M IL
x

S10
0
S8

S6

4

2

0


Al A2 B1 B2 C1 C2 D1 D2


O Dec-01


* Feb-02


O Dec-02


* Feb-03


Figure 4-25. Number of Chironomidae taxa for upstream and downstream sites of
individual streams (A-D) over the entire study period.


100

90


Al A2 B1 B2 C1 C2 D1 D2


O Dec-01


* Feb-02


O Dec-02


* Feb-03


Figure 4-26. Percentage of total abundance contributed by Chironomidae for upstream
and downstream sites of individual streams (A-D) over the entire study period.










Percent Diptera

Eighty-four percent of samples had >50% Diptera, and 47% of samples had >75%

Diptera. Minimum and maximum values for percent Diptera were December 2001 at A2

(29%) and D2 (96%) (Figure 4-27) Repeated measures ANOVA detected no differences

due to time, position, or site (Table 4-4 and 4-5).


100
90
80
70
60
.- 50

40 -
40

30

20
10
0 -_ 11 I^ I^ ^ ^ - -
Al A2 B1 B2 C1 C2 D1 D2

O Dec-01 U Feb-02 O Dec-02 Feb-03


Figure 4-27. Percentage of total abundance contributed by Diptera for upstream and
downstream sites of individual streams (A-D) over the entire study period.

Percent Elmidae

All sites had <20% of the family Elmidae, which are a family of beetles which

prefer swifter parts of streams such as oxygen rich riffles (Merritt and Cummins 1996).

Sites in A and B had no occurrences of elmids in the December 2001 and February 2002

sampling period with site Al having no occurrences in any sample (Figure 4-28).







59


Repeated measures ANOVA detected no significant differences due to position

(Table 4-6), but significant differences due to time (P<0.001), site (P=0.003), and an

interaction between time and site (P=0.002) (Table 4-7).

Figure 4-29 illustrates the interaction because the lines are not parallel, implying

that the effect of site upon percent Elmidae depends upon the time period examined. This

interaction seems to be the result of the December 2001 sampling period having highest

mean percent Elmidae at C, where the remaining sampling periods have highest mean

percent Elmidae at D. The December 2002 sampling period had the highest mean

percent Elmidae compared to the remaining sampling periods (Figure 4-29) and D had

highest mean percent Elmidae, followed by C, B, and A.


20
18
16
14
cc 12
E 10
LU

6-
8







Al A2 B1 B2 C1 C2 D1 D2

O Dec-01 U Feb-02 O Dec-02 U Feb-03


Figure 4-28. Percent of the total assemblage represented by Elmidae for upstream and
downstream sites of individual streams (A-D) over the entire study period.








60



Table 4-6. Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02,
Feb 03) and position (upstream vs. downstream) on macroinvertebrate
metrics. Significant results are highlighted.


Clinger Taxa
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
% Filtering Collectors
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)
% Elmidae
Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)


Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)

Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)

Between subjects
Position
error
Within subjects
Time
Position*Time
error (time)


1 23.205
6 4.442


1.841
11.654
1.949


1 0.006
6 0.002


0.023
0.013
0.012


1 0.000
6 0.004

1.218 0.009
1.218 0.001
7.307 0.002


1 204.905
6 505.827


75.279
208.151
72.992


1 0.633
6 45.82


276.865
5.531
13.948


1 8.000
6 183.875


EPD (200 individual subsample)
Between subjects
Position 1
error 6
Within subjects
Time 3
Position*Time 3
error (time) 18


327.167
89.500
101.611


5.281
209.99

323.208
53.375
96.292


5.224 0.06


0.945 0.44
5.98 0.005



2.71 0.15


1.99 0.15
1.147 0.35




0.017 0.89


3.854 0.08
0.496 0.53



0.405 0.54


1.031 0.40
2.852 0.06



0.014 0.91


19.850 <0.001
0.397 0.75



0.044 0.84


3.220 0.04
0.881 0.47



0.025 0.87


3.357 0.04
0.554 0.65


FL SCI








GA AAS








EPD








61



Table 4-7. Repeated measures analyses for the effects of time (Dec 01, Feb 02, Dec 02,
Feb 03) and stream (A, B, C, D) on macroinvertebrate metrics. Significant
results are highlighted.


Clinger Taxa
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
% Filtering Collectors
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
% Elmidae
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
FL SCI
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
GA AAS
Between subjects
Stream
error
Within subjects
Time
Time*Stream
error (time)
EPD


Between subjects
Stream 3
error 4
Within subjects
Time 3
Time*Stream 9
error (time) 12
EPD (200 individual subsample)
Between subjects
Stream 3
error 4
Within subjects
Time 3
Time*Site 9
error (time) 12


3 8.601
4 6.014


1.841
1.098
5.013


3 0.004
4 0.002


0.023
0.012
0.012


3 0.002
4 0.000


0.003
0.002
0.000


3 215.518
4 40.853

1.158 194.962
3.475 329.229
4.633 171.406


1.43 0.35


0.367 0.77
0.219 0.98



1.744 0.29


1.97 0.17
1.026 0.47



34.075 0.003


13.88 <0.001
6.464 0.002


5.275


1.137
1.921


3 87.258 25.327
4 3.445


276.865 27.149
16.142 1.583
10.198


329.188 10.646
30.922


327.167
108.472
93.437


328.802
69.703

323.208
112.181
73.646


3.501
1.161



4.717


4.389
1.523


0.07


0.35
0.25



0.005


<0.001
0.22



0.02


0.50
0.390



0.08


0.02
0.24







62



time
AA C CI a
-, Feb02 /
12 D--- c02
A- Feb 03 /
A 10C



4 -



2



A B C D
Streams


Figure 4-29. Interaction plot (data means) for percent Elmidae. Site 1, 2, 3, 4, represents
A, B, C, D, respectively and Time 1,2,3,4 represents Dec 01, Feb 02, Dec 02,
and Feb 03, respectively.

Feeding Type and Habitat Type

The relative contribution of functional feeding groups to the total assemblage of

each stream varied. The assemblages of B, C, and D were co-dominated by shredders,

predators, and collectors, while collectors were dominant in A (Figure 4-30). Within the

collector functional feeding group, collector-gatherers were dominant over filter feeders.

Each site for all sampling periods had <15% filter feeders (Figure 4-31), which are

thought to be sensitive in low gradient streams with high percent filter feeders indicating

healthy coastal plain streams (Barbour et al. 1996). Repeated measures ANOVA

detected no differences due to time, position, or site (Table 4-6 and Table 4-7).

The number of clinger taxa generally increased at each site from December 2001

through February 2003 (Figure 4-32); however, there was no significant effect due to











time of sampling, sampling position, or interaction between position and time (Table 4-6


and Table 4-7).


100% ...........

90%

80%

g 70%
0
S 60%
30%
50%



10%
r 40%- 32%






20
10- 9%

0% 4% 7% 6%
A B C D

M Unknown D Scrapers 0 Shredders O Predators D Collector-gatherers e Filter feeders


Figure 4-30. Percentage of the total assemblage contributed by individual functional
feeding groups for individual streams (A-D) over the entire study period.

25


20


15


S10 -


5




Al A2 B1 B2 C1 C2 D1 D2

O Dec-01 U Feb-02 O Dec-02 U Feb-03


Figure 4-31. Percentage of the total assemblage represented by filter feeders for upstream
and downstream sites of individual streams (A-D) over the entire study period.










12

10

8
I-


4

2



Al A2 B1 B2 C1 C2 D1 D2

D Dec-01 Feb-02 D Dec-02 Feb-03


Figure 4-32. Clinger taxa for upstream and downstream sites of individual streams (A-D)
over the entire study period.

Biotic Indices

The Florida Stream Condition Index (SCI) scored Al as Very Poor for every

sampling period (Figure 4-33). December 2001, February 2002, and February 2003

samples for A2 scored Poor, while the December 2002 sample fell within the Very Poor

category. The earliest sample for B1, December 2001, scored Very Poor, with the

remaining samples in the Poor category. December 2001, December 2002, and February

2003 samples for B2 scored Poor, while February 2002 was Fair. C1 had the greatest

number of samples (December 2001 and December 2002) in the Fair category, with the

remaining samples, February 2002 and February 2003, listed as Poor. All C2 samples

scored Poor. December 2001, February 2002, and February 2003 samples for D1 scored

Poor, while the December 2002 sample fell into the Fair category. All D2 samples scored

Poor.











100

90

80-

70

60

50-

40

30

20 -

10

0
Al


Good




Fair




Poor



Very
Poor

D1 D2


Figure 4-33. Florida Stream Condition Index (SCI) scores for upstream and downstream
sites of each stream (A-D) over the entire study period.

Repeated measures ANOVA did not detect significant differences due to time,


position, or site (Table 4-6 and Table 4-7). Overall, the Florida SCI scored 9.4% of the


samples for the eight sites as Fair, 59.3% Poor, and 31.3% Very Poor. No sites were


classified as Good. Cl and Al had the highest and lowest average score, respectively, for


every sampling period.


Results from the Georgia Environmental Protection Division (EPD) Biological


Assessment were more favorable. 12.5% of scores for the four samples each at the eight


sites were Very Good, 53.1% Good, 21.9% Fair, 6.3% Poor, and 3.1% Very Poor when


compared to the Georgia DNR reference stream from the Southeastern Plains Ecoregion,


Tifton Upland sub-ecoregion. Al and A2 December 2001 samples scored Poor, but the


February 2002, December 2002, and February 2003 samples of both scored Fair (Figure


4-34). The December 2001 sample for Blwas the only one in the study to score Very


Poor. The remainder of B1 samples scored Good. December 2001 and February 2002


B1 B2 C1 C2
O Dec-01 U Feb-02 O Dec-02 U Feb-03


A2











samples for B2 scored Good, while the December 2002 sample fell into the Good


condition, and the February 2003 was in the Very Good category. Cl had the greatest


number of samples (December 2002, February 2002, and February 2003) in the Very


Good condition, with one sample (December 2001) in the Good category. All samples


for C2 scored in the Good category. December 2001 and February 2003 samples for Dl


scored Good, while the February 2002 sample scored Fair, and the December 2002


sample scored Very Good. All samples for D2 scored Good (Figure 4-34).

100
90 Very
90 Good

80

S70 Good
0

S60
SFair
0 50
-' 0o 0 -- -Pr-very
40 Poor
_0 -- --- ----- -------- --- --- --- -
30
Wu 30

20 Very
Poor
10

0 -, -r r -, -
Al A2 B1 B2 C1 C2 D1 D2
O 12/01 U 2/02 O 12/02 0 2/03


Figure 4-34. Georgia EPD Biological Assessment scores for upstream and downstream
sites of each stream (A-D) over the entire study period.

For the Georgia EPD Biological Assessment applied to a 200 individual subsample,


as called for in Georgia EPD standard operating procedures, site condition scores


changed slightly from results presented above, with 11 samples increasing by 10%, 11


samples decreasing by 10%, and 10 sites remaining unchanged. Overall scores improved


slightly with 15.6% listed as Very Good, 56.2% Good, 18.8% Fair, 6.2% Poor, and 3.1%


Very Poor (Figure 4-35). For both the complete and 200 individual subsample, the











Georgia EPD Biological Assessment was similar to the Florida SCI in scoring Cl the


highest and Al the lowest across all sampling periods.

100
T -Very
C 90
E Good
80
SGood
70

r 60
o Fair
T 50
8 0
40 Poor

g 30
0
S20 Very
Poor
S10 -

0-- -- --- -- -------- ----- -- -
Al A2 B1 B2 C1 C2 D1 D2
O 12/01 U 2/02 O 12/02 E 2/03


Figure 4-35. Georgia EPD Biological Assessment scores (based on a 200 individual
subsample) for upstream and downstream sites of each stream (A-D) over the
entire study period.

Repeated measures ANOVA detected weak but significant differences due to time


(Table 4-6) for the Georgia EPD Biological Assessment scores calculated from both the


complete sample (P=0.04) and 200 individual subsample (P=0.04), with varying


significance between specific time periods. For the complete sample (P=0.08) (Figure 4-


36) and 200 individual subsample (P=0.04) (Figure 4-37), December 2002 had


significantly higher scores than February 2002, although results from the complete


sample were marginally significant. No differences were detected due to position (Table


4.6). A significant difference (P=0.02) was found between sites for the Georgia EPD


Biological Assessment scores calculated from the complete sample, but differences were


not detected for the 200 individual subsample (Table 4.7). For the complete sample,


stream A had significantly lower scores than stream C (P=0.01) (Figure 4-38).








































Dec 01 Feb 02 Dec 02 Feb 03
Time *value is significantly different (P previous time period


Figure 4-36. Means for GA EPD Index for all streams combined during each time period

with standard error and repeated contrast results (alpha = 0.05) across time.

100

90o


S80
i.
E
^ 70

60

* 50
6
50
4o
X 40

o 30
a.
LU
20


Dec 01 Feb 02 Dec 02 Feb 03
Time *value is significantly different (P previous time penod


Figure 4-37. Means for GA EPD Index for all sites combined (200 individual subsample)

within each time period with standard error and repeated contrast results
(alpha = 0.05) across time.











100
b
90

80 ab abc

70
a
s 60

0 50
a-
LU
40

30

20

10

0 -
A B C D
Stream


Figure 4-38. Means for GA EPD Index (individual streams for the entire study) and
pairwise multiple comparison test results (Tukey's honestly significant
difference (HSD) test, alpha = 0.05). Letters above bars indicate statistical
groupings.

The Georgia Adopt-A-Stream water quality rating was excellent for 50% of


samples, good for 12.5%, fair for 12.5%, and poor for 25%. Five of eight sites collected


in December 2001 were rated as having poor water quality (Figure 4-39). Repeated


measures ANOVA found significant differences due to time (P<0.001) and site


(P=0.005), but not for position (Table 4-6 and Table 4-7). The December 2001 samples


had significantly (P=0.008) lower scores than February 2002. February 2003 samples had


significantly higher scores when compared to December 2002 (P=0.03) (Figure 4-40).


Scores from stream A were significantly lower than scores for stream B (P=0.02), C


(P=0.006), and D (P=0.006) (Figure 4-41).













45


40


35
cellent

30


x25


S20 Good


15 -
Fair

10


5- P2 I oor



Al A2 B1 B2 C1 C2 D1 D2

012/01 2/02 012/02 2/03



Figure 4-39. Georgia Adopt-A-Stream Index scores for upstream and downstream sites of
each stream (A-D) over the entire study period.

45


40


35


X
a"
C 25
-ii

20
<
15


10


5


0


Dec 01 Feb 02 Dec 02 Feb 03

Time *value is significantly different (P previous time period


Figure 4-40. Means for GA AAS Index for all sites combined within each time period
with standard error and repeated contrast results (alpha = 0.05) across time.










45

40

35

30 b
"c
25

S20

15 a

10

5


A B C D
Stream


Figure 4-41. Means for GA AAS Index (individual streams for the entire study) and
pairwise multiple comparison test results (Tukey's honestly significant
difference (HSD) test, alpha = 0.05). Letters above bars indicate statistical
groupings.

The Georgia Ecological Condition Worksheet was used to compare among sites for

year to year, downstream vs. upstream, and stream to stream. Sites with lower percent

comparability scores indicate greater similarity between sites, and higher scores indicate

greater dissimilarity between sites. A score of 0 indicates 100% comparable

assemblages, as shown in the comparison of B (study site) and Cl (reference) for the

February 2002 samples (Table 4-8). Year to year site comparisons indicate generally

higher percent comparability in year two (February 2002 to February 2003) of the study

compared to year one (December 2002 to December 2003) (Table 4-9). Downstream vs.

upstream percent comparability varied more in watersheds B and C across time than

watersheds A and D (Table 4-10).










Table 4-8. Sample comparison of sites (Bl vs. Cl for February 2002)
ECOLOGICAL CONDITION WORKSHEET FOR B1 and C1 (2-02)
SOUTHEASTERN PLAINS (65)
SCORE RANGES C1
METRIC: B1 Data: C1 Data: 5 3 1 0 B1 Score: Score:
Taxa Richness (Total # Taxa) 35 37 >30 30-16 <16 5 5
EPT Index 5 14 >6 6-4 <4 3 5
# Chironomidae Taxa 16 11 >8 8-5 <5 5 5
% Contribution of Dominant Taxon 28 23 <23 23-61 >61 3 3
% Diptera 91 68 --- <51 >50 1 1
Florida Index 13 16 >15 15-8 <8 5 5
% Filterers 8 2 >11 11-6 <6 3 1
Total Habitat Score: >89% 89-75% 74-60% <59%
Total Points Earned 25 25
% of Difference 100
100 % of Difference 0

Table 4-9. Percent comparability scores for year to year comparison of sites.
Year to Year
Al A2 B1 B2 C1 C2 D1 D2
12-01 vs 12-02 15 31 156 11 26 9 8 11
2-02 vs 2-03 0 12 0 32 0 21 10 10

Table 4-10. Percent comparability scores for downstream vs. upstream comparison of
sites.
Downstream vs Upstream
12-01 2-02 12-02 2-03
Al vs A2 15 12 12 0
B1 vs B2 53 21 10 8
C1 vs C2 0 32 26 9
D1 vs D2 21 19 19 21


Table 4-11 displays three watershed to watershed comparisons in grey or white

boxes for each watershed for one sampling date. The lowest percent comparability score

for each sampling date is highlighted. Across sampling dates, there is no consistently

lower percent comparability score for one site over another. However, when the data are

viewed for year one (12-01 to 2-02) and year two (12-02 to 2-03), the format shows no

consistent results. Year two scores showed lowest percent comparability between Al and

D1, B1 and DI, Cl and Dl and Dl and Bl.











Table 4-11. Percent comparability scores for stream to stream comparison of sites.
Stream to Stream
12-01 2-02 12-02 2-03
Al vs B1 22 35 35 35
Al vs C1 52 40 48 40
Al vs D1 52 12 29 35
B1 vs Al 31 67 53 53

B1 vs C1 65 0 21 8
B1 vs D1 65 47 10 0
C1 vs Al 17 67 93 67
C1 vs B1 188 0 26 9
C1 vs D1 8 47 7 9
D1 vs Al 17 13 67 53
D1 vs B1 188 32 9 0
D1 vs C1 9 32 14 8

Multivariate Analysis

The first two PCA axes explained 57% of variability in macroinvertebrate data

(Figure 4-42). Points in the plot represent individual sites for four time periods (e.g.,

B11= site B1, at December 2001). The Georgia EPD index was highly correlated with

Axis 1 for both the complete sample (r2=0.91) and 200 individual subsample (r2=0.89).

EPT taxa, Georgia AAS index, and total taxa were also strongly correlated with Axis 1

(r2=0.71, 0.71, and 0.62, respectively). Percent filter feeders was correlated (r2=0.58)

with Axis 2. Abundance and percent dominant taxa were negatively correlated (r2=0.54

and 0.41, respectively) with the same axis. Samples from watershed A tended to separate

along Axis 1.

Regression Analysis

Five models were run with: 1) all samples pooled (n=31), 2) December 2001

samples only (n=7), 3) February 2002 samples only (n=8), 4) December 2002 samples







74







GA D (200)


A ..






%0 0mlna nTotal Tax
on





Abundance









Figure 4-42. Principal components ordination for macroinvertebrate metrics and indices.

only (n=8), and 5) February 2003 samples only (n8). These five models were run with


water chemistry and hydrology data from one, three, and six months prior to

macroinvertebrate sampling (Table 4-12). The models run with predictor variable data

from three months prior to macroinvertebrate sampling cumulatively explained 51.8% of

variation, whereas one and six month prior data explained 50.5% and 50.9%, respectively


(Table 4-12). As a result, the remaining discussion will be restricted to the set of models

run with predictor data from three months prior to macroinvertebrate sampling.

The first predictive model using all samples pooled (n=31) explained 82.7% of

variation (Georgia AAS) to 15.8% (percent filter feeders). The remaining models with

each time period as a separate model (n=8) generally had higher adjusted R2 than the











Table 4-12. Adjusted R2 values (%) for five *models: 1) all samples pooled (n=31), 2)
Dec 01 samples only (n=7), 3) Feb 02 samples only (n=8), 4) Dec 02 samples
only (n=8), 5) Feb 03 samples only (n=8). (--)= no variables entered model at
alpha=0.05.
A. Predictor variables in models summarized for one month prior to macroinvertebrate sampling.

*Model (%)
1 2 3 4 5
Response Variable Average
GA EPD 45.85 89.24 80.66 98.1 79.86 78.74
GA AAS 79.2 67.8 85.61 68.29 80.16 76.21
EPTtaxa 67.69 -- 90.81 79.35 93.02 66.17
Abundance 55.66 -- -- 55.31 81.92 38.58
Total taxa 55.47 85.69 88.19 47.87 -- 55.444
% Elmidae 66.29 51.28 72.96 94.53 86.73 74.358
% Dominant taxon 12.11 49.18 -- -- -- 12.26
% Filter feeders 9.76 -- -- -- -- 1.95
Average 49.0 42.9 52.3 55.4 52.7 50.46

B. Predictor variables in models summarized for three months prior to macroinvertebrate sampling.


Response Variable
GA EPD
GA AAS
EPT taxa
Abundance
Total taxa
% Elmidae
% Dominant taxon
% Filter feeders


*Model (%)
1 2 3 4 5
Average
54.46 83.16 80.66 60.63 90.34 73.85
82.65 70.31 85.61 87.56 80.16 81.26
72.83 63.92 90.81 97.19 93.97 83.74
74.53 -- -- 53.26 71.26 39.81
61.39 93.89 88.19 -- -- 48.69
43.78 54.19 72.96 91.18 81.42 68.71
16.77 58.83 -- -- -- 15.12
15.79 -- -- -- -- 3.16


52.78


53.04


52.28


48.73


52.14 51.79


C. Predictor variables in models summarized for six months prior to macroinvertebrate sampling.


Response Variable
GA EPD
GA AAS
EPT taxa
Abundance
Total taxa
% Elmidae
% Dominant taxon
% Filter feeders


*Model (%)
1 2 3 4 5
Average
52.34 86.08 61.75 82.19 94.98 75.47
63.46 68.94 86.23 75.46 63.24 71.47
59.14 70.92 51.42 75.53 91.18 69.64
68.17 48.72 -- 74.36 68.4 51.93
51.47 88.55 76.9 48.94 -- 53.17
49.85 50.98 85.04 92.09 84.94 72.58
-- 51.68 -- -- -- 10.34
12.89 -- -- -- -- 2.58


44.67


58.23


45.17


56.07


50.34 50.90


*Models: 1) all samples pooled (n=31), 2) Dec 01 samples only (n=7),
3) Feb 02 samples only (n=8), 4) Dec 02 samples only (n=8), 5) Feb 03 samples only (n=8).
(--) = no variables entered model at alpha 0.05


pooled models, especially for regressions with Georgia EPD, Georgia AAS, and EPT


taxa. Percent Elmidae, dominant taxa and filter feeders had the lowest number of









significant regressions (Table 4-12-B). EPT taxa had the highest cumulative adjusted R2

of the response variables (83.7%) with 72.8% (Model 1-Pooled), 63.9% (Model 2-

December 2001), 90.8% (Model 3-February 2002), 97.2% (Model 4-December 2002),

and 94.0% (Model 5-February 2003) (Table 4-12-B).

Predictor variables selected for Models 1 (samples pooled), 2 (December 2001), 3

(February 2002), 4 (December 2002), and 5 (February 2003) varied. This is likely due to

ANOVA results that indicated differences between time periods for abundance, EPT

taxa, total taxa, Georgia EPD index, Georgia AAS index, and percent Elmidae. As a

result, one time period, February 2003, was selected for discussion of predictor variable

results because abundance, EPT taxa, total taxa, and Georgia AAS index had the highest

average values for this time period. Also, annual rainfall data from 1967-2003 for the

study site indicated that 2003 was closest to normal climatic conditions than 2001 or

2002 (Figure 4-43).

Variation in abundance was explained by average daily flow (P=0.005) for the

February 2003 model (adjusted R2=71.3%). The model for EPT taxa resulted in average

daily flow (P<0.001) and inorganic phosphorus (P=0.03) explaining 94% (adjusted R2) of

variation (Table 4-13). Variation in Georgia EPD index was explained (adjusted

R2=90%) by specific conductance (P=0.002) and minimum daily flow (P=0.04), while

specific conductance (P=0.002) alone explained variation (adjusted R2=80%) in Georgia

AAS index values (Table 4-14). Inorganic phosphorus (P=0.006) and dissolved oxygen

(P=0.04) were significant predictors (adjusted R2=81%) for percent Elmidae. Total taxa,

percent dominant taxon, and percent filtering collectors did not result in significant

regressions for February 2003 (Table 4-15).










2000
Avg. annual: 1353mm
1800

1600-- 2003

S1400 2001 1999 2002
1400 t _20 200100

1200

1000

800

600

400

200

0



Figure 4-43. Total annual rainfall from 1967-2003 at the Bainbridge, GA station (90586)
at International Paper (SRCC 2004) arranged from lowest to highest annual
values.

As a result of hydrology being a significant predictor for abundance, EPT taxa, and

Georgia EPD index, for the February 2003 time period, the relationship between

hydrology for the entire study period was examined. Plots of abundance (Figure 4-44),

EPT taxa (Figure 4-45), and Georgia EPD index (Figure 4-46) with average daily flow

for all sites and time periods (indicated with different symbols), showed an increasing

positive relationship, particularly for abundance.

For abundance (Figure 4-47), when a linear regression fit was applied to each time

period, the December 2001 and February 2002 time period had no relationship with

average daily flow, but the December 2002 time period was marginally significant

(P=0.09) with an r2 of 40% and finally the February 2003 time period resulted in a highly

significant relationship (P=0.005) with an r2 of 75%.











Table 4-13. Stepwise regression models of the relationship between EPT taxa and
abundance (response) with water chemistry and hydrology parameters
(predictors). Alpha to Enter/Remove: 0.05.
Response: EPT Taxa Response: Abundance
Step Predictor(s) P value R2 R2 (adj) PRESS Step Predictor(s) P value R2 R2 (adj) PRESS
(%) (%) (%) (%)
Pooled Pooled
1 DO <0.001 59 57 248 1 Maxdf <0.001 50 49 3.1
2 DO <0.001 74 72 163 2 Maxdf <0.001 69 67 2.0
Turbidity <0.001 Temp <0.001
3 Maxdf <0.001 77 74 1.7
Temp <0.001
Min df 0.007

Dec 01 Dec 01
1 Temperature 0.01 69 63 109 1 No variables entered or removed

Feb 02 Feb 02
1 Turbidity 0.01 63 57 91 1 No variables entered or removed
2 Turbidity <0.001 93 90 36
NH4 0.005

Dec 02 Dec 02
1 DO 0.002 81 78 32 1 Inorg N 0.02 59 53 0.3
2 DO 0.002 93 90 17
Turbidity 0.03
3 DO 0.001 98 97 9
Turbidity 0.005
Inorg P 0.02

Feb 03 Feb 03
1 Avg df 0.001 87 85 20 1 Avg df 0.005 75 71 0.1
2 Avgdf <0.001 95 93 14
Inorg P 0.030

EPT taxa (Figure 4-48) was slightly different in that the December 2001 and time

period had no relationship with average daily flow, but February 2002 and December

2002 had marginally significant regressions (P=0.17 and r2= 28%, P=0.16 and r2= 30%,

respectively). Finally, the February 2003 time period resulted in a highly significant

regression (P=0.001) for EPT and average daily flow with an r2 of 87%.

For Georgia EPD index (Figure 4-49), when a linear regression fit was applied to

each time period, the December 2001 time period had no relationship with average daily

flow. February 2002 and December 2002 displayed similar trends with EPT index in that

both time periods had marginally significant regressions (P=0.15 and r2= 30%, P=0.09

and r2= 40%, respectively). Finally, the February 2003 time period resulted in a highly








79



significant regression (P=0.005) for Georgia EPD index and average daily flow with an r2


of 75%.


For each metric, overall the increasing positive relationship improves with each


time period with a marked difference in relationship between the December 2001 time


period and February 2003.


Table 4-14. Stepwise regression models of the relationship between Georgia EPD index
and Georgia AAS index (response) with water chemistry and hydrology
parameters (predictors). Alpha to Enter/Remove: 0.05.


R2 R2 (adj) PRESS
(%) (%)

35 33 5407
57 54 4101


64 56 1460
88 83 2250


59 52
86 80


0.01 66 60 938


82 79
93 90


Response: GA AAS Index
Step Predictor(s) P value


Pooled
1 DO
2 DO
Turbidity
3 DO
Turbidity
InorgN

Dec 01
1 Inorg N



Feb 02
1 pH



Dec 02
1 Turbidity
2 Turbidity
Inorg P

Feb 03
1 SC


<0.001
<0.001
<0.001
<0.001
<0.001
0.03


R2 R2 (adj) PRESS
(%) (%)


60 58
81 80

84 82


0.01 75 70 46




0.001 87 85 83


0.003
0.001
0.04


78 75
91 87


0.002 83 80 95


Response: GA EPD Index
Step Predictor(s) P value


<0.001
<0.001
0.001


0.03
0.006
0.04


0.02
0.003
0.02


Pooled
1 DO
2 DO
SC


Dec 01
1 Inorg N
2 Inorg N
Inorg P

Feb 02
1 SC
2 SC
NH4

Dec 02
1 SC



Feb 03
1 SC
2 SC
Mindf


0.002
0.002
0.04











Table 4-15. Stepwise regression models of the relationship between percent dominant
taxa, percent filter feeders, total taxa, and percent Elmidae (response) and
water chemistry and hydrology parameters (predictors). Alpha to


Enter/Remove: 0.05.
Response: % Dominant taxon
Step Predictor(s) P value R2 R2 (adj) PRESS
(%) (%)
Pooled
1 SC 0.02 16 13 0.5

Dec 01
1 pH 0.04 58 50 0.2

Feb 02
1 No variables entered or removed

Dec 02
1 No variables entered or removed

Feb 03
1 No variables entered or removed


Response: % Filter feeders
Step Predictor(s) P value R2 R2 (adj) PRESS
(%) (%)


Pooled
1 SC


0.01 18 15 0.3


Dec 01
1 No variables entered or removed

Feb 02
1 No variables entered or removed

Dec 02
1 No variables entered or removed

Feb 03
1 No variables entered or removed


Response: Total taxa
Step Predictor(s) P value


Pooled
1 DO
2 DO
Maxdf

Dec 01
1 Inorg N
2 Inorg N
Turbidity


Feb 02
1 SC
2 SC
NH4


R2 R2 (adj) PRESS
(%) (%)


<0.001
<0.001
0.004


0.02
0.001
0.006


0.01
0.001
0.01


1253
989


Dec 02
1 No variables entered or removed



Feb 03
1 No variables entered or removed


Response: % Elmidae
Step Predictor(s) P value


Pooled
1 Inorg P
2 Inorg P
Max df

Dec 01
1 Inorg N



Feb 02
1 Inorg P



Dec 02
1 Inorg P
2 Inorg P
DO

Feb 03
1 Inorg P
2 Inorg P
DO


0.001
0.001
0.04


0.01
0.006
0.04


R2 R2 (adj) PRESS
(%) (%)


0.002
<0.001
0.004


0.03 61 54 0.00




0.004 76 72 0.00


85.00 82
93 91












A
A


A
*
+



*
** *
+




time
Dec 01
Feb02
Dec 02
A Feb03

S1 2 3 4
Average daily flow (L/s)


Figure 4-44. Abundance vs. average daily flow for all sites and time periods (1-December
2001, 2-February 2002, 3-December 2002, 4-February 2003).


1
Average


2 3
daily flow (L/s)


Figure 4-45. EPT taxa vs. average daily flow for all sites and time periods (1-December
2001, 2-February 2002, 3-December 2002, 4-February 2003).


A

g A

A A
* A

B
U time
Dec 01
U Feb02
* **+ Dec02
.a A Feb03















B A A

* m 4 A A A



U 0 I


A time
Dec01
Feb02
S* Dec 02
A Feb 03

1 2 3 4
Average daily flow (L/s)


Figure 4-46. GA EPD Index vs. average daily flow for all sites and time periods (1-
December 2001, 2-February 2002, 3-December 2002, 4-February 2003).


3.5



3.0


r=75% A


+ A,







time
Dec 01
Feb02
--*-- Dec 02
-*- FsbJ3

0 1 2 3 4
Average daily flow (L/s)


Figure 4-47. Abundance vs. average daily flow for all sites and time periods with linear
regression fit for each time period (1-December 2001, 2-February 2002, 3-
December 2002, 4-February 2003).





















* -i
- I..


r7=87%
AA
A /
/

A


s /:


,,


0*A


* a


time
Dec 01

--*-- Dec 02
-- Feb03


2
Average daily flow (L/s)


Figure 4-48. EPT taxa vs. average daily flow for all sites and time periods with linear
regression fit for each time period (1-December 2001, 2-February 2002, 3-
December 2002, 4-February 2003).


a= 75%
* A ,-A


I 40 A A.'-


-


I 7,


a


time
--- Dec 01
-Feb 02
Dec 02
-a Feb03

1 2 3 4
Average daily flow (L/s)


IA


Figure 4-49. GA EPD Index vs. average daily flow for all sites and time periods with
linear regression fit for each time period (1-December 2001, 2-February 2002,
3-December 2002, 4-February 2003).


ill














CHAPTER 5
DISCUSSION AND CONCLUSIONS

Discussion

Macroinvertebrate Assemblages All Streams

Although Diptera comprised >60% of the total macroinvertebrate assemblages in

the sand dominated study streams, they were still quite diverse with EPT taxa and other

taxa sensitive to disturbance being well represented. Sand is generally considered a poor

substrate for macroinvertebrates because of its instability and lack of interstitial oxygen,

but some macroinvertebrates are specialists of this habitat. For example, the

ephemeropteran, Hexagenia limbata, found in this study creates a U-shaped burrow in

fine sediments, then beats its gills to create a current through its burrow (Allan 1995). A

study of three steephead streams adjacent to the Dry Creek watershed in the International

Paper Southlands Forest found that macroinvertebrate assemblages in all streams had

high diversity with some taxa typically found in the southern Appalachians (Entrekin et

al. 1999). The total number of EPT taxa (genus level) from all streams of the current

study (26) was greater than reported for other streams in southwestern Georgia, 20

(Muenz 2004), 11 (Gregory 1996), and 15 (Davis 2000). A study of low gradient, higher

order streams in Georgia had 31 taxa (Benke et al. 1984), a low gradient, low order

stream in southeastern Virginia had 34 (Wright and Smock 2001), and in high gradient,

low order streams of North Carolina, 29 EPT taxa were present (Stone and Wallace

1998).









Repeated measures ANOVA results for abundance, total taxa, EPT taxa, Georgia

AAS index, Georgia EPD index, and percent Elmidae indicated that there were

differences in the macroinvertebrate assemblages due to sampling period. More

specifically, ANOVA results for Georgia EPD index and percent Elmidae were similar

with the December 2002 sampling period having significantly greater average values than

December 2001 and February 2002. The reason for the similarity in higher average

values for December 2002 is not apparent and may be coincidental because the EPD

index is composed of seven metrics (taxa richness, EPT index, number of Chironomidae

taxa, percent contribution of dominant taxon, percent Diptera, Florida Index, and percent

filterers), and Elmidae would only influence one of these metrics, taxa richness.

Abundance, total taxa, EPT taxa, and GA AAS index consistently indicated that the

December 2001 sampling period had significantly lower values than February 2003 and

that February 2002 did not differ from December 2002. Macroinvertebrate assemblages

respond to temporal variability, whether seasonal (Gibbins et al. 2001, Hutchens et al.

1998) or interannual (Hutchens et al. 1998). Seasonal variation is expected in

macroinvertebrate communities due to life history patterns, especially for taxa that

complete their life cycle within one year. The aforementioned ANOVA results for

abundance, total taxa, EPT taxa, and GA AAS index indicate that seasonal variation was

not the controlling factor for differences because the two seasons collected in 2002 did

not differ, while the same two seasons from different years, 2001 and 2003, were

significantly different.

Interannual variation in macroinvertebrate communities can be influenced by

drought (Feminella 1996), although Hutchens et al. (1998) reported that no consistent









drought-induced pattern in macroinvertebrate assemblages was apparent. This apparent

contradiction of results may be due to the substrate sampled. Hutchens et al. (1998)

suggested that drought-induced effects were possibly not detected because mixed

substrates, in this case red maple litter bags, were less sensitive to disturbance than other

habitats, such as bedrock outcrops. In the study of macroinvertebrate assemblages in

small streams of Alabama along a gradient of flow permanence, riffles were the substrate

sampled and total taxa was found to significantly differ between years; 1994, a wet year

preceded by a dry year and 1995 a normal year preceded by a wet year (Feminella 1996).

EPT taxa were not significantly different between years, but showed a strong positive

relationship with stream permanence (Feminella 1996).

In southwestern Georgia, drought conditions occurred during 1998-2002 and

resulted in an accumulated rainfall deficit of 711-1270 mm in some areas (Pam Knox,

Assistant Georgia State Climatologist, oral communication as cited in Warner and

Norton, 2003). The depressed rainfall totals resulted in low average daily flows (all

streams combined) that were most severe in December 2001 (1.25 L/s), then steadily

increased through February 2002 (1.40 L/s) and December 2002 (1.57 L/s), to February

2003 (2.78 L/s). The biota was affected by these conditions as evidenced by the

generally increasing positive relationship through time between average daily flow and

abundance, EPT taxa, and Georgia EPD index.

Poff and Ward (1989) analyzed long-term discharge records for 78 streams across

the US to develop quantitative characterizations of streamflow variability and

predictability. Acknowledging that there is generally a lack of empirical data on stream

organisms relative to long-term flow data, this characterization was used to suggest