ABSTRACT Title of Dissertation: MACROINVERTEBRATE COMMUNITY STRUCTURE AND ECOLOGICAL FUNCTION IN MARYLAND COASTAL PLAIN STREAMS Degree Candidate: Nicholas A. Baer Degree and Year: Doctor of Philosophy, 2004 Thesis directed by: Professor William O. Lamp Department of Entomology Abiotic conditions within streams, especially those conditions impacted by human activities, often influence the community structure and ecosystem function. While coastal regions have been strongly impacted by urban development and agriculture, little research has focused on characterizing the biotic community structure and function in these Coastal Plain streams. Such watersheds are characterized by low gradient, blackwater streams with sandy and silty substrate, coupled with large amounts of human disturbance. The objectives of this research were 1) to characterize the macroinvertebrate community and the chemical and physical characteristics of two Coastal Plain watersheds with differing landuse practices, 2) to examine appropriate macroinvertebrate sampling protocol comparing leaf pack and Maryland Biological Stream Sampling (MBSS) methods, 3) to compare these community structure measures with the functional measure 1 of leaf decomposition, and 4) to investigate potential mechanisms for shifts in decomposition due to elevated nutrients and dissolved organic carbon (DOC) concentrations in mesocosms. Results of three years of monthly sampling showed differences between watersheds in a number of chemical parameters, including nutrient concentrations. However, structural differences between the macroinvertebrate communities, using both three years of leaf pack sampling and a MBSS survey, were only identified for certain taxa and depended on the taxa resolution used. Also, two in situ leaf decomposition experiments using leaf decomposition tubes showed no differences in the macroinvertebrate or microbial contribution to detrital processing. Correlation analyses demonstrated that rates of decomposition were negatively associated with macroinvertebrate predator abundance and positively associated with the abundance of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa in the community. Lastly, a laboratory mesocosm experiment illustrated the strong effect of DOC from blackwater streams in reducing rates of leaf decomposition and processing efficiency by a macroinvertebrate shredder. While abiotic measurements of Coastal Plain stream sites varied greatly both spatially and temporally, and the field experiments yielded little consistent pattern with the macroinvertebrate community, the mesocosm experiment demonstrated the strong inhibitory effect of DOC on detrital processing and processing efficiencies of a macroinvertebrate shredder. Thus, while measuring rates of decomposition may not be suitable as a biomonitoring tool to differentiate already 2 nutrient enriched Coastal Plain streams, it can add to stream assessments by providing a measure of ecosystem function where impacts are less subtle. MACROINVERTEBRATE COMMUNITY STRUCTURE AND ECOLOGICAL FUNCTION IN MARYLAND COASTAL PLAIN STREAMS BY Nicholas Arthur Baer Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2004 Advisory Committee: Professor William O. Lamp, Chair Professor Bruce R. James Professor Margaret A. Palmer Professor Karen L. Prestegaard Professor Estelle Russek-Cohen ?COPYRIGHT BY Nicholas Arthur Baer 2004 ii DEDICATION To Dr. Leslie Baer, for showing me the importance of knowledge and discovery. iii ACKNOWLEDGEMENTS I owe a great deal of gratitude to my advisor, Dr. Bill Lamp, for his mentoring and friendship as I progressed with this research. Bill opened my eyes to the incredible world of aquatic insects. I truly appreciated his open door policy and willingness to provide technical guidance, as well as to jump into the stream work when needed. I am deeply indebted to my committee members who have all provided crucial guidance. Bruce James sparked my interest in understanding the biogeochemical mechanisms behind ecological processes. Margaret Palmer whose valuable insight in ecology pushed me to broaden my perspective. Karen Prestegaard expanded my understanding of the complexities of running water. I thank Estelle Russek-Cohen for her patience and willingness to make statistics tangible. It is this committee?s critical comments and suggestions that helped to shape this dissertation. I am grateful to my fellow Lamp lab graduate, and undergraduate students who spent many hours in the laboratory and field sampling and processing samples by my side, including: Laurie Alexander, Shelly Alicia, Louise Carroll, Sandy Crane, Megan DeOcampo, Joshua Han, Amy Kulesza, Chris Long, Jenny Maier, Amy Miller, Lauren Moffatt, Long Nguyendo, Patrick Rodgers, and Amy Soli. I truly valued the collaboration and friendship from many of my fellow graduate students, postdocs, and colleagues, whose invaluable discussions and statistical consultations improved the quality and focus of this work. I thank Laurie Alexander, Emily Bernhardt, Andie Huberty, Danny Lewis, Holly Menninger, Aaron Moore, Bob Smith, Chris Swan, and Philip Wirth III for enriching my graduate career and enhancing my understanding of the scientific process. There are a number of colleagues who provided additional help in study design, including: Owen Bricker, Judith Denver, Lou Kaplan, Mark Gessner, Manuel Graca, Dev Niyogi, Mike Paul, Doug Samson, and Keller Suberkropp. Aaron Barkatt and Lois Lane assisted with chemical analyses, and Steve Burrian and Ellen Friedman provided invertebrate identification confirmation. Finally, I would like to thank my wife, Kristin, and daughter, Marliese, for being my foundation of support and encouragement throughout this project. I am grateful for your love and patience on this long road. This work was funded, in part, by The Nature Conservancy and the US Geological Survey. I also thank the Maryland Water Resources Research Center, Department of Entomology, Marine-Estuarine-Environmental-Science program and Behavioral, Ecology, Evolution, and Systematics program at the University of Maryland whose support made this research possible. iv TABLE OF CONTENTS LIST OF TABLES............................................................................................................. vi LIST OF FIGURES ........................................................................................................... ix Chapter 1. Patterns of chemical, physical, and biological characteristics in two Coastal Plain watersheds in Maryland and the consequences of non-point source pollution ......... 1 INTRODUCTION: ............................................................................................................... 1 Study Site..................................................................................................................... 5 METHODS: ....................................................................................................................... 7 Chemical and Physical sampling................................................................................ 7 Biological Sampling.................................................................................................. 14 Landscape parameters.............................................................................................. 16 Data Analysis............................................................................................................ 16 RESULTS: ....................................................................................................................... 17 Chemical and physical parameters........................................................................... 17 Macroinvertebrate sampling..................................................................................... 19 Multiple Regression Models ..................................................................................... 20 DISCUSSION: .................................................................................................................. 21 Chapter 2. Development of a new method to measure the biotic contributions to leaf decomposition in Coastal Plain streams ........................................................................... 44 INTRODUCTION: ............................................................................................................. 44 METHODS: ..................................................................................................................... 47 Decomposition tube design....................................................................................... 47 Comparison of methods ............................................................................................ 48 Current flow.............................................................................................................. 50 Dissolved oxygen concentration ............................................................................... 52 Macroinvertebrate abundances ................................................................................ 52 RESULTS: ....................................................................................................................... 53 Comparison of Methods............................................................................................ 53 Current flow.............................................................................................................. 54 Dissolved oxygen concentration ............................................................................... 54 Macroinvertebrate abundances ................................................................................ 54 DISCUSSION: .................................................................................................................. 54 Chapter 3. A comparison of structural indices to leaf decomposition .......................... 65 INTRODUCTION: ............................................................................................................. 65 METHODS: ..................................................................................................................... 70 Study System.............................................................................................................. 70 Community structure measurements......................................................................... 71 Leaf pack sampling ................................................................................................... 71 Leaf decomposition measurement............................................................................. 74 Statistical Analysis.................................................................................................... 76 RESULTS: ....................................................................................................................... 76 Community structure................................................................................................. 76 Community function.................................................................................................. 78 DISCUSSION: .................................................................................................................. 81 v Chapter 4. Effects of nutrient and dissolved organic carbon levels on leaf litter decomposition rates by microbes and macroinvertebrates in coastal plain streams......... 99 INTRODUCTION: ............................................................................................................. 99 METHODS: ................................................................................................................... 103 Water Chemistry ..................................................................................................... 104 Experimental Setup ................................................................................................. 105 Observations ........................................................................................................... 107 Statistical analysis .................................................................................................. 108 RESULTS: ..................................................................................................................... 109 DISCUSSION: ................................................................................................................ 113 References:...................................................................................................................... 138 vi LIST OF TABLES Table 1.1. GPS coordinates of sample sites within two Coastal Plain watersheds.......... 27 Table 1.2. Chemical and physical parameters measured monthly from August 1998 to August 2001.............................................................................................................. 27 Table 1.3. Differences in chemical and physical parameters measured monthly over three years, 1998 - 2001, between the Nanjemoy and Nassawango Creek watersheds. ANOVA tests were used to test for significant differences between watersheds. A non-parametric, Kruskal-Wallis, test (denoted by the ? 2 statistical test) was performed when normality was not met. (*) represent statistical results based on Log transformed data in order to meet the assumptions of normality. Bold chemical and physical parameters are significantly different between the Nanjemoy and Nassawango Creek watersheds. ?BD? denotes below instrument detection............. 28 Table 1.4. Substrate profile for each sample site measured using EPA?s qualitative Rapid Bioassessment Protocol (Barbour et al. 1999).......................................................... 29 Table 1.5. Landscape analyses using GISHydro2000 software (Moglen and Casey 2000). Area represents watershed area above sampling site................................................ 29 Table 1.6. Mean abundance and percent of total community structure (in parentheses) for each taxa identified in leafpack samples measured once each season from fall 1998 through spring 2001. Insects were identified to the genus level or the lowest taxonomic level possible, except for Chironomidae, which were identified to sub- family. (*) indicates Class level taxanomic resolution. ........................................... 30 Table 1.7. Macroinvertebrate community metrics used to compare the Nanjemoy and Nassawango Creek watersheds. Analyses based on taxa per leafpack data. Bold Community metrics indicate significant differences between the watersheds (? = 0.05). ......................................................................................................................... 34 Table 1.8. Testing the difference between watersheds based on the macroinvertebrate taxa Orders, using the Atchison?s log ratio MANOVA test. Analysis is performed on the proportional data for each Order in the community. The Wilks? Lambda was used to generate the F-statistic presented.................................................................. 35 Table 1.9. Testing the difference between watersheds based on the macroinvertebrate functional feeding groups (FFG), using the Atchison?s log ratio MANOVA test. Analysis is performed on the proportional data for each FFG in the community. The Wilks? Lambda was used to generate the F-statistic presented. ............................... 35 Table 1.10. Shaded boxes represent significant explanatory variables (selected as significant in model with p<0.15) that explain the variance in the macroinvertebrate community structure response variables measured using multiple regression analysis...................................................................................................................... 36 Table 1.11. Multiple regression models selected using stepwise method to identify significant environmental explanatory variables that describe some of the variance found in the community structure response variables measured. Only models with 3 explanatory variables or less are illustrated. Explanatory variable were included in the model if significant with p< 0.15. Abbreviations used are; N = nitrate nitrite-N, TP = total phosphorus, F = fluoride, Alk = alkalinity, Cond = conductivity, Temp = temperature, DO = dissolved oxygen, Q = discharge, Qarea = discharge by vii watershed area, H 2 Oarea = watershed area, ChanSlope=channel slope, %Urban = percent urban area, %Forest = percent forest area.................................................... 37 Table 2.1. A Mixed model ANOVA comparing the rates of leaf decomposition using two field methods (tubes versus bags), and two mesh sizes (coarse versus fine) to evaluate decomposition tubes as an alternative method of measuring biotic contributions to detrital processing. Degrees of freedom represent numerator and denominator. ............................................................................................................. 59 Table 2.2. Testing flow effects on the percent salt loss between the two mesh size tube treatments in April 2001 in the Paint Branch Stream, Prince Georges County, Maryland. T-test is for the differences between treatment means of percent mass loss. ........................................................................................................................... 59 Table 2.3. Testing flow effects on the percent salt loss between the two treatments in February 2002 in the Nassawango Creek, Wicomico County, Maryland. T-test is for the differences between treatment means of percent salt loss............... 59 Table 2.4. Testing flow effects on the percent salt loss between the two mesh size tube treatments in October 2002 in the Nassawango Creek, Wicomico County, Maryland. T-test is for the differences between treatment means of percent mass loss. ........... 59 Table 2.5. Paired t-test comparing the differences in dissolved oxygen between the coarse and fine mesh tube treatments. ...................................................................... 59 Table 2.6. Chi-squared Wilcoxon rank sums test comparing differences in the number of individual macroinvertebrates between the coarse and fine mesh tube treatments. . 60 Table 3.1. Macroinvertebrate taxa abundance and percent of the community structure (in parentheses) measured within two Coastal Plain watersheds in Maryland using two sampling techniques; Leaf Pack and MBSS. (*) indicates Class level taxanomic resolution................................................................................................................... 87 Table 3.2. MANOVA using Atchison's log ratio test to test for differences in taxa, using Order level data, comparing sampling method and watershed................................. 91 Table 3.3. MANOVA using Atchison's log ratio test to test for differences in taxa, using FFG data, comparing sampling method and watershed............................................ 91 Table 3.4. Comparison of mean community metrics (? SEM) to compare watersheds, sampling method and the interaction using a Mixed model ANOVA. A non- parametric, Kruskal-Wallis, test (denoted by the ? 2 statistical test) was performed when normality was not met. (*) represent statistical results based on Log transformed data in order to meet the assumptions of normality. Bold p-values indicate significant differences. ................................................................................ 92 Table 3.5. Association between community measurements derived from Leaf Pack and MBSS sampling techniques. Bold metrics were those found to have significant relations to one another............................................................................................. 93 Table 3.6. A Mixed model ANOVA test for differences in the rates of leaf decomposition between the Nanjemoy and Nassawango Creeks using coarse and fine mesh tubes as treatments for the Fall 2000 field study. Analysis based on log transformed data........................................................................................................ 94 Table 3.7. A Mixed model ANOVA test for differences in the rates of leaf decomposition between the Nanjemoy and Nassawango Creeks using coarse and fine mesh tubes as treatments for the Summer 2001 field study. ............................. 94 viii Table 4.1. Ion concentrations characterizing the Nassawango Creek water used as the experiments stock solution. Shaded rows indicate the ion concentrations that were kept constant for the serial dilutions to dilute DOC concentrations. ...................... 119 Table 4.2. Amount of chemicals added to maintain background ion concentrations in diluted DOC treatments. ......................................................................................... 120 Table 4.3. Amount chemicals added for elevated nutrient and salt treatments. ............ 120 Table 4.4. Satterthwaite T-test showing no significant difference between salt and ambient treatments.................................................................................................. 120 Table 4.5. The analysis of variance table for the percent of dry leaf mass remaining shows the significant main effects and interactions................................................ 121 Table 4.6. The analysis of variance table for the rate of leaf decomposition (k value) shows the significant main effects and interactions................................................ 121 Table 4.7. The analysis of variance table shows the significant main effects and interactions for the respiration rates of the microbial community on the leaves.... 122 Table 4.8. The analysis of variance table shows the significant main effects and interactions for the total cumulative FPOM production summed at the termination of the experiment......................................................................................................... 122 Table 4.9. The analysis of variance table shows the significant main effects and interactions for the adjusted total cumulative FPOM with C. communis present. The FPOM was standardized by the final weight of the isopods at the end of the experiment .............................................................................................................. 123 Table 4.10. The analysis of variance table shows the significant main effects and interactions for the adjusted total cumulative FPOM with C. communis present. The FPOM was standardized by the number of days isopods were in contact with the leaves in each experimental unit............................................................................. 123 Table 4.11. The analysis of variance table shows the significant main effects and interactions for the processing efficiency of C. communis..................................... 123 ix LIST OF FIGURES Figure 1.1. Map of the Nanjemoy and Nassawango Creek watersheds in the Coastal Plain region of Maryland. Site names for each of the five sample sites are included. ................................................................................................................................... 39 Figure 1.2. Comparing the rank abundance curves for the 5 samples sites within the Nanjemoy Creek watershed, Charles County, MD. Pooled data collected from seasonal benthic sampling using leaf packs from Fall 1998 to Spring 2001............ 40 Figure 1.3. Comparing the rank abundance curves for the 5 samples sites within the Nassawango Creek watershed, Wicomico county, MD. Pooled data collected from seasonal benthic sampling using leaf packs from Fall 1998 to Spring 2001............ 40 Figure 1.4. Comparison across watersheds of macroinvertebrate community metrics (? SEM). Pooled data collected from seasonal benthic sampling using leaf packs from Fall 1998 to Spring 2001........................................................................................... 41 Figure 1.5. Comparison across watersheds of macroinvertebrate functional feeding group abundance data (? SEM). Pooled data collected from seasonal benthic sampling using leaf packs from Fall 1998 to Spring 2001....................................................... 42 Figure 1.6. The percent of each macroinvertebrate order comprising the community structure within each watershed. Community structure based on pooled data from Spring, Summer, and Fall samples collected from Fall 1998 to Spring 2001. ......... 43 Figure 1.7. The percent of each of the macroinvertebrate functional feeding groups (FFG) comprising the community structure within each watershed. Community structure from pooled data; Spring, Summer, and Fall samples collected Fall 1998 to Spring 2001............................................................................................................... 43 Figure 2.1. Small decomposition tubes developed to measure biotic contributions to leaf loss while reducing hydrologic leaf abrasion and breakdown. The far left tube (A) represents the fine mesh treatment measuring the microbial contributions to leaf decomposition, while the far left tube (C) illustrates the coarse mesh treatment measuring the additional effect of including macroinvertebrates to colonize the leaf material. The middle tube (B) shows the blank coarse tube that was used to measure organic material accumulated from upstream flow. ................................................. 61 Figure 2.2. Methods comparison using large PVC decomposition tubes (A), smaller decomposition tubes (B), and mesh bags.................................................................. 62 Figure 2.3. The mean rates of leaf decomposition, k, (?SEM) for 4 treatments tested in Nanjemoy Creek in Charles County during the summer 2000. Treatments with differing letter values (a and b) represent significant differences measured using ANOVA with ? = 0.05.............................................................................................. 63 Figure 2.4. The mean rates of leaf decomposition, k, (?SEM) comparing tube and bag field designs with coarse and fine mesh conducted in the Nassawango Creek in Wicomico county, Maryland during the winter 2003. Treatments with differing letter values (a and b) represent significant differences with ? =0.05. ...................... 63 Figure 2.5. The mean number of individuals (?SEM) within each coarse and fine mesh tube used in field leaf decomposition studies. Mean values and standard errors based on n=70. Treatments with differing letter values (a and b) represent significant differences with ? =0.05. ........................................................................................... 64 x Figure 3.1. Comparing of macroinvertebrate community structure using two field sampling methods; leaf pack and MBSS techniques. ............................................... 95 Figure 3.2. Comparing functional feeding groups for each watershed using two different sampling techniques; leaf pack and MBSS............................................................... 95 Figure 3.3. Leaf pack sampling community metrics and IBI score from spring macroinvertebrate collections. .................................................................................. 96 Figure 3.4. MBSS community metrics and IBI score for spring macroinvertebrate collection................................................................................................................... 96 Figure 3.5. A comparison across watersheds of the macroinvertebrate and microbial community (represented by the coarse treatment) and the microbial community (represented by the fine mesh treatment) contributions to the mean (+1 SE) rate of leaf decomposition. Data from a fall 2000 field experiment. ................................... 97 Figure 3.6. A comparison across watersheds of the macroinvertebrate and microbial community (represented by the coarse treatment) and the microbial community (represented by the fine mesh treatment) contributions to the mean (+1 SE) rate of leaf decomposition. Data from a summer 2001 field experiment............................ 98 Figure 4.1. Flask mesocosm design representing one experimental unit...................... 124 Figure 4.2. Regression of the fresh to dry weight conversion for the isopod to calculate for the starting biomass........................................................................................... 125 Figure 4.3. The rate of leaf decomposition, k, for the microbial and isopod shredder, C. communis, treatments under 4 different water nutrient regimes; ambient, elevated nitrate-N, elevated phosphorus, and elevated nitrate-N and phosphorus concentrations. ........................................................................................................ 126 Figure 4.4. Relationship of remaining dry leaf mass (%) across DOC concentrations after 30 d with the isopod present. .................................................................................. 127 Figure 4.5. Relationship of remaining dry leaf mass (%) across DOC concentrations after 30 d without the isopod present...................................................................... 128 Figure 4.6. The rate of leaf decomposition, k, with the isopod present........................ 129 Figure 4.7. Rate of leaf decomposition, k, without the isopod present.......................... 130 Figure 4.8. Respiration rates for the microbial community measured from treatment samples where the isopod was present.................................................................... 131 Figure 4.9. Respiration rates for the microbial community measured from treatment samples where the isopod was absent..................................................................... 132 Figure 4.10. FPOM produced with the isopod present. ................................................ 133 Figure 4.11. FPOM produced with isopod present and standardized for the final isopod weight at the end of 30 days. .................................................................................. 134 Figure 4.12. FPOM produced with isopod present and standardized by the number of days the isopods were presents. .............................................................................. 135 Figure 4.13. FPOM produced without the isopod present. ........................................... 136 Figure 4.14. The processing efficiency of the isopod under different water treatment regimes over the 30 day experiment. ...................................................................... 137 1 Chapter 1. Patterns of chemical, physical, and biological characteristics in two Coastal Plain watersheds in Maryland and the consequences of non-point source pollution Introduction: Doubling of the world?s food supply through modern agricultural practices doesn?t come without its consequences. There have been dramatic increases in the use of fertilizers, the cultivated land cover, and the amount of irrigated land (Tilman 1999). These changes can lead to alteration in aquatic ecosystems, which are receiving waters to altered landscapes (Cooper et al. 1995, Carpenter et al. 1998, Arbuckle and Downing 2001, Niyogi 2003). It has been suggested that the extinction rate for aquatic fauna is occurring at faster rate than in terrestrial systems (Ricciardi and Rasmussen 1999). Agriculture can have several associated adverse effects on water quality and the biota that inhabit these aquatic ecosystems. Impacts include loss of riparian zone vegetation, increased sediment loads, nutrient enrichment, diversion and loss of water for irrigation, and potential contamination from pesticides, herbicides, and fungicides. Elevated nutrient loads have been documented throughout the world where intensive agriculture is practiced (Malmqvist and Rundle 2002, Donner 2003, Little et al. 2003). Of particular interest are nutrient enrichment and the changes in the biotic community that result. Biomonitoring can be used as a tool to assess how natural or human derived disturbances can affect aquatic organisms (Karr and Chu 1999). For example, McDougal et al. (1997) showed that increased nutrient concentrations could cause community structure shifts. Other studies have shown changes in the community 2 composition due to agricultural influences (Stewart et al. 2001, Huryn et al. 2002, Shieh et al. 2003, Davis et al. 2003). Specifically, studies have shown that percent forest cover and agriculture were important variables influencing both fish and macroinvertebrate communities on a large landscape scale, while embeddedness was a strong reach-scale factor (Stewart et al. 2001). Huryn et al. (2002) focused on the effects of non-point source nutrient loading to streams and how it affects the macroinvertebrate community structure and the rate for detrital processing. Their work showed that shifts in the richness of macroinvertebrate shredders, who function to decompose the terrestrially derived leaf material, explained differences in decomposition rates across different land use areas. They also illustrated different dominant taxa within the shredder functional feeding group changed with the varied landscapes. Human derived disturbances, such as agriculture, urbanization, and forestry practices have the capacity to alter stream chemical and physical characteristics, which in turn, can have adverse consequences on the aquatic biota dependent. Karr and Chu (1999) illustrate the need to monitor aquatic environments to document biotic changes as indicators of anthropogenic changes to these systems. Long term monitoring to help characterize streams can aid in identifying shifts in community structure (Cairns and Pratt 1993). The mid-Atlantic Coastal Plain region has been heavily influenced by anthropogenic impacts for hundreds of years due to its temperate climate, fertile alluvial soils and accessible river and coastal areas for trade (Cooper 1995). Agriculture in Maryland?s Coastal Plain results in elevated levels of phosphorus (P) and nitrogen (N) in 3 running waters that eventually impact the Chesapeake Bay (EPA 1999). This nutrient enrichment was responsible for major shifts observed in the microorganisms, macrophytes, benthic fauna, fish, and crab communities within the bay (Davis 1985, Burkholder and Glasgow Jr. 1997, Boesch et al. 2001, Cronin and Vann 2003). Stratigraphic methods have demonstrated the dramatic changes in sediment transport, nutrient enrichment, and anoxia within the Chesapeake Bay. The 1800?s saw major sedimentation transport due to up to 80% of the land being cleared, while the post 1940?s has seen dramatic rise in nutrient transport due to fertilizers (Cooper and Brush 1991). Best management practices have been implemented in agricultural production systems throughout Maryland to abate some of the problems associated with non-point source pollution and its effect on the State?s surface and ground water supplies. Although these practices have assisted in reducing some of the contaminant loads to streams, certain contaminants continue to appear in both the surface water and groundwater (EPA 1999). The soil conditions and hydrologic influences in this region may contribute to the increased levels of soluble phosphorus in the streams (Bricker et al. 2003). The physical conditions of sandy soils with low clay content and the presence of organic materials, combined with low gradient watersheds with a relatively high water table level, create a reduced chemical condition where the P present in the system may not be readily bound to the soil (Brady and Weil 1999). In these environments, elevated available phosphate levels can be observed. Additionally, a shallow water table environment allows nitrate from non-point sources to leach into the groundwater and readily enter the streams through groundwater flow. However, there are several natural processes that can attenuate nitrate as it moves 4 through shallow groundwater like those surficial flows found in Coastal Plain regions with low gradient landscapes. Plant roots that are in contact with this high water table have an opportunity to assimilate nitrates from the groundwater. Also, hydrologic and geologic conditions can facilitate denitrification, commonly mediated by bacteria, through a number of chemical pathways using nitrate as an oxidizing agent (Krantz and Powers 2000). As a consequence, Coastal Plain streams that are impacted by agriculture may be nitrogen-limited due to the relative high abundance of the available phosphorus. These changes in the available nutrient may alter the bottom up controls on the aquatic ecosystem (Miltner and Rankin 1998, Forrester et al 1999, Robinson and Gessner 2000, Barlocher and Corkum 2003). Other studies have documented the macroinvertebrate community structure unique to swampy Coastal Plain streams (Smock et al. 1985). More recent work has demonstrated community metrics that can help to differentiate impaired stream conditions in Coastal Plain streams (Stribling et al. 1998, Davis et al. 2003). Here, I studied two watersheds, the Nassawango and Nanjemoy, which differed in land use, particularly for agriculture. The objectives of this study of the Nassawango and Nanjemoy watersheds were to conduct a biohydrological survey to characterize the chemical, physical, hydrological and biological components of streams within two Coastal Plain watersheds, and relate environmental conditions to the biotic community structure observed. I hypothesized that differences in the water chemical and physical conditions would be associated with differences in the macroinvertebrate community structure when we compare an agriculturally impacted watershed with a more pristine watershed. 5 Study Site This study was initiated in collaboration with The Nature Conservancy to conduct a biohydrological study on two watersheds in the coastal plains region of Maryland. The Nassawango Creek, south of Salisbury on the Eastern Shore, and the Nanjemoy, in southern Maryland, are the two systems of particular interest (Fig. 1.1). There are a number of rare plants and animals found in the wetland habitats of the Nassawango watershed (The Nature Conservancy 1996), while the Nanjemoy Creek is one of four unique Maryland environments home to the dwarf wedge mussels (Alasmidonta heterodon) (The Nature Conservancy 1998). The unique flora and fauna of these two stream systems has spurred efforts to gain more information about these habits. This was the primary reason that the current study was established. The objectives of this study were to provide a greater understanding of the patterns of these two aquatic conditions and to relate these parameters to the biotic communities in these environments. These two Coastal Plain watersheds represent relatively less impacted watersheds in a landscape of urbanization, agricultural use, forestry practices and preservation efforts. While both of these watersheds have greater than 70% forested land cover, they differ in the remaining 30%. The Nassawango watershed extends from Worcester County to Wicomico County on the Eastern Shore. It is a tributary to the Pocomoke River that flows into the Chesapeake Bay. The Nassawango Creek is located between the towns of Salisbury and Snow Hill. The watershed has woodland, small farms, and residential areas. According to the Maryland Department of Natural Resources (MDNR), the watershed has an area of approximately 177.0 km 2 . Based on 1994 landuse surveys, it consists of 2.3% urban, 25.8% agricultural, 71.7% forested, 0.2% wetland, and 0.1% barren land cover. This watershed has 24 % non-forested riparian zones. MDNR also 6 estimated that the fertilizer application rate is 3.1 kg/acre nitrogen and 0.2 kg/acre phosphorus (MDNR retrieved April 5, 2004). The watershed soils are dominated by sandy and sandy loam soils. These soil surveys characterized the soils as a Lakeland- Klej-Plummer association and a Pocomoke-Mattapex-Elkton association. The Lakeland- Klej-Plummer association spans a wide area, which has both steep gradients with excessively drained soils to very poorly drained sandy and loamy sand soils. The Pocomoke-Mattapex-Elkton association located in the upper watershed area consists of level to near level, very poorly drained to moderately well drained with sandy loam and sandy clay loam subsoils (USDA 1973). The Nanjemoy Creek is located in Charles County and is a tributary of the Potomac River. The MDNR estimated that the watershed has an area of 188.6 km 2 . The 1994 landuse survey shows that the watershed consists of 6.5% urban, 15.5% agricultural, 73.9% forested, 4.0% wetland, and 0.1% barren land cover. The watershed has 8 % non- forested riparian zones. It is also estimated that the fertilizer application rate is 2.0 kg/acre nitrogen and 0.1 kg/acre phosphorus (MDNR retrieved April 5, 2004). The soils within the watershed are a mix of clay, small cobble, silt and sand. The soils are comprised of Bibb-Tidal Marsh-Swamp association in the upper part of the watershed. These areas have a level to moderate slope, a moderately well drained loamy soils, and only moderately deep to a hard dense fragipan. The lower reaches of the watershed are considered a Beltsville-Exum-Wickham association, characterized by a level or near level slope and poorly drained soils on the flood plain (USDA 1974). Although both watersheds have large amounts of forested lands I considered the Nassawango to have more intensive agricultural practices and overall reduced riparian 7 buffers as compared to the less disturbed, forested watershed within the Maryland Coastal Plains. Each of the five study sites within each watershed was located on Nature Conservancy lands with readily available access. Sample sites were selected with the cooperation of the Nature Conservancy (Table 1.1). Sample sites were selected in wooded riparian region along the stream corridor and consisted of 2 nd to 4 th order streams. Methods: Chemical, physical, hydrologic, and benthic macroinvertebrate samples were collected from August 1998 to August 2001 in the two watersheds in the Maryland Coastal Plain region: the Nassawango Creek in Worchester and Wicomico Counties, and the Nanjemoy Creek in Charles County. Chemical and Physical sampling Water samples were collected monthly for a three year period to determine a suite of chemical and physical characteristics of the watersheds. Table 1.2 provides a list the parameters measured on a monthly basis. Both 500 ml brown glass bottles and 125 ml plastic bottles were used to collect the water samples. Both bottles were soap washed, and rinsed with deionized water prior to sampling. The brown glass bottle, as well as all other glassware used in the water chemistry analyses had an additional 1:1 HCL acid rinse followed by deionized water cleaning to ensure that no phosphorus was bound to the glass. The water in the glass bottle was used to analyze the nutrient concentrations, while the water in the plastic bottle was used to determine the alkalinity, hardness, and turbidity levels. All chemical tests, with the exception of total phosphorus and fluoride, 8 were tested the same day water samples were collected. The total phosphorus and fluoride tests were performed within a two-day period of water collection. All water samples were stored on ice until returned to the laboratory. Samples were then stored at 4 o C until the remaining chemical measurements were made. The chemical and physical parameters, including nitrate and nitrite-nitrogen, reactive and total phosphorus, alkalinity, hardness, and turbidity were measured from one water sample for the first one and one half years of this study. For the second half of the study three water samples were used in order to get an estimate of variance for each of these parameters. The nitrate and nitrite-nitrogen, reactive and total phosphorus, and fluoride were analyzed using a Hach DT-890 Colorimeter. This is a spectrophotometric technique to measure color changes that quantify a chemicals relative concentration in solution. The combined nitrate and nitrite-nitrogen were measured using a modification of the cadmium reduction method, which reduces the nitrates (NO 3 - ) in the water sample to nitrites (NO 2 - ). Under acid conditions nitrite ions then react with sulfanilic acid forming a diazonium salt. This salt in turn creates an amber colored compound when it reacts with gentisic acid. This method replaces 1-naphthylamine with gentisic acid to bring about the color change (Hach 1998). Two cuvettes were rinsed three times with stream water followed by 10 ml of sample stream water being placed in each cuvette. A packet of NitraVer5 chemical pillow was added to one of the cuvettes while the second cuvette was used as a blank to zero the colorimeter. After adding the chemical packet the cuvette was shaken for 1 minute followed by a waiting period of 5 minutes before measuring the nitrate-nitrogen concentration (Hach 1998). The colorimeter was zeroed using the sample blank before each reading. 9 The soluble reactive phosphorus (SRP) concentration was measured using the ascorbic acid method. Orthophosphates reacted with molybdate under acid conditions to create a phosphomolybdate complex. This complex was then reduced by ascorbic acid that forms a blue solution due the formation of a molybdenum species. 10 ml of water sample was poured into two cuvettes. A PhosVer3 Phosphate reagent powder pillow was added to one of the cuvettes and shaken for 15 seconds. The colorimeter was zeroed using the sample blank before each reading. The cuvette with the chemical reaction was then placed in the spectrophotometer and the phosphorus concentration measured. Each of the chemical tests had a preprogrammed channel on the Hach DR 890 spectrophotometer so no manual wavelength adjustments were necessary between chemical tests (Hach 1998). In order to measure total phosphorus (TP), an additional acid digestion step was necessary to convert all organic and inorganic phosphates to organophosphate prior to analysis. Using a graduated cylinder, 25 ml of water sample were poured into a 75 ml Erlenmeyer flask. The sample was acidified using 2 ml of a 5.25 N sulfuric acid solution. The sample was then heated to a low boil for 30 minutes while ensuring that approximately 20 ml of sample was maintained. Deionized water was added to the sample as needed to maintain volume. The samples were then cooled to room temperature and neutralized, using 5.0 N sodium hydroxide. The pH was adjusted using dilute sodium hydroxide and sulfuric acid solutions until it was stabilized between pH 7.0 and 8.0. The sample solution was then measured in a graduated cylinder and deionized water added until the total sample volume equaled 25 ml (Hach 1998). This sample was then divided with 10 ml used as a sample blank for the colorimeter and the other 10 ml 10 used as the test sample, which was then tested using the same reactive phosphorus methods previously described. Fluoride measurements are used to assess whether there is municipal waters in the stream waters from upstream water treatment plant, sewage treatment, or other sources of community water that was previously fluoridated. Fluoride concentration is determined using a solution of sodium arsenite and red zirconium-dye (SPADNS reagent). The dye bleaches in an amount proportional to the fluoride concentration present. The test was performed by pipetting 10.0 ml of sample water into one cuvette and 10.0 ml of deionized water into a second cuvette. To both cuvettes, 2.0 ml of SPADNS reagent was added and swirled to homogenize the solution. After one minute of reaction time the colorimeter was zeroed using the deionized water solution, followed by the stream water sample being read (Hach 1998). Conversion to chemical concentrations from absorbance reading using the colorimeter was automatically calculated using the Hach DR 890. This calculation is based on Beer?s Law relating spectrophotometric absorbance to the relative concentration of a compound in solution. Beer?s Law is expressed as: OD = eCL where OD is the absorbance, e is the extinction coefficient, C is the chemical concentration, and L is the length the light travels, which is the width of the cuvette in the spectrophotometer (Kegley and Andrews 1998). Standards were run on the Hach colorimeter early in 1999 and in 2001 to ensure that the machine was reading accurately. Also, each new package of chemical packets was run with deionized water to calculate the reagent blank to be subtracted from the 11 colorimeter reading. This information was input into the DR 890 directly, so the colorimeter automatically adjusted the output results. A digital titrator, Hach model 16900, was used to quantify both the alkalinity and hardness of the stream water samples. The alkalinity measures the neutralizing capacity of the water that is predominately due to the presence of bicarbonate and carbonate. The phenolphthalein method converts bicarbonate and carbonate to carbonic acid if acidified to pH 4.5. The Hach method uses a bromocresol green-methyl red color indicator to identify when the reaction is complete. The reaction changes the blue indicator to a pink color. Total alkalinity was measured by pouring 100 ml of the water sample in a 250 ml Erlenmeyer flask. Then one phenolphthalein indicator powder pillow to the sample and a color change identified. Because all the samples did not show a color change the method called for the addition of one bromocresol green-methyl red indicator powder pillow prior to titration. A sulfuric acid 1.6 N solution was digitally titrated into the water sample while swirling flask. The reaction was stopped when a light pink color appeared indicating a pH of 4.5 was reached. The amount of sulfuric acid added was then used to determine the concentration of calcium carbonate present in the original water sample. This was determined by multiplying the number of digits added by 1.0 to yield (mgL -1 ) total alkalinity as calcium carbonate (Hach 1996). Hardness measures the concentrations of dissolved minerals, comprised mostly of divalent cations. These are primarily magnesium and calcium, but also include iron, zinc, manganese, and strontium. Water hardness was measured by titrating EDTA into the water sample with calmagite. The Hach method measures calcium hardness, which accounts for the hardness in the water sample due to calcium ions in solution. Following 12 the Hach procedure 50 ml of water sample were poured into a 250 ml Erlenmeyer flask with an additional 50 ml of deionized water. The addition of 2 ml 8.0 N potassium hydroxide was added to this solution and swirled. One packet of CalVer 2 was added and swirled. This was followed by digitally titrating 0.714 M ethylenedianimetetraacetic acid (EDTA) into the water sample solution with the Hach digital titrator model 16900. The titration was stopped when the color of the water sample changes from pink to blue. This occurred at pH 10.1. The amount of EDTA added was then used to determine the concentration of calcium ions present in the original water sample. This was determined by multiplying the number of digits added by 0.1 to yield (mgL -1 ) calcium hardness as calcium carbonate (Hach 1996). A Corning Checkmate II handheld field meter was used to record pH, dissolved oxygen, conductivity, and temperature. Each probe was calibrated in the laboratory prior to each sampling effort. In addition to measuring the parameter of interest all three of the probes recorded temperature. For the purpose of consistency, the temperature used in the analyses was recorded from the pH probe. The pH and conductivity was measured immediately from a sample of stream water collected in a plastic cup. Dissolved Oxygen was measured by placing the probe in the water and allowed to stabilize. Each parameter was measured three times in order to estimate variance. Turbidity was measured using a visual assessment of particulates in the stream water solution. The first of two modified volumetric cylinders was filled with 50 ml stream water, while the second was filled with 50 ml deionized water. A standard turbidity reagent (LaMotte Company reagent 7520) was added two drops at a time to the deionized water cylinder until the visual clarity of a black dot on the bottom of the 13 cylinder appeared to be the same. The number of drops added to equalize the visual opacity between the two cylinders was then divided by 2 in order to calculate the Jackson Turbidity Units (JTU?s) (LaMotte Co. 1996). The photosynthetic available radiation (PAR) was measured using a Decagon Sunfleck Ceptometer (Decagon Devices, Inc. 1989). The PAR was measured in three places at each site, in direct open canopy sunlight, along the stream-side riparian area (referred to as the stream bank), and above the in-stream water surface. A mean of 5 PAR measurements was calculated for each of the three places for each site. The proportion of sunlight reaching the stream water surface and the stream bank are then compared across sites and watersheds. Both the stream bank PAR and in-stream PAR were divided by the open canopy PAR to calculate these proportions. Stream discharge was measured to assess the relative magnitude of hydrologic force each watershed and sites within watershed experience. The flow regime is a crucial environmental parameter that affects the biotic community within the stream. The discharge was calculated by first measuring the cross-sectional width and depth of the stream in order to determine cross-sectional area. The depth measurements were taken every 50 cm and the water velocity was measured, using a Marsh-McBirney flow meter, half way in between each depth measurement (Marsh-McBirney Inc. 1990). In this way the velocity per unit area could be calculated for every 50 cm segment of the cross- section and summed together for the stream discharge. The water velocity was measured at two-thirds depth of the stream water. This is to obtain the average water velocity in the vertical column (Leopold et al. 1992). A standardized discharge was also calculated on a per unit area basis as another way to compare discharge across sites. Additionally, 14 qualitative sediment characteristics were measured for each of the sample sites using the EPA?s Rapid Bioassessment Protocol (Barbour et al. 1999). Biological Sampling Artificial leaf packs were used to collect benthic macroinvertebrate samples three times each year; spring, summer, and fall. Red maple (Acer rubrum) leaves were selected for my study, because they are commonly found in both watershed study areas and are one of the terrestrially derived food sources that the benthic community readily utilizes. They have also been shown to have a moderate rate of decomposition, with medium range k-values (approximately 0.0075 - 0.0060 day -1 ) and a relatively small variance (Petersen and Cummins 1974, Webster and Benfield 1986). Five grams of desiccated red maple leaves were bound to a brick and left in the stream for 30 days. Eight replicate leaf pack samples were deployed at each site. The leaf packs were placed across the cross-section of the stream in order to measure the community structure including the organisms that prefer the slow water edge and the ones found in the faster mid-stream region. The leaf packs were then collected, put in plastic bags and stored on ice until returned to the laboratory where they were preserved at 4 o C until processed. To process the samples the leaves were rinsed in a pan and all the leaf material washed and discarded, leaving the macroinvertebrates in the pan of water. The pan contents were then filtered through a 425-micrometer mesh size sieve to collect the macroinvertebrates. Each sample was labeled and preserved in 80% alcohol solution. The macroinvertebrates were sorted and identified to genus level or as far as was taxonomically possible (McCafferty 1983, Merritt and Cummins 1996, Peckarsky et al. 1990, Wiggins 1996, Williams 1972, Mackay 1978). The family Chironomidae was the 15 exception with individuals identified to the subfamily level. The mean number of taxa, and abundance of individuals were calculated per brick per site. This standardized the data across sites in case there were missing leaf packs at the time when the leaf packs were collected. The taxa present and absent at each site was determined and used to calculate a number of indices including; the number of taxa, the number of Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa, the proportion of Ephemeroptera in the community, the proportion of Tanytarsini in the Chironomidae family, the Beck?s sensitive taxa index, the number of macroinvertebrates that are in the functional feeding group ?scrapers?, and the proportion of macroinvertebrates considered ?clingers? in the community. The classifications used for sensitive taxa, functional feeding groups, and taxa habit (e.g. clinger) were based on the MDNR classification (Stribling et al. 1998). Maryland?s Montgomery County Department of Environmental Protection taxa listings, and Merritt and Cummins (1996) taxa information were used as additional resources when taxa characteristics were missing. These above metrics were then averaged to create an Index of Biological Integrity (benthic IBI) based on the MDNR methods (Stribling et al. 1998). These metrics were selected because the Maryland Biological Stream Survey had analyzed what measures of the community best differentiated impaired streams in the Coastal Plain region (Stribling et al. 1998). Additional metrics including, total abundance, the Shannon diversity index, the number of taxa were considered predators, shredders, collectors, filterers, and scrapers, as well as the percent each of these five functional feeding groups were assessed to incorporate other trophic measurements when evaluating the watersheds (Barbour et al. 1999). 16 Landscape parameters A global positioning system (GPS) was used to determine the coordinates of each sample site within the two watersheds. A correction antenna was used to improve the accuracy of the coordinates received. The points were then converted to units that could be recognized by a GIS software program called GISHYDRO developed at the University of Maryland (Moglen and Casey 2000). Using this software the watersheds were delineated for the area above each of the sample points within the two watersheds. The program also provided several landscape characteristics for each of the sites, including, channel slope, land slope, percent agriculture, percent urbanization, percent impervious surface, and percent forest cover. Data Analysis A mixed model analysis of variance (ANOVA) was used to determine the significant chemical, physical, and hydrologic parameters that differentiated the two watersheds (SAS Institute Inc. version 8.2). However, it was necessary to log transform some of the explanatory variables prior to the ANOVA to satisfy the assumptions of normality and homogeneity of variance. Several of the parameters were analyzed using a nonparametric Kruskal-Wallis tests when the assumptions of normality were not met (Table 1.3). This method was also used to distinguish sites within each watershed that were significantly different from the majority of sites. The mean per leaf pack per site was calculated to standardize the number of macroinvertebrates found per leaf pack for further biotic community structure comparisons. The community taxa information was then compared across watersheds using the Atchison?s log ratio test for the taxa at the order level, and the functional feeding groups. ANOVA and a non-parametric, Kruskal- 17 Wallis test were used to compare community metrics, including the ones used by MBSS as well as total abundance, the Shannon diversity metric, and the abundance and numbers of taxa in functional feeding groups. Also, rank abundance curves were created to compare the taxa diversity within and across watershed. Multiple regressions, using stepwise selection method, were used to identify the key environmental parameters that can help explain the critter community structure and the variance observed in the sampling of these two watersheds. Results: The chemical, physical, and biological database compiled for this study, from August 1998 to September 2001, is available from the author, or Dr. William O. Lamp at the University of Maryland, College Park. Chemical and physical parameters There were significant differences between the Nanjemoy Creek and the Nassawango Creek watersheds both chemically and physically. The Nassawango Creek watershed had significantly higher nutrient and ion concentrations, as measured by SRP, TP, nitrate-nitrite nitrogen, alkalinity, hardness, and conductivity parameters (Table 1.3). All but the ratio of stream to direct sun PAR were significantly different between the two watersheds with p<0.0001. Both the phosphorus (SRP and TP) and the nitrate-nitrite nitrogen concentrations yielded greater values in the Nassawango Creek than in the Nanjemoy Creek watershed. Fluoride concentrations were also significantly higher in the Nassawango Creek watershed (p<0.0001) (Table 1.3). Measurements of overall ion concentrations, both anion and cation followed the same trend with Nassawango Creek 18 watershed having higher alkalinity, hardness and conductivity concentrations than Nanjemoy Creek watershed (all with p<0.0001). Dissolved oxygen concentrations and turbidity measures were lower, while the pH levels were higher in the Nassawango Creek watershed (all with p<0.0001). Because the Nassawango Creek watershed was larger in overall area it is not surprising that this watershed has significantly great discharge (p<0.0001). The light availability to the stream and bank areas, as measured using PAR, showed that two watersheds did not differ in stream PAR to open sunlight PAR ratio, while the bank PAR to open sunlight PAR ratio was larger (0.46) in the Nanjemoy Creek watershed (p<0.0001). Reach scale differences in substrate composition between sample sites demonstrated within watershed variability of substrate ranging from clay dominated to sand or gravel dominated in the Nanjemoy Creek and sand, silt or clay dominated sites in the Nassawango watershed (Table 1.4). There were also differences in the percent organic matter present in the substrate. Sites such as MOC, TBC, and HBC in the Nassawango Creek, and PTR in the Nanjemoy Creek had relatively greater organic matter content in the substrate when compared to the other sample sites within each watershed. Results from the GISHydro2000 analysis for each of the sample sites provided landscape information both on physical attributes and landuse (Table 1.5). The Nanjemoy Creek sample sites ranged in watershed area from 4.9 km 2 in the second order stream to 37.8 km 2 at the highest order sample site (NMS), while the Nassawango Creek had sample sites with contributing watershed areas ranging from 7.8 km 2 for HBC to 113.0 km 2 at RTE12. The overall channel slope was steeper for the Nanjemoy site, with 19 a mean of 3.4 m/km, than the Nassawango sites averaging a channel slope of 0.6 m/km. Percent urbanization ranged from 6.9% to 14.6% in the Nanjemoy Creek watershed as compared to the 0.0% to 12.6% in the Nassawango Creek. Agricultural landuse was between 10% and 17% in the Nanjemoy watershed compared to a range of 14% to 48% in the Nassawango watershed. The HBC sample site in the Nassawango had the highest agricultural landuse with 48%. The forest cover in the Nanjemoy Creek had a range of 69.6% to 81.3% while the Nassawango Creek sample sites were much more variable, ranging from 31.8% at HBC to 87.9% at STC. Macroinvertebrate sampling The macroinvertebrate sampling collected over the 8 sampling dates from fall 1998 to spring 2001 consisted of 10,896 individuals comprising 106 different taxa with the majority identified to the genus level. Mean abundance and the relative percent of each taxa metrics are presented by season for each watershed (Table 1.6). For all seasons and within each watershed Diptera taxa dominated the community structure. Within watershed variation was demonstrated using rank abundance curves for the sample sites (Fig. 1.2 and Fig 1.3). These graphs illustrate that these sites were dominated by a few taxa. It also shows that in both watersheds, the highest order stream furthest downstream in the watershed, RTE12 in the Nassawango Creek and NMS in the Nanjemoy Creek, had the shallowest slope indicating the most even community structure of all the sites sampled. None of the Maryland Biological Stream Survey (MBSS) taxa metrics differentiated the two watersheds. However, the Shannon diversity index (p<0.03) (Fig. 1.4), the number of predator taxa (p<0.01), and the abundance of predators (p<0.001) 20 (Fig. 1.5) were found to be significantly different between watersheds (Table 1.7). The abundance of scrapers was marginally significant (p<0.06) when comparing the two watersheds. Overall the MANOVA analysis showed that the Nanjemoy and Nassawango Creek watersheds differed in community structure based on order level information (p<0.0001) (Table 1.8, Fig. 1.6). The watershed also differed using the FFG partitioning of the community (p<0.0001) (Table 1.9, Fig. 1.7). Multiple Regression Models As much as 39% of the taxa metrics variance could be explained by the explanatory variable measured. There were a number of the community metric regression models that had similar environmental parameters explaining some of the variation observed (Table 1.11). Dissolved oxygen, pH, temperature and fluoride all contributed to explaining several of the metrics measured. Of particular interest were those models that contained only a few environmental parameters. For instance, 31% of the variation in the number of taxa could be explained by temperature, dissolved oxygen, and watershed area (p<0.0001) (Table 1.11). Dissolved oxygen was the only significant explanatory variable that explained the number of EPT taxa present (p<0.045). However, the dissolved oxygen only explained 4% of the variation. Although significant, (p<0.025), only 9% of the variation in the percent of mayflies, Ephemeroptera, present was explained by pH, conductivity, and temperature. A portion of the variability in the percent of filter feeding, Tanytarsini, (19%), was due to turbidity, pH, and temperature. Dissolved oxygen and watershed area explained 25% of the variance in the number of scrapers (p<0.0001). Alkalinity, pH, and conductivity contributed to explaining 19% of the variance of the abundance of predators in the community (p<0.0006), while only 8% 21 of the variability of the abundance of shredders was explained by fluoride, alkalinity and percent forest cover (p<0.035). Of particular interest was that fluoride and the percent urbanization accounted for 19% of the variance in the percent shredders in the community (p<0.0001). Also the percent filters were influenced by the turbidity (p<0.051). Discussion: This study showed significant differences in the chemical and physical habitats between the Nanjemoy and Nassawango Creek watersheds. As predicted the Nassawango watershed with its non-point source agriculture influences, had significantly higher nutrient levels (Table 1.3). Both the elevated nitrate and phosphorus concentrations measured over this three-year study are supported by the Maryland Biological Stream Survey (MBSS) performed in 2000. The MBSS study illustrated the higher nutrient concentrations within the Eastern Shore watersheds than in the Nanjemoy watershed (Roth et al 2001). Streams without anthropogenic influences commonly have phosphorus concentrations of 0.025 mgL -1 (Allan 1995). While both watersheds exceeded this level, indicating some human or unique geological derived nutrient influences, the Nassawango Creek had significantly great SRP and TP concentrations (Table 1.3). The elevated phosphorus levels probably have two origins; the intensive agricultural practices of row cropping and poultry farms within the Nassawango watershed, and the underlying geology. The Nassawango watershed has bog-iron ore or swamp ore deposits which can contain up to 10% phosphorus (Singewald 1911). Both phosphorus rich sediments 22 flowing into the streams from agricultural areas and the leaching of phosphorus from the bog ore under low pH conditions could increase the phosphorus concentrations in the streams. Although nitrate-nitrite nitrogen concentrations were higher in the Nassawango Creek watershed, they were still relatively low levels (0.48 mgL -1 ?0.05) for having row crop and poultry farming located in the watershed when compared to other Eastern Shore agricultural areas (US EPA 1999). There may be several reasons for the low nitrogen levels. Coastal Plain stream environments are conducive to denitrification due to the high organic content, and potentially anoxic conditions along the stream bottom or within the groundwater. There is also the potential for riparian vegetation to uptake the nitrogen from the high water table (Krantz and Powars 2000). These conditions create a novel stream condition where nitrogen limitation may occur for the in-stream biotic community. This is uncommon, as stream systems are often found to be phosphorus limiting due to more common elevated nitrogen inputs (Allan 1995). All measurements of ion concentrations, alkalinity, hardness and conductivity showed significantly greater levels in the Nassawango Creek watershed again supporting my assertion of non-point source influences on the water chemistry. Differences in pH showed that overall the Nanjemoy Creek had lower pH levels than the Nassawango (Table 1.3). Maryland Department of Natural Resources (2001) reported the greatest extent of low pH levels (0.05) (Fig. 4.3). It increased from 74% to 82% leaf dry mass remaining from the low to high DOC concentration, respectively (Fig. 4.3). When the isopod was present, no significant changes in the percent of dry leaf mass remaining at low DOC concentrations were observed across nutrient addition treatments. However, the presence of the isopod was associated with a significant decrease in the percent of dry leaf mass remaining at high DOC concentrations for all three nutrient addition treatments, compared with the ambient water treatment. The N addition decreased the percent of leaf mass remaining by 11% (p<0.004), while the P addition decreased it by 7% (p=0.05). The N + P addition magnified the depression in the percent of leaf mass 22% from the ambient treatment results (p<0.0001) (Fig. 4.4). Without the isopod present, no significant changes in the percent of leaf material remaining were found across DOC and nutrient treatments (Fig. 4.5). 111 The rate of leaf decomposition, k, mirrored the leaf mass remaining response for both the treatments with and without the isopod present (Table 4.6). In particular, the analysis of variance of the k values showed a significant main effect of N (p<0.001) and the presence of the isopod (p<0.0001). There were significant interactions of both DOC with N (p<0.01) and with P (p<0.05). There was one significant three-way interaction of DOC, P, and the isopod (p<0.05). The DOC concentration had a significant impact on the rate of leaf decomposition for treatments with isopods present. The k value significantly decreased from a mean value of 0.010 d -1 at the low DOC concentration, to 0.007 d -1 when there was a high DOC treatment concentration, representing a 30 % decline (Fig 4.6). However, without the isopod, there were no significant differences observed in k values as DOC concentrations increased (Fig. 4.7). Nutrient additions followed a similar response as the percent of dry leaf mass remaining. While there were no significant differences in the k values at low DOC concentrations when comparing the ambient treatment to each of the nutrient treatments, there were significant increases at the high DOC concentration (Fig. 4.6). The nutrient additions increased the rate of leaf decomposition from 0.0066? 0.0010 d -1 , under ambient water chemistry, to 0.009? 0.0010 d -1 with elevated P, 0.0105? 0.0010 d -1 with elevated N, and 0.0151? 0.0010 d -1 with elevated N + P, respectively. This shows an increase in k values by 35%, 59%, and 127% respectively. A significant decline in the microbial respiration rate was measured between the low DOC and mid-DOC treatment concentrations within the N + P nutrient treatment when the isopod was present (p<0.02). However, no significant trends in respiration rates for both the isopod and without isopod treatment was likely due to the high degree of 112 variance in measuring this endpoint (Fig. 4.8 and 4.9). Overall, only the three-way interaction of DOC, N, and isopod was significant (p<0.02) (Table 4.7). In the presence of the isopod there was a 110% increase in the production of FPOM when comparing the N + P treatment to the ambient nutrient treatment at the high DOC concentration. No difference in production was measured when either of the two nutrients was added independently at any of the DOC concentrations (Table 4.8, Fig. 4.10). Although there were no significant differences between any of the treatments when the FPOM production was adjusted by the final weight of isopods within each treatment (Table 4.9, Fig. 4.11), a significant increase in the FPOM production was observed when adjusted for the number of isopod days within treatments (Table 4.10, Fig. 4.12). The pattern was the same as when the FPOM production was not adjusted. The N + P treatment increased FPOM production by 80% at the high DOC concentration when compared with the ambient treatment (p<0.0001). The microbial community in the absence of the isopod only increased FPOM production with the addition of P (Fig. 4.13). At the lowest DOC concentration, the P addition treatment increased the microbial community production of FPOM from 0.0093?0.0016 gm/30d to 0.0141? 0.0015 gm/30d, when compared with the ambient treatment (p<0.04), representing a 50% increase in FPOM production. Lastly, the processing efficiency of the isopod was significantly reduced as DOC concentrations increased (p<0001) (Table 4.11). Under ambient water chemistry conditions, the isopod processing efficiency declined 11% from the low DOC to high DOC concentrations. Additionally, processing efficiency for the elevated N + P treatment decreased by 16% as DOC concentration increased (p<0.02) (Fig. 4.15). 113 Discussion: The increase in DOC concentrations had a strong negative effect on the rate of leaf decomposition under ambient nutrient conditions (Fig. 4.6). Nutrient additions only showed a significant increase in the amount of leaf material processed by the isopod under the high DOC treatment. This result suggests that the isopod shifted its feeding activity in response to a change in the food quality. For example, the isopod may obtain a greater food quality from the biofilm layer on the leaf as the microbial biomass increased in response to the high DOC concentration, in comparison to the more recalcitrant carbon bound in the leaf material. Meyer et al. (1987) showed increases in the bacteria biomass when exposed to low molecular weight DOC sources. Thus, the isopods may either shift from shredding to more scraping to obtain food and consume less leaf material due to improved food quality per gram leaf material, or they may passively acquire additional microbes and carbon from the water column. The processing efficiency results do not necessarily support this hypothesized shift from shredding to scraping the leaf surface. While one would expect improved processing efficiency for scrapers as they are not consuming as much carbon rich leaf material as shredders, the results illustrated a decline in processing efficiency (Fig. 4.14). The results do suggest that the isopod may be acquiring excess carbon passively by ingesting DOC. This scenario would elicit the observed response of greater amounts of carbon egested, reducing the processing efficiencies at the high DOC concentration. An alternative reason for the shift in the rate of leaf decomposition could be due to the elevated DOC causing an inhibitory response by the isopod or the microbial 114 community to leaf litter consumption. While no positive or negative microbial response to DOC was measured due to high variability, other research does not support this inhibitory hypothesis, and in fact has demonstrated the opposite for autumn senesced leaves (Koetsier et al. 1997). Numerous studies show that bacteria use DOC both from naturally occurring stream DOC (Meyer et al. 1987, Findlay et al. 1993, and Koetsier et al. 1997) and from other labile carbon sources, such as acetate (Bernhardt and Likens 2002). Researchers suggest that the microbial community shifts to a more labile carbon source in the water column rather than the more recalcitrant leaf carbon (Strauss and Lamberti 2000). Bernhardt and Likens (2002) showed that heterotrophic bacteria will out-compete other autotrophs, thereby providing additional microbial activity to decompose leaf material. Although my study did not see any significant increase or decline in the microbial respiration as DOC concentration increased, the variation was too high to effectively gauge these changes. Previous research has shown that there are bacterial shifts when a labile DOC source is made available (Bernhardt and Likens 2002, Strauss and Lamberti 2000). The interaction of the elevated nutrient and DOC treatments on leaf decomposition illustrates that nutrient limitation is dependent on not only on the relative ratio of N to P, but also the amount of available carbon (Redfield 1958). While N, P, and N + P treatments illustrate limiting resources under high DOC concentrations, there is no nutrient addition effect at low DOC concentrations when the isopods are present. This result is coupled with the observation of significant declines of the percent of dry leaf mass remaining only at the high DOC concentration, suggesting nutrient limitations at high DOC. This is further supported by a greater than additive effect of N and P 115 additions to depress the leaf mass remaining. An associated acceleration in the rate of leaf decomposition, k, was shown as N and P were added together at high DOC. In both cases, the isopod had strong measured responses. N and P are often limiting factors in the rate of detrital processing by both the microbial community (Suberkropp 1998, Grattan and Suberkropp 2001) and the macroinvertebrate contributions (Robinson and Gessner 2001, Niyogi et al. 2003). While my study was unable to demonstrate changes in the microbial activity, several other studies show the importance of N and P to both the fungal and bacterial communities colonizing and conditioning the leaves (Carreiro et al. 2000, Sridhar and Barlocher 2000, Grattan and Suberkropp 2001, Gulis and Suberkropp 2003). Other studies have shown a co-limitation of N and P on decomposition of leaf material by microbes (Grattan and Suberkropp 2001). Other researchers demonstrate microbial assemblage shifts due to DOC from leaf leachate associated with low and high order stream riparian vegetation (Koetsier et al. 1997). Their work demonstrates that microbial community structure may shift from generalist to specialist depending on the DOC quality and riparian leaf inputs. Shifts in the rate of leaf decomposition observed in my study may be due to reductions of DOC dependent microbial populations in low DOC treatments, thereby reducing the overall processing rate. While a number of studies have investigated the effects of DOC on the basal trophic level of the detrital foodweb, little work has demonstrated macroinvertebrate responses to shifts in DOC concentration and their corresponding functional responses. Additional work may help to quantify the effects of nutrient enrichment coupled with elevated DOC on the microbial contributions to detrital processes. 116 The FPOM production increased only when both N and P was added in the treatments containing the isopod (Fig. 4.10). While similar results were found when normalizing the FPOM production by the number of isopod days (Fig. 4.12), no significant increase was measured when normalizing isopod biomass (Fig. 4.11). Adjusting FPOM production by the number of days that isopods were present seems like an improved measure, because the correction made with end weights does not account for contribution to FPOM production by isopods that died prior to the end of the experiment. The processing rate by the isopod declined as DOC increased regardless of nutrient amendments (Fig. 4.14). This suggests that the isopod had to process a greater amount of carbon to acquire the necessary nutrients. It also shows that the elevated DOC masked the benefit increased available nutrients for the isopod. DOC may contribute to reducing the rate of leaf decomposition via providing the microbial community with an alternate carbon source, as well as disrupt the macroinvertebrate shredders from efficiently utilizing the leaf litter for energy. Other conditions associated with Coastal Plain systems may contribute to slower leaf decomposition rates. The low gradient, slow moving stream water reduces the physical breakdown of the leaf material due to hydrologic forces, as well as reduces the water turbulence, thereby reducing the available dissolved oxygen for the biotic community (Davis et al. 2002). O?Connell et al. (2000) showed that shifts in dissolved oxygen can lead to changes from a fungal dominated biofilm on decaying leaves in aerobic conditions, to a bacterial dominated microbial community in anaerobic conditions which in turn lead to differences in DOC utilization. Furthermore, Gulis and Suberkropp (2003) showed that even under aerobic conditions and nutrient additions bacterial 117 dominated biofilm contributes a relatively small amount to leaf decomposition when compared to the fungal biota. Coastal Plain blackwater streams may have slower rates of decomposition than upland streams due to abiotic and biotic factors. For example, Grattan and Suberkropp (2001) found similar results as Suberkropp and Chauvet (1995), illustrating the low species diversity of fungal communities in Coastal Plain streams. This may in turn affect the rate of leaf decomposition. Further studies are needed to develop a mechanism for shifts in detrital processing by the microbial and macroinvertebrate communities. Although my study managed to identify changes in the shredders? ability to assimilate detritus under variable DOC concentrations, as well as nutrient co-limitation as a mechanism for stimulating leaf decomposition in blackwater streams, it is still uncertain whether this is due to community structure shifts in the microbial community, or if the shredders are responding to an additional carbon source. Hall and Meyer (1998) suggests that even shredding macroinvertebrates acquire some of their carbon from exopolymers formed on amorphous detrital particles on the benthic substrate rather than on the decaying leaves. This suggests that perhaps a shredder will select a food source among various substrates. As my laboratory study only had the leaf material present, further in situ studies could provide additional information. This study adds to our understanding of how the detrital foodweb responds to water quality perturbations. The implications of this work coupled with other research suggests that Coastal Plain blackwater streams with elevated DOC concentrations can induce very different rates of leaf decomposition due to an alternate carbon source being present. Naturally high DOC creates a greater limitation of nutrients thereby slowing 118 down the loss of leaf material. Nutrient enrichment, which is common in these agricultural Coastal Plain areas (EPA 1999), can lead to increases in the rate of leaf decomposition. Thus, while previous research has demonstrated the effects of nutrient enrichment and elevated levels of DOC independently, this study suggests that interactions between these two water constituents can lead to different functional responses than expected. DOC and nutrients antagonistically affected the rate of leaf decomposition for an isopod shredder. Future work examining the mechanism behind this shift in the shredders functional response can contribute to our understanding of how Coastal Plain ecosystems respond to eutrophication and other human induced disturbances. 119 Table 4.1. Ion concentrations characterizing the Nassawango Creek water used as the experiments stock solution. Shaded rows indicate the ion concentrations that were kept constant for the serial dilutions to dilute DOC concentrations. Ions Concentrations Concentrations used in experiment mg/L mM mM/L Na 8.856 0.39 0.39 Si 8.732 0.31 Ca 5.774 0.14 0.14 K 5.27 0.13 0.13 Mg 2.652 0.11 0.11 Fe 1.406 0.03 P 0.127 0.004 0.004 Al 0.45 0.02 Zn 0.086 0.00 Mn 0.076 0.00 Cu 0.022 0.00 B 0.02 0.00 Cr 0.005 0.00 Cl 14.07 0.40 0.4 SO 4 -2 13.27 0.41 0.41 NO 3 - 1.2 0.09 0.09 F - 0.02 0.00 Total mM equivalents 2.03 1.67 120 Table 4.2. Amount of chemicals added to maintain background ion concentrations in diluted DOC treatments. Maintaining background ions for DOC dilution treatments Chemicals added Amount (mM) NaCl 0.39 K 2 SO 3 0.14 CaSO 4 0.13 MgSO 4 7H 2 O 0.11 NaNO 3 0.09 NaH 2 PO 4 H 2 O 0.004 Table 4.3. Amount chemicals added for elevated nutrient and salt treatments. Nutrient and salt treatments Chemicals added Amount (mM) NaNO 3 0.9 NaH 2 PO 4 H 2 O 0.04 NaCl 0.94 Table 4.4. Satterthwaite T-test showing no significant difference between salt and ambient treatments. Variable df t-value p-value Leaf loss 22 -0.09 0.93 FPOM Production 22 -0.46 0.65 Respiration rate 16 -0.10 0.92 k-value 22 -0.08 0.93 121 Table 4.5. The analysis of variance table for the percent of dry leaf mass remaining shows the significant main effects and interactions. Effect df (numerator, denominator) F-value p-value DOC (2,116) 2.90 0.0589 N (1,116) 13.42 0.0004 DOC*N (2,116) 5.33 0.0061 P (1,116) 1.53 0.2183 DOC*P (2,116) 3.56 0.0315 N*P (1,116) 1.97 0.1636 DOC*N*P (2,116) 0.34 0.7097 Isopod (1,116) 124.23 <0.0001 DOC*Isopod (2,116) 0.12 0.8878 N*Isopod (1,116) 1.87 0.1736 DOC*N*Isopod (2,116) 2.38 0.0973 P*Isopod (1,116) 0.05 0.8243 DOC*P*Isopod (2,116) 4.34 0.0152 N*P*Isopod (1,116) 0.47 0.4935 DOC*N*P*Isopod (2,116) 0.10 0.9037 Table 4.6. The analysis of variance table for the rate of leaf decomposition (k value) shows the significant main effects and interactions. Effect df (numerator, denominator) F-value p-value DOC (2,116) 1.94 0.1477 N (1,116) 12.18 0.0007 DOC*N (2,116) 5.44 0.0055 P (1,116) 1.05 0.3077 DOC*P (2,116) 3.52 0.0328 N*P (1,116) 2.13 0.1468 DOC*N*P (2,116) 0.43 0.6531 Isopod (1,116) 111.43 <0.0001 DOC*Isopod (2,116) 0.12 0.8842 N*Isopod (1,116) 2.27 0.1347 DOC*N*Isopod (2,116) 2.71 0.0707 P*Isopod (1,116) 0.06 0.8064 DOC*P*Isopod (2,116) 4.57 0.0123 N*P*Isopod (1,116) 0.17 0.6788 DOC*N*P*Isopod (2,116) 0.18 0.8377 122 Table 4.7. The analysis of variance table shows the significant main effects and interactions for the respiration rates of the microbial community on the leaves. Effect df (numerator, denominator) F-value p-value DOC (2,117) 1.83 0.165 N (1,117) 0.09 0.762 DOC*N (2,117) 0.24 0.790 P (1,117) 0.00 0.952 DOC*P (2,117) 1.58 0.209 N*P (1,117) 0.06 0.800 DOC*N*P (2,117) 1.39 0.254 Isopod (1,117) 0.96 0.329 DOC*Isopod (2,117) 0.30 0.743 N*Isopod (1,117) 1.65 0.201 DOC*N*Isopod (2,117) 4.36 0.015 P*Isopod (1,117) 0.65 0.423 DOC*P*Isopod (2,117) 0.60 0.552 N*P*Isopod (1,117) 0.83 0.365 DOC*N*P*Isopod (2,117) 0.92 0.401 Table 4.8. The analysis of variance table shows the significant main effects and interactions for the total cumulative FPOM production summed at the termination of the experiment. Effect df (numerator, denominator) F-value p-value DOC (2,116) 4.28 0.016 N (1,116) 2.65 0.106 DOC*N (2,116) 3.12 0.048 P (1,116) 0.56 0.455 DOC*P (2,116) 2.44 0.091 N*P (1,116) 0.09 0.767 DOC*N*P (2,116) 1.61 0.205 Isopod (1,116) 127.39 <0.0001 DOC*Isopod (2,116) 3.53 0.033 N*Isopod (1,116) 7.49 0.007 DOC*N*Isopod (2,116) 1.45 0.238 P*Isopod (1,116) 0.09 0.770 DOC*P*Isopod (2,116) 7.04 0.001 N*P*Isopod (1,116) 3.63 0.059 DOC*N*P*Isopod (2,116) 0.81 0.447 123 Table 4.9. The analysis of variance table shows the significant main effects and interactions for the adjusted total cumulative FPOM with C. communis present. The FPOM was standardized by the final weight of the isopods at the end of the experiment . Effect df (numerator, denominator) F-value p-value DOC (2,52) 1.93 0.156 N (1,52) 0.64 0.428 DOC*N (2,52) 2.93 0.062 P (1,52) 0.12 0.727 DOC*P (2,52) 0.59 0.559 N*P (1,52) 0.05 0.830 DOC*N*P (2,52) 0.51 0.604 Table 4.10. The analysis of variance table shows the significant main effects and interactions for the adjusted total cumulative FPOM with C. communis present. The FPOM was standardized by the number of days isopods were in contact with the leaves in each experimental unit. Effect df (numerator, denominator) F-value p-value DOC (2,57) 7.15 0.002 N (1,57) 10.08 0.002 DOC*N (2,57) 5.06 0.010 P (1,57) 2.17 0.146 DOC*P (2,57) 2.15 0.126 N*P (1,57) 2.04 0.158 DOC*N*P (2,57) 2.69 0.077 Table 4.11. The analysis of variance table shows the significant main effects and interactions for the processing efficiency of C. communis. Effect df (numerator, denominator) F-value p-value DOC (2,58) 17.74 <0.0001 N (1,58) 0.14 0.707 DOC*N (2,58) 0.21 0.814 P (1,58) 0.52 0.473 DOC*P (2,58) 2.36 0.103 N*P (1,58) 0.91 0.344 DOC*N*P (2,58) 1.00 0.373 124 Figure 4.1. Flask mesocosm design representing one experimental unit. 125 y = 0.1806x + 0.0004 R 2 = 0.8634 0 0.001 0.002 0.003 0.004 0.005 0.006 0 0.005 0.01 0.015 0.02 0.025 0.03 Fresh Weight (gm) Dry Weight (gm). Figure 4.2. Regression of the fresh to dry weight conversion for the isopod to calculate for the starting biomass. 126 DOC concentration (mgL -1 ) 02468101214161820 Ra te o f L e a f D e c o m p o s it io n ( k , d a y -1 ) 0.000 0.004 0.006 0.008 0.010 0.012 0.014 0.016 Isopod + Microbial Microbial Figure 4.3. The rate of leaf decomposition, k, for the microbial and isopod shredder, C. communis, treatments under 4 different water nutrient regimes; ambient, elevated nitrate- N, elevated phosphorus, and elevated nitrate-N and phosphorus concentrations. 127 DOC concentration (mgL -1 ) 0 2 4 6 8 10 12 14 16 18 20 % Dry le a f ma ss re ma i n ing 60 65 70 75 80 85 90 Ambient High N High P High N + P Figure 4.4. Relationship of remaining dry leaf mass (%) across DOC concentrations after 30 d with the isopod present. 128 DOC concentration (mgL -1 ) 0 2 4 6 8 10 12 14 16 18 20 % Dry le a f ma ss re ma i n ing 74 76 78 80 82 84 86 88 90 Ambient High N High P High N + P Figure 4.5. Relationship of remaining dry leaf mass (%) across DOC concentrations after 30 d without the isopod present. 129 DOC concentration (mgL -1 ) 0 2 4 6 8 101214161820 R a t e of l e af decom p os i t i on (k, d -1 ) 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 Ambient High N High P High N + P Figure 4.6. The rate of leaf decomposition, k, with the isopod present. 130 DOC concentration (mgL -1 ) 0 2 4 6 8 101214161820 R a t e of l e af decom p os i t i on (k, d -1 ) 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010 Ambient High N High P High N + P Figure 4.7. Rate of leaf decomposition, k, without the isopod present. 131 DOC concentration (mgL -1 ) 0 2 4 6 8 101214161820 Re sp ir a t io n r a te s (mg O 2 L -1 g m l eaf -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 Ambient High N High P High N + P Figure 4.8. Respiration rates for the microbial community measured from treatment samples where the isopod was present. 132 DOC concentration (mgL -1 ) 0 2 4 6 8 10 12 14 16 18 20 R e spi r ati on rate (m g O 2 L -1 gm l e af -1 ) -0.1 0.0 0.1 0.2 0.3 0.4 Ambient High N High P High N + P Figure 4.9. Respiration rates for the microbial community measured from treatment samples where the isopod was absent. 133 DOC concentration (mgL -1 ) 02468101214161820 F P OM produced (g m/ 30 d) 0.00 0.01 0.02 0.03 0.04 0.05 Ambient High N High P High N + P Figure 4.10. FPOM produced with the isopod present. 134 DOC concentration (mgL -1 ) 02468101214161820 FPOM produced (gm/ gm i s opod/ 30 d ) 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 0.22 Ambient High N High P High N + P Figure 4.11. FPOM produced with isopod present and standardized for the final isopod weight at the end of 30 days. 135 DOC concentration (mgL -1 ) 0 2 4 6 8 101214161820 FPO M pro d u c e d / i s op od da y s (g m/ d a y ) 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 Ambient High N High P High N + P Figure 4.12. FPOM produced with isopod present and standardized by the number of days the isopods were presents. 136 DOC concentration (mgL -1 ) 0 2 4 6 8 10 12 14 16 18 20 F P OM prod uced ( g m/ 3 0 d ) 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 Ambient High N High P High N + P Figure 4.13. FPOM produced without the isopod present. 137 DOC concentration (mgL -1 ) 0 2 4 6 8 10 12 14 16 18 20 Assi mi l a t i on Effi c i e n cy (% food re t a i n ed) 65 70 75 80 85 90 95 Ambient High N High P High N + P Figure 4.14. The processing efficiency of the isopod under different water treatment regimes over the 30 day experiment. 138 References: Allan, J.D. 1995. Stream ecology structure and function of running waters. Chapman and Hall, New York. Atchison, J. 1986. The statistical analysis of compositional data. Chapman and Hall, New York. Arbuckle, K.E. and J.A. Downing. 2001. The influence of watershed land use on lake N:P in a predominantly agricultural landscape. Limnology and Oceanography 46(4): 970-975. Barbour, M.T., J. Gerritsen, B.D. Snyder, and J.B. Stribling. 1999. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates and fish. Second edition. EPA 841-B-99-002. U.S. Environmental Protection Agency, Office of Water, Washington, DC. Barlocher, F. and M. Corkum. 2003. Nutrient enrichment overwhelms diversity effects in leaf decomposition by stream fungi. Oikos 101: 247-252. Battin, T.J., L.A. Kaplan, J.D. Newbold, and S.P. Hendricks. 2003. A mixing model analysis of stream solute dynamics and the contribution of a hyporheic zone to ecosystem function. Freshwater Biology 48: 995-1014. 139 Benfield, E.F. 1996. Leaf breakdown in stream ecosystems. Pages 579-589 in F.R. Hauer and G.A. Lamberti, editors. Methods in stream ecology. Academic Press, New York. Bernhardt, E.S. and G.E. Likens. 2002. Dissolved organic carbon enrichment alters nitrogen dynamics in a forest stream. Ecology 83(6):1689-1700. Boesch, D.F., R.B. Brinsfield, and R.E. Magnien. 2001. Chesapeake Bay Eutrophication, scientific understanding, ecosystem restoration, and challenges for agriculture. Journal of Environmental Quality 30: 303-320. Brady, N.C. and R.R. Weil. 1999. The nature and properties of soils, twelfth edition. Prentice-Hall Inc., New Jersey. Bricker, O.P., W.L. Newell, and N.N. Simon. 2003. Bog iron formation in the Nassawango watershed, Maryland. Open-File Report 03-346. US Geological Survey. Bunn, S.E., P.M. Davies, and T.D. Mosisch. 1999. Ecosystem measures of river health and their response to riparian and catchment degradation. Freshwater Biology 41: 333- 345. Burkholder, J.M. and H.B. Glasgow Jr. 1997. Pfiesteria piscicida and other Pfiesteria- like dinoflagellates: Behavior, impacts and environmental controls. Limnology and Oceanography 42(5): 1052-1075. 140 Cairns, J. Jr. and J.R. Pratt. 1993. A history of biological monitoring using benthic macroinvertebrates. Pages 10-27 in D.M. Rosenberg and V.H. Resh, editors. Freshwater biomonitoring and benthic macroinvertebrates. Chapman and Hall, New York. Cao, Y., D.D. Williams, and N.E. Williams. 1998. How important are rare species in aquatic community ecology and bioassessment? Limnology and Oceanography 43(7): 1403-1409. Cardinale, B.J., M.A. Palmer, S.L. Collins. 2002. Species diversity enhances ecosystem functioning through interspecific facilitation. Nature 415: 426-429. Cardinale, B.J., K. Nelson, and M.A. Palmer. 2002. Species diversity increases ecosystem functioning through interspecific facilitation. Nature 415: 426-429. Cardinale, B.J., M.A. Palmer, C.M. Swan, S. Brooks, and N.L. Poff. 2002. The influence of substrate heterogeneity on biofilm metabolism in a stream ecosystem. Ecology 83(2): 412-422. Carpenter, S.R., N.F. Caraco, D.L. Correll, R.W. Howarth, A.N. Sharpley, and V.H. Smith. 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications 8(3): 559-568. 141 Carreiro, M.M., R.L. Sinsabaugh, D.A. Repert, and D.F. Parkhurst. 2000. Microbial enzyme shifts explain litter decay responses to simulated nitrogen deposition. Ecology 81(9): 2359-2365. Chadwick, M.A. and A.D. Huryn. 2003. Effect of a whole-catchment N addition on stream detritus processing. Journal of the North American Benthological Society 22(2): 194-206. Collier, K.J. and J.M. Quinn. 2003. Land-use influences macroinvertebrate community response following a pulse disturbance. Freshwater Biology 48: 1462-1481. Cooper, S.R. 1995. Chesapeake Bay watershed historical land use: impact on water quality and diatom communities. Ecological Applications 5(3): 703-723. Cooper, S.R. and G.S. Brush. 1991. Long-term history of Chesapeake Bay anoxia. Science 254: 992-996. Cooper, A.B., C.M. Smith, and M.J. Smith. 1995. Effects of riparian set-aside on soil characteristics in an agricultural landscape: Implications for nutrient transport and retention. Agriculture, Ecosystems, and Environment 55: 61-67. Corning Incorporated. 1999. Checkmate II instruction manual. Corning, New York. 142 Covich, A.P., M.A. Palmer, and T.A. Crowl. 1999. The role of benthic invertebrate species in freshwater ecosystems: Zoobenthic species influence energy flows and nutrient cycling. Bioscience 49(2): 119-127. Creed, I.F. and L.E. Band. 1998. Export of nitrogen from catchments within a temperate forest: evidence for a unifying mechanism regulated by variable source area dynamics. Water Resources Research 34(11): 3105-3120. Cronin, T.M. and C.D. Vann. 2003. The sedimentary record of climatic and anthropogenic influences on the Patuxent estuary and Chesapeake Bay ecosystems. Estuaries 26(2A): 196-209. Cuffney, T.F., J.B. Wallace, and G.J. Lugthart. 1990. Experimental evidence quantifying the role of benthic invertebrates in organic matter dynamics of headwater streams. Freshwater Biology 23: 281-299. Cummins, K.W. 1974. Structure and function of stream ecosystems. BioScience 24:631- 641. Cummins, K.W., and M.J. Klug. 1979. Feeding ecology of stream invertebrates. Annual Review of Ecology and Systematics 10:147-72. 143 Cummins, K.W., R.C. Petersen, F.O. Howard, J.C. Wuycheck, and V.I. Holt. 1973. The utilization of leaf litter by stream detritivores. Ecology 54(2): 336-345. Davis, F.W. 1985. Historical changes in submerged macrophyte communities of upper Chesapeake Bay. Ecology 66(3): 981-993. Davis, S., S.W. Golladay, G. Vellidis, and C.M. Pringle. 2003. Macroinvertebrate biomonitoring in intermittent Coastal Plain streams impacted by animal agriculture. Journal of Environmental Quality 32(3): 1036-1043. D?Angelo, D.J. and J.R. Webster. 1991. Phosphorus retention in streams draining pine and hardwood catchments in the southern Appalachian Mountains. Freshwater Biology 26: 335-345. Dangles, O., M.O. Gessner, F. Guerold, and E. Chauvet. 2004. Impacts of stream acidification on litter decomposition: implications for assessing ecosystem functioning. Journal of Applied Ecology 41(2): 365-378. Decagon Devices, Inc. 1989. Sunfleck ceptometer user's manual. Pullman, Washington. Doberstien, C.P., J.R. Karr, and L.L. Conquest. 2000. The effect of fixed-count subsampling on macroinvertebrate biomonitoring in small streams. Freshwater Biology 44: 355-371. 144 Donner, S. 2003. The impact of cropland cover on river nutrient levels in the Mississippi River Basin. Global Ecology and Biogeography 12(4): 341-355. Edwards, R.T., J.L. Meyer, and S.E.G. Findlay. 1990. The relative contribution of benthic and suspended bacteria to system biomass, production, and metabolism in a low- gradient blackwater river. Journal of North American Benthological Society 9: 216-228. Elwood, J.W., J.D. Newbold, A.F. Trimble, and R.W. Stark. 1981. The limiting role of phosphorus in a woodland stream ecosystem: effects of P enrichment of leaf decomposition and primary producers. Ecology 62(1): 146-158. Elmqvist, T., C. Folke, M. Nystrom, G. Peterson, J. Bengtsson, B. Walker, and J. Norberg. 2003. Response diversity, ecosystem change, and resilience. Frontiers in Ecology and the Environment 1(9): 488-494. Findlay, S., D. Strayer, C. Goumbala, and K. Gould. 1993. Metabolism of streamwater dissolved organic carbon in the shallow hyporheic zone. Limnology and Oceanography 38(7): 1493-1499. Fisher, S.G., and G.E. Likens. 1973. Energy flow in Bear Brook, New Hampshire: An integrative approach to stream ecosystem metabolism. Ecological Monographs 43: 421- 439. 145 Forrester, G.E., T.L. Dudley, and N.B. Grimm. Trophic interactions in open systems: effects of predators and nutrients on stream food chains. Limnology and Oceanography 44(5): 1187-1197. Fuss, C.L. and L.A. Smock. 1996. Spatial and temporal variation of microbial respiration rates in a blackwater stream. Freshwater Biology 36: 339-349. Gessner, M.O., and E. Chauvet. 1994. Importance of stream microfungi in controlling breakdown rates of leaf litter. Ecology 75(6): 1807-1817. Gessner, M.O. and E. Chauvet. 2002. A case for using litter breakdown to assess functional stream integrity. Ecological Applications 12(2): 498-510. Gessner, M.O., P. Inchausti, L. Persson, D.G. Raffaelli, and P.S. Giller. 2004. Biodiversity effects on ecosystem functioning: insights from aquatic systems. Oikos 104: 419-422. Giller, P.S., H. Hillebrand, U.G. Berninger, M.O. Gessner, S. Hawkins, P. Inchausti, C. Inglis, H. Leslie, B. Malmqvist, M.T. Monaghan, P.J. Morin, and G. O?Mullan. 2004. Biodiversity effects on ecosystem functioning: Emerging issues and their experimental test in aquatic environments. Oikos 104: 423-436. 146 Gonzalez, J.M. and M.A.S. Graca. 2003. Conversion of leaf litter to secondary production by a shredding caddis-fly. Freshwater Biology 48: 1578-1592. Grattan, R.M. II., and K. Suberkropp. 2001. Effects of nutrient enrichment on yellow poplar leaf decomposition and fungal activity in streams. Journal of North American Benthological Society 20(1): 33-43. Grimm, N.B. 1988. Role of macroinvertebrates in nitrogen dynamics of a desert stream. Ecology 69(6): 1884-1893. Grubaugh, J.W. and J.B. Wallace. 1995. Functional structure and production of the benthic community in a Piedmont river: 1956-1957 and 1991-92. Limnology and Oceanography 40(3): 490-501. Gulis, V. and K. Suberkropp. 2003. Leaf litter decomposition and microbial activity in nutrient-enriched and unaltered reaches of a headwater stream. Freshwater Biology 48: 123-134. Hach Company. 1996. Digital titrator, model 16900, procedures manual. Loveland, Colorado. Hach Company. 1998. DR/890 colorimeter procedures manual. Loveland, Colorado. 147 Hall, R.O. and J.L. Meyer. 1998. The trophic significance of bacteria in a detritus-based stream food web. Ecology 79(6): 1995-2012. Hall, R.O., J.B. Wallace, and S.L. Eggert. 2000. Organic matter flow in stream food webs with reduced detrital resource base. Ecology 81(12): 3445-3463. Harding, J.S., E.F. Benfield, P.V. Bolstad, G.S. Helfman, and E.B.D. Jones III. 1998. Stream biodiversity: The ghost of land use past. Proceedings of the National Academy of Science 95: 14843-14847. Hauer, F.R., N.L. Poff., and P.L. Firth. 1986. Leaf litter decomposition across broad thermal gradients in Southeastern Coastal Plain streams and swamps. Journal of Freshwater Ecology 3(4): 545-552. Hilsenhoff, W.L. 1988. Rapid field assessment of organic pollution with a family-level biotic index. Journal of North American Benthological Society 7(1): 65-68. Howarth, R.W., and S.G. Fisher. 1976. Carbon, nitrogen, and phosphorus dynamics during leaf decay in nutrient-enriched stream microecosystems. Freshwater Biology 6: 221-228. 148 Huryn, A.D., V.M. Butz Huryn, C.J. Arbuckle, and L. Tsomides. 2002. Catchment land- use, macroinvertebrates and detritus processing in headwater streams: taxonomic richness versus function. Freshwater Biology 47: 401-415. Jenkins, C.C. and K. Suberkropp. 1995. The influence of water chemistry on the enzymatic degradation of leaves in streams. Freshwater Biology 33: 245-253. Jones, J.B. and P.J. Mulholland. 2000. Streams and ground waters. Academic Press, New York. Jonsson, M. and B. Malmqvist. 2000. Ecosystem process rate increases with animal species richness: evidence from leaf-eating, aquatic insects. Oikos 89: 519-523. Jonsson, M., B. Malmqvist, and P. Hoffsten. 2001. Leaf litter breakdown rates in boreal streams: Does shredder species richness matter? Freshwater Biology 46: 161-171. Kaplan, L.A. and T.L. Bott. 1983. Microbial heterotrophic utilization of dissolved organic matter in a piedmont stream. Freshwater Biology 13: 363-377. Karr, J. R. 1991. Biological integrity ? a long-neglected aspect of water-resource management. Ecological Applications 1(1): 66-84. 149 Karr, J.R. and E.W. Chu. 1999. Restoring life in running waters: Better biological monitoring. Island Press, Washington, DC. Kaushik, N.K. and H.B.N. Hynes. 1971. The fate of the dead leaves that fall into streams. Archive of Hydrobiologie 68(4): 465-515. Kazyak, P.F. 1997. Maryland biological stream survey: Sampling manual. Department of Natural Resources, Maryland. Kegley, S.E. and J. Andrews. 1998. The chemistry of water. University Science Books, Sausalito, California. King, R.S. and C.J. Richardson. 2003. Integrating bioassessment and ecological risk assessment: an approach to developing numerical water-quality criteria. Environmental Management 31(6): 795-809. Kinzig, A.P., S.W. Pacala, and D. Tilman. 2001. The functional consequences of biodiversity; empirical progress and theoretical extensions. Princeton University Press, Princeton, New Jersey. Kobayashi, S. and T. Kagaya. 2004. Litter patch types determine macroinvertebrate assemblages in pools of a Japanese headwater stream. Journal of North American Benthological Society 23(1): 78-89. 150 Koetsier P., J.V. McArthur, and L.G. Leff. 1997. Spatial and temporal response of stream bacteria to sources of dissolved organic carbon in a blackwater stream system. Freshwater Biology 37: 79-89. Krantz, D.E. and D.S. Powars. 2000. Hydrogeologic setting and potential for denitrification in ground water, coastal plain of southern Maryland. U.S. Geological Survey. Water Resources Investigations Report 00-4051. Lenant, D.R. and J.K. Crawford. 1994. Effects of land use on water quality and aquatic biota of three North Carolina piedmont streams. Hydrobiologia 294:185-199. Leopold, L.B., M.G. Wolman, and J.P. Miller. 1992. Fluvial processes in geomorphology. Dover Publication, Inc. New York. Little, J.L., K.A. Saffran, and L. Fent. 2003. Land use and water quality relationships in the lower little Bow River Watershed, Alberta, Canada. Water Quality Research Journal of Canada 38(4): 563-584. Lugthart, G.J. and J.B. Wallace. 1992. Effects of disturbance on benthic functional structure and production in mountain streams. Journal of North American Benthological Society 11:138-164. 151 Mackay, R.J. 1978. Larval identification and instar association in some species of Hydropsyche and Cheumatopsyche (Trichoptera: Hydropsychidae). Annals of the Entomological Society of America 499-509. Malmqvist, B. and S. Rundle. 2002. Threats to the running water ecosystems of the world. Environmental Conservation 29(2): 134-153. Maloney, D.C. and G.A. Lamberti. 1995. Rapid decomposition of summer-input leaves in a northern Michigan stream. American Midland Naturalist 133: 184-195. Marsh-McBirney. 1990. Model 2000 installation and operations manual. Marsh- McBirney Inc., Frederick, Maryland. Maryland Department of Natural Resources. 1997. Maryland biological stream survey: ecological status of non-tidal streams in six basins sampled in 1995. Maryland Department of Natural Resources. Annapolis, Maryland. Maryland Department of Natural Resources. 1998. Development of a benthic index of biotic integrity for Maryland streams. Report number: CBWP-EA-98-3. Maryland Department of Natural Resources. Annapolis, Maryland. 152 Maryland Department of Natural Resources. 2004. Watershed profiles. Retrieved April 5, 2004, http://mddnr.chesapeakebay.net McCafferty, W.P and A.V. Provonsha. 1983. Aquatic entomology, the fisherman?s and ecologists? illustrated guide to insects and their relatives. Jones and Bartlett Publishers, Boston, Massachusetts. McDougal, R.L., L.G. Goldsborough, and B.J. Hann. 1997. Responses of a prairie wetland to press and pulse additions of inorganic nitrogen and phosphorus: production by planktonic and benthic algae. Hydrobiologia 140(2): 145-167. Merritt, R.W. and K.W. Cummins. 1996. An introduction to the aquatic insects of North America. Third edition. Kendall/Hunt Publishing Company, Dubuque, Iowa. Meyer, J.L. 1986. Dissolved organic carbon dynamics in two subtropical blackwater rivers. Archiv fur Hydrobiologie (108): 119-134. Meyer, J.L., R.T. Edwards, and R. Risley. 1987. Bacterial growth on dissolved organic carbon from a blackwater river. Microbial Ecology (13): 13-29. Meyer, J.L. and G.E. Likens. 1979. Transport and transformation of phosphorus in a forest stream ecosystem. Ecology 60(6): 1255-1269. 153 Meyer, J.L., J.B. Wallace, and S.L. Eggert. 1998. Leaf litter as a source of dissolved organic carbon in streams. Ecosystems (1): 240-249. Miltner, R.J. and E.T. Rankin. 1998. Primary nutrients and the biotic integrity of rivers and streams. Freshwater Biology 40: 145-158. Moglen, G.E. and M.J. Casey. 2000. GISHydro2000 user?s manual. Maryland State Highway Administration. Office of Bridge Development. Mulholland, P.J., J.D. Newbold, J.W. Elwood, and C.L. Hom. 1983. The effect of grazing intensity on phosphorus spiraling in autotrophic streams. Oecologia 58: 358-366. Mulholland, P. J., J.W. Elwood, J.D. Newbold, and L.A. Ferren. 1985. Effect of a leaf- shredding invertebrate on organic matter dynamics and phosphorus spiralling in heterotrophic laboratory streams. Oecologia 66: 199-206. Mulholland, P.J., E.R. Marzolf, J.R. Webster, D.R. Hart, and S.P. Hendricks. 1997. Evidence that hyporheic zones increase heterotrophic metabolism and phosphorus uptake in forest streams. Limnology and Oceanography 42(3): 443-451. Naeem, S. 2002. Ecosystem consequences of biodiversity loss: the evolution of a paradigm. Ecology 83(6): 1537-1552. 154 Naeem, S. 2002. Disentangling the impacts of diversity on ecosystem functioning in combinatorial experiments. Ecology 83 (10): 2925-2935. Naeem, S. and J.P. Wright. 2003. Disentangling biodiversity effects on ecosystem functioning: deriving solutions to a seemingly insurmountable problem. Ecology Letters 6: 567-579. Newbold, J.D., R.V. O?Neill, J.W. Elwood, and W. Van Winkle. 1982. Nutrient spiralling in streams: implications for nutrient limitation and invertebrate activity. The American Naturalist 120: 628-652. Newbold, J.D., J.W. Elwood, M.S. Schulze, R.W. Stark, and J.C. Barmeier. 1983. Continuous ammonium enrichment of a woodland stream: uptake kinetics, leaf decomposition, and nitrification. Freshwater Biology 13: 193-204. Niyogi, D.K. W.M. Lewis Jr., and D.M. McKnight. 2001. Leaf litter breakdown in mountain streams affected by mine drainage: biotic mediation of abiotic controls. Ecological Applications 11(2): 506-516. Niyogi, D.K., K.S. Simon, and C.R. Townsend. 2003. Breakdown of tussock grass in streams along a gradient of agricultural development in New Zealand. Freshwater Biology 48: 1698-1708. 155 O?Connell, M., D.S. Baldwin, A.I. Robertson, and G. Rees. 2000. Release and bioavailability of dissolved organic matter from floodplain litter: influence of origin and oxygen levels. Freshwater Biology 45: 333-342. Palmer, M.A., A.P. Covich, B.J. Finlay, J. Gilbert, K.D. Hyde, R.K. Johnson, T. Kairesalo, S. Lake, C.R. Lovell, R.J. Naiman, C. Ricci, F. Sabater, and D. Strayer. 1997. Biodiversity and ecosystem processes in freshwater sediments. Ambio 26: 571-577. Palmer, M.A., A.P. Covich, S. Lake, P. Biro, J.J. Brooks, J. Cole, C. Dahm, J. Gibert, W. Goedkoop, K. Martens, J. Verhoeven, and W.J. van de Bund. 2000. Linkages between aquatic sediment biota and life above sediments as potential drivers of biodiversity and ecological processes? Bioscience 50: 1062-1075. Paul, M.J. and J.L. Meyer. 1996. Fungal biomass of three leaf litter species during decay in an Appalachian stream. Journal of the North American Benthological Society 15(4): 421-432. Peckarsky, B.L., P.R. Fraissinet, M.A. Penton, and D.J. Conklin Jr. 1990. Freshwater macroinvertebrates of Northeastern North America. Comstock Publishing Associates, Ithaca, New York. 156 Peckarsky, B.L. 1985. Do predaceous stoneflies and siltation affect the structure of stream insect communities colonizing enclosures? Canadian Journal of Zoology 63: 1519-1530. Peckarsky B.L., P.R. Fraissinet, M.A. Penton, and D.J. Conklin, Jr. 1990. Freshwater macroinvertebrates of northeastern North America. Cornell University Press, Ithaca, New York. Petchey, O.L., A.L. Downing, G.G. Mittelbach, L. Persson, C.F. Steiner, P.H. Warren, and G. Woodward. 2004. Species loss and the structure and functioning of multitrophic aquatic systems. Oikos 104: 467-478. Petersen, R.C. and K.W. Cummins. 1974. Leaf processing in a woodland stream. Freshwater Biology 4: 343-368. Poff, N.L. and J.D. Allan. 1995. Functional organization of stream fish assemblages in relation to hydrological variability. Ecology 76(2): 606-627. Qualls, R.G. and C.J. Richardson. 2000. Phosphorus enrichment affects litter decomposition, immobilization, and soil microbial phosphorus in wetland mesocosms. Soil Science Society of America Journal 64: 799-808. 157 Ramirez, A., C.M. Pringle, and L. Molina. 2003. Effects of stream phosphorus levels on microbial respiration. Freshwater Biology 48: 88-97. Redfield, A.C. 1958. The biological control of chemical factors in the environment. Am. Sci. 46: 205-221. Ricciardi, A. and J.B. Rasmussen. 1999. Extinction rates of North American freshwater fauna. Conservation Biology 13(5): 1220-1222. Robinson, C.T., M.O. Gessner, and J.V. Ward. 1998. Leaf breakdown and associated macroinvertebrates in alpine glacial streams. Freshwater Biology 40: 215-228. Robinson, C.T. and M.O. Gessner. 2000. Nutrient addition accelerates leaf breakdown in an alpine springbrook. Oecologia (Berlin). 122: 258-263. Romani, A.M., H. Guasch, I. Munoz, J. Ruana, E. Vilalta, T. Schwartz, F. Emtiazi, and S. Sabater. 2003. Biofilm structure and function and possible implications for riverine DOC dynamics. Microbial Ecology. Published online, DOI 10.1007/s00248-003-2019-2, 23 December: 1-23. Rosenberg, D.M. and V.H. Resh. 1993. Introduction to freshwater biomonitoring and benthic macroinvertebrates. Pages 1-9 in D.M. Rosenberg and V.H. Resh, editors. 158 Freshwater biomonitoring and benthic macroinvertebrates. Chapman and Hall, New York. Roth, N.E., M.T. Southerland, G. Mercurio, and J.H. Volstad. 2001. Maryland biological stream survey 2000-2004, Volume I: Ecological assessment of watersheds sampled in 2000. Maryland Department of Natural Resources. Maryland. Royer, T.V. and G.W. Minshall. 2001. Effects of nutrient enrichment and leaf quality on the breakdown of leaves in a hardwater stream. Freshwater Biology 46: 603-610. SAS Institute Inc. 1999. SAS/STAT ? User?s guide, Release 8.0 Edition. Cary, NC: SAS Institute. SAS Institute Inc. 1999. SAS/STAT ? User?s guide, Release 8.2 Edition. Cary, NC: SAS Institute. Schindler, D.W. 1987. Determining ecosystem responses to anthropogenic stress. Canadian Journal of Fisheries and Aquatic Sciences 44(suppl.1): 6-25. Schindler, D.W. 1990. Experimental perturbations of whole lakes as tests of hypotheses concerning ecosystem structure and function. Oikos 57: 25-41. 159 Shieh, S.H., J.V. Ward, and B.C. Kondratieff. 2003. Longitudinal changes in macroinvertebrate production in a stream affected by urban and agricultural activities. Archiv Fur Hydrobiologie 157(4): 483-503. Singewald, J.R. Jr. 1911. Report on the iron ores of Maryland. Maryland Geological and Economic Survey Special Publication, Volume IX, Part III. Johns Hopkins Press, Baltimore. Smock, L.A., E. Gilinsky, and D.L. Stoneburner. 1985. Macroinvertebrate production in a southeastern united states blackwater stream. Ecology 66(5): 1491-1503. Sponseller, R.A., E.F. Benfield, and H.M. Valett. 2001. Relationships between land use, spatial scale and stream macroinvertebrate communities. Freshwater Biology 46(10): 1409-1424. Sponseller, R.A. and E.F. Benfield. 2001. Influences of land use on leaf breakdown in southern Appalachian headwater streams: a multiple-scale analysis. Journal of the North American Benthological Society 20(1): 44-59. Sridhar, K.R. and F. Barlocher. 2000. Initial colonization, nutrient supply, and fungal activity on leaves decaying in streams. Applied and Environmental Microbiology 66(3): 1114-1119. 160 Steinman, A.D. and G.A.Lamberti. 1996. Biomass and pigments of benthic algae. Pages 295-313 in F.R. Hauer and G.A. Lamberti, editors. Methods in stream ecology. Academic Press, New York. Stewart, J.S., L. Wang, J. Lyons, J.A. Horwatich, and R. Bannerman. 2001. Influences of watershed, riparian-corridor, and reach-scale characteristics on aquatic biota in agricultural watersheds. Journal of the American Water Resources Association 37(6): 1475-1488. Strathkelvin Instruments. 2001. Instruction Manual for the Strathkelvin 928 6-Channel Dissolved Oxygen System. Strathkelvin Instruments. Strauss, E.A. and G.A. Lamberti. 2000. Regulation of nitrification in aquatic sediments by organic carbon. Limnol. Oceanogr. 45(8): 1854-1859. Stribling, J.B., B.K. Jessup, J.S. White, D. Boward, and M. Hurd. 1998. Development of a benthic index of biotic integrity for Maryland streams. Report no. CBWP-EA-98-3. Maryland Department of Natural Resources. Maryland. Suberkropp, K. 1998. Effect of dissolved nutrients on two aquatic hyphomycetes growing on leaf litter. Mycological Research 102(8): 998-1002. 161 Suberkropp, K. 2003. Effects of inorganic nutrients on relative contributions of fungi and bacteria to carbon flow from submerged decomposing leaf litter. Microbial Ecology 45: 11-19. Suberkropp, K. and E. Chauvet. 1995. Regulation of leaf breakdown by fungi in streams: influences of water chemistry. Ecology 76(5): 1433-1445. Suberkropp, K., G.L. Godshalk, and M.J. Klug. 1976. Changes in the chemical composition of leaves during processing in a woodland stream. Ecology 57: 720-727. Suberkropp, K. and M.J. Klug. 1976. Fungi and bacteria associated with leaves during processing in a woodland stream. Ecology 57: 707-719. Swan, C.M. 1997. Heterogeneity in patch quality: microbial-invertebrate dynamics in a coastal plain stream. Masters Thesis. University of Maryland, College Park. Swan, C.M. and M.A. Palmer. 2004. Leaf diversity alters litter breakdown in a Piedmont stream. Journal of the North American Benthological Society 23(1): 15-28. The Nature Conservancy. 1998. Nanjemoy Creek: site conservation plan. The Nature Conservancy Maryland/DC Chapter, Bethesda, Maryland. 162 The Nature Conservancy. 1996. Nassawango watershed plan. The Nature Conservancy Maryland/DC Chapter, Bethesda, Maryland. Tilman, D. 1996. Biodiversity: population versus ecosystem stability. Ecology 77(2): 350-363. Tilman, D. 1999. Global environmental impacts of agricultural expansion: The need for sustainable and efficient practices. Proceeding for the National Academy of Science 96: 5995-6000. Triska, F.J., and J. R. Sedell. 1976. Decomposition of four species of leaf litter in response to nitrate manipulation. Ecology 57: 783-792. Tuchman, N.C. 1993. Relative importance of microbes versus macroinvertebrate shredders in the process of leaf decay in lakes of differing pH. Canadian Journal of Fisheries and Aquatic Sciences 50: 2707-2712. USDA. 1973. Soil survey of Worchester County, Maryland. USDA Soil Conservation Service. USDA. 1974. Soil survey of Charles County, Maryland. USDA Soil Conservation Service. 163 US EPA (U.S. Environmental Protection Agency). 1986. Ambient water quality criteria for dissolved oxygen. EPA 440-5-86-003. U.S. Environmental Protection Agency. Office of Water. Washington, DC. US EPA. 1999. From the mountains to the sea: the state of Maryland?s freshwater streams. EPA 903-R-99-023. US EPA. 2000. Nutrient criteria technical guidance manual: rivers and streams. EPA 822-B-00-002. Vannote, R.L., G.W. Minshall, K.W. Cummins, J.R. Sedell, and C.E. Cushing. 1980. The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences 37: 130-137. Vitousek, P.M. and S. Hobbie. 2000. Heterotrophic nitrogen fixation in decomposing litter: patterns and regulation. Ecology 81(9): 2366-2376. Walker, B.H. 1992. Biological diversity and ecological redundancy. Conservation Biology 6: 18-23. Wallace, J.B., J.W. Grubaugh, and M.R. Whiles. 1996. Biotic indices and stream ecosystem processes: results from an experimental study. Ecological Applications 6(1): 140-151. 164 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. Science 102-104. Wallace, J.B., S.L. Eggert, J.L. Meyer, and J.R. Webster. 1999. Effects of resource limitation on a detrital-based ecosystem. Ecological Monographs 64(4): 409-442. Wallace, J.B. and J.R. Webster. 1996. The role of macroinvertebrates in stream ecosystem function. Annual Review of Entomology 41: 115-139. Wallace, J.B., J.R. Webster, and T.F. Cuffney. 1982. Stream detritus dynamics: regulation by invertebrate consumers. Oecologia 53: 197-200. Webster, J.R. and E.R. Benfield. 1986. Vascular plant breakdown in freshwater ecosystems. Annual Review of Ecology and Systematics 17: 567-594. Webster, J.R., J.B. Wallace, and E.F. Benfield. 1995. Organic processes in streams of the eastern United States. Pages 117-187 in C.E. Cushing, K.W. Cummins, and G.W. Minshall, editors. Ecosystems of the world 22: River and stream ecosystems. Elsevier, New York. Wellnitz, T. and N.L. Poff. 2001. Functional redundancy in heterogeneous environments: implications for conservation. Ecology Letters 4: 177-179. 165 Wiggins, G.B. 1996. Larvae of the North American caddisfly genera (Trichoptera). Second edition. University of Toronto Press, Buffalo, New York. Williams, W.D. 1972. Biota of freshwater ecosystems; Identification manual number 7. Freshwater isopods (Asellidae) of North America. U.S. Environmental Protection Agency. Washington, District of Columbia. Wright, A.B. and L.A. Smock. 2001. Macroinvertebrate community structure and production in a low-gradient stream in an undisturbed watershed. Archiv Fur Hydrobiologie 152(2) 297-313. Wootton, R.J. 1998. Ecology of Teleost fishes, second edition. Kluwer Academic Publishers, Boston, MA. YSI Incorporated, 1999. YSI model 55, handheld dissolved oxygen and temperature system, operations manual. Yellow Springs, Ohio. 166