Estimating reference nutrient criteria for Maryland ecoregions

Management of stream nutrients is becoming increasingly important in order to protect both water quality and aquatic resources throughout the USA. Using an extensive water quality database from the long-term Maryland Biological Stream Survey (MBSS), we describe nutrient relationships to landscape characteristics as total nitrogen (TN) and total phosphorus (TP) of small-order, non-tidal streams in USEPA L2 and L3 ecoregions in Maryland and by MBSS stream order at the L2 and L3 ecoregion levels. To protect stream ecosystem integrity, preliminary reference nutrient estimates (TN and TP) as percentiles (25th of all stream reaches and 75th of stream reference reaches) for the six Maryland L3 ecoregions are: Blue Ridge TN 0.29 and 0.64 mg/L, TP 0.0065 and 0.0090 mg/L; Central Appalachians TN 0.40 and 1.0 mg/L, TP 0.0060 and 0.015 mg/L; Middle Atlantic Coastal Plains TN 0.93 and 2.5 mg/L, TP 0.094 and 0.065 mg/L; Northern Piedmont TN 1.6 and 1.8 mg/L, TP 0.010 and 0.015 mg/L; Ridge and Valley TN 0.40 and 0.98 mg/L, TP 0.0063 and 0.012 mg/L; and Southeastern Plains TN 0.33 and 0.82 mg/L, TP 0.016 and 0.042 mg/L. High levels of both TN and TP are present in many streams found in non-tidal watersheds associated with all Maryland ecoregions, but are especially elevated in the Northern Piedmont and Middle Atlantic Coastal Plain ecoregions, with the latter second-order streams (average TN?>?2.9 mg/L) significantly higher than all other ecoregion–order combinations. Across all six ecoregions, mean nutrient loading for both TN and TP was generally equivalent in first-order streams to nutrient concentrations seen in both second- and third-order streams, indicating a definite need to increase efforts in preventing nutrients from entering first-order streams. Small-order stream nutrient levels are the drivers for subsequent TN and TP inputs into the upper freshwater tidal reaches of the Chesapeake Bay, resulting in a potential risk for altered estuarine ecosystems.     

Maryland Biological Stream Survey: A State Agency Program to Assess the Impact of Anthropogenic Stresses on Stream Habitat Quality and Biota

The Maryland Department of Natural Resources is conducting the Maryland Biological Stream Survey, a probability-based sampling program, stratified by river basin and stream order, to assess water quality, physical habitat, and biological conditions in first through third order, non-tidal streams. These streams comprise about 90% of all lotic water miles in the state. About 300 sites (75 m segments) are being sampled during spring and summer each year. All basins in the state will be sampled over a three-year period, 1995-97. MBSS developments in 1995-96 included (1) an electrofishing capture efficiency correction method to improve the accuracy of fish population estimates, (2) two indices of biotic integrity (IBI) for fish assemblages to identify degraded streams, and (3) land use information for catchments upstream of sampled sites to investigate associations between stream condition and anthropogenic stresses. Based on fish IBI scores at 270 stream sites in six basins sampled in 1995, 11% of non-tidal stream miles in Maryland were classified as very poor, 15% as poor, 24% as fair, and 27% as good. IBIs have not yet been developed for stream sites with catchment areas less than 120 hectares (23% of non-tidal stream miles). IBI scores declined with stream acid neutralizing capacity (ANC) and pH, an association that was also evident for fish species richness, biomass, and density. Low IBI scores were associated with several measures of degraded stream habitat, but not with local riparian buffer width. There was a significant negative association between IBI scores and urban land use upstream of sampled sites in the only extensively urbanized basin assessed in 1995. Future plans for the MBSS include (1) identifying all benthic macroinvertebrate samples to genus, (2) developing benthic macroinvertebrate, herpetofaunal, and physical habitat indicators, and (3) enhancing the analysis of stream condition-stressor associations by refining landscape metrics and using multi-variate techniques.     

Maryland Biological Stream Survey: Development of a Fish Index of Biotic Integrity

As a step towards determining the extent of degradation in non-tidal streams, a multi-metric Index of Biotic Integrity (IBI) based on fish assemblages was developed for the Maryland Biological Stream Survey (MBSS). The MBSS is a probability-based statewide sampling program designed to assess the status of biological resources and to evaluate the effects of anthropogenic activities. We used data from 419 MBSS sites sampled in 1994-95 to develop the IBI. Two distinct geographic strata, corresponding with ecoregional and physiographic boundaries, were identified via cluster analysis and multivariate analysis of variance (MANOVA) as supporting distinctly different species groups. Reference conditions were based on minimally degraded sites. We quantitatively evaluated the ability of various attributes of the fish assemblage (candidate metrics) to discriminate between these reference sites and sites known to be degraded, using statistical tests and classification efficiency. Provisional formulations of the IBI were selected for each region based on high classification efficiency and broad representation of fish assemblage attributes. Fish IBI scores for 1995 MBSS sites spanned a wide range of biological conditions, from good to very poor. Over all six basins sampled in 1995, half of the stream miles fell into the range of good to fair. Roughly 25% of stream miles showed some degradation. The IBI will be used in conjunction with physical and chemical data to answer critical questions about the health of Maryland streams and the relative impacts of human-induced stresses on the state's aquatic systems.     

Relations between macroinvertebrates, nutrients, and water quality criteria in wadeable streams of Maryland, USA

In an ongoing effort to propose biologically protective nutrient criteria, we examined how total nitrogen (TN) and its forms were associated with macroinvertebrate communities in wadeable streams of Maryland. Taxonomic and functional metrics of an index of biological integrity (IBI) were significantly associated with multiple nutrient measures; however, the highest correlations with nutrients were for ammonia-N and nitrite-N and among macroinvertebrate measures were for Beck’s Biotic Index and its metrics. Since IBI metrics showed comparatively less association, we evaluated how macroinvertebrate taxa related to proposed nutrient criteria previously derived for those same streams instead of developing nutrient–biology thresholds. We identified one tolerant and three intolerant taxa whose occurrence appeared related to a TN benchmark. Individually, these taxa poorly indicated whether streams exceeded the benchmark, but combining taxa notably improved classification rates. We then extracted major physiochemical gradients using principal components analysis to develop models that assessed their influence on nutrient indicator taxa. The response of intolerant taxa was predominantly influenced by a nutrient-forest cover gradient. In contrast, habitat quality had a greater effect on tolerant taxa. When taxa were aggregated into a nutrient sensitive index, the response was primarily influenced by the nutrient-forest gradient. Multiple lines of evidence highlight the effects of excessive nutrients in streams on macroinvertebrate communities and taxa in Maryland, whose loss may not be reflected in metrics that form the basis of biological criteria. Refinement of indicator taxa and a nutrient-sensitive index is warranted before thresholds in aquatic life to water quality are quantified.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

Response of algal metrics to nutrients and physical factors and identification of nutrient thresholds in agricultural streams

Many streams within the United States are impaired due to nutrient enrichment, particularly in agricultural settings. The present study examines the response of benthic algal communities in agricultural and minimally disturbed sites from across the western United States to a suite of environmental factors, including nutrients, collected at multiple scales. The first objective was to identify the relative importance of nutrients, habitat and watershed features, and macroinvertebrate trophic structure to explain algal metrics derived from deposition and erosion habitats. The second objective was to determine if thresholds in total nitrogen (TN) and total phosphorus (TP) related to algal metrics could be identified and how these thresholds varied across metrics and habitats. Nutrient concentrations within the agricultural areas were elevated and greater than published threshold values. All algal metrics examined responded to nutrients as hypothesized. Although nutrients typically were the most important variables in explaining the variation in each of the algal metrics, environmental factors operating at multiple scales also were important. Calculated thresholds for TN or TP based on the algal metrics generated from samples collected from erosion and deposition habitats were not significantly different. Little variability in threshold values for each metric for TN and TP was observed. The consistency of the threshold values measured across multiple metrics and habitats suggest that the thresholds identified in this study are ecologically relevant. Additional work to characterize the relationship between algal metrics, physical and chemical features, and nuisance algal growth would be of benefit to the development of nutrient thresholds and criteria.     

A Stream Network Model for Integrated Watershed Modeling

We describe a flexible, computationally efficient stream network model, which forms the core of a simulation framework that spatially integrates the contributions from point and nonpoint sources in a watershed. The model uses the map and stream topology information in the US Environmental Protection Agency’s Reach File 3 to generate a spatially explicit network of stream reaches. Water and materials are routed through the stream network to the watershed outlet, and the routing process accounts for transit times and for possible nutrient losses in streams. This model can be applied wherever Reach File maps or maps from the newer National Hydrography Dataset are available, and it can be combined with models of other watershed processes to create a complete watershed simulation system. We present an application of the stream network model to two watersheds of different sizes in the Patuxent River watershed of Maryland, USA. Simulated predictions of streamflow and nitrate concentrations are either very good or good according to standards developed for evaluating the widely used Hydrologic Simulation Program – Fortran (HSPF) watershed model.     

Application of the probability-based Maryland Biological Stream Survey to the state’s assessment of water quality standards

The Clean Water Act presents a daunting task for states by requiring them to assess and restore all their waters. Traditional monitoring has led to two beliefs: (1) ad hoc sampling (i.e., non-random) is adequate if enough sites are sampled and (2) more intensive sampling (e.g., collecting more organisms) at each site is always better. We analyzed the 1,500 Maryland Biological Stream Survey (MBSS) random sites sampled in 2000–2004 to describe the variability of Index of Biotic Integrity (IBI) scores at the site, reach, and watershed scales. Average variability for fish and benthic IBI scores increased with increasing spatial scale, demonstrating that single site IBI scores are not representative at watershed scales and therefore at best 25% of a state’s stream length can be representatively sampled with non-random designs. We evaluated the effects on total taxa captured and IBI precision of sampling for twice as many benthic macroinvertebrates at 73 MBSS sites with replicate samples. When sampling costs were fixed, the precision of the IBI decreased as the number of sites had to be reduced by 15%. Only 1% more taxa were found overall when the 73 sites where combined. We concluded that (1) comprehensive assessment of a state’s waters should be done using probability-based sampling that allows the condition across all reaches to be inferred statistically and (2) additional site sampling effort should not be incorporated into state biomonitoring when it will reduce the number of sites sampled to the point where overall assessment precision is lower.     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.     

Stream water nutrient enrichment in a mixed-use watershed

Eutrophic conditions, in both saline and freshwater systems, result from nutrient export from upstream watersheds. The objective of this study was to quantify the surface runoff losses of nitrate-nitrogen (NO?-N), total nitrogen (TN), dissolved reactive phosphorus (DRP), and total phosphorus (TP) resulting from prevailing practices on a managed golf course. Inflow and outflow discharge waters on a sub-area of Northland Country Club (NCC) located in Duluth, Minnesota were measured for both quantity and quality from April through November from 2003 to 2008. Nutrient losses were detectable throughout the year, had a seasonal trend, and routinely exceeded recommended levels to minimize eutrophication. The median outflow TN concentration (1.04 mg L?1) was significantly greater (p < 0.05) than the median inflow (0.81 mg L?1) concentration. Similarly, the median outflow TP concentration (0.03 mg L?1) was significantly greater (p < 0.05) than the median inflow concentration (0.02 mg L?1). Maximum recorded concentrations during the study period were 1.9 mg L?1 NO?-N, 3.93 mg L?1 TN, 0.34 mg L?1 DRP, and 1.11 mg L?1 TP. Mean annual export coefficients at NCC were 0.7 kg ha?1 NO?-N (1.7% of applied), 4.43 kg ha?1 TN (10.7% of applied), 0.14 kg ha?1 DRP (2.6% of applied), and 0.25 kg ha?1 TP (4.6% of applied). The findings of this study highlight the need for adopting conservation practices aimed at reducing offsite nutrient transport.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

Development of a Provisional Physical Habitat Index for Maryland Freshwater Streams

Provisional physical habitat indices were developed and validatedfor Maryland Coastal and Non-Coastal Plain streams using variables (commonly called metrics) that best discriminated reference and degraded conditions based on biological, chemicaland land use data from the 1994–97 Maryland Biological Stream Survey (MBSS). These habitat indices contained variables that described structural, hydrological, vegetative and aesthetic components of stream habitat. Variables with the best discriminatory power for Coastal Plain streams were: instream habitat, velocity/depth diversity, pool/glide/eddy quality, embeddedness, maximum depth and aesthetic rating. Physical habitat variables with the best discriminatory power for Non-Coastal Plain sites were: instream habitat, velocity/depth diversity, riffle/run quality, embeddedness, number of rootwads and aesthetic rating. The overall classification efficiency forindex validation was 76% for both indices pooled over both strata. Scaled physical habitat index values (0–100) for bothstrata identified nearly twice as many good sites (31%) as very poor sites (16%). More than half the Maryland sites werein the poor to fair range (53%).     

A Spatially Explicit Model for Estimating Annual Average Loads of Nonpoint Source Nutrient at the Watershed Scale

The overloaded nonpoint source (NPS) nutrients in upper streams always result in the nutrient enrichment at lakes and estuaries downstream. As NPS pollution has become a serious environmental concern in watershed management, the information about nutrient output distribution across a watershed has been critical in the designing of regional development policies. But existing watershed evaluation models often encounter difficulties in application because of their complicated structures and strict requirements for the input data. In this paper, a spatially explicit and process-based model, Integrated Grid’s Exporting and Delivery model, was introduced to estimate annual in-stream nutrient levels. Each grid cell in this model was regarded as having potentials of both exporting new nutrients and trapping nutrients passing by. The combined nutrient dynamics of a grid is mainly determined by the grid’s features in land use/land cover, soil drainage, and geomorphology. This simple-concept model was tested at some basins in north Georgia in the USA. Stations in one basin were used to calibrate the model. Then an external validation was employed by applying the calibrated model to stations in the other neighbor basins. Model evaluation statistics implied the model’s validity and good performance in estimating the annual NPS nutrients’ fluxes at the watershed scale. This study also provides a promising prospect that in-stream annual nutrient loads can be accurately estimated from a few public available datasets.     

丹江口水库流域氮素时空分布特征

为全面了解丹江口水库流域氮素污染状况,对库区26个点位及10条主要入库河流入库口处的表层水样进行了丰水期、平水期、枯水期采样与监测,探讨了氮素时空分布特征。入库口总氮检出范围为1.31~10.96 mg/L,其中泗河和神定河入库口总氮最高。总氮为库区水质主要限制因子,年均总氮质量浓度为1.13~2.71 mg/L;汉江库区整体上总氮污染水平略高于丹江库区,且与丹江库区相比,汉江库区受点源排放的影响较大。10条入库河流总氮的总年均输入量为63 347.31 t/a,其中汉江的总氮输入量最大;入库河流总氮控制的关键在于溶解性有机氮和硝酸盐氮的控制。     

Spatial and temporal patterns of dissolved nitrogen and phosphorus in surface waters of a multi-land use basin

Research on relationships between dissolved nutrients and land-use at the watershed scale is a high priority for protecting surface water quality. We measured dissolved nitrogen (DN) and ortho-phosphorus (P) along 130 km of the Calapooia River (Oregon, USA) and 44 of its sub-basins for 3 years to test for associations with land-use. Nutrient concentrations were analyzed for spatial and seasonal patterns and for relationships with land-use and stream discharge. Ortho-P and DN were higher in lower-elevation sub-basins dominated by poorly drained soils and agricultural production compared with higher-elevation sub-basins dominated by well-drained soils and forests. Eight lower basins had at least one sample period with nitrate-N?>?10 mg L^?1. The Calapooia River had lower concentrations of dissolved nutrients compared with lower sub-basins, often by an order of magnitude. Dissolved organic N represented a greater proportion of DN in the upper forested sub-basins. Seasonal nutrient concentrations had strong positive correlations to the percent of a sub-basin that was managed for agriculture in all seasons (p?values?≤?0.019) except summer. Results suggest that agricultural lands are contributing to stream nutrient concentrations. However, poorly drained soils in agricultural areas may also contribute to the strong relationships that we found between dissolved nutrients and agriculture.     

Using Geographically Isolated Loading Scenarios to Analyze Nitrogen and Phosphorus Exchanges and Explore Tailored Nutrient Control Strategies for Efficient Management

A set of geographically isolated differential nitrogen (N) and phosphorus (P) load model scenarios from major Chesapeake basins provides information on the relative impact of nutrient loads on primary production and dissolved oxygen in the Chesapeake Bay. Model results show the relationships of deep water dissolved oxygen with nutrient limitation-related algal blooms, organic carbon loads from the watershed, estuarine circulation, nutrient cycling, and nutrient diagenesis. The combined effect of changes in load from multiple basins is additive for changes in both chlorophyll-a and deep water dissolved oxygen concentrations. Management of both N and P are required in the Chesapeake watershed and tidal waters to achieve water quality standards, but overall efficiencies could be gained with strategies that place greater emphasis on P control in the upper Bay and greater emphasis on N control in the lower Bay. The areas of the Bay with the highest degree of dissolved oxygen degradation that generally drive management decisions are mostly P-limited and are significantly influenced by the load from the upper Bay’s basins. Reducing P from the upper Bay’s basins will intensify P limitation and would allow an increase in N of about six times the weight of P reduction. Combining the relative nutrient reduction effectiveness with the relative control cost information could improve management efficiency and provide benefits at a lower cost. This article describes initial steps that can be taken to examine the benefits from N-P exchanges.     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay Watershed

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.     

The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams

Watershed land use in suburban areas can affect stream biota through degradation of instream habitat, water quality, and riparian vegetation. By monitoring stream biotic communities in various geographic regions, we can better understand and conserve our watershed ecosystems. The objective of this study was to examine the relationship between watershed land use and the integrity of benthic invertebrate communities in eight streams that were assessed over a 3-year period (2001-2003). Sites were selected from coastal Rhode Island watersheds along a residential land-use gradient (4-59%). Using the rapid bioassessment protocol, we collected biological, physicochemical, habitat, and nutrient data from wadeable stream reaches and compared metrics of structure and integrity. Principal component analyses showed significant negative correlation of indicators for stream physicochemical, habitat, and instream biodiversity with increasing residential land use (RLU) in the watershed. The physicochemical variables that were most responsive to percent RLU were conductivity, instream habitat, nitrate, and dissolved inorganic nitrogen (DIN). The positive correlation of DIN with percent RLU indicated an anthropogenic source of pollution affecting the streams. The biotic composition of the streams shifted from sensitive to insensitive taxa as percent RLU increased; the most responsive biological variables were percent Ephemeroptera, percent Scrapers, percent Insects, and the Hilsenhoff biotic index. These data show the importance of land management and conservation at the watershed scale to sustaining the biotic integrity of coastal stream ecosystems.     

Watershed-Based Survey Designs

Watershed-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification of impaired water bodies or watersheds to meet Section 303(d), and development of empirical relationships between causes or sources of impairment and biological responses. Creation of GIS databases for hydrography, hydrologically corrected digital elevation models, and hydrologic derivatives such as watershed boundaries and upstream–downstream topology of subcatchments would provide a consistent seamless nationwide framework for these designs. The elements of a watershed-based sample framework can be represented either as a continuous infinite set defined by points along a linear stream network, or as a discrete set of watershed polygons. Watershed-based designs can be developed with existing probabilistic survey methods, including the use of unequal probability weighting, stratification, and two-stage frames for sampling. Case studies for monitoring of Atlantic Coastal Plain streams, West Virginia wadeable streams, and coastal Oregon streams illustrate three different approaches for selecting sites for watershed-based survey designs.