Correspondence of biological condition models of California streams at statewide and regional scales

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n?=?1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n?≤?75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.     

Carbon Tetrachloride Marine Risk Assessment with Special Reference to the Osparcom Region: North Sea

Accurate estimates of stressor levels in unsampled streams would provide valuable information for managing these resources over large regions. Spatial interpolation of stream characteristics have rarely been attempted, partly because defining separation distances between distinct stream samples is not straightforward. That is, conventional Eulerian definitions of separation distance may not apply to stream networks where information flows along distinct paths. A two-stage model for estimating stressor levels in unsampled streams is presented. Mean characteristics within streams are predicted usign a generalized additive model and residual variation is estimated using a conventional application of spatial statistics. The model is developed and tested using stream survey data collected in the state of Maryland, USA. Model efficiency is compared for three stream variables (nitrate concentration, sulfate concentration, and epifaunal substrate score) known to be associated with biological impairments in streams. Accounting for spatial autocorrelation in the residual variation improved model R2 from 0.71 to 0.81 for nitrate, from 0.29 to 0.63 for sulfate, and from 0.21 to 0.31 for epifaunal substrate score.     

Can Basin Land Use Effects on Physical Characteristics of Streams Be Determined at Broad Geographic Scales?

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed.     

On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin,Indiana, USA

Mechanistic hydrologic and water quality models provide useful alternatives for estimating water quality in unmonitored streams. However, developing these elaborate models for large watersheds can be time-consuming and expensive, in addition to challenges that arise during calibration when there is limited spatial and/or temporal monitored in-stream water quality data. The main objective of this research was to investigate different approaches for developing multivariate analysis models as alternative methods for rapidly assessing relationships between spatio-temporal physical attributes of the watershed and water quality conditions in monitored streams, and then using the developed relationships for estimating water quality conditions in unmonitored streams. The study compares the use of various statistical estimates (mean, geometric mean, trimmed mean, and median) of monitored water quality variables to represent annual and seasonal water quality conditions. The relationship between these estimates and the spatial data is then modeled via linear and non-linear multivariate methods. Overall, the non-linear techniques for classification outperformed the linear techniques with an average cross-validation accuracy of 79.7%. Additionally, the geometric mean based models outperformed models based on other statistical indicators with an average cross-validation accuracy of 80.2%. Dividing the data into annual and quarterly datasets also offered important insights into the behavior of certain water quality variables impacted by seasonal variations. The research provides useful guidance on the use and interpretation of the various statistical estimates and statistical models for multivariate water quality analyses.     

Hydrologic disturbance reduces biological integrity in urban streams

The impact of urbanization on stream ecosystems is linked by land cover changes to the alteration of the natural hydrology and subsequent physical disruption of stream biota and habitat. Seasonal floods are part of the natural disturbance regime of many streams, but urbanization increases their frequency and magnitude. This study evaluated the impact of hydrologic disturbance on fish and aquatic macroinvertebrates in 81 (56 urban/25 reference) Ohio streams. Hydrologic variables included annual and monthly 24-h rainfall maxima and computed annual peak discharge, with computation supported by GIS-based drainage area delineation and land cover characterization. Ohio biological criteria for fish and macroinvertebrates measured during the late spring and summer were negatively impacted by annual peak discharge in urban streams as compared to reference streams. Results support the application of stormwater best management practices as part of stream restoration efforts to mitigate urbanization impacts to fish and macroinvertebrates.     

Integrated Environmental Assessment of the Mid-Atlantic Region with Analytical Network Process

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account the interdependency among variables, the method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic Region of the United States, we were able to point out areas which were in relatively poor condition and/or vulnerable to future deterioration regarding various environmental aspects. The method offered an easy and comprehensive way to combine the strengths of conventional multivariate statistics (PCA) and decision-making science tool (ANP) for integrated environmental assessment.     

CORINE land cover and floristic variation in a Mediterranean wetland

The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.     

Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.     

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.     

Statistically Extracted Fundamental Watershed Variables for Estimating the Loads of Total Nitrogen in Small Streams

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km²) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.     

Nutrient concentrations in Maryland non-tidal streams

Using a spatially extensive database from the Maryland Biological Stream Survey (MBSS), we describe nutrient relationships of small-order, non-tidal streams to Maryland watershed basins, Maryland Tributary Strategy basins, and stream order. In addition, we estimate the number of stream km affected by nutrient loading, using derived nutrient criteria. Based on the MBSS spring water quality sampling, we determined several important factors relating to nutrient levels in non-tidal streams. There are strong linear relationships of nutrients to the percentage of agriculture and forested land present within MBSS sampling strata. Both mean total nitrogen (TN) and mean total phosphorus (TP) levels for watershed basins by stream order show exceedances of derived nutrient reference criteria for Maryland. Four Maryland basins have over 85% of their stream kilometers exceeding the TN criterion, with three basins over 90% of the TP criterion. To protect small stream integrity in Maryland, we recommend an upper stream TN criterion between 1.34 and 1.68 mg/L and an upper stream TP criterion between 0.025 and 0.037 mg/L, based on quantile analyses. Elevated levels of both TN and TP are present in non-tidal streams, with subsequent nutrient inputs into the upper freshwater tidal reaches of the Chesapeake Bay.     

The Stream and Its Altered Valley: Integrating Landscape Ecology into Environmental Assessments of Agro-Ecosystems

Little is known about the importance of landscape and land cover to the implementation and performance of agricultural conservation projects designed to improve stream quality. In our study, we addressed the potential importance of landscape and land cover to conservation projects by measuring variation across 191 μ-basins (100–2400 ha) and integrating the observed variation into a study design aimed at determining the effectiveness of conservation projects. Our findings indicate that there are strong gradients across which landscape and land cover attributes vary. Land cover varied along a gradient of agricultural intensity, basin morphometry across gradients of stream closure and basin size, basin substrate was described by variation in drumlin formation, glacial landform type, and soil drainage, while agricultural conservation projects varied according to the level of project implementation. Correlation of these gradients found several associations between landscape and land cover, indicating that agricultural intensity was being constrained predominantly by drumlin formation and glacial landform type. Landscape and land cover did not appear to be determining factors in the implementation of conservation projects by land owners. Based on these findings we chose 32 μ-basins which represented the variability along each of the defined gradients for further study. We conclude that landscape scale variables demonstrate important variation and covariation that can and should be integrated into study designs for the assessment of streams and human activities affecting streams.     

Relations of Habitat-Specific Algal Assemblages to Land Use and Water Chemistry in the Willamette Basin, Oregon

Benthic algal assemblages, water chemistry, and habitat were characterized at 25 stream sites in the Willamette Basin, Oregon, during low flow in 1994. Seventy-three algal samples yielded 420 taxa — mostly diatoms, blue-green algae, and green algae. Algal assemblages from depositional samples were strongly dominated by diatoms (76% mean relative abundance), whereas erosional samples were dominated by blue-green algae (68% mean relative abundance).Canonical correspondence analysis (CCA) of semiquantitative and qualitative (presence/absence) data sets identified four environmental variables (maximum specific conductance, % open canopy, pH, and drainage area) that were significant in describing patterns of algal taxa among sites. Based on CCA, four groups of sites were identified: streams in forested basins that supported oligotrophic taxa, such as Diatoma mesodon;small streams in agricultural and urban basins that contained a variety of eutrophic and nitrogen-heterotrophic algal taxa; larger rivers draining areas of mixed land use that supported planktonic, eutrophic, and nitrogen-heterotrophic algal taxa; and streams with severely degraded or absent riparian vegetation (> 75% open canopy) that were dominated by other planktonic, eutrophic, and nitrogen-heterotrophic algal taxa. Patterns in water chemistry were consistent with the algal autecological interpretations and clearly demonstrated relationships between land use, water quality, and algal distribution patterns.     

Relationships of sedimentation and benthic macroinvertebrate assemblages in headwater streams using systematic longitudinal sampling at the reach scale

Investigating relationships of benthic invertebrates and sedimentation is challenging because fine sediments act as both natural habitat and potential pollutant at excessive levels. Determining benthic invertebrate sensitivity to sedimentation in forested headwater streams comprised of extreme spatial heterogeneity is even more challenging, especially when associated with a background of historical and intense watershed disturbances that contributed unknown amounts of fine sediments to stream channels. This scenario exists in the Chattahoochee National Forest where such historical timber harvests and contemporary land-uses associated with recreation have potentially affected the biological integrity of headwater streams. In this study, we investigated relationships of sedimentation and the macroinvertebrate assemblages among 14 headwater streams in the forest by assigning 30, 100-m reaches to low, medium, or high sedimentation categories. Only one of 17 assemblage metrics (percent clingers) varied significantly across these categories. This finding has important implications for biological assessments by showing streams impaired physically by sedimentation may not be impaired biologically, at least using traditional approaches. A subsequent multivariate cluster analysis and indicator species analysis were used to further investigate biological patterns independent of sedimentation categories. Evaluating the distribution of sedimentation categories among biological reach clusters showed both within-stream variability in reach-scale sedimentation and sedimentation categories generally variable within clusters, reflecting the overall physical heterogeneity of these headwater environments. Furthermore, relationships of individual sedimentation variables and metrics across the biological cluster groups were weak, suggesting these measures of sedimentation are poor predictors of macroinvertebrate assemblage structure when using a systematic longitudinal sampling design. Further investigations of invertebrate sensitivity to sedimentation may benefit from assessments of sedimentation impacts at different spatial scales, determining compromised physical habitat integrity of specific taxa and developing alternative streambed measures for quantifying sedimentation.     

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.     

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.     

Land cover classification with an expert system approach using Landsat ETM imagery: a case study of Trabzon

The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover classification in a part of Trabzon city. Expert systems allow for the integration of remote-sensed data with other sources of geo-referenced information such as land use data, spatial texture, and digital elevation model to obtain greater classification accuracy. Logical decision rules are used with the various datasets to assign class values for each pixel. Expert system is very suitable for the work of image interpretation as a powerful means of information integration. Landsat ETM data acquired in the year 2000 were initially classified into seven classes for land cover using a maximum likelihood decision rule. An expert system was constructed to perform post-classification sorting of the initial land cover classification using additional spatial datasets such as land use data. The overall accuracy of expert classification was 95.80%. Individual class accuracy ranged from 75% to 100% for each class.     

Development of a reference coastal wetland set in Southern New England (USA)

Various measures of plants, soils, and invertebrates were described for a reference set of tidal coastal wetlands in Southern New England in order to provide a framework for assessing the condition of other similar wetlands in the region. The condition of the ten coastal wetlands with similar hydrology and geomorphology were ranked from least altered to highly altered using a combination of statistical methods and best professional judgment. Variables of plants, soils, and invertebrates were examined separately using principal component analysis to reduce the multidimensional variables to principal component scores. The first principal component scores of each set of variables (i.e., plants, soil, invertebrates) significantly (p?<?0.05) correlated with both residential land use and watershed nitrogen (N) loads. Using cumulative frequency diagrams, the first principal component scores of each plant, soil, and invertebrate data set were plotted, and natural breaks and best professional judgment were used to rank the first principal component scores among the sites. We weighted all three ranked components equally and calculated an overall salt marsh condition index by summing the three ranks and then transforming the index to a 0–1 scale. The overall salt marsh condition index for the reference coastal wetland set significantly correlated with the residential land use (R?=???0.87, p?=?0.001) and watershed N loads (R?=???0.86, p?=?0.001). Overall, condition deteriorated in salt marshes and their associated discharge streams when subjected to increasing watershed residential land use and N loads.     

Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.     

The response of hydrophobic organics and potential toxicity in streams to urbanization of watersheds in six metropolitan areas of the United States

Semipermeable membrane devices (SPMDs) were deployed in streams along a gradient of urban land-use intensity in and around six metropolitan areas: Atlanta, Georgia; Raleigh-Durham, North Carolina; and Denver-Fort Collins, Colorado, in 2003; and Dallas-Fort Worth, Texas; Milwaukee-Green Bay, Wisconsin; and Portland, Oregon, in 2004 to examine relations between percent urban land cover in watersheds and the occurrence, concentrations, and potential toxicity of hydrophobic compounds. Of the 142 endpoints measured in SPMD dialysates, 30 were significantly (alpha = 0.05) related to the percent of urban land cover in the watersheds in at least one metropolitan area. These 30 endpoints included the aggregated measures of the total number of compounds detected and relative toxicity (Microtox(R) and P450RGS assays), in addition to the concentrations of 27 individual hydrophobic compounds. The number of compounds detected, P450RGS assay values, and the concentrations of pyrogenic polycyclic aromatic hydrocarbons (PAHs) were significantly related to percent urban land cover in all six metropolitan areas. Pentachloroanisole, the most frequently detected compound, was significantly related to urban land cover in all metropolitan areas except Dallas-Fort Worth. Petrogenic PAHs and dibenzofurans were positively related to percent urban land cover in Atlanta, Raleigh-Durham, Denver, and Milwaukee-Green Bay. Results for other endpoints were much more variable. The number of endpoints significantly related to urban land cover ranged from 6 in Portland to 21 Raleigh-Durham. Based on differences in the number and suite of endpoints related to urban intensity, these results provide evidence of differences in factors governing source strength, transport, and/or fate of hydrophobic compounds in the six metropolitan areas studied. The most consistent and significant results were that bioavailable, aryl hydrocarbon receptor agonists increase in streams as basins become urbanized. Potential toxicity mediated by this metabolic pathway is indicated as an important factor in the response of aquatic biota to urbanization.