Biological Condition Of Streams Research Articles

Assessing the added value of antecedent streamflow alteration information in modeling stream biological condition

In stream systems, disentangling relationships between biology and flow and subsequent prediction of these relationships to unsampled streams is a common objective of large-scale ecological modeling. Often, streamflow metrics are derived from aggregating continuous streamflow records available at a subset of stream gages into long-term flow regime descriptors. Despite demonstrated value, shortcomings of these long-term approaches include spatial restriction to locations with long-term continuous flow records (commonly, biased toward larger systems) and omission of potentially ecologically important short-term (i.e., ≤1 year) antecedent streamflow information. We used long-term flow regime and short-term antecedent streamflow alteration information to evaluate relative performance in modeling stream fish biological condition. We compared results to understand whether short-term antecedent streamflow information improved models of fish biological condition. Results indicated that models incorporating short-term antecedent data performed better than those relying solely on long-term flow regime data (kappa statistic = 0.29 and 0.23, respectively) and improved prediction accuracy among stream sizes and in six of nine ecoregions. Additionally, models relying solely on short-term streamflow information performed similarly to those with only long-term streamflow information (kappa = 0.23). Incorporating short-term antecedent streamflow metrics may provide added ecological information not fully captured by long-term flow regime summaries in macroscale modeling efforts or perform similarly to long-term streamflow data when long-term data are not available.

A multiscale landscape approach for prioritizing river and stream protection and restoration actions.

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

Developing Ecological Flow Needs in a Highly Altered Region: Application of California Environmental Flows Framework in Southern California, USA

Flow alteration is a pervasive issue across highly urbanized watersheds that can impact the physical and biological condition of streams. In highly altered systems, flows may support novel ecosystems that may not have been found under natural conditions and reference-based environmental flow targets may not be relevant. Moreover, stream impairments such as altered channel morphology may make reference-based environmental flow targets less effective in supporting ecosystem functions. Here, we develop an approach for determining ecological flow needs in highly modified systems to support existing ecological uses utilizing the California Environmental Flows Framework (CEFF). CEFF was established to provide guidance on developing environmental flow recommendations across California’s diverse physical landscape and broad array of management contexts. This paper illustrates the application of CEFF in informing ecologically-based flow restoration in a highly altered region of South Orange County, California. The steps of CEFF were implemented including a stakeholder process to establish goals and provide input throughout the project; identifying the natural ranges of functional flow metrics, or distinct components of the natural flow regime that support ecosystem functions; refining ecological flow needs to account for altered channel morphology and the life history needs of riparian and fish species; and assessing flow alteration to inform management strategies. Key considerations and lessons learned are discussed in the context of developing ecological flow needs in highly altered systems including when non-flow related management actions (i.e., channel rehabilitation) are necessary to achieve ecological goals.

The use of multiscale stressors with biological condition assessments: A framework to advance the assessment and management of streams

Incorporating information on landscape condition (or integrity) across multiple spatial scales and over large spatial extents in biological assessments may allow for a more integrated measure of stream biological condition and better management of streams. However, these systems are often assessed and managed at an individual scale (e.g., a single watershed) without a larger regional multiscale context. In this paper, our goals were: (1) To develop a conceptual framework that could combine stream biological condition to abiotic landscape integrity (or, conversely, stressor) data at three spatial scales: watershed, catchment and stream-reach scale, to enable more targeted management actions. Measures of landscape integrity and stressors are negatively related, i.e., integrity on a 0–1 scale is equal or equivalent to stressors on a 1–0 scale. (2) To develop the framework in such a way that allows operational flexibility, whereby different indicators can be used to represent biological condition, and landscape integrity (or stressors) at various scales. (3) To provide different examples of the framework's use to demonstrate the flexibility of its application and relevance to management. Examples include stream biological assessments from different regions and states across the U.S. for fish, macroinvertebrates and diatoms using a variety of assessment tools (e.g., the Biological Condition Gradient (BCG), and an Index of Biotic Integrity (IBI)). Landscape integrity indicators comprise U.S. EPA's nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI), and state and regional derived watershed and stream-reach scale integrity indicators. Scatterplots and a landscape integrity map were used to relate samples of stream condition classes (e.g., good, fair, poor) to watershed, catchment and stream-reach scale integrity. This framework and approach could provide a powerful tool for prioritizing, targeting, and communicating management actions to protect and restore stream habitats, and for informing the spatial extent at which management is applied.

Understanding Landscape Influences on Aquatic Fauna across the Central and Southern Appalachians

For the success of aquatic conservation efforts, it is imperative for there to be an understanding of the influences multiple stressors across the landscape have on aquatic biota, as it provides an understanding of spatial patterns and informs regional stakeholders. The central and southern Appalachians contain biodiversity hotspots for aquatic fauna. Therefore, we sought to create a comprehensive multimetric model that is based on the influence of abiotic factors on fish and aquatic macroinvertebrates that could predict watershed quality. Good spatial coverage exists for land use/land cover (LULC) and other physicochemical components throughout the region, yet biological data is unevenly distributed, which creates difficulties in making informed management and conservation decisions across large landscapes. We used boosted regression trees (BRT) to model a variety of biological responses (fish and aquatic macroinvertebrate variables) to abiotic predictors and by combining model outputs created a single score for both abiotic and biotic values throughout the region. The mean variance that was explained by BRT models for fish was 73% (range = 48–85%) and for aquatic macroinvertebrates was 81% (range = 76–89%). We categorized both predictor and response variables into themes and targets, respectively, to better understand large scale patterns on the landscape that influence biological condition of streams. The most important themes in our models were geomorphic condition for fish and water quality for aquatic macroinvertebrates. Regional models were developed for fish, but not for aquatic macroinvertebrates due to the low number of sample sites. There was strong correlation between regional and global watershed scores for fish models but not between fish and aquatic macroinvertebrate models. We propose that the use of such multimetric scores can inform managers, NGOs, and private land owners regarding land use practices, thereby contributing to large landscape scale conservation efforts.

Multi-Scale Assessment of Relationships between Fragmentation of Riparian Forests and Biological Conditions in Streams

Due to anthropogenic activities within watersheds and riparian areas, stream water quality and ecological communities have been significantly affected by degradation of watershed and stream environments. One critical indicator of anthropogenic activities within watersheds and riparian areas is forest fragmentation, which has been directly linked to poor water quality and ecosystem health in streams. However, the true nature of the relationship between forest fragmentation and stream ecosystem health has not been fully elucidated due to its complex underlying mechanism. The purpose of this study was to examine the relationships of riparian fragmented forest with biological indicators including diatoms, macroinvertebrates, and fish. In addition, we investigated variations in these relationships over multiple riparian scales. Fragmentation metrics, including the number of forest patches (NP), proportion of riparian forest (PLAND), largest riparian forest patch ratio (LPI), and spatial proximity of riparian forest patches (DIVISION), were used to quantify the degree of fragmentation of riparian forests, and the trophic diatom index (TDI), benthic macroinvertebrates index (BMI), and fish assessment index (FAI) were used to represent the biological condition of diatoms, macroinvertebrates, and fish in streams. PLAND and LPI showed positive relationships with TDI, BMI, and FAI, whereas NP and DIVISION were negatively associated with biological indicators at multiple scales. Biological conditions in streams were clearly better when riparian forests were less fragmented. The relationships of NP and PLAND with biological indicators were stronger at a larger riparian scale, whereas relationships of LPI and DIVISION with biological indicators were weaker at a large scale. These results suggest that a much larger spatial range of riparian forests should be considered in forest management and restoration to enhance the biological condition of streams.

Assessing the influence of multiple stressors on stream diatom metrics in the upper Midwest, USA

Water resource managers face increasing challenges in identifying what physical and chemical stressors are responsible for the alteration of biological conditions in streams. The objective of this study was to assess the comparative influence of multiple stressors on benthic diatoms at 98 sites that spanned a range of stressors in an agriculturally dominated region in the upper Midwest, USA. The primary stressors of interest included: nutrients, herbicides and fungicides, sediment, and streamflow; although the influence of physical habitat was incorporated in the assessment. Boosted Regression Tree was used to examine both the sensitivity of various diatom metrics and the relative importance of the primary stressors. Percent Sensitive Taxa, percent Highly Motile Taxa, and percent High Phosphorus Taxa had the strongest response to stressors. Habitat and total phosphorous were the most common discriminators of diatom metrics, with herbicides as secondary factors. A Classification and Regression Tree (CART) model was used to examine conditional relations among stressors and indicated that fine-grain streams had a lower percentage of Sensitive Taxa than coarse-grain streams, with Sensitive Taxa decreasing further with increased water temperature (>30°C) and triazine concentrations (>1500ng/L). In contrast, streams dominated by coarse-grain substrate contained a higher percentage of Sensitive Taxa, with relative abundance increasing with lower water temperatures (<29°C) and shallower water depth (<0.3m). Quantile regression indicated that maximum water temperature appears to be a major limiting factor in Midwest streams; whereas both total phosphorus and percent fines showed a slight subsidy-stress response. While using benthic algae for assessing stream quality can be challenging, field-based studies can elucidate stressor effects and interactions when the response variables are appropriate, sufficient stressor resolution is achieved, and the number and type of sites represent a gradient of stressor conditions and at least a quasi-factorial design.

Predictive mapping of the biotic condition of conterminous U.S. rivers and streams.

Understanding and mapping the spatial variation in stream biological condition could provide an important tool for conservation, assessment, and restoration of stream ecosystems. The USEPA's 2008-2009 National Rivers and Streams Assessment (NRSA) summarizes the percentage of stream lengths within the conterminous United States that are in good, fair, or poor biological condition based on a multimetric index of benthic invertebrate assemblages. However, condition is usually summarized at regional or national scales, and these assessments do not provide substantial insight into the spatial distribution of conditions at unsampled locations. We used random forests to model and predict the probable condition of several million kilometers of streams across the conterminous United States based on nearby and upstream landscape features, including human-related alterations to watersheds. To do so, we linked NRSA sample sites to the USEPA's StreamCat Dataset; a database of several hundred landscape metrics for all 1:100,000-scale streams and their associated watersheds within the conterminous United States. The StreamCat data provided geospatial indicators of nearby and upstream land use, land cover, climate, and other landscape features for modeling. Nationally, the model correctly predicted the biological condition class of 75% of NRSA sites. Although model evaluations suggested good discrimination among condition classes, we present maps as predicted probabilities of good condition, given upstream and nearby landscape settings. Inversely, the maps can be interpreted as the probability of a stream being in poor condition, given human-related watershed alterations. These predictions are available for download from the USEPA's StreamCat website. Finally, we illustrate how these predictions could be used to prioritize streams for conservation or restoration.

Effects of human disturbance and riparian conditions on Odonata (Insecta) assemblages in eastern Amazon basin streams

Riparian vegetation is an important determinant of the physical, chemical, and biological condition of streams, and odonates are useful indicators of riparian condition. To identify environmental factors that structure Odonata assemblages in tropical forest streams, we collected adult odonate specimens and habitat data from 50 stream sites located in the Brazilian municipality of Paragominas (Pará state). We collected 1769 specimens representing 11 families, 41 genera, and 97 species. Of these species, 56 were Zygoptera, and 41 were Anisoptera. Improved environmental condition was reflected in increased Zygoptera species richness and reduced Anisoptera species richness. Channel shading was strongly and positively related to Zygoptera richness, and negatively to Anisoptera richness. Zygoptera species richness, but not Anisoptera species richness, was related positively to bank angle, quantity of wood in the stream bed, electrical conductivity, and decreased water temperature. Altered riparian vegetation structure was the principal determinant of odonate assemblage structure. Our results indicate that maintaining intact riparian vegetation is fundamental for conserving or re-establishing aquatic odonate assemblage structure.

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.

Bank erosion hazard index as an indicator of near-bank aquatic habitat and community structure in a southeastern Piedmont stream

Streams in the southeastern Piedmont region display varying degrees of bank erosion, which in turn can influence multiple physical and biological processes. In efforts to assess and predict bank erosion, the multi-metric tool Bank Erosion Hazard Index (BEHI) is often calculated. As designed, the BEHI takes into consideration many physical phenomena and scores stream banks categorically from very low to extreme bank erosion hazard; however the power of this index to directly predict in-stream biological conditions is unknown. The predictive ability of BEHI was evaluated on near-bank aquatic biota and organic matter (OM) retention in an AL Piedmont stream with a range of bank conditions. Fifteen banks were characterized using the BEHI and subsequently, macroinvertebrates, crayfishes, fishes and organic matter associated with each bank were quantified. Results suggest increased macroinvertebrate richness and OM retention with low BEHI score. Multivariate analyses suggest functional similarity in macroinvertebrate assemblages associated with low BEHI banks and greater variation in assemblages as BEHI increased. Crayfish were more abundant at banks with high BEHI, a pattern attributed to increases in a generalist species in more-degraded habitats. Fish response showed no discernible pattern in relationship to BEHI score. These results suggest that BEHI may have applications as an informative ecological evaluation tool integrating physical and biological conditions in streams.

Linking land use, in-stream stressors, and biological condition to infer causes of regional ecological impairment in streams

We used field-derived data from streams in Nevada, USA, to quantify relationships between stream biological condition, in-stream stressors, and potential sources of stress (land use). We used 2 freshwater macroinvertebrate-based indices to measure biological condition: a multimetric index (MMI) and an observed to expected (O/E) index of taxonomic completeness. We considered 4 categories of potential stressors: dissolved metals, total dissolved solids, nutrients, and flow alteration. For physicochemical factors that varied predictably across natural environmental gradients, we quantified potential stress as the site-specific difference between observed (O) and expected (E) levels of each factor (O–Estress). We then used 2 sets of Random Forest models to quantify relationships between: 1) biological condition and potential stressors, and 2) stressor values and land uses. The 2 indices of biological condition were differentially responsive to stressors, indicating that no single measure of biological condition could fully characterize assemblage response to stress. Total dissolved solids (as measured by electrical conductivity [EC]) and metal contamination were the stressors most strongly associated with biological degradation. The most likely sources of these stressors were agriculture, urban development, and mining. Our findings highlight the need to develop EC criteria for streams. Measures of biological condition and stress that account for natural variability should reduce errors of inference and increase confidence in causal analyses. This approach will require development of robust models capable of predicting physical and chemical reference conditions. Causal analyses for individual sites require appropriate hypotheses about which stressors and what levels of stress can cause biological degradation. Our study demonstrates the usefulness of field data collected from multiple sites within a region for developing these hypotheses.

Evaluating the use of algal pigments to assess the biological condition of streams

Assessments of stream condition using benthic algal communities have traditionally relied on taxonomy-based approaches to compare community structure at sites exposed to a stressor versus reference sites. Taxonomy-based methods are often effective, but they require high levels of training and are relatively time consuming and expensive. We examined the utility of assessing stream biological condition using algal pigments. We used gradient and control-impact study designs in 2008 and 2009 to compare the extent that algal pigments versus taxonomic descriptors of algal community structure varied along a 10.5-km stretch of the Flat River (South Nahanni River watershed, NWT, Canada) encompassing a gradient of nutrients and metals at sites upstream, adjacent to and downstream of a northern metals mine. We also calculated costs to quantify algal pigments relative to taxonomy-based methods. Multivariate analyses (ANOSIM tests, redundancy analysis) identified that pigment concentrations from benthic algal samples differed significantly (p < 0.05) between non-exposed and exposed river sites and were related to variations in water physico-chemical conditions. By contrast, community composition determined from taxonomy-based enumeration to the Order and Family levels did not differ significantly between non-exposed and exposed sites, and relations with water physico-chemical conditions were weaker and inconsistent between the study years. In-house costs to quantify algal pigments were lower than commercial rates to describe community structure using taxonomy. Thus, our data suggests that analysis of benthic algal pigments represents a viable and cost-effective bio-monitoring method for assessing anthropogenic effects on stream condition that merits further evaluation.

A native species-based index of biological integrity for Hawaiian stream environments

Based upon ecological data provided by a 6-year study of native species assemblage structure and function in near-pristine Limahuli Stream (Kauai), The Hawaii Stream Index of Biological Integrity (HS-IBI) incorporates 11 metrics covering five ecological categories (taxonomic richness, sensitive species, reproductive capacity, trophic-habitat capacity, and tolerance capacity). The HS-IBI was shown to effectively distinguish stream biological condition on a continuum from undisturbed (near-pristine) to severely impaired in sampling of 39 sites (6 estuarine reaches) on 18 Hawaiian streams located on all major islands. A significant relationship was validated between relative levels of human impact occurring within-watersheds (determined through use of a landscape indicator) and IBI ratings with metrics responding predictably to gradients of human influence. For management interpretation of HS-IBI results, a framework comprised of five "integrity classes" (excellent-good-fair-poor-impaired) is provided which can be used to operationalize HS-IBI results obtained through standardized sampling of stream sites that "...translates into a verbal and visual portrait of biological condition." Through its focus on native species, the HS-IBI incorporates evolutionary and biogeographic variation for the region with biological expectations based upon reference condition benchmarks established in near-pristine stream environments where ecological functioning is naturally self-sustaining and resilient to normal environmental variation. The methods and tools described in this study are appropriate for application in all perennial streams in Hawaii and may be adapted for use in streams on other tropical Pacific islands where native species assemblages persist in near-pristine stream environments.

Predicting biological condition in southern California streams

As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI<40) and 78% of unimpaired sites (B-IBI≥40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.

Geoadditive regression modeling of stream biological condition

Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained.

Determining subsampling effort for the development of a rapid bioassessment protocol using benthic macroinvertebrates in streams of Southeastern Brazil

The purpose of this study was to establish a subsampling procedure for benthic macroinvertebrates to aid in the development of a multimetric index to assess the biological condition of streams. Data from six streams that are considered minimally impaired were used. Subsampling was done using a device divided into 24 quadrats. The sediment from each quadrat was sorted, and all organisms were removed and identified. Richness metrics were the most affected by subsample size. Relative-abundance metrics were the most stable, proving that the sample was well distributed throughout the tray and abundance proportions were maintained. The results showed that the macroinvertebrate assemblage present in the six quadrats was similar to that present in the full sample. These analyses indicated that six quadrats, randomly designated, with a minimum of 200 collected specimens could be used in place of the full sample. In routine water management, managing time and costs are a major challenge; therefore, this type of simplification is absolutely necessary to ensure that a biomonitoring tool is useful for practical applications.

Classifying the biological condition of small streams: an example using benthic macroinvertebrates

AbstractThe ability to classify the biological condition of unsurveyed streams accurately would be an asset to the conservation and management of streams. We compared the ability of 5 modeling methods (classification and regression trees, conditional inference trees, random forests [RF], conditional random forests [cRF], and ordinal logistic regression) to predict stream biological condition (very poor, poor, fair, or good) based on benthic macroinvertebrate Index of Biotic Integrity data taken from the Maryland Biological Stream Survey. Predictor variables included land use and land cover (e.g., impervious surface, row-crop agriculture, and population density) and landscape measures (annual precipitation and watershed area). We included 1561 sites on small nontidal streams in the Maryland portion of the Chesapeake Bay watershed. We used 1248 sites (80%) as a training data set to build models and 313 sites (20%) as an independent evaluation data set. RF and cRF models most accurately predicted observed in...

Assessment Tools for Urban Catchments: Defining Observable Biological Potential1

Abstract: Urbanization represents a strong and increasingly more prevalent impact on stream quality worldwide. One of the characteristic effects of increased urbanization is a consistent decline in biological stream condition. The characterization of this biological degradation with increasing urbanization presents a number of advantages for the study and management of urban streams and catchments. In this paper, the limitation of biological condition with urbanization, called observed biological potential, is characterized. Using an urban intensity index and a biological index developed specifically for urban systems in the Baltimore, Maryland; Cleveland, Ohio; and San Jose, California regions, two principal techniques were compared (quantile regression and bin regression) to define observed biological potential along urban gradients. Quantile regression was selected as the preferable tool for describing observed biological potential given the consistency with which it can be applied and its statistical efficiency, however, bin quantile regression performed similarly. Having identified a numeric approximation of observed biological potential, two methods for identifying factors related to distance from potential as a way of identifying critical environmental factors affecting biological condition in urban areas were explored. The results of this work can be used for identifying benchmarks for urban stream biological condition, identifying limiting catchment characteristics, and prioritizing urban stream management efforts.

Algae–P relationships, thresholds, and frequency distributions guide nutrient criterion development

We used complementary information collected using different conceptual approaches to develop recommendations for a stream nutrient criterion based on responses of algal assemblages to anthropogenic P enrichment. Benthic algal attributes, water chemistry, physical habitat, and human activities in watersheds were measured in streams of the Mid-Atlantic Highlands region as part of the Environmental Monitoring and Assessment Program of the US Environmental Protection Agency. Diatom species composition differed greatly between low- and high-pH reference streams; therefore, analyses for criterion development were limited to a subset of 149 well-buffered streams to control for natural variability among streams caused by pH. Regression models showed that TP concentrations were ;10 lg/L in streams with low levels of human activities in watersheds and that TP increased with % agriculture and urban land uses in watersheds. The 75 th percentile at reference sites was 12 lg TP/L. Chlorophyll a and ash-free dry mass increased and acid and alkaline phosphatase activities decreased with increasing TP concentration. The number of diatom taxa, evenness, proportion of expected native taxa, and number of high-P taxa increased with TP concentration in streams. In contrast, the number of low-P native taxa and % low-P individuals decreased with increasing TP. Lowess regression and regression tree analysis indicated nonlinear relationships for many diversity indices and attributes of taxonomic composition with respect to TP. Thresholds in these responses occurred between 10 and 20 lg/L and helped justify recommending a P criterion between 10 and 12 lg TP/L to protect high- quality biological conditions in streams of the Mid-Atlantic Highlands.