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Streams and other waterbodies in poor ecological condition often require causal assessment to determine appropriate follow-up actions. However, site-specific causal assessments can be time ...

Accurate and informative methods for evidence synthesis that are also simple and inexpensive to implement would greatly increase our ability to use scientific research results to better manage natural environments. Across the world, pressure to use evidence-based environmental management is increasing, but little guidance exists as to what ‘evidence-based’ actually means. Methods for systematic review of literature evidence have been modified from those used in medical research, but the effort involved in using these methods means that they have not been widely adopted. We compared 3 independently developed approaches to ‘rapid evidence synthesis’ methods developed in an attempt to improve efficiency and responsiveness compared to standard methods for systematic review. Each method has features that should be included in an ideal rapid evidence-synthesis method and has potential for further development. Increasing standardization of methods for evidence extraction, quality assessment, and synthesi...

Sound environmental management relies on scientific evidence to indicate whether action is warranted and, if so, which actions will be most effective. We discuss conceptual model diagrams that schematically describe how sources or human activities lead to specific stressors and ultimately to biotic effects. They are useful for describing how undesirable effects are produced and identifying where management actions may be most effective in preventing unwanted effects or improving existing conditions. We illustrate the use of conceptual model diagrams in a literature-based assessment of the impacts of mountaintop removal mining on downstream aquatic systems. The diagram-development process combined extraction and evaluation of research results with iterative refinement of diagrams depicting source-to-stressor-to-effect causal pathways. Conceptual-model diagrams provided a useful scaffold for organizing and synthesizing multiple individual pieces of evidence extracted from different studies and an ef...

Background Eutrophication of freshwater ecosystems resulting from nitrogen and phosphorus pollution is a major stressor across the globe. Despite recognition by scientists and stakeholders of the problems of nutrient pollution, rigorous synthesis of scientific evidence is still needed to inform nutrient-related management decisions, especially in streams and rivers. Nutrient stressor-response relationships are complicated by multiple interacting environmental factors, complex and indirect causal pathways involving diverse biotic assemblages and food web compartments, legacy (historic) nutrient sources such as agricultural sediments, and the naturally high spatiotemporal variability of lotic ecosystems. Determining nutrient levels at which ecosystems are affected is a critical first step for identifying, managing, and restoring aquatic resources impaired by eutrophication and maintaining currently unimpaired resources. The systematic review outlined in this protocol will compile and synthesize literature on the response of chlorophyll a to nutrients in streams, providing a state-of-the-science body of evidence to assess nutrient impacts to one of the most widely-used measures of eutrophication. This review will address two questions: “What is the response of chlorophyll a to total nitrogen and total phosphorus concentrations in lotic ecosystems?” and “How are these relationships affected by other factors?” Methods Searches for published and unpublished articles (peer-reviewed and non-peer-reviewed) will be conducted using bibliographic databases and search engines. Searches will be supplemented with bibliography searches and requests for material from the scientific and management community. Articles will be screened for relevance at the title/abstract and full text levels using pre-determined inclusion criteria; 10% (minimum 50, maximum 200) of screened papers will be examined by multiple reviewers to ensure consistent application of criteria. Study risk of bias will be evaluated using a questionnaire developed from existing frameworks and tailored to the specific study types this review will encounter. Results will be synthesized using meta-analysis of correlation coefficients, as well as narrative and tabular summaries, and will focus on the shape, direction, strength, and variability of available nutrient-chlorophyll relationships. Sensitivity analysis and meta-regression will be used to evaluate potential effects of study quality and modifying factors on nutrient-chlorophyll relationships.

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.

Metrics characterizing the benthic macroinvertebrate assemblages in wadeable streams in the Mid-Atlantic region of the United States were analyzed to explore the relative responses of the metrics to different types of anthropogenic stress. The data used in our study were collected by the US Environmental Protection Agency Environmental Monitoring and Assessment Program from 1993 to 1996. Regression models were developed relating metric values at reference sites to natural sources of variability. These models were then used to predict reference values at test sites. Test site metric observations were scaled by subtracting the predicted reference value and dividing by the standard deviation of residuals at reference sites. Stressor–response relationships for each scaled metric were then estimated using generalized additive models. Metric responses to 4 groups of stressors (nutrient enrichment, habitat degradation, elevated metals concentrations, and elevated ion concentrations) were different. The p...

Individual chemical logistic regression models were developed for 37 chemicals of potential concern in contaminated sediments to predict the probability of toxicity, based on the standard 10-d survival test for the marine amphipods Ampelisca abdita and Rhepoxynius abronius. These models were derived from a large database of matching sediment chemistry and toxicity data, which includes contaminant gradients from a variety of habitats in coastal North America. Chemical concentrations corresponding to a 20, 50, and 80% probability of observing sediment toxicity (T20, T50, and T80 values) were calculated to illustrate the potential for deriving application-specific sediment effect concentrations and to provide probability ranges for evaluating the reliability of the models. The individual chemical regression models were combined into a single model, using either the maximum (P(Max) model) or average (P(Avg) model) probability predicted from the chemicals analyzed in a sample, to estimate the probability of toxicity for a sample. The average predicted probability of toxicity (from the P(Max) model) within probability quartiles closely matched the incidence of toxicity within the same ranges, demonstrating the overall reliability of the P(Max) model for the database that was used to derive the model. The magnitude of the toxic effect (decreased survival) in the amphipod test increased as the predicted probability of toxicity increased. Users have a number of options for applying the logistic models, including estimating the probability of observing acute toxicity to estuarine and marine amphipods in 10-d toxicity tests at any given chemical concentration or estimating the chemical concentrations that correspond to specific probabilities of observing sediment toxicity.

Two stream reaches in the Little Scioto River (OH, USA) were characterized for the causes of impairments measured at two locations. By inductive inference, six candidate causes were winnowed down to three and five candidate causes for each of the two stream reaches. Using a formal strength-of-evidence process, a single cause was determined. At the most upstream location, habitat alterations, including fine-textured substrates and low DO, were characterized as the probable causes for an increased percentage of anomalies of fish, a decreased percentage of mayflies, and an increased percentage of tolerant macroinvertebrates. An increase in the relative weight of fish was attributed to an artificially narrow, deepened channel. Approximately 2 km downstream, polycyclic aromatic hydrocarbon (PAH)-contaminated sediments were identified as the cause for both fish and macroinvertebrate impairments. Causal characterization using first elimination and then a strength-of-evidence approach narrowed and defined the causes of ecological impairment even in this situation, where many complex and interacting candidate causes existed. Applying a formal method highlighted types of data and associations that can strengthen and present a more convincing determination of the causes of impairment.

Biological surveys have become a common technique for determining whether aquatic communities have been injured. However, their results are not useful for identifying management options until the causes of apparent injuries have been identified. Techniques for determining causation have been largely informal and ad hoc. This paper presents a logical system for causal inference. It begins by analyzing the available information to generate causal evidence; available information may include spatial or temporal associations of potential cause and effect, field or laboratory experimental results, and diagnostic evidence from the affected organisms. It then uses a series of three alternative methods to infer the cause: Elimination of causes, diagnostic protocols, and analysis of the strength of evidence. If the cause cannot be identified with sufficient confidence, the reality of the effects is examined, and if the effects are determined to be real, more information is obtained to reiterate the process.

We investigated the feasibility of using the structure of fish and benthic macroinvertebrate communities to distinguish among major types of stressors (e.g., siltation, nutrient enrichment, and stream structural degradation) using spatially and temporally matched data on stressors and responses. The 19 stressor variables addressed stream chemistry and in-stream habitat and included biological oxygen demand (BOD), total suspended solids, nitrogen, phosphorus, and components of the Qualitative Habitat Evaluation Index. The 42 response variables addressed fish and invertebrate community structure and included many of the component metrics of the Index of Biological Integrity and the Invertebrate Community Index as well as variables specifically calculated for this project. All data were collected between 1988 and 1994 by the Ohio Environmental Protection Agency in the Eastern Corn Belt Plains ecoregion. Prior to analysis, variables were transformed to near normality, and variables significantly correlated with drainage area were fit to regression models and the resulting residuals used in the analyses. Multivariate analyses included factor and discriminant analysis. The first six stressor factors explained 69% of the variation. Discriminant functions formed using the response variables significantly separated site clusters classified into high, medium, and low categories along stressor gradients. Both fish and macroinvertebrate variables were important in distinguishing site categories. For example, percentage Tanytarsini midges and percentage Glyptotendipes were important in distinguishing sites having high and low BOD. Percentage darters was associated with sites having high scores for stream corridor structure and low concentrations of inorganic nutrients, and percentage round-bodied suckers was associated with sites having low BOD and low concentrations of zinc and lead. These results indicate that diagnostic models may be developed that will be useful for site-specific and regional assessments.

Discussions and applications of the policies and practices of the U.S. Environmental Protection Agency (USEPA) in ecological risk assessment will benefit from continued clarification of the concepts of assessment endpoints and of levels of biological organization. First, assessment endpoint entities and attributes can be defined at different levels of organization. Hence, an organism-level attribute, such as growth or survival, can be applied collectively to a population-level entity such as the brook trout in a stream. Second, assessment endpoints for ecological risk assessment are often mistakenly described as "individual level," which leads to the idea that such assessments are intended to protect individuals. Finally, populations play a more important role in risk assessments than is generally recognized. Organism-level attributes are used primarily for population-level assessments. In addition, the USEPA and other agencies already are basing management decisions on population or community entities and attributes such as production of fisheries, abundance of migratory bird populations, and aquatic community composition.

Water quality monitoring data are usually used independently to report on the condition of streams and watersheds. For example, watersheds are often rated as good, fair, or poor with regard to a single stressor or with regard to an index of biotic integrity. The utility of monitoring data may be enhanced by integrating stressor-response information with the observed stressor data, and reporting stressor levels in terms of their relative effects upon valued ecological resources. We estimated stressor-response relationships at the regional scale using data collected in the Eastern Cornbelt Plains Ecoregion of Ohio. Generalized additive models were used to visualize stressor-response relationships. Piecewise linear functions and simple linear functions were then used to parameterize the observed responses. Parameters derived from the regional models were used to scale observations of stressors in the Big Darby Creek watershed, OH. After scaling, stressors were compared in terms of their spatial distribution and in terms of the severity with which they influenced the biological endpoint of interest. Stressors most strongly associated with the current ecological condition of the watershed were identified. In the Big Darby Creek watershed, decreases in substrate quality were associated with the most severe decrements in biological condition. At smaller decrements in biological condition, three stressors were important: substrate quality, riparian quality, and increased concentrations of NOx.

Responsible care and management of Earth's resources requires scientific support, but the pool of underused research is growing rapidly. Environmental science research studies describe associations between variables (e.g. statistical relationships between stressors and responses). We propose open-access and online sharing of such associations. This concept differs from various efforts around the world to promote sharing of primary research data, but holds similar goals of improved use of existing knowledge. The initiative is made possible by recent developments in information technology and evolving online culture (e.g. crowdsourcing and citizen science). We have begun to connect existing projects that catalog and store associations, thereby moving toward a single virtual repository. Researchers and decision makers may share and re-use associations for myriad purposes, including: increasing efficiency and timeliness of systematic reviews, environmental assessments and meta-analyses, identifying knowledge gaps and research opportunities, providing evolved metrics of research impact, and demonstrating connections between research and environmental improvement.