Assessing the relative severity of stressors at a watershed scale

Headwater stream condition and nutrient runoff: Relating SWAT to empirical ecological measures in an agricultural watershed in Pennsylvania

Managing nonpoint sources of nutrients and sediments is the primary challenge for improving conditions in the Susquehanna-Chesapeake basin. Aquatic macroinvertebrates are widely used indicators of stream ecological integrity, but the relationship between nutrient runoff and macroinvertebrate response remains indistinct. Logistical and financial hurdles hinder collection of high-resolution empirical nutrient data, but landscape-based models like the Soil and Water Assessment Tool (SWAT) offer a more practical approach. Nutrient runoff was simulated with SWAT for a small, upland, agricultural Pennsylvania watershed. Three levels of ecological assessment were used to interpret SWAT results. Macroinvertebrate communities (intensive) were sampled at 14 sites and described using an Index of Biotic Integrity (IBI). Biological integrity was moderately degraded in many reaches. The Stream-Wetland-Riparian (SWR) Index (rapid) and landscape metrics (remote) also indicated prevalent agricultural stressors. Baseflow nitrate grab samples, collected once per season, showed no significant relationship with IBI score. Thirty spatiotemporal scales of nutrient data were extracted from SWAT for phosphorus, nitrate, and organic nitrogen. Best subsets regression was performed on IBI scores using SWAT, land cover, and SWR variables. Results were significant (p < .001) with high R² values (84.8 and 86.2), signifying a negative relationship between instream nutrient concentration and IBI score. This study demonstrates the viability of SWAT as an alternative to in-field nutrient sampling, the value of spatiotemporal scale in model outputs, and the importance of site condition variables in relating nutrients to stream ecological health.

Failure to engage the public in issues related to inland fishes and fisheries: strategies for building public and political will to promote meaningful conservation

Generating awareness of environmental conservation issues among the public is essential if there is an expectation of them to alter their behaviour, facilitate informed decisions and engage governments or regulatory authorities to take action. There are, however, exceedingly few public engagement success stories related to inland fishes and fisheries policy and resource allocation decisions. Inland aquatic resources and their associated fisheries provide employment, recreation, culture and, in developing regions, a considerable proportion of human nutrition and food security. Freshwater fishes are incredibly diverse but are among the most endangered organisms globally. Many threats to inland fisheries are driven largely by externalities to inland fisheries. The purpose of this paper is to draw attention to the role and plight of inland fishes and fisheries, and the need to generate the public and political will necessary to promote meaningful conservation. With this paper, the extent to which the scientific and environmental management communities have failed to engage the public in issues related to inland fishes and fisheries is characterized. Next, the barriers or factors that serve as the basis for the problem with public engagement are identified. The paper concludes by identifying strategies, including those focused on environmental education initiatives, for building the public and political will necessary to promote meaningful conservation of inland fishes and fisheries in developed and developing countries. Scientists, environmental managers, non-governmental organizations, politicians, regulatory authorities and the media all have important roles to play in overcoming challenges to inland fisheries. Failure to engage the public in freshwater conservation and management issues will impede efforts to stem the loss of freshwater habitats, fisheries and aquatic biodiversity. Thankfully, there are opportunities to learn from success stories related to other environmental issues and initiatives that have been successful in marine fish conservation.

Use of fish functional traits to associate in-stream suspended sediment transport metrics with biological impairment

Loss of ecological integrity due to excessive suspended sediment in rivers and streams is a major cause of water quality impairment in the USA. Current assessment protocols for development of sediment total maximum daily loads (TMDLs) lack a means to link temporally variable sediment transport rates with specific losses of ecological functions as loads increase. In order to accomplish this linkage assessment, a functional traits-based approach was used to correlate site occurrences of 17 fish species traits in three main groups (preferred rearing habitat, trophic feeding guild, and spawning behavior) with suspended sediment transport metrics. The sediment transport metrics included concentrations, durations, and dosages for a range of exceedance frequencies; and mean annual suspended sediment yields (SSY). In addition, this study in the Northwestern Great Plains Ecoregion examined trait relationships with three environmental gradients: channel stability, drainage area, and elevation. Potential stressor responses due to elevated suspended sediment concentration (SSC) levels were correlated with occurrences of five traits: preferred pool habitat; feeding generalists, omnivores, piscivores, and nest-building spawners; and development of ecologically based TMDL targets were demonstrated for specific SSC exceedance frequencies. In addition, reduced site occurrences for preferred pool habitat and nest-building spawners traits were associated with unstable channels and higher SSY. At an ecoregion scale, a functional traits assessment approach provided a means to quantify relations between biological impairment and episodically elevated levels of suspended sediment, supporting efforts to develop ecologically based sediment TMDLs.

Prediction of biological integrity based on environmental similarity--revealing the scale-dependent link between study area and top environmental predictors

Indices of Biological integrity (IBI) are considered valid indicators of the overall health of a water body because the biological community is an endpoint within natural systems. However, prediction of biological integrity using information from multi-parameter environmental observations is a challenging problem due to the hierarchical organization of the natural environment, the existence of nonlinear inter-dependencies among variables as well as natural stochasticity and measurement noise. We present a method for predicting the Fish Index of Biological Integrity (IBI) using multiple environmental observations at the state-scale in Ohio. Instream (chemical and physical quality) and offstream parameters (regional and local upstream land uses, stream fragmentation, and point source density and intensity) are used for this purpose. The IBI predictions are obtained using the environmental site-similarity concept and following a simple to implement leave-one-out cross validation approach. An IBI prediction for a sampling site is calculated by averaging the observed IBI scores of observations clustered in the most similar branch of a dendrogram--a hierarchical clustering tree of environmental observations--built using the rest of the observations. The standardized Euclidean distance is used to assess dissimilarity between observations. The constructed predictive model was able to explain 61% of the IBI variability statewide. Stream fragmentation and regional land use explained 60% of the variability; the remaining 1% was explained by instream habitat quality. Metrics related to local land use, water quality, and point source density and intensity did not improve the predictive model at the state-scale. The impact of local environmental conditions was evaluated by comparing local characteristics between well- and mispredicted sites. Significant differences in local land use patterns and upstream fragmentation density explained some of the model's over-predictions. Local land use conditions explained some of the model's IBI under-predictions at the state-scale since none of the variables within this group were included in the best final predictive model. Under-predicted sites also had higher levels of downstream fragmentation. The proposed variables ranking and predictive modeling methodology is very well suited for the analysis of hierarchical environments, such as natural fresh water systems, with many cross-correlated environmental variables. It is computationally efficient, can be fully automated, does not make any pre-conceived assumptions on the variables interdependency structure (such as linearity), and it is able to rank variables in a database and generate IBI predictions using only non-parametric easy to implement hierarchical clustering.

Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Forecasting relative impacts of land use on anadromous fish habitat to guide conservation planning

Land use change can adversely affect water quality and freshwater ecosystems, yet our ability to predict how systems will respond to different land uses, particularly rural-residential development, is limited by data availability and our understanding of biophysical thresholds. In this study, we use spatially explicit parcel-level data to examine the influence of land use (including urban, rural-residential, and vineyard) on salmon spawning substrate quality in tributaries of the Russian River in California. We develop a land use change model to forecast the probability of losses in high-quality spawning habitat and recommend priority areas for incentive-based land conservation efforts. Ordinal logistic regression results indicate that all three land use types were negatively associated with spawning substrate quality, with urban development having the largest marginal impact. For two reasons, however, forecasted rural-residential and vineyard development have much larger influences on decreasing spawning substrate quality relative to urban development. First, the land use change model estimates 10 times greater land use conversion to both rural-residential and vineyard compared to urban. Second, forecasted urban development is concentrated in the most developed watersheds, which already have poor spawning substrate quality, such that the marginal response to future urban development is less significant. To meet the goals of protecting salmonid spawning habitat and optimizing investments in salmon recovery, we suggest investing in watersheds where future rural-residential development and vineyards threaten high-quality fish habitat, rather than the most developed watersheds, where land values are higher.

Extracting knowledge on the links between the water body stressors and biotic integrity

Multi-metric indices of biological integrity (IBIs) are most frequently created by examining single biological metrics along gradients of environmental degradation, and then combining multiple metrics using "best professional judgment" to characterize and calibrate stressor-response relationships. We aim to provide an efficient data analysis and visualization tool to assess the simultaneous effects of anthropogenic stressors on the fish population through the fish metrics and the associated Index of Biotic Integrity (IBI). Kohonen's self-organizing feature maps (SOM), unsupervised neural networks, are employed to pattern the sampling sites in the state of Ohio based on similar metrics characteristics. Canonical correspondence analysis (CCA) allows us then to draw conclusions about the role of the environmental variables in maintaining the perfect abode for fishes. Different visualizations superimposed with SOM clustering are realized to explore the complex interrelationships in the aquatic system and aid watershed managers to comprehend the effects of the environment on the fish.

Using relative risk to compare the effects of aquatic stressors at a regional scale

The regional-scale importance of an aquatic stressor depends both on its regional extent (i.e., how widespread it is) and on the severity of its effects in ecosystems where it is found. Sample surveys, such as those developed by the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP), are designed to estimate and compare the extents, throughout a large region, of elevated conditions for various aquatic stressors. In this article, we propose relative risk as a complementary measure of the severity of each stressor's effect on a response variable that characterizes aquatic ecological condition. Specifically, relative risk measures the strength of association between stressor and response variables that can be classified as either "good" (i.e., reference) or "poor" (i.e., different from reference). We present formulae for estimating relative risk and its confidence interval, adapted for the unequal sample inclusion probabilities employed in EMAP surveys. For a recent EMAP survey of streams in five Mid-Atlantic states, we estimated the relative extents of eight stressors as well as their relative risks to aquatic macroinvertebrate assemblages, with assemblage condition measured by an index of biotic integrity (IBI). For example, a measure of excess sedimentation had a relative risk of 1.60 for macroinvertebrate IBI, with the meaning that poor IBI conditions were 1.6 times more likely to be found in streams having poor conditions of sedimentation than in streams having good sedimentation conditions. We show how stressor extent and relative risk estimates, viewed together, offer a compact and comprehensive assessment of the relative importances of multiple stressors.