Quantifying flow-ecology relationships across flow regime class and ecoregions in South Carolina.

The natural flow regime (i.e. magnitude, frequency, duration, timing and rate of change of flow events) is crucial for maintaining freshwater biodiversity and ecosystem services. Protecting instream flow from anthropogenic alterations first requires an understanding of the relationship between aquatic organisms and the flow regime. In this study, we used a unique framework based on random forest modeling to quantify effects of natural flow regime metrics on fish and macroinvertebrate assemblages across ecoregions and flow regime types in the state of South Carolina, USA. We found that all components of the natural flow regime affected both fish and benthic macroinvertebrate assemblages, suggesting that maintaining natural aspects of all flow regime components is critical for protecting freshwater diversity. We identified hydrologic metrics and flow regime components such as magnitude, frequency, and duration of flow events, that were associated with the greatest ecological responses for individual stream classes to help managers prioritize hydrologic and biological metrics of interest during environmental flow standard development. The response of aquatic organisms to hydrologic metrics varied across stream classifications and ecoregions, highlighting the importance of accounting for differences in flow regime and ecoregion when designing environmental flow standards. We provide a flexible framework based on statistical flow-ecology relationships that can be used to inform instream flow management and assess effects of flow alteration on riverine assemblages.

Integrating Regional Frameworks and Local Variability for Riverine Bioassessment.

Regional frameworks enable bioassessment methods to detect anthropogenic effects on ecosystems amid natural variability. Conventional approaches to regionalization have used coarse geographical frameworks to separate sites similar in their ecological (ecoregion) or faunal (basin) characteristics. Expectations for individual streams are then adjusted for within-region variability in local environmental characteristics. Integrating regional frameworks and local variability may improve the sensitivity and performance of bioassessments. In this study, we used a biologically-informed stream classification to develop an integrated regional framework for bioassessment considering the effects of ecoregion, basin, and local environmental variables on wadeable stream fish communities of South Carolina, USA. Our integrated framework was compared against conventional regional frameworks indexing ecoregions or basins alone. Frameworks were evaluated by their ability to (1) efficiently partition community variation and (2) allow for the detection of anthropogenic effects on fish communities. We found an integrated framework better described natural variability in stream fish communities. In addition, we found highly regional relationships between fish metrics and anthropogenic disturbance among frameworks, suggesting appropriate bioassessment metrics will differ across regions in our study area. Differences in community response to disturbance among frameworks emphasize the importance of testing metrics for their hypothesized sensitivity before using them in bioassessment. This study ultimately supports the integration of regional frameworks across spatial scales to classify streams for bioassessment, and provides an analytical framework from which to evaluate biotic variation and metric utility in the context of bioassessment.

Incorporating Network Connectivity into Stream Classification Frameworks.

Stream classification frameworks are important tools for conserving aquatic resources. Yet despite their utility, most classification frameworks have not incorporated network connectivity. We developed and compared three biologically informed stream classification frameworks considering the effects of variables indexing local habitat and/or connectivity on stream fish communities. The first framework classified streams according to local environmental variables largely following the precedent set by previous stream classifications. The second framework classified streams according solely to network connectivity variables, while the third framework considered both local and connectivity variables. Using fish community data from 291 wadeable streams in South Carolina, USA, we used conditional inference tree analyses to identify either seven or eight discrete types of wadeable streams within each framework. Classifications were evaluated on their ability to describe community composition at a subset of sites not used in model training, and canonical correspondence analysis suggested that each framework performed similarly in describing overall community variation, with about 19% of variation explained. After accounting for the effects of biogeography and land use in our analytical approach, each classification explained a substantially higher amount of community variation with 46% of variation explained by our connectivity-informed classification and 42% explained by our locally informed classification. Classifications differed in their ability to describe elements of community structure; a classification incorporating connectivity predicted species richness better than the one that did not. This study ultimately addresses an important knowledge gap in the classification literature while providing broader implications for the conservation of aquatic organisms and their habitats.

Linking stream and landscape trajectories in the southern Appalachians.

A proactive sampling strategy was designed and implemented in 2000 to document changes in streams whose catchment land uses were predicted to change over the next two decades due to increased building density. Diatoms, macroinvertebrates, fishes, suspended sediment, dissolved solids, and bed composition were measured at two reference sites and six sites where a socioeconomic model suggested new building construction would influence stream ecosystems in the future; we label these "hazard sites." The six hazard sites were located in catchments with forested and agricultural land use histories. Diatoms were species-poor at reference sites, where riparian forest cover was significantly higher than all other sites. Cluster analysis, Wishart's distance function, non-metric multidimensional scaling, indicator species analysis, and t-tests show that macroinvertebrate assemblages, fish assemblages, in situ physical measures, and catchment land use and land cover were different between streams whose catchments were mostly forested, relative to those with agricultural land use histories and varying levels of current and predicted development. Comparing initial results with other regional studies, we predict homogenization of fauna with increased nutrient inputs and sediment associated with agricultural sites where more intense building activities are occurring. Based on statistical separability of sampled sites, catchment classes were identified and mapped throughout an 8,600 km(2) region in western North Carolina's Blue Ridge physiographic province. The classification is a generalized representation of two ongoing trajectories of land use change that we suggest will support streams with diverging biota and physical conditions over the next two decades.