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.

The effects of urbanization on Lepomis macrochirus using the comet assay.

Urbanization has been linked to increased concentrations of polycyclic aromatic hydrocarbons in natural waterways. This study was designed to examine the impact of urbanization and a wastewater treatment plant by investigating the impact on field-collected bluegill (Lepomis macrochirus). Results show a significant increase in DNA strand breaks in blood cells (comet assay) linked to urbanization and a reduction in DNA strand breaks downstream of the WWTP, likely the result of dilution. A laboratory study exposing L. macrochirus to the known mutagen, methyl methanesulfonate, was performed to validate the comet assay endpoints in this species. Results of the laboratory study showed that the comet assay endpoints of tail length and tail extent moment responded in a dose- and time-dependent manner. Habitat quality assessments, along with chemical concentrations of polycyclic hydrocarbons in sediments showed that habitat quality between all sites were similar and that hydrocarbons likely contributed to the DNA strand breaks observed.