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"name": "Using fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA",
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"abstract": "The development of indicators to assess relative freshwater condition is critical for management and conservation. Predictive modeling can enhance the utility of indicators by providing estimates of condition for unsurveyed locations.\u00a0Such approaches grant understanding of where \u201cgood\u201d and \u201cpoor\u201d conditions occur and provide insight into landscape contexts supporting such conditions. However, as assessments are conducted at large extents crossing jurisdictional boundaries, combined datasets are likely not suited for traditional assessment approaches which rely on jurisdictionally-specific reference sites. Here, we used a large dataset compiled from multiple providers to assess the condition of fish habitat for non-tidal streams and rivers in the Chesapeake Bay watershed\u00a0(CBW), USA. We concurrently used community and species-level analyses to provide a more holistic view of habitat conditions by using random forest\u00a0models\u00a0to predict\u00a0selected\u00a0metrics\u00a0and species occurrence with landscape data for\u00a0inland CBW stream reaches.\u00a0Community analyses included metrics describing composition, tolerances, habitat preferences, and functional traits of fish communities whereas species-level analyses consisted of distribution models for key sensitive and gamefish species. For community analyses, a final index was calculated as the average of\u00a0selected\u00a0metric deciles\u00a0with higher scores inferring\u00a0less biologically altered (i.e., better) conditions, providing an alternative to using reference sites.\u00a0For species analyses, species occurrence was predicted\u00a0for\u00a0stream reaches, with presence indicating suitable habitat. Uncertainty was calculated for both approaches using model prediction intervals.\u00a0Results indicated different numbers of suitable metrics for each region,\u00a0with most in the Northern Appalachian (15) and least in the Southern Appalachian Piedmont (3). Four species\u00a0(three sensitive)\u00a0were suitable for modeling.\u00a0At the CBW scale, predictions\u00a0did not vary\u00a0greatly\u00a0among deciles\u00a0for the community or species analyses for 2001, 2006, 2011, and 2016. Most stream reaches did not vary in mean decile rank or in species occurrence between 2001 and 2016; however, the largest community changes occurred in large rivers in the Coastal Plains\u00a0ecoregion and the largest species occurrence changes occurred in Torrent Suckers in medium-sized rivers. When compared, results from community analyses agreed for one\u00a0sensitive\u00a0species (Brook Trout) but not\u00a0the other three, potentially due to regionally inappropriate tolerance assignment. Comparisons also demonstrated substantial variation among approaches suggesting a lack of redundancy. While each approach traditionally has its targeted audience and respective strengths and weaknesses, concurrent use of these approaches permits direct comparisons and may assuage shortcomings of each approach when considered separately.",
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