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Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring stream habitats is needed, as this provides a physical template upon which stream biodiversity is organized and maintained. To adequately represent the heterogeneity of stream ecosystems, such a classification needs to be spatially extensive where multiple stream habitat components are represented at the highest resolution possible. Herein, we present a multi-layered empirically-driven stream classification system for the conterminous US, constructed from over 2.6 million stream reaches within the NHDPlus V2 stream network. The classification is based on emergent natural variation in six habitat layers meaningful at the stream-reach resolution: size, gradient, hydrology, temperature, network bifurcation, and valley confinement. To support flexibility of use, we provide multiple alternative approaches to developing classes and report uncertainty in classes assigned to stream reaches. The stream classification and underlying data provide valuable resources for stream conservation and research.

Environmental mitigation plays an important role in the environmentally sustainable development of 2 hydropower resources. However, comprehensive data on mitigation required by the Federal Energy 3 Regulatory Commission (FERC) at United States (US) hydropower projects is lacking. Therefore, our 4 objective was to create a comprehensive database of mitigation required at non-federal hydropower 5 projects and provide a synthesis of available mitigation data. Mitigation data was collated for over 300 6 plants licensed or relicensed from 1998 through 2013. We observed that the majority of FERC mitigation 7 requirements deal with either hydrologic flows or recreation and that hydropower plants in the Pacific 8 Northwest had the highest number of requirements. Our data indicate opportunities exist to further 9 explore hydropower mitigation in the areas of environmental flows, fish passage, and water quality. 10 Connecting these data with ecological outcomes, actual flow data, and larger landscape level information 11 will be necessary to evaluate the effectiveness of mitigation and ultimately inform regulators, managers, 12 and planners.

The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species of interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. We suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.