Abstract:
The choice of study species when conducting environmental assessments of hydropower facilities is of great importance from a licensing and policy perspective. Power analyses are commonly used to provide quantitative backing for the numbers of study organisms and trials used, but there is not frequent use of quantitative methods for choosing appropriate study species. Species choice can be especially important when measuring the impacts of ecosystem alteration, such as in a hydropower system, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. In this study, we step through two examples using a combination of GIS, a fish traits database, and multivariate statistical analyses to present a quantitative, traits-based approach for designating study species. In our first example, we present a case study where we select broadly-representative fish species for understanding the effects of turbine passage on fishes based on traits that suggest sensitivity to turbine passage. In our second example, we build off of our first example and 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 also delineating the expanded inference space of study results
