Impact of Extreme Streamflows on Brook Trout Young-of-Year Abundance

An understanding of how extreme streamflows influence ecological outcomes is necessary to prioritize, protect and restore ecosystems threatened by climate change and other human impacts. Highly sensitive to stream flows and temperature, salmonids, such as brook trout, are often used as ecological indicators. Unfortunately, streamflow measurements at brook trout sampling sites are rarely available, making it difficult to assess the relationship between flows and trout abundance. In this study, a long-term dataset of brook trout counts from 29 years across 115 sites in Shenandoah National Park (SNP) was used to assess the utility of predicted extreme streamflows for improving our understanding of brook trout young-of-the-year (YOY) abundance. High and low streamflows at ungaged trout sampling sites were predicted using regional regression equations based on gaged flows at nearby unregulated sites. We assessed a range of flow metrics with the goal of identifying which metrics were most closely related to variations in brook trout YOY abundance. Bayesian hierarchical models which allowed coefficients on predicted streamflows to vary by site and accounted for imperfect detection of brook trout were used. We found that estimates of extreme streamflows are important predictors of next summer brook trout YOY abundance in SNP. These findings can help inform streamflow targets and thereby promote environmental conservation and management. For areas with similar data scarcity challenges, these methods can be used to predict the response of other species to extreme flows. In many regions, extreme hydrologic events are expected to increase with climate change, making an understanding of the relationship between extreme streamflows and population resilience particularly important.