IAN Seminar Series

A recent assessment of stream habitat conditions was used to construct a model f brook trout distributions throughout their native range in the Chesapeake Bay. Our approach uses very large datasets and machine learning statistics to quantify conditions at the stream segment level (64,000 stream segments) and accumulated conditions at the watershed scale. Through this assessment we are able to quantify current conditions, likely historic conditions in the absence of stress, and stream-to-stream level measures of stress associated with mining, agriculture, and urbanization. Model results are then integrated into a web-based GIS modeling tool that can be used for interactive visualization, conservation prioritization, and quantitative scenario analysis. When coupled with climate change predictions and large river species models, the brook trout will provide a powerful means for optimizing restoration actions that will produce measurable benefits to stream habitats and fish populations throughout the bay watershe