Assessing the Risk of Rising Temperature on Brook Trout: A Spatial Dynamic Linear Risk Model

Abstract

Understanding the relationship between air temperature and water temperature is a critical component in the management of aquatic resources. One important application is for stream fisheries that have temperature-sensitive fish. Co-located devices were used to obtain air and water temperature for summer periods from 100 locations in Virginia that have native brook trout populations. We develop a dynamic spatiotemporal model that accounts for the relationship between air and water temperature, and the spatial and temporal correlation in the data. Our model allows for the inclusion of land use, solar gain and other site level characteristics that might influence the relationship. Our model also allows for predictive forecasts of the risk to fish at individual sites and one can track how the risk changes over time. The model may be used to rank sites with regard to risk, which aids management in prioritizing decisions about restoration and preservation.