Modeling Migration of Silver Eels to Forecast Critical Intervals of Risk

Populations of eels are in decline worldwide.  One potentially significant source of mortality may occur at hydroelectric facilities during the downstream migration of adult silver eels.  To help mitigate this mortality, a tool that can forecast migratory events could be of great use to managers that aim to reduce dam mortality while minimizing disruption of power generation at hydroelectric facilities.  A number of studies have demonstrated relationships between downstream movements of silver eels and environmental events; however, there have been few attempts to summarize this available information into a predictive framework.  Herein, we assess the utility of Bayesian hierarchical modeling methods to forecast the probability of migratory events of silver eels.  We compare two approaches that combine information on daily counts of migrating eels with information on environmental conditions to predict migration.  We apply our modeling approach to multiple datasets of migrating eels and assess the ability to forecast migration in systems that are both data rich and data poor.  The hierarchical framework we adopt combines information from a number of sources to provide robust estimates of the probability of eel migration and provides a flexible forecasting tool to aid managers in making decisions in regards to reducing turbine mortality.