Bayesian hierarchical modeling of larval walleye (Sander vitreus) abundance and mortality: Accounting for spatial and temporal variability on a large river

摘要: Abstract Larval fish are extremely variable in space and time while sampling of populations is generally restricted incomplete. However, estimates abundance mortality important for understanding population dynamics, habitat quality, anthropogenic impacts. Acknowledging addressing variability during data analysis imperative to producing informative estimates. A combination spatially temporally distributed ichthyoplankton Bayesian hierarchical state-space modeling was used partition variance estimate larval walleye ( Sander vitreus ) the Maumee River 2010 2011. System degree coverage have a direct impact on quality Small scale factors (i.e., within site day-to-day) accounted most variation densities, therefore should concentrate capturing these sources. can improve by sharing information through time, properly accounting uncertainty, probability distribution based highly difficult sample; however, application methods process lead improved informed management actions.