Estimation of survival and detection probabilities for multiple tagged salmon stocks with nested migration routes, using a large-scale telemetry array

Abstract

Mark–recapture models for estimating survival and detection probabilities of tagged animals that migrate past successive receiver stations can incorporate multiple, linked stocks to improve detection probability estimates. When multiple release groups are analysed in a common framework, detection information can be shared to compensate for small sample sizes and provide generality beyond single-stock approaches. Methods for structuring complex detection history data and applying standard mark–recapture models are presented, allowing for information sharing among multiple stocks under nested migration route structures, where some portions of routes are shared with other stocks and other portions are unique. Possible biases from split-route migration patterns within a release group are described, along with a simple method of correcting these biases using stock-specific parameters that incorporate movement probabilities. Environmental covariates can be paired with stock-specific run timing data to model stock-specific detection probabilities that change seasonally. Finally, a method for assessing the redundancy of receivers on a multiple-receiver detection line is described, based on considerations of receiver line geometry. Examples are drawn from detection data of juvenile salmon on the Pacific Ocean Shelf Tracking Project (POST) array, but the methods presented here are transferable to other systems.