Informative priors assess tradeoffs between mark-recapture and telemetry-based fish movement in a large river system

Telemetry and mark-recapture provide movement information, but each approach comes with tradeoffs, potentially producing conflicting understandings of fish movement patterns. Using a Bayesian framework that allows exchanging priors from either method may help assess these inconsistencies. We evaluated channel catfish Ictalurus punctatus movements in the Red River of the North and Lake Winnipeg system, which impacts harvest management across different jurisdictions and affects different ecosystems (e.g., lotic and lentic). Channel catfish were tagged with T-bar tags or acoustic transmitters. The resulting movement data were modeled using a Bayesian multi-state Cormack-Jolly-Seber model to estimate survival, movement, and recapture probabilities. Model estimates with uninformative priors showed a greater tendency of downstream movement from the Red River into Lake Winnipeg for the T-bar tags. In contrast, the telemetry method showed fish predominantly stay in the river. However, exchanging increasingly stronger prior information from the alternative method's model revealed that telemetry movement estimates were less sensitive than the T-bar model to informative priors. Using priors from both methods provided a transparent means to assessing tagging approach tradeoffs quantitatively.

Automated summary

Telemetry and mark-recapture methods can provide inconsistent understandings of fish movement patterns. Using a Bayesian framework can help assess these inconsistencies and provide a transparent means of tradeoff evaluation in tagging approaches.