Accurate estimation of post-release survival is fundamental to fisheries stock assessment and effective management. Conventional tag-return studies and acoustic telemetry are commonly used to estimate this probability, yet each approach has limitations when applied independently. Using gag (Mycteroperca microlepis) as a case study, we integrated data from a large-scale conventional tagging program and an acoustic telemetry experiment into a discrete-time statistical modeling framework that links relative recapture risk with telemetry-derived fate. This approach enabled estimation of post-release survival across a broad gradient of depths representative of recreational fishing conditions. Estimated survival was high in shallow waters (≈96%) but declined with increasing depth, consistent with depth-related barotrauma. Applying model predictions to data from the recreational fishery yielded annual and monthly post-release survival probabilities. Annual estimates were consistent with values assumed in recent stock assessments, while monthly values highlighted seasonal patterns relevant for management. This integrated framework advances post-release survival estimation by combining the extensive sample sizes and environmental coverage characteristic of conventional tagging data with the individual-level fate inference provided by acoustic telemetry, and offers a transferable approach applicable to other highly targeted fishery species.
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Hyman et al. (2026) studied this question.
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