Enhancing the predictive power of population dynamics models for highly migratory fish species with the use of data from advanced survey technologies

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This study aims to enhance the accuracy and predictive power of population dynamics models for highly migratory fishes with the use of advanced survey technology data. The objectives include: (1) Formulate and fit area-, and seasonally-structured population dynamics models to data obtained from electronic data storage, radio-telemetry and conventional tags, and stock identification (ID) studies, i.e., genetic and micro-constituent (MC) analyses of fish body parts. (2) Evaluate the potential reductions in bias in abundance estimates obtained from models fitted to these data compared to models fitted to more commonly used data such as fisheries dependent data and conventional tagging data only. (3) Project the models to evaluate the potential biological consequences of alternative management actions for the fish populations studied. (4) Evaluate the hypothesis that multi-century episodes of exploitation in the Pacific and Mediterranean populations of bluefin tuna have caused genetic adaptations for lower, i.e., 4 yr age at maturity in these populations compared to that of 12 yrs in the Southern Ocean and Gulf of Mexico populations. New stock assessment models are to be developed for Atlantic and Pacific bluefin tuna that are fitted to records from conventional, pop-up and archival tagging studies and genetic stock IDs from some of these fish. Statistical methods to reconstruct seasonal and ontogenetic migrations of individual white sturgeon are to be developed. Migration pathway models will be fitted to mark-recapture, radio-telemetry, fin ray MC data for 100 Nechako River sturgeon. Multivariate statistical methods will be applied to the reconstructed migration histories to identify different spawning populations. These results will be utilized as inputs to spatially and stock structured population dynamics models that are to be fitted to available mark-recapture data to estimate total annual survival rates and abundance of the one or more spawning stocks. The research offers to improve understanding of fish migratory behaviours, population structure and dynamics, the reliability of predictions from population dynamics models, and the design of recovery activities, and offers methodologies for application to other populations.