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

本研究的目的是利用先进的调查技术数据，提高高度洄游鱼类种群动态模型的准确性和预测能力。目标包括：(1)建立区域和季节性结构的种群动力学模型，并将其与电子数据存储、无线电遥测和常规标签以及种群识别研究(即鱼类身体部分的遗传和微量成分分析)获得的数据相适应。(2)与适用于更常用数据的模型相比，评估根据这些数据拟合的模型获得的丰度估计值的偏差可能减少的可能性，如渔业依赖数据和传统标记数据。(3)设计模型，以评估替代管理行动对所研究的鱼类种群的潜在生物后果。(4)评估这样一种假设，即太平洋和地中海蓝鳍金枪鱼种群经过多个世纪的捕捞，导致这些种群成熟时的遗传适应年龄较低，即4岁，而南大洋和墨西哥湾种群的适应年龄为12岁。将为大西洋和太平洋蓝鳍金枪鱼开发新的种群评估模型，这些模型适用于来自常规、弹出和档案标记研究的记录以及其中一些鱼类的遗传种群ID。将开发统计方法来重建个体白鲟鱼的季节性和个体发育迁徙。迁徙路径模型将适用于100条内查科河鲟鱼的标记-再捕获、无线电遥测、鳍线MC数据。多变量统计方法将应用于重建的迁徙历史，以识别不同的产卵种群。这些结果将被用作空间和种群结构种群动力学模型的输入，这些模型将与现有的标记-重新捕获数据相适应，以估计一个或多个产卵种群的年总存活率和丰度。这项研究有助于更好地了解鱼类的迁徙行为、种群结构和动态、种群动态模型预测的可靠性以及恢复活动的设计，并提供了适用于其他种群的方法。

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.