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

利用先进调查技术的数据增强高度洄游鱼类种群动态模型的预测能力

• 批准号: 342570-2008
• 负责人: McAllister, Murdoch
• 金额: $ 1.58万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=497543
• 关键词: Enhancing; predictive; power; population; dynamics

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.

本研究旨在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。这些目标包括：（1）根据从电子数据储存、无线电遥测和传统标签以及种群识别研究中获得的数据，制定并拟合区域和季节性结构种群动态模型，即：鱼体各部分的遗传和微量成分分析。(2)评价与更常用的数据（如依赖渔业的数据和仅常规标记数据）拟合的模型相比，从拟合这些数据的模型获得的丰度估计值偏差的可能减少。(3)设计模型，以评估替代管理行动对所研究鱼类种群的潜在生物后果。(4)评估以下假设：太平洋和地中海蓝鳍金枪鱼种群的多个世纪的开发事件已导致遗传适应性降低，即，4岁的成熟年龄在这些人群相比，在南大洋和墨西哥湾人口的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，这些模型将与传统、弹出式和档案标记研究的记录以及其中一些鱼类的遗传种群编号相匹配。统计方法重建季节性和个体发育迁移的个别白色鲟鱼的发展。迁移路径模型将适合标记-再捕获，无线电遥测，鳍射线MC数据为100 Nechako河鲟鱼。多元统计方法将应用于重建的迁移历史，以确定不同的产卵种群。这些结果将被用作空间和种群结构化种群动态模型的投入，这些模型将与现有标记-再捕获数据拟合，以估计一个或多个产卵种群的总年存活率和丰度。这项研究有助于更好地了解鱼类洄游行为、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。