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

拟议的研究旨在提高人口动态模型的预测能力，高度洄游的iteroparous鱼类，如大西洋蓝鳍金枪鱼（Thunnus thyunnus），白色鲟鱼（Acipenser transmontanus）和公牛鳟鱼（Salvelinus confluentus）。主要目标是扩大和改进各种方法，以便对从使用先进调查技术的研究中获得的高质量数据进行统计分析，这些技术包括地理范围广泛的电子数据存储标签、无线电遥测、声波发射标签-接收器系统以及鱼类身体各部分的遗传和元素微成分组成分析。已经有了解释多次生育的高度洄游物种季节性行为的种群动态模型，但在种群亚组成部分的行为差异如何影响种群动态模型结果和政策评价方面，仍存在相当大的不确定性。拟议的研究将（1）扩展种群动态模型，以更准确地解释亚种群和空间结构，（2）将模型与不同类型的高质量数据以及常规渔业开发数据相结合，以估计模型参数，（3）将模型应用于评估种群状况和渔业及栖息地管理政策选择。这项研究的目的是更好地了解共同出现的种群组成部分在季节性迁移模式、成熟年龄、自然死亡率和体细胞生长和开发历史方面的一系列差异对渔业管理的影响。经改进的种群动态模型一旦与扩大的数据集相吻合，将用于重新评价种群状况和渔业管理备选办法的潜在后果。

The proposed research aims to enhance the predictive power of population dynamics models for highly migratory iteroparous fishes such as Atlantic bluefin tuna (Thunnus thyunnus), white sturgeon (Acipenser transmontanus) and bull trout (Salvelinus confluentus). The chief objective is to extend and improve methodologies to statistically analyze high quality data obtained from studies that have used advanced survey technologies, for example, geographically extensive electronic data-storage tags, radio-telemetry, acoustic transmitter tag-receiver systems, and genetic and elemental micro-constituent composition analyses of fish body parts. Population dynamics models that account for seasonal behaviours for iteroparous highly migratory species already exist but considerable uncertainty remains over how differences in the behaviours of population subcomponents can affect population dynamics model results and policy evaluations. The proposed research will (1) extend population dynamics models to more accurately account for subpopulation and spatial structure, (2) fit the models to different types of high quality data together with conventional fisheries exploitation data to estimate model parameters, and (3) apply the models in evaluations of population status and fisheries and habitat management policy options. The research will be designed to improve understanding of the implications for fisheries management of suites of differences between co-occurring population components in their seasonal migration patterns, age at maturity, natural mortality rates and somatic growth and exploitation histories. The improved population dynamics models, once they have been fitted to the extended data sets, are to be applied to re-evaluate population status and the potential consequences of fisheries management options.