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大西洋蓝鳍金枪鱼(Thunnus Hyunnus)、白鲟鱼(Acipenser Transmontanus)和牛鲑鱼(Salvelinus Confluentus)等高度迁徙的陆栖鱼类种群动力学模型的预测能力。主要目标是推广和改进方法，以统计分析从研究中获得的高质量数据，这些研究使用了先进的调查技术，例如地理上广泛的电子数据储存标签、无线电遥测、声学发射器标签-接收器系统以及鱼类身体部分的遗传和元素微量成分分析。现有的种群动态模型可以解释高度迁徙物种的季节性行为，但种群各组成部分的行为差异如何会影响种群动态模型的结果和政策评价，仍然存在相当大的不确定性。拟议的研究将(1)扩展种群动力学模型，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和常规渔业开发数据进行拟合，以估计模型参数；(3)将模型应用于种群状况以及渔业和生境管理政策选择的评估。这项研究的目的将是更好地了解同一种群在季节性迁徙模式、成熟年龄、自然死亡率以及体细胞生长和捕捞史方面的差异对渔业管理的影响。改进的种群动态模型一旦适用于扩展的数据集，将用于重新评估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.