Predictive power and risk assessment for marine fisheries in Canada

加拿大海洋渔业的预测能力和风险评估

• 批准号: RGPIN-2014-03934
• 负责人: Cox, Sean
• 金额: $ 1.75万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=566185
• 关键词: Predictive; power; risk; assessment; marine

All fisheries exist within feedback systems that link harvest decisions to highly uncertain environment-fish stock dynamics. Failure rates of historical fishery management procedures, combined with the possibility that environment-stock interactions are changing faster than we can learn about them, raises concerns about our ability to accurately predict risks of future fishery failure. I propose research aimed at improving fishery models used to represent environment-stock interactions in fishery management strategy research. I will use (i) empirical analyses to test fishery model predictive power, (ii) empirical and simulation models to evaluate mechanistic hypotheses to explain changes in key population dynamics processes, and (iii) simulation of fishery management systems to identify how perceptions of risk depend on underlying model assumptions. Fishery system simulations integrating realistic ecological processes into fishery management planning will help identify critical knowledge gaps that affect risks in Canadian fisheries. Our broad selection of species will increase both the power of specific case studies and the broader relevance to management strategy evaluation research.

所有渔业都存在于反馈系统中，该系统将捕捞决定与高度不确定的环境鱼类种群动态联系起来。历史上渔业管理程序的失败率，加上环境-种群相互作用的变化速度可能比我们所能了解的要快，这引起了人们对我们准确预测未来渔业失败风险的能力的担忧。我提出的研究，旨在改善渔业模型用于代表渔业管理战略研究中的环境-股票的相互作用。我将使用（i）实证分析来测试渔业模型的预测能力，（ii）实证和模拟模型来评估机制假设，以解释关键种群动态过程的变化，以及（iii）模拟渔业管理系统，以确定风险感知如何取决于基础模型假设。渔业系统模拟将现实的生态过程纳入渔业管理规划，将有助于确定影响加拿大渔业风险的关键知识差距。我们对物种的广泛选择将增加具体案例研究的力量和管理战略评估研究的更广泛相关性。