Advanced fish stock assessment models

先进的鱼类种群评估模型

• 批准号: RGPIN-2016-04307
• 负责人: Cadigan, Noel
• 金额: $ 2.04万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753471
• 关键词: Advanced; fish; stock; assessment; models

Increasingly consumers want to buy fish that is caught sustainably - meaning that the fishery is not affecting the health of future fisheries. Although it can be difficult to decide if a fishery is sustainable, the United Nations Food and Agricultural Organization (FAO) and other organizations have developed detailed standards to help assess this. In Canada many fisheries have pursued certification with the International Marine Stewardship Council (MSC), which is a major organization involved in setting standards for sustainable fishing practices and certifying that fisheries meet these standards. MSC certified fish can result in better market access and improved prices to harvesters, leading to sustainable and more profitable fisheries in the long-term. This research program will focus on quantifying if existing fisheries harvest strategies (e.g. catch levels) are sustainable and proposing better alternatives when necessary. A related and important challenge in fish stock assessment is providing short (1-3 years) and medium-term (3-10 years) quantitative projections of the impacts of future management actions on changes in stock size. Mathematical models are used for these purposes and these models are based on the birth, growth, and death processes of the stock. Information available on these processes may come from large scale surveys or smaller but high intensity surveys. The complexity of the information and varying spatial scales is a problem for stock assessment. Best practice is evolving and case-specific.The objectives of this program are to develop novel integrated and spatial stock assessments models. An integrated model strives to include all relevant data on stock productivity which is necessary to ensure that management decisions are based on the best possible information. Spatial models are required to include data sources from a range of spatial scales. Equally important, the productivity of a fish stock may depend on its spatial distribution. Initial applications will include Atlantic cod and snow crab. Integrated and spatial stock assessment models for such species do not exist because of the complexity of the species life-history processes and available data. Such models will be used to evaluate short to medium-term impacts of future harvest levels which will be important contributions to MSC certification initiatives for these stocks. These models will also be used to evaluate and optimize harvest strategies, with the objective of prosperous and sustainable fisheries.This project will provide advanced training opportunities for students to develop skills for stock assessment and to assist governments and the fishing industry with their fisheries sustainability objectives and contribute to more prosperous fisheries in the future. Such skills are in high demand internationally and within Canada.

越来越多的消费者想购买可持续捕获的鱼类 - 这意味着渔业不会影响未来渔业的健康。尽管很难确定渔业是否可持续，但联合国食品和农业组织（FAO）和其他组织已经制定了详细的标准以帮助评估这一点。在加拿大，许多渔业已与国际海洋管理委员会（MSC）获得认证，该委员会是一个主要组织，涉及为可持续捕鱼实践制定标准，并证明渔业符合这些标准。 MSC认证的鱼可以使收割机的市场获得更好的市场获取和提高的价格，从而导致可持续性和更有利可图的渔业。该研究计划将着重于量化现有的渔业收获策略（例如，捕捞水平）是否可持续，并在必要时提出更好的替代方案。鱼类库存评估的相关挑战是简短（1 - 3年）和中期（3 - 10年）的定量预测，对未来管理措施对股票变化的影响的影响。数学模型用于这些目的，这些模型基于股票的出生，生长和死亡过程。有关这些过程的信息可能来自大规模调查或较小但高强度调查。信息的复杂性和不同的空间尺度是库存评估的问题。最佳实践是不断发展和特定于病例的。该计划的目标是开发新颖的集成和空间库存评估模型。综合模型努力包括所有有关股票生产力的相关数据，这是确保管理决策基于最佳信息所必需的。空间模型必须包括来自一系列空间尺度的数据源。同样重要的是，鱼类种群的生产率可能取决于其空间分布。最初的应用将包括大西洋鳕鱼和雪蟹。由于物种生命历史的过程和可用数据的复杂性，因此不存在该物种的综合和空间库存评估模型。此类模型将用于评估未来收获水平的短期至中期影响，这将是对这些股票的MSC认证计划的重要贡献。这些模型还将用于评估和优化收获策略，以繁荣和可持续的渔业为目标。该项目将为学生提供高级培训机会，以开发股票评估的技能，并协助政府和渔业以其渔业的可持续性目标，并在未来为更繁荣的渔业做出贡献。这种技能在国际和加拿大境内的需求量很高。