Predicting fish production from lake size using novel measurement strategies of fish behavior

使用鱼类行为的新颖测量策略根据湖泊大小预测鱼类产量

• 批准号: 556300-2020
• 负责人: McMeans, Bailey
• 金额: $ 7.14万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705885
• 关键词: Predicting; fish; production; lake; size

Freshwater fish are an exceptionally important resource to Canadians. Disturbingly, recent research demonstrates some recreational fisheries are suffering from hidden collapses; fish production (i.e. the amount of new tissue generated per area per year) is declining while harvest (kg yr-1) remained constant, leading to overharvest. Fisheries closure due to declining production and overharvest is an enormous economic and cultural threat to Canadians and indigenous peoples, and to global society as a whole. Currently, however, whether fish production is declining across Canada's inland lakes remains unknown. Warming global temperatures that affect fish habitat also remain a looming uncertainty for fish production and sustainable harvest into the future. A major knowledge gap facing fisheries managers is how fish habitat use and production change predictably through time (seasonally and interannually) and from small to large lakes. The partnership between 4 Universities and the Ontario Ministry of Natural Resources and Forestry (OMNRF) will address this knowledge gap by using an easily measured variable, lake size, to predict fish habitat use and production. To do so, we will generate highly resolved data on fish habitat use (i.e. position in the lake) and diet, using acoustic telemetry and stable isotopes, in 3 co-occuring species of recreational and cultural value: lake trout (Salvelinus namaycush), cisco (Coregonus artedi), and smallmouth bass (Micropterus dolomieu). Our novel approach will, for the first time, quantify habitat and diet overlap among 3 species throughout all seasons and across 5 years in a small, intermediate and large-sized lake, simultaneously. The results will provide fisheries managers with an unprecedented ability to predict fish habitat use and production from easily measured lake characteristics. Our findings will shed fundamental new light on the importance of seasonal variation, including poorly studied winter periods, in structuring species interactions and shaping fish behavior across a lake size gradient. The results will lead to new fisheries management methods and policies that will be applied broadly Canada-wide to benefit all Canadians by helping protect freshwater fishes into the future.

淡水鱼对加拿大人来说是非常重要的资源。令人不安的是，最近的研究表明，一些休闲渔业正在遭受隐性崩溃;鱼类产量（即每年每面积产生的新组织数量）正在下降，而收获量（千克yr-1）保持不变，导致过度捕捞。由于产量下降和过度捕捞而关闭渔业对加拿大人和土著人民以及整个全球社会都是一个巨大的经济和文化威胁。然而，目前，加拿大内陆湖泊的鱼类产量是否正在下降仍不得而知。影响鱼类栖息地的全球气温变暖也仍然是未来鱼类生产和可持续收获的不确定性。渔业管理人员面临的一个主要知识缺口是鱼类栖息地的使用和生产如何随着时间的推移（季节性和年际）以及从小型湖泊到大型湖泊的可预测变化。4所大学和安大略省自然资源和林业部（OMNRF）之间的伙伴关系将通过使用一个易于测量的变量，湖泊大小，来预测鱼类栖息地的使用和生产，以解决这一知识差距。要做到这一点，我们将产生高度分辨率的数据，鱼类栖息地的使用（即在湖中的位置）和饮食，使用声学遥测和稳定同位素，在3个共存的物种的娱乐和文化价值：湖鳟鱼（红点鲑namaycush），思科（白鲑artedi），和smallmouth低音（Micropterus bassieu）。我们的新方法将首次在一个小型，中型和大型湖泊中，同时在所有季节和5年内量化3种物种之间的栖息地和饮食重叠。研究结果将为渔业管理人员提供前所未有的能力，从容易测量的湖泊特征预测鱼类栖息地的使用和生产。我们的研究结果将揭示季节性变化的重要性，包括研究不足的冬季，在构建物种相互作用和塑造鱼类行为在湖泊大小梯度。研究结果将产生新的渔业管理方法和政策，这些方法和政策将在加拿大范围内广泛应用，通过帮助保护未来的淡水鱼类，使所有加拿大人受益。