Modeling the effects of environmental variability on marine zooplankton dynamics and production

气候变化正在深刻影响海洋生态系统，从食物链底部的初级生产者到鱼类和鲸鱼等大型捕食者。我们需要能够预测未来的变化，以便可持续地管理我们在生态和经济上具有重要意义的海洋资源，包括价值数十亿美元的渔业。在这方面，必须了解气候如何影响海洋浮游动物的动态和生产，因为它们是海洋食物链的关键环节，它们作为捕食者和猎物的作用调节着海洋生态系统的结构和功能。这项工作将开发和应用模型，以量化环境变化如何影响海洋浮游动物的种群动态，目标是推进浮游动物生态学，提高预测能力，并为决策者和环境管理人员提供重要信息。 短期项目将针对两个物种，这两个物种是全世界不同区域的主要浮游动物，也是重要经济鱼类的主要猎物。模拟将确定上游与当地过程、平流与死亡率、繁殖与捕食的相对重要性，以及确定对年际变化影响最大的关键环境变量。这些见解可以纳入基于生态系统的渔业模式，以提高管理能力。模型代码将提供给科学界，以便它可以用于正在进行的和未来的建模工作，以及用于学术目的。这项工作还将涉及与国家和国际科学家的合作，并支持研究生和本科生在应用数学方法，战略模拟和数据分析方面的培训。

Climate change is profoundly affecting marine ecosystems, from the primary producers at the bottom of the food chain to large predators like fish and whales. We need to be able to anticipate future changes in order to sustainably manage our ecologically and economically important marine resources, including multi-billion dollar fisheries. In this regard, it is critical to understand how climate influences the dynamics and production of marine zooplankton, as they are key links in marine food chains, and their roles as both predator and prey regulate marine ecosystem structure and function. This work will develop and apply models to quantify how changes in the environment affect the population dynamics of marine zooplankton, with the goals of advancing zooplankton ecology, improving predictive capabilities and providing crucial information to policy makers and environmental managers. Short-term projects will target two species that are dominant zooplankton in various regions throughout the world, and are major prey items for economically important fish. Simulations will determination of the relative importance of upstream vs. local processes, advection vs. mortality and reproduction vs. predation, as well as identification of the key environmental variables most influencing interannual variability. Such insights can be incorporated into ecosystem-based fisheries models to enhance management capabilities. The model code will be made available to the scientific community, so that it can be used in ongoing and future modeling efforts, as well as used for academic purposes. The work will also involve collaboration with national and international scientists, and support the training of graduate and undergraduate students in applied mathematical methods, strategic simulation, and data analyses.