Collaborative Research: NSFGEO-NERC: Using population genetic models to resolve and predict dispersal kernels of marine larvae

合作研究：NSFGEO-NERC：利用群体遗传模型解析和预测海洋幼虫的扩散内核

• 批准号: 2334798
• 负责人: Eric Crandall
• 金额: $ 81.88万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334798&HistoricalAwards=false
• 关键词: Collaborative; Research; NSFGEO; NERC; Using

Most marine organisms reproduce by creating millions of tiny planktonic larvae which are dispersed across a variety of distances and directions by ocean currents. The spatial distribution of larvae from a given population, also known as the dispersal kernel, is an important parameter both for basic understanding of marine ecology and evolution, as well as for management and conservation of marine resources. Larval dispersal kernels are often studied using computer models which simulate the dispersal of larvae within ocean circulation models. However, there are very few measurements of marine larval dispersal with which to evaluate these computer models, due the cost and infeasibility of current genetic tagging methods. This project uses isolation by distance (IbD) population models, which the project team has shown gives similar results to genetic tagging methods, but at a fraction of the cost. Dispersal kernels are thought to be shaped by both species traits, such as the amount of time spent as planktonic larvae, as well as the environment through which the larvae disperse. To tease apart the effects of species traits and regional seascapes, the team is taking advantage of the unique setting of the South Pacific, where the numerous isolated archipelagos each independently replicate the dispersal process the team is studying. Six reef-fish species at ten locations in each of the New Caledonia, Vanuatu, and Fijian archipelagic seascapes are being sampled, IbD estimates of dispersal kernels are then used to select a set of computer models, and the models are simulated across twenty years of oceanographic data (many generations of fish) and a selection of species traits. The results of this research are being used to improve the design of networks of marine protected areas in each of the archipelagos in a way that accounts for variability in larval dispersal over time. This research builds on the efforts of the Diversity of the Indo-Pacific Network (DIPnet), created by the project’s principal investigators and senior personnel to promote collaborative research on the ecology and evolution of the immense biodiversity of the Indo-Pacific. The project also provides training for postdoctoral scientists, graduate and undergraduate students, and supports capacity building workshops for local policymakers and students.Populations of most marine species are functionally, demographically, and genetically connected by planktonic dispersal of tiny larvae. Understanding the spatial distribution of dispersal events (the dispersal kernel) is a fundamental goal of marine ecology and is critical to predicting population dynamics and evolutionary outcomes. Yet, general principles for predicting dispersal outcomes across communities remain elusive. The project team is developing the first-ever data-assimilated biophysical models of larval dispersal by: 1) applying isolation-by-distance (IbD) theory to estimate mean parent-offspring distance (σIbD) for six reef fish species co-sampled and RAD-seq genotyped at three isolated South Pacific archipelagos that each replicate the IbD process with relatively continuous reef systems, 2) using empirical estimates of σIbD to constrain biophysical models of larval dispersal, which are iterated over twenty years of high-resolution hydrodynamic models, to test hypotheses about the relative role of species traits and seascape characteristics in shaping larval dispersal kernels, and 3) developing a new conservation portfolio approach to design managed area networks that capture temporal variability in larval dispersal over many generations, and engaging with local stakeholders in each archipelago to implement this approach.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

大多数海洋生物通过产生数以百万计的微小浮游幼虫来繁殖，这些幼虫通过洋流分散在不同的距离和方向上。给定种群的幼虫的空间分布（也称为分散核）是基本理解的重要参数。然而，海洋生态和进化以及海洋资源的管理和保护经常使用模拟海洋环流模型中幼虫扩散的计算机模型进行研究。由于当前基因标记方法的成本和不可行性，该项目使用距离隔离（IbD）种群模型，项目团队已证明该模型可以提供与基因标记方法类似的结果，但分散颗粒的成本被认为是由两种物种特征决定的，例如作为浮游幼虫的时间，以及幼虫分散的环境。考虑到物种特征和区域海景的影响，该团队正在利用南太平洋的独特环境，那里众多的孤立群岛各自独立地复制了该团队正在每个地点的十个地点研究的六种珊瑚鱼物种。正在对新喀里多尼亚、瓦努阿图和斐济群岛的海景进行采样，然后使用 IbD 对扩散核的估计来选择一组计算机模型，并根据二十年的海洋学数据对这些模型进行模拟（许多代鱼类）和一些物种特征的选择，这项研究的结果被用来改进每个群岛的海洋保护区网络的设计，以考虑幼虫传播随时间的变化。该项目以印度-太平洋多样性网络 (DIPnet) 的努力为基础，该网络由该项目的主要研究人员和高级人员创建，旨在促进印度-太平洋地区巨大生物多样性的生态和进化方面的合作研究。该项目还为博士后科学家、研究生和本科生提供培训，并支持为当地政策制定者和学生举办能力建设研讨会。大多数海洋物种的种群在功能、人口和遗传上通过微小幼虫的浮游扩散而相互联系。扩散事件（扩散核心）是海洋生态学的一个基本目标，对于预测种群动态和进化结果至关重要，然而，预测跨群落扩散结果的一般原则仍然难以捉摸。正在开发首个幼虫扩散的数据同化生物物理模型，方法是：1) 应用距离隔离 (IbD) 理论来估计联合采样和 RAD-seq 的六种珊瑚礁鱼类的平均亲子距离 (σIbD)在三个孤立的南太平洋群岛进行基因分型，每个群岛都使用相对连续的珊瑚礁系统复制 IbD 过程，2）使用 σIbD 的经验估计来约束幼虫的生物物理模型扩散，这是在二十年的高分辨率水动力模型中迭代的，以测试有关物种性状和海景特征在塑造幼虫扩散核心中的相对作用的假设，以及3）开发一种新的保护组合方法来设计管理区域网络，该网络捕获幼虫传播在多代中的时间变异性，并与每个群岛的当地利益相关者合作实施这一方法。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和能力进行评估，被认为值得支持。更广泛的影响审查标准。