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.

大多数海洋生物会通过产生数百万个微小的浮游幼虫来繁殖，这些幼虫分散在各种距离和方向上。幼虫的空间分布（也称为分散核）是对海洋生态和进化的基本理解以及海洋资源的管理和保护的重要参数。经常使用计算机模型对幼体分散核进行研究，这些计算机模型模拟了海洋循环模型中幼虫的扩散。但是，由于当前遗传标记方法的成本和不可行性，很少有海洋幼虫分散的测量值可以评估这些计算机模型。该项目使用距离（IBD）人口模型的隔离，项目团队已显示出与遗传标记方法相似的结果，但成本的一小部分。散布核被认为是由两个物种特征所塑造的，例如花费的时间作为浮游幼虫，以及幼虫分散的环境。为了嘲笑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，在这里，众多孤立的群岛各自独立地复制了团队正在研究的分散过程。在每个新的喀里多尼亚，瓦努阿图和斐济档案库中的十个位置的五个珊瑚礁鱼类都在采样，然后使用分散核的IBD估计来选择一组计算机模型，并在二十年的海洋数据（许多世代的鱼类）和物种特征的选择中进行了模型，并在二十年的大洋学数据中进行了模拟。这项研究的结果被用来改善每个群岛中海洋保护区网络的设计，以一种随着时间的推移而变化的方式。这项研究是基于该项目的主要研究人员和高级人员创建的印度太平洋网络（DIPNET）多样性的努力，以促进有关印度太平洋生物多样性的生态学和演变的合作研究。该项目还为博士后科学家，研究生和本科生提供培训，并为当地决策者和学生提供支持的能力建设研讨会。大多数海洋物种在功能，人口统计学上和遗传上是通过理解分散事件的空间分布（分散核心）的基本渐进式启动和预测的人群的基本人数，这是海洋生态的基本动力，这是一个重要的人口。然而，预测整个社区分散结果的一般原则仍然难以捉摸。该项目团队正在开发有史以来的第一个数据概类的幼虫分散生物物理模型：1）通过以下方式使用隔离（IBD）理论估算六种reef鱼类物种的平均父母距离（σibd），用于在每个隔离的South Pacific croper preciper pacific consyptial coef co pacific contyperip consection coef Fish物种中使用IB的三个隔离式基因组，该系统使用IB依次使用IB，该系统使用IB依次使用IB的IB，IB在IB中进行了反复使用。 σiBD的经验估计以限制幼虫分散的生物物理模型，这些模型在二十年的高分辨率流体动力学模型中被迭代，以测试有关物种性状和海景特征相对作用的假设，并在塑造幼虫分散方面的范围内，以及3）在塑造范围内的变化方面，以设计新的保存网络，以设计范围的范围。几代人，并与每个档案馆中的当地利益相关者互动以实施这种方法。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响标准，被视为通过评估而被视为珍贵的支持。