权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

RUI: Stochastic Interactions: Understanding Invasion and Extinction in Ecological Systems

RUI：随机相互作用：了解生态系统中的入侵和灭绝

基本信息

批准号：
1853610
负责人：
Eric Forgoston
金额：
$ 25万
依托单位：
Montclair State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1853610&HistoricalAwards=false
关键词：
RUI Stochastic Interactions Understanding Invasion

项目摘要

The goal of this project is to develop mathematical and statistical approaches to understand how environmental disturbances or invading species affect communities connected in large food webs. Biological systems are very complex, involving a multitude of interactions among many components at different scales. How ecological communities may be grouped to explain how they coexist and evolve has been a subject of intense interest among biologists and ecologists. Even after a century of research, the mathematical tools and models needed to fully understand observed species invasions and extinctions do not exist. Moreover, very few ecological studies have considered mathematical models with random effects. Real world systems are inherently noisy, and only by including random effects can one properly understand an ecological community. The work involves collaboration with ecologists based at British Antarctic Survey in the United Kingdom to create an interdisciplinary approach grounded in specific data. The outcome of the research will be disseminated through seminars, presentations at meetings, and publications in peer-reviewed journals. The project will train undergraduate and graduate students in interdisciplinary mathematical research. Many students at Montclair State University are members of underrepresented groups in STEM (including women and minorities), and the research program will leverage existing programs which support these students. The project involves the use of theoretical, statistical, and computational approaches to improve our understanding of how models of large ecological systems respond to stochastic interactions and perturbations. Of particular interest is the study of primary and secondary extinction cascades in food webs as well as the susceptibility of food webs to invasive species. By considering a variety of empirical and synthetic food webs and incorporating full dynamics with stochasticity, the work will shed light on which ecosystem mechanisms (e.g., self-regulation, interaction strengths, feedback loops) serve to stabilize food webs against perturbations. The three major components of the work are to: (i) perform comprehensive numerical studies of the stochastic systems to improve our understanding of stochastic invasion, primary extinction, and the resulting secondary extinction cascade; (ii) develop new approaches using continuous Markov chain models to find the optimal path to extinction when considering pairwise, three-way, and higher-order interactions between species; and (iii) determine the vulnerability of an existing food web to invasion by exotic species using innovative asymptotic analysis The results will be useful in improving our understanding of biodiversity and the organization of living communities as well as factors that can stabilize or destabilize ecosystems.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.

该项目的目标是开发数学和统计方法，以了解环境干扰或入侵物种如何影响大型食物网中连接的社区。生物系统是非常复杂的，涉及许多组件在不同尺度上的大量相互作用。如何将生态群落分组以解释它们是如何共存和进化的，一直是生物学家和生态学家非常感兴趣的课题。即使经过了世纪的研究，完全理解观察到的物种入侵和灭绝所需的数学工具和模型仍然不存在。此外，很少有生态学研究考虑了随机效应的数学模型。真实的世界系统本来就是嘈杂的，只有通过包括随机效应才能正确理解生态群落。这项工作涉及与设在联合王国的英国南极调查局的生态学家合作，以具体数据为基础制定跨学科办法。研究成果将通过研讨会、会议介绍和在同行评审期刊上发表文章等方式传播。该项目将培养跨学科数学研究的本科生和研究生。蒙特克莱尔州立大学的许多学生都是STEM中代表性不足的群体（包括妇女和少数民族）的成员，研究计划将利用现有的支持这些学生的计划。该项目涉及使用理论，统计和计算方法，以提高我们对大型生态系统模型如何响应随机相互作用和扰动的理解。特别令人感兴趣的是研究食物网中的初级和次级灭绝级联以及食物网对入侵物种的敏感性。通过考虑各种经验和合成食物网，并将完全动态与随机性结合起来，这项工作将揭示哪些生态系统机制（例如，自我调节、相互作用强度、反馈回路）的作用是稳定食物网，抵御扰动。工作的三个主要组成部分是：（i）进行全面的随机系统的数值研究，以提高我们对随机入侵，初级灭绝，以及由此产生的二次灭绝级联的理解;（ii）开发新的方法，使用连续马尔可夫链模型，以找到最佳的灭绝路径时，考虑物种之间的两两，三向和更高阶的相互作用;以及（iii）利用创新的渐近分析确定现有食物网对外来物种入侵的脆弱性研究结果将有助于提高我们对生物多样性和生物群落组织以及稳定或破坏生态系统的因素的理解。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的学术价值和更广泛的影响审查标准。