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DMS-EPSRC Eco-Evolutionary Dynamics of Fluctuating Populations

DMS-EPSRC 种群波动的生态进化动力学

基本信息

批准号：
2128587
负责人：
Uwe Tauber
金额：
$ 30万
依托单位：
Virginia Polytechnic Institute and State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-15 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2128587&HistoricalAwards=false
关键词：
DMS EPSRC Eco Evolutionary Dynamics

项目摘要

A fundamental scientific puzzle is understanding the origin of diversity and the evolution of cooperation, which can be understood through understanding the stability of populations composed of competing species. It directly addresses deep societal concerns, such as the maintenance of endangered ecologies, the effective prevention of the loss of biodiversity, and stemming the rise of antimicrobial resistance. To this end, one must address the coupled eco-evolutionary dynamics of fluctuating populations, namely the interdependence and combined effects of (i) random internal variability in population numbers, composition, and each species’ traits and (ii) sudden, gradual, or repetitive external changes in environmental conditions on the evolution of an ecological system. This transdisciplinary research is situated at the interface of biology, mathematics, physics, statistics, and computer science and will combine a set of advanced theoretical and mathematical tools from these fields that so far have rarely been utilized together. It will be pursued in an international collaboration, funded jointly through National Science Foundation – Division of Mathematical Sciences and the U.K. Engineering and Physical Sciences Research Council, and provide advanced training for a postdoctoral research fellow at the University of Leeds and a graduate student at Virginia Tech. Conceptual and technical advances in the basic understanding of complex interacting systems in general, and specifically of spontaneous pattern formation under the combined influence of intrinsic noise and environmental variability, are anticipated, and will be disseminated to the scientific community at tailored workshops to be organized alternatingly at Leeds, U.K. and Blacksburg, Virginia.While population dynamics traditionally ignores fluctuations and considers static and homogeneous environments, demographic noise arising from randomly occurring birth or death events as well as external environmental variations play a crucial role in understanding the eco-evolutionary dynamics of a population in time. The interdependence of external environmental variability and internal demographic noise is poorly understood to date, but it is of eminent importance, for example in microbial communities, which are often subject to sudden and extreme environmental changes. In particular, modelling populations of varying size and composition subject to changing external factors is crucial to gain a full understanding of the evolution of microbial antibiotic resistance. Standard theoretical techniques, like mean-field approximations or system-size expansions cannot be straightforwardly used, and new mathematical approaches are needed. A suite of novel theoretical methods, based on and combining evolutionary and nonlinear dynamics, deterministic and stochastic partial differential equations, agent-based computer simulations, and tools from non-equilibrium statistical physics such as dynamical scaling theory, renormalization group approaches to critical phenomena, and mathematical representations of stochastic kinetics in terms of continuum field theories, will be developed. The goal is to design and quantitatively characterize biologically relevant evolutionary models of increasing levels of complexity, which incorporate both switching environmental features and fully account for the underlying stochasticity. These theoretical advances will be utilized to generate directly testable predictions for laboratory experiments to further explore how demographic noise and environmental variability conjointly influence the emergence of collective features and affect species coexistence and their organization into spatial patterns.This project is jointly funded by the MPS Division of Mathematical Sciences (DMS) through the Mathematical Biology Program and the LS-BioTech Venture Fund, and the Division of Materials Research (DMR) through the Condensed Matter and Materials Theory program.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.

一个基本的科学难题是理解多样性的起源和合作的进化，这可以通过理解由竞争物种组成的种群的稳定性来理解。它直接解决了深层次的社会问题，例如维护濒危生态，有效防止生物多样性的丧失，以及遏制抗生素耐药性的上升。为此，必须解决波动种群的耦合生态进化动力学，即相互依存和综合影响（i）随机内部变异的人口数量，组成，和每个物种的性状和（ii）突然，渐进的，或重复的外部环境条件的变化对生态系统的演变。这种跨学科的研究位于生物学，数学，物理学，统计学和计算机科学的接口，并将联合收割机结合一套先进的理论和数学工具，从这些领域，迄今为止很少一起使用。它将在国际合作中进行，由国家科学基金会-数学科学部和英国联合资助。工程和物理科学研究理事会，并为利兹大学的一名博士后研究员和弗吉尼亚理工大学的一名研究生提供高级培训。预计在一般复杂相互作用系统的基本理解方面，特别是在固有噪声和环境变化的综合影响下自发模式形成方面，将在概念和技术上取得进展，并将在英国利兹交替组织的专门讲习班上向科学界传播。虽然人口动态学传统上忽略波动，并考虑静态和同质的环境，随机发生的出生或死亡事件以及外部环境的变化所产生的人口噪音在理解生态进化动态的人口在时间上发挥了至关重要的作用。外部环境变异性和内部人口噪音的相互依赖性迄今为止知之甚少，但它是非常重要的，例如在微生物群落中，这往往是突然和极端的环境变化。特别是，模拟不同大小和组成的种群受到不断变化的外部因素的影响，对于充分了解微生物抗生素耐药性的演变至关重要。标准的理论技术，如平均场近似或系统尺寸扩展不能直接使用，需要新的数学方法。一套新的理论方法，基于并结合进化和非线性动力学，确定性和随机偏微分方程，基于代理的计算机模拟，和工具，从非平衡统计物理学，如动态标度理论，重整化群方法的临界现象，和随机动力学的数学表示在连续场理论，将开发。我们的目标是设计和定量表征生物相关的进化模型的复杂程度不断增加，其中包括切换环境功能，并充分考虑到潜在的随机性。这些理论进展将被用来产生直接可检验的预测，为实验室实验，以进一步探讨人口统计噪声和环境变化如何共同影响集体特征的出现，影响物种共存及其组织成空间格局。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。