NSF Postdoctoral Fellowship in Biology: Statistical Mechanics Reveals the Long-Term and Multi-Scale Consequences of Perturbations to Ecological and Evolutionary Dynamics

研究员姓名：Renata diaz提案号：2208901研究标题：统计力学揭示了扰动对生态和进化动力学的长期和多尺度后果赞助科学家和主办机构：安德鲁·罗明格博士，缅因州大学这一行动资助了美国国家科学基金会2022财年生物学博士后研究奖学金，综合研究调查基因组，环境和表型之间相互作用的生命规则。该奖学金支持将以创新方式对生活规则领域作出贡献的研究员的研究和培训。21世纪生态学面临的一个关键挑战是，预测诸如物种丧失、物种数量下降和环境条件变化等扰动如何在生物系统中跨组织层面和随时间传播。生态系统在具体细节上很难预测，但在更大的、聚集的尺度上往往符合可预测的模式。在许多情况下，这些聚合模式与随机出现的模式汇聚在一起——不是因为生态和进化过程对这些模式没有贡献，而是因为在组织的多个层次上，许多相互作用的过程相互平滑或相互抵消。然而，强烈的扰动可以暂时使聚合模式偏离它们随机假设的形式。该研究员将构建一个统一的理论、经验和计算框架，用于使用破坏来聚合模式，以检测和诊断对生态和进化动力学的强烈干扰。作为这项工作的一部分，他们将开发计算和教育材料，以促进生态学中更广泛地采用复杂系统方法，并在大学环境和早期科学家的计算技能方面领导积极合作的讲习班。该研究员将使用基于主体的随机、过程驱动和实验扰动的生态进化动力学模拟来表征不同类型和程度的扰动对生态系统中聚集模式的预期影响。他们将把这些发现与来自社区生态学、群体遗传学和统计力学的已有理论的预测结合起来。他们将使用案例研究和干扰实验的荟萃分析来测试在实验操纵的经验系统中扰动和破坏聚合模式之间的因果关系。他们将为理论生态学课程开发一个关于突现现象的实验模块，并制作软件包、研讨会课程和交互式在线教程，以支持这一概念框架在新环境中的应用。他们将接受模拟建模、人口遗传学、软件和课程开发以及指导方面的培训。这项工作的成果将被公开存档，并公开供重用。该奖项反映了美国国家科学基金会的法定使命，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。

Fellow's name: Renata DiazProposal number: 2208901Research title: Statistical mechanics reveals the long-term and multi-scale consequences of perturbations to ecological and evolutionary dynamicsSponsoring scientist(s) and host institution(s): Dr. Andrew Rominger, University of MaineThis action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2022, Integrative Research Investigating the Rules of Life Governing Interactions Between Genomes, Environment and Phenotypes. The fellowship supports research and training of the fellow that will contribute to the area of Rules of Life in innovative ways. A key challenge for ecology in the 21st century is predicting how perturbations, such as species loss, declines in abundance, and changing environmental conditions, propagate across levels of organization and over time in biological systems. Ecological systems can be extremely difficult to predict in specific detail, but often conform to predictable patterns at larger, aggregated scales. In many instances, these aggregate patterns converge with patterns that emerge at random - not because ecological and evolutionary processes do not contribute to these patterns, but because many interacting processes at multiple levels of organization smooth or cancel each other out. However, strong perturbations can temporarily drive aggregate patterns away from the forms they assume at random. The fellow will construct a unified theoretical, empirical, and computational framework for using disruptions to aggregate patterns to detect and diagnose strong disturbances to ecological and evolutionary dynamics. As part of this work, they will develop computational and educational materials to facilitate wider uptake of complex systems approaches in ecology, and lead workshops in active allyship in the university setting and computational skills for early-stage scientists. The fellow will use agent-based simulations of random, process-driven, and experimentally perturbed eco-evolutionary dynamics to characterize the expected impacts of different types and magnitudes of disturbances on aggregated patterns in ecological systems. They will integrate these findings with the predictions from established theories derived from community ecology, population genetics, and statistical mechanics. They will test the causal link between perturbations and disruptions to aggregate patterns in experimentally manipulated empirical systems using case studies and a meta-analysis of disturbance experiments. They will develop a lab module on emergent phenomena for a theoretical ecology course, and produce software packages, workshop curricula, and interactive online tutorials to support applications of this conceptual framework in new contexts. They will receive training in simulation modeling, population genetics, software and curriculum development, and mentoring. The products of this work will be publicly archived and made openly available for re-use.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.