Collaborative Research: Evolutionary Resilience and Species Persistence in Disturbed Habitats

合作研究：受干扰栖息地的进化弹性和物种持久性

• 批准号: 1714386
• 负责人: Daniel Bolnick
• 金额: $ 20万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1714386&HistoricalAwards=false
• 关键词: Collaborative; Research; Evolutionary; Resilience; Species

Globally, humans are causing substantial environmental perturbations, and these perturbations are likely to become more frequent and more severe in the future. Such disturbances can have profound impacts on the structure of ecological communities (e.g. species diversity and abundance) and on the ecosystem services that those communities provide. Given the potential significance of such changes for human well-being, it is essential that we develop effective tools to predict these ecological and ecosystem impacts. Traditionally, the study of the resilience of ecological communities to severe environmental perturbations (e.g. hurricanes, floods) has focused on ecological processes. However, there is mounting evidence that feedbacks between the ecological and evolutionary processes (eco-evolutionary feedbacks) occur over commensurate time scales. This raises the possibility that evolutionary processes may play an important role in community resilience and species persistence. This project tackles the challenges posed by this possibility by developing a mathematical framework for analyzing models of disturbance which account for eco-evolutionary feedbacks and applying this framework to two real world systems whose properties have not been synthetically treated. In addition, this project will also support multiple outreach activities to K-12 education. The investigators will develop new analytical methods models accounting for environmental stochasticity, eco-evolutionary feedbacks, and demographic stochasticity. Stochastic difference equations (SDEs) will be used to model eco-evolutionary feedbacks in disturbed habitats. For these SDEs, new methods will be developed for verifying persistence of species and exponential rates of convergence to positive stationary distributions (which provides a measure of resilience). For models also accounting for finite population sizes, large deviation methods will be used to prove that stochastic persistence for the mean field SDE implies that the mean time to extinction of any species or genotype increases exponentially with habitat size, and the meta-stable behavior of the system dynamics are characterized by the positive stationary distributions of the mean field SDE. These mathematical methods will be applied to a nested set of common models associated with two prominent empirical systems: Anolis lizards on Bahamian Islands recovering from hurricanes, and stickleback fish in streams on Vancouver Island recovering from catastrophic floods. Using such different model systems provides the unique opportunity to more readily find generalities and plays to the two systems' complementary experimental strengths. Field experiments and observations as well as existing data will be used to parameterize the individual-based eco-evolutionary models. These models will be used to examine the impact of an environmental disturbance on (1) local adaptation of a focal predator (Anolis or stickleback), (2) community resilience, (3) long-term species persistence, and (4) projections about the rate and nature of ecological and evolutionary recovery under present and future climatic conditions. For outreach, the investigators will run and develop material for the modelling in the life sciences cluster of the California State Summer School for Mathematics and Science, will develop short educational videos about field research, ecology, and evolution for K-12 students in Austin, and create additional educational opportunities for local Bahamian school children in collaboration with Friends of the Environment (a Bahamian conservation organization).

在全球范围内，人类正在引起大量的环境扰动，这些扰动可能会变得更加频繁，更加严重。这种干扰可能会对生态社区的结构（例如物种多样性和丰度）以及这些社区提供的生态系统服务产生深远的影响。鉴于这种变化对人类福祉的潜在意义，我们必须开发有效的工具来预测这些生态和生态系统的影响。传统上，对生态社区对严重环境扰动的弹性（例如飓风，洪水）的研究一直集中在生态过程上。然而，有越来越多的证据表明，生态和进化过程（生态进化反馈）之间的反馈在相称的时间尺度上发生。这增加了进化过程可能在社区弹性和物种持久性中发挥重要作用的可能性。该项目通过开发一个数学框架来分析扰动模型，从而解决了生态进化反馈的模型，并将此框架应用于两个现实世界系统，这些框架尚未得到合成处理，从而解决了这种可能性所带来的挑战。此外，该项目还将支持K-12教育的多种外展活动。研究人员将开发新的分析方法模型，以说明环境随机性，生态进化的反馈和人口统计学随机性。随机差方程（SDE）将用于模拟受干扰栖息地的生态进化反馈。对于这些SDE，将开发新的方法来验证物种的持久性以及收敛速率与正固定分布的指数速率（这提供了弹性的衡量）。对于还考虑有限人口规模的模型，将使用大型偏差方法来证明，平均场SDE的随机持久性意味着，任何物种或基因型灭绝的平均时间随着栖息地的大小而成倍增加，并且系统动态的元稳定行为由平均场平均场的积极静止分布来表征。这些数学方法将应用于与两个突出的经验系统相关的一组嵌套的通用模型：从飓风中恢复的巴哈马群岛上的Anolis蜥蜴，以及从灾难性洪水中恢复的温哥华岛上的溪流中的st虫鱼。使用这样的不同模型系统，可以为更容易找到两种系统的互补实验强度而更容易地找到一般性并发挥独特的机会。现场实验和观测以及现有数据将用于参数化基于个体的生态进化模型。这些模型将用于检查环境干扰对（1）局部适应局部捕食者（Anolis或Stickleback），（2）社区弹性，（3）长期物种持久性以及（4）有关当前和将来的气候恢复条件的生态和进化恢复的速度和性质的预测。对于外展活动，调查人员将在加利福尼亚州立大学数学和科学暑期学校的生命科学集群中运行并开发材料，将制作有关奥斯汀K-12学生的现场研究，生态学和进化的简短教育视频，并为与环境合作（Bahamian Sancermation Armissional of Bahamian Sermandyment of Bahamian Compless）创造其他教育机会。