OPUS: CRS: Phenotypic selection in nature: Analysis and synthesis

OPUS：CRS：自然界的表型选择：分析与合成

• 批准号: 1950055
• 负责人: Joel Kingsolver
• 金额: $ 29.72万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1950055&HistoricalAwards=false
• 关键词: OPUS; CRS; Phenotypic; selection; nature

Natural selection is the primary evolutionary mechanism that adapts organisms to their environments, but the general patterns of selection in natural populations remain poorly understood. In particular, biologists lack a framework for connecting environmental change to changes in selection in the wild. The goal of this project is to develop such a framework, by integrating empirical and experimental data from field studies of insect populations with mathematical modeling and new statistical methods. The approach will be used to evaluate how recent environmental change has changed patterns of selection in insect populations. The general framework will provide new tools for understanding how habitat destruction, pollution, and other aspects of environmental change will alter natural selection in populations in the wild—and whether natural populations can keep up with human-induced environmental changes. The project will also synthesize and analyze the published scientific literature on selection in the wild, and provide research training in biology, data science, and statistical modeling for graduate students.Phenotypic selection is a primary mechanism that drives evolutionary change and adaptation, but biologists lack a quantitative framework that connects phenotype, environment, fitness and selection in natural populations. The proposed research will develop such a framework using the underlying data from field studies of selection in insect populations obtained over the past 30+ years. The studies focus on three general themes: integrating information from studies of natural variation, experimental manipulations of phenotype and environment, and functional models to quantify non-linear fitness surfaces and the resulting patterns of selection; applying new statistical models for estimating selection on reaction norms, performance curves, and growth trajectories; and modeling the relationship between environmental change and changes in the fitness surface. The project will also update existing datasets for standardized selection coefficients, and provide new meta-analyses to evaluate the current evidence for stabilizing and disruptive selection in the field, and whether variation in selection is associated with variation in climate and other environmental factors. The findings from these studies will be summarized in a research monograph on phenotypic selection in the wild, and the data, associated metadata, and R code for the analyses will be made openly available in an appropriate repository.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.

自然选择是使生物体适应环境的主要进化机制，但自然种群选择的一般模式仍然知之甚少。特别是，生物学家缺乏将环境变化与野外选择变化联系起来的框架。该项目的目标是通过将昆虫种群实地研究的经验和实验数据与数学模型和新的统计方法相结合，开发这样一个框架。该方法将用于评估最近的环境变化如何改变昆虫种群的选择模式。总体框架将为了解栖息地破坏、污染和环境变化的其他方面将如何改变野生种群的自然选择以及自然种群是否能够跟上人类引起的环境变化提供新的工具。该项目还将综合和分析已发表的关于野外选择的科学文献，并为研究生提供生物学、数据科学和统计建模方面的研究培训。表型选择是驱动进化变化和适应的主要机制，但生物学家缺乏将自然种群中的表型、环境、适应度和选择联系起来的定量框架。拟议的研究将利用过去 30 多年来获得的昆虫种群选择实地研究的基础数据来开发这样一个框架。这些研究集中在三个一般主题：整合自然变异研究的信息、表型和环境的实验操作以及功能模型，以量化非线性适应表面和由此产生的选择模式；应用新的统计模型来估计反应规范、性能曲线和增长轨迹的选择；并对环境变化和健身表面变化之间的关系进行建模。该项目还将更新标准化选择系数的现有数据集，并提供新的荟萃分析来评估该领域稳定和破坏性选择的当前证据，以及选择的变化是否与气候和其他环境因素的变化有关。这些研究的结果将总结在关于野外表型选择的研究专着中，并且用于分析的数据、相关元数据和 R 代码将在适当的存储库中公开提供。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。