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其环境的主要进化机制，但是自然种群中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。该项目的目的是通过将昆虫种群现场研究的经验和实验数据与数学建模和新的统计方法整合在一起来开发这种框架。该方法将用于评估最近的环境变化如何改变昆虫种群选择模式。一般框架将提供新的工具，以了解栖息地破坏，污染和环境变化的其他方面将如何改变野外人群中的自然选择，以及自然种群是否可以跟上人类引起的环境变化。该项目还将合成和分析有关野外选择的已发表的科学文献，并为研究生提供生物学，数据科学和统计建模的研究培训。Phenotypic选择是一种驱动进化变化和适应性的主要机制，但是生物学家缺乏连接表观，环境，拟合度和自然量的定量框架。拟议的研究将使用从过去30多年中获得的昆虫种群中选择的现场研究中的基本数据来开发这样的框架。研究重点介绍了三个一般主题：从自然变异的研究，表型和环境的实验操作以及量化非线性适应性表面的功能模型以及所得选择模式的功能模型中整合信息；应用新的统计模型来估算反应规范，性能曲线和生长轨迹的选择；并建模环境变化与健身表面变化之间的关系。该项目还将更新现有的数据集以进行标准化选择系数，并提供新的荟萃分析，以评估当前在现场稳定和破坏性选择的证据，以及选择的变化是否与气候和其他环境因素的变化有关。这些研究的发现将在有关野外表型选择的研究专着中进行总结，数据，相关元数据和R守则将在适当的存储库中公开提供。该奖项反映了NSF的法定任务，并通过根据基金会的知识分子优点和广泛的影响来评估NSF的法定任务，并被认为是宝贵的支持。