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

自然选择是生物适应环境的主要进化机制，但对自然种群中选择的一般模式仍然知之甚少。特别是，生物学家缺乏一个框架，将环境变化与野外选择的变化联系起来。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建模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。这个总体框架将提供新的工具来理解栖息地的破坏、污染和环境变化的其他方面将如何改变野外种群的自然选择，以及自然种群是否能跟上人类引起的环境变化。该项目还将综合和分析已发表的关于野生选择的科学文献，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，但生物学家缺乏一个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。拟议的研究将使用过去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：整合来自自然变异研究的信息，表型和环境的实验操作，以及量化非线性适应面和由此产生的选择模式的功能模型;应用新的统计模型来估计反应规范，性能曲线和生长轨迹的选择;以及对环境变化和适应度表面中的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，并提供新的元分析，以评估该领域稳定和破坏性选择的现有证据，以及选择的变化是否与气候和其他环境因素的变化有关。这些研究的结果将被总结在一本关于野生表型选择的研究专著中，数据、相关的元数据和用于分析的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，并被认为值得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来支持。

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.