OPUS: Predicting species' responses to environmental change

一个物种的个体可以通过调整，例如，他们的发育，新陈代谢，外观或行为来应对环境的变化。移动的物种的个体也可以移动到其他环境更适合的地方。 同一物种的种群可以对相同的环境变化做出反应，通过大量的增长或减少，或者通过适应性进化，如果个体遗传差异。 在试图了解物种如何对历史环境变化作出反应并预测它们对未来变化的潜在反应时，必须同时考虑所有这些可能性。 该项目的目标是开发一个基于数学的理论框架，将所有这些生物过程结合起来，可以沿着使用现场和实验室研究的数据来推断过去的反应并预测物种对变化环境的未来反应。该项目将产生一本指南，并免费提供相关-可用的计算机编程脚本包，实证研究人员可以使用它来设计关于物种如何应对环境变化的高效和有效的实验或观察研究。 反过来，这些数据和模型将为野生动物管理者、政策制定者和保护生物学家提供基于过程的定量工具，以预测感兴趣物种对预期环境变化的反应。 此外，将根据拟议的书中的材料编写一门新的研究生课程。 根据广泛的土拨鼠数据集为指南创建说明性示例将有助于研究生培训，并促进与美国和国外研究人员的新合作。该奖项由三个项目联合颁发：1）环境生物学的进化过程（生物理事会），2）人口和社区生态学在环境生物学（生物理事会），和3）数学生物学在数学科学部（MPS理事会）。

Individuals of a species can respond to changes in their environment by making adjustments in, for example, their development, metabolism, appearance, or behavior. Individuals of mobile species can also move to other locations with more suitable surroundings. Populations of the same species can respond to the same environmental changes by growing or shrinking in abundance, or by evolving adaptively if individuals vary genetically. It is important to consider all these possibilities simultaneously when trying to understand how species have responded to historical environmental changes and to forecast their potential responses to future changes. The objective of this project is to develop a mathematically-based theoretical framework combining all these biological processes that could be used along with data from field and laboratory studies to deduce past reactions and predict future responses of species to changed environments.This project will result in a guidebook with an associated freely-available package of computer programming scripts that empirical researchers can use to design efficient and effective experimental or observational studies about how species respond to environmental change. These data and models will, in turn, provide wildlife managers, policy makers, and conservation biologists with process-based quantitative tools to forecast responses of species of interest to anticipated environmental changes. In addition, a new graduate course will be developed based on the material in the proposed book. The creation of illustrative examples for the guidebook based on an extensive marmot dataset will contribute to graduate training and foster new collaborations with researchers in the United States and abroad.This award is being made jointly by three programs: 1) Evolutionary Processes in the Division of Environmental Biology (BIO Directorate), 2) Population and Community Ecology in the Division of Environmental Biology (BIO Directorate), and 3) Mathematical Biology in the Division of Mathematical Sciences (MPS Directorate).