OPUS: Predicting species' responses to environmental change

一个物种的个体可以通过调整自身的发育、新陈代谢、外表或行为来应对环境的变化。流动物种的个体也可以迁移到其他环境更适宜的地方。同一物种的种群可以对相同的环境变化做出反应，要么大量增加，要么大量减少，要么在个体基因变化时进行适应性进化。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，同时考虑所有这些可能性是很重要的。该项目的目标是建立一个基于数学的理论框架，将所有这些生物过程结合起来，与来自野外和实验室研究的数据一起使用，以推断过去的反应并预测物种对变化环境的未来反应。这个项目将产生一本指导手册，附带免费提供的计算机编程脚本包，经验研究人员可以使用它来设计关于物种如何对环境变化作出反应的高效实验或观察研究。这些数据和模型将反过来为野生动物管理者、政策制定者和保护生物学家提供基于过程的定量工具，以预测感兴趣的物种对预期环境变化的反应。此外，一门新的研究生课程将以拟议的书中的材料为基础。在广泛的旱獭数据集的基础上为指南创建说导性例子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。该奖项由三个项目共同颁发：1)环境生物学部（BIO Directorate）的进化过程，2)环境生物学部（BIO Directorate）的人口与群落生态学，以及3)数学科学学部（MPS Directorate）的数学生物学。

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).