OPUS: Predicting species' responses to environmental change

一个物种的个体可以通过对其发育、新陈代谢、外表或行为等方面的调整来对环境的变化做出反应。活动物种的个体也可以迁徙到其他环境更合适的地方。同一物种的种群可以通过数量的增长或减少来应对相同的环境变化，或者在个体遗传差异的情况下通过适应性进化来应对。在试图了解物种如何对历史环境变化作出反应并预测其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。这个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与来自野外和实验室研究的数据结合起来，以推断物种过去的反应和预测物种对环境变化的未来反应。该项目将产生一本指南，其中包括一套免费提供的计算机编程脚本，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做出反应的高效和有效的实验或观察研究。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量化工具，以预测感兴趣的物种对预期环境变化的反应。此外，还将根据提议的书中的材料开发一门新的研究生课程。该奖项由三个项目联合颁发：1)环境生物学部门的进化过程(BIO理事会)；2)环境生物学部门的人口和群落生态学(BIO理事会)；3)数学科学部门的数学生物学(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).