Collaborative LTREB Research: How will local adaptation and environmental extremes shape continental-scale changes in species distribution and abundance?

预测物种将如何应对全球环境变化是当今面临的最大生物挑战之一，因为这些反应将决定自然生态系统的持续运作，以及地球继续为人类提供食物、清洁水和其他资源的能力。大多数预测生态对环境变化反应的努力只试图预测物种未来的地理范围，而不是整个范围内的实际个体数量，尽管数字可能是衡量生态功能的一个重要得多的指标。预测范围转移或数量变化的问题之一是环境的年复一年的变化，因此物种的短期反应可能与长期趋势非常不同，这就需要在这个项目中进行长期研究。此外，广布物种的种群往往表现出对当地环境的适应，因此一个物种作为一个整体所能容忍的气候条件的范围可能不能反映任何一个种群中的个体的适宜条件。忽视当地适应可能导致对地理范围和个体数量的不准确预测。最后，领导该项目的科学家将开发培训材料并向高中教师讲授工作坊，以提高学生对气候和其他环境条件变化的生态反应的理解。该项目旨在利用长期数据集结合新的实验，解决这些和其他问题，预测未来环境条件的生态反应。这项研究的重点是北美西部从最北部的阿拉斯加到新墨西哥州中部的两种广泛分布的植物。17年来在这个纬度范围内的物种数据表明，环境变化如何影响这些植物的生存、生长和繁殖。在目前的项目中，植物将在多个地点之间移植，以测试当地对田间环境变化的适应(来自生长室实验的证据表明这种适应的可能性)。利用这些数据以及来自过去和正在进行的自然种群调查的数据，将开发新的模型来预测植物数量，以响应整个大陆人口的当地环境条件。然后，这些预测将与当前的分布和人口规模进行检验。在这一验证之后，本地模型将与全球模型捆绑在一起，以改进对未来环境条件的生态反应的预测。该项目的目标是更好地预测这些特定物种将如何对环境变化做出反应，并开发和测试做出此类预测的方法，可用于许多其他物种。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Predicting how species will respond to environmental changes across the globe is among the greatest biological challenges faced today, as these responses will determine the continued functioning of natural ecosystems and the ability of the Earth to continue to provide food, clean water, and other resources for humankind. Most efforts to predict ecological responses to environmental changes only try to predict the future geographical ranges of species, not the actual number of individuals across the range, even though numbers are likely to be a far more important measure of ecological functioning. Among the problems with forecasting either range shifts or changes in numbers is the variability in the environment from year to year, such that short-term responses of species may be very different than long-term trends, necessitating the long-term studies to be carried out in this project. In addition, populations of widespread species often show adaptation to the local environment, so that the range of climatic conditions tolerated by a species as a whole may not reflect the suitable conditions for individuals in any one population. Ignoring local adaptation may lead to inaccurate predictions of both geographical ranges and numbers of individuals. Finally, the scientists leading this project will develop training materials and teach workshops to high school teachers in order to improve students' understanding of the ecological responses to changes in climate and other environmental conditions.This project is designed to address these and other problems in predicting ecological responses to future environmental conditions, using a long-term data set combined with new experiments. The study focuses on two wide-spread plants that occur in western North America from northernmost Alaska to central New Mexico. Seventeen years of data on the species at sites across this latitudinal range have shown how environmental change can influence survival, growth and reproduction of these plants. In the current project, plants will be transplanted between multiple sites to test for local adaptation to environmental change in the field (evidence from growth chamber experiments suggests the potential for such adaptation). Using these data and those from past and ongoing surveys of natural populations, new models will be developed to predict plant numbers in response to local environmental conditions for populations across the continent. These predictions will then be tested against current distributions and population sizes. After this validation, the local models will be tied to global models to improve predictions of ecological responses to future environmental conditions. The goals of the project are both to better predict how these particular species will respond to changes in their environment and to develop and test methods for making such predictions that can be used for many other species.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.