EAGER: Using eco-evolutionary interactions to understand forest responses to environmental change

EAGER：利用生态进化相互作用来了解森林对环境变化的反应

• 批准号: 1838425
• 负责人: Emily Moran
• 金额: $ 20万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838425&HistoricalAwards=false
• 关键词: EAGER; Using; eco; evolutionary; interactions

Trees take a long time to grow and begin producing seeds, which means they have long generation times. Therefore, it has been thought that the main way they could survive rapidly changing climates is by spreading into areas that are more suitable before they die out in areas that are becoming less suitable. However, tree species may also harbor a substantial amount of genetic diversity among individual trees within a populations, which may allow them to adapt to changing conditions on short time frames (50-100 years). This research will test this idea using computer models developed using information from real forest sites. If trees species can adapt quickly, this could influence how forests are managed and how we predict forests will change in the future. This project will also support the research of an early career scientist, provide research training to students, including those from under-served populations, in the use of computer simulations for biology, and provide outreach to the public. This project uses a multi-species individual-based modeling approach to examine how heritable variation in demographic responses to climate may influence how forests respond when climates shift. These responses include changes in tree species ranges and local forest composition. The researchers will modify the forest simulator SORTIE-ND to allow parameters determining how temperature and precipitation affect tree demography to differ between individuals and be passed to offspring with various degrees of heritability. Traditional simulations that assume all individuals of a species are the same will be compared to simulations that allow adaptation to changing temperature and rainfall over 90 years. If heritable environmental responses can substantially affect forest responses to rapid environmental change, this would greatly affect our understanding of the role eco-evolutionary processes will play in future forest dynamics. It would suggests that models need to take these responses into account, and that measuring the magnitude of potential responses to selection is a key empirical need.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.

树木需要很长时间才能生长并开始结籽，这意味着它们有很长的世代时间。因此，人们一直认为，它们生存在快速变化的气候中的主要方式是，在它们在变得不太适合的地区灭绝之前，扩散到更适合的地区。然而，树种也可能在种群内的个体树之间蕴藏着大量的遗传多样性，这可能使它们能够在短时间内(50-100年)适应不断变化的条件。这项研究将使用使用真实林地信息开发的计算机模型来测试这一想法。如果树木物种能够快速适应，这可能会影响森林的管理方式以及我们对未来森林变化的预测。该项目还将支持一名早期职业科学家的研究，向学生，包括那些来自服务不足人群的学生，提供利用计算机模拟进行生物学的研究培训，并向公众提供宣传。该项目使用基于多物种个体的建模方法来研究人口对气候反应的可遗传变化如何影响森林在气候变化时的反应。这些反应包括树种范围和当地森林构成的变化。研究人员将对森林模拟器TOSSIE-ND进行修改，以允许决定温度和降水如何影响树木人口统计的参数在个体之间有所不同，并以不同程度的遗传力传递给后代。假设一个物种的所有个体都是相同的传统模拟将与允许适应90年来不断变化的温度和降雨的模拟进行比较。如果可遗传的环境反应能够在很大程度上影响森林对快速环境变化的反应，这将极大地影响我们对生态进化过程在未来森林动态中所起作用的理解。这将表明，模型需要考虑这些反应，衡量对选择的潜在反应的幅度是一个关键的实证需求。这个奖项反映了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。