Collaborative Proposal: Redefining the ecological memory of disturbance over multiple temporal and spatial scales in forest ecosystems

合作提案：重新定义森林生态系统多个时空尺度扰动的生态记忆

• 批准号: 1945921
• 负责人: Jaclyn Matthes
• 金额: $ 8.88万
• 依托单位: Wellesley College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945921&HistoricalAwards=false
• 关键词: Collaborative; Proposal; Redefining; ecological; memory

Most research on forests occurs within a single forest or only over a few years or, less often, a few decades. It is typically believed that local disturbances affect trees only in that forest. However, recent evidence suggests that disturbances affected forests over hundreds of miles and more by the same series of drought events and a hard spring frost that occurred 250 years ago. These extreme weather events made it possible for many ancient trees within this region to grow from small saplings into the canopy trees they are now. These large-scale but very short-lived events like drought and frost are predicted to occur more often and become worse in the future. If that happens, regional forest declines could become more important in the future. To see if this is a real possibility, this award will yield new data from old forests throughout the Northeastern U.S. to investigate how trees and forests respond to extreme events similar to those from 250 years ago. The broader impacts will focus on recruiting people who are not well represented in scientific and academic institutions. Students and project participants will be trained on how to conduct science with humility, have respect for all people, and to combat institutional racism and gender bias. The team will be active on social media and make presentations at scientific meetings, public lectures, and educational events to share what is learned through our study.The ecological memory of forested ecosystems to extreme climatic events is not adequately captured by theories of disturbance and vegetation models; the common scale of ecological research is spatially too small and temporally too short to capture long-term ecosystem development. This award will investigate multiple data streams with two dynamic vegetation models and Bayes hierarchical modelling to answer several questions, including: 1) How do extreme climatic events impact ecosystem development and ecological processes? and 2) What are the long-term interactions between local, high-frequency disturbance (windstorms, gap dynamics, etc.) and large-scale, low-frequency disturbance (severe drought)? Through these questions, the research will rigorously test theory by confronting models with realistic disturbance scenarios from 600 years of tree-growth data covering 400,000 km2 of the northeastern US to determine to what extent extreme climatic events synchronize disturbance across spatial scales and their potential long-term legacies. The award outcomes will be useful in forecasting climate-forest interactions, as extreme events are expected to increase in the future. By scaling from seasons to centuries, this project bridges short- and long-term studies to provide information at the scales necessary to guide land use decisions in complex systems under a changing climate. In addition to training, the project will conduct a modelling workshop to push the margins of forest science by inviting experts and people from a range of disciplines and underrepresented groups to produce a conceptual paper at the intersection of data-model assimilation, Bayesian statistics, and spatial and temporal analyses.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.

大多数关于森林的研究发生在一个森林中，或者仅在几年中或少数几十年。通常认为，局部干扰仅影响树木。然而，最近的证据表明，骚乱影响了数百英里，以及一系列干旱事件以及250年前发生的硬弹簧霜。这些极端的天气事件使该地区的许多古老树木有可能从小树苗生长到现在的树冠树中。这些大规模但非常短暂的事件（如干旱和霜冻）被预计会更频繁地发生，并在将来变得更糟。如果发生这种情况，那么区域森林的下降可能会在将来变得越来越重要。为了了解这是否是一种可能性，该奖项将产生美国东北部旧森林的新数据，以调查树木和森林如何应对与250年前类似的极端事件的反应。更广泛的影响将着重于招募在科学和学术机构中没有很好代表的人。学生和项目参与者将接受有关如何谦卑地进行科学，尊重所有人的培训，并打击机构种族主义和性别偏见。该团队将活跃于社交媒体上，并在科学会议，公开讲座和教育活动中进行演讲，以分享通过我们的研究所学的知识。对极端气候事件的森林生态系统的生态记忆并不能被干扰和植被模型的理论充分捕捉；生态研究的共同规模在空间上太小，在时间上太短，无法捕获长期生态系统的发展。该奖项将通过两个动态植被模型和贝叶斯分层建模研究多个数据流，以回答几个问题，包括：1）极端气候事件如何影响生态系统的发展和生态过程？ 2）局部，高频干扰（风暴，间隙动态等）与大规模低频干扰（严重干旱）之间有什么长期相互作用？通过这些问题，研究将通过与600年的树木生长数据相遇，涵盖400,000 km2美国东北部的模型，以确定极端气候事件在空间尺度及其潜在的长期遗产中同步障碍。由于极端事件预计将来会增加，因此奖励成果将在预测气候森林互动中有用。通过从季节到几个世纪的扩展，该项目桥接了短期和长期研究，以在不断变化的气候下指导复杂系统中的土地使用决策所需的尺度提供信息。除培训外，该项目还将通过邀请专家和来自一系列学科的专家和人员来推动森林科学的边缘，并在数据模型同化，贝叶斯统计数据，贝叶斯统计数据，贝叶斯统计，以及空间和时间上的基础上的基础上的概念上的概念宣传，并以NSF的规定来表现出众多宣传，并在数据模型相交的交集上生产一份概念性论文。和更广泛的影响审查标准。