Collaborative Research: MRA: Estimating and forecasting nonstationary, multi-scale climate and land-use effects on avian communities

合作研究：MRA：估计和预测非平稳、多尺度气候和土地利用对鸟类群落的影响

• 批准号: 2213565
• 负责人: Elise Zipkin
• 金额: $ 72.84万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2027-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213565&HistoricalAwards=false
• 关键词: Collaborative; Research; MRA; Estimating; forecasting

Birds are declining worldwide, with an estimated loss of three billion individuals in North America alone over the last 50 years. The goal of this project is to examine how two major global change drivers, climate and land-use change, have affected – and will continue to affect – breeding birds across the United States. The research combines bird observations from four nationwide data sources (National Ecological Observatory Network [NEON], eBird, Breeding Bird Survey, and National Park Service Inventory and Monitoring Program) to estimate the historical impacts of climate and land-use change on individual species’ occurrences and biodiversity metrics over the last two decades for hundreds of species within six avian communities: eastern forests, western forests, aridlands, habitat generalists, grasslands, and urban/suburban. Using estimates from the recent past, the project will then forecast bird occurrences and distributions under a range of projected climate and land-use scenarios during the mid-century and end-of-century. Forecasts will be used to identify vulnerable species and bird communities at multiple spatial scales across the United States. Species forecasts will account for multiple sources of uncertainty, which is critical for understanding where conservation efforts could have the greatest impact in the face of ongoing global change. Findings from this work will be available via a web-based tool, which will provide the public and resource managers with detailed information on both vulnerable and resilient bird communities to enhance avian stewardship nationwide. A post-doc and graduate student will be trained in data science and statistical methods. This research focuses on evaluating and forecasting the occurrence dynamics of both individual species and entire ecological communities by quantifying the multi-scale effects of environmental drivers, while simultaneously merging independent data sources, via development of a ‘macrosystems integrated community occupancy model.’ The model will be applied to North American avifauna to examine the effects of several climate and land-use variables on the dynamics of species across biogeographical communities in the continental United States throughout the 21st century. The results will lead to (1) a macroscale understanding of bird species’ distributions and biodiversity metrics during the last two decades; and (2) forecasts of distribution dynamics from local to regional scales across the continental United States under plausible climate and land-use scenarios, allowing for assessments of species and community vulnerabilities to potential global changes. The methodological approaches developed during this project will expand the scope of community-level analyses to encompass macroscale drivers of spatiotemporal biodiversity changes during an era of accelerated species loss.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.

鸟类在全球范围内都在减少，在过去的50年里，仅北美就估计损失了30亿只。该项目的目标是研究两个主要的全球变化驱动因素，气候和土地利用变化，如何影响-并将继续影响-美国各地的繁殖鸟类。这项研究结合了来自四个全国性数据来源的鸟类观察结果（国家生态观测网络[氖]、eBird、繁殖鸟类调查和国家公园服务目录和监测计划），以估计气候和土地利用变化在过去二十年中对六个鸟类群落中数百个物种的单个物种出现和生物多样性指标的历史影响：东部森林、西部森林、干旱地区、生境通才、草地和城市/郊区。利用最近的估计，该项目将预测世纪中期和世纪末一系列预测气候和土地使用情况下的鸟类发生和分布。预测将用于确定美国各地多个空间尺度上的脆弱物种和鸟类群落。物种预测将考虑多种不确定性来源，这对于了解在面临持续全球变化的情况下，保护工作可能产生最大影响至关重要。这项工作的结果将通过一个基于网络的工具提供，该工具将为公众和资源管理人员提供有关脆弱和有弹性的鸟类社区的详细信息，以加强全国范围内的鸟类管理。博士后和研究生将接受数据科学和统计方法的培训。本研究的重点是通过量化环境驱动因素的多尺度效应来评估和预测单个物种和整个生态群落的发生动态，同时合并独立的数据源，通过开发“宏观系统集成社区占用模型”。该模型将被应用到北美鸟类区系，以检查几个气候和土地利用变量的影响，在整个世纪在美国大陆的跨地理群落的物种动态。结果将导致（1）在过去的二十年中，鸟类物种的分布和生物多样性指标的宏观尺度的理解;（2）分布动态的预测，从当地到整个美国大陆的区域尺度下合理的气候和土地利用的情况下，允许物种和社区的脆弱性评估潜在的全球变化。该项目期间开发的方法将扩大社区层面分析的范围，以涵盖在物种加速丧失的时代时空生物多样性变化的宏观驱动因素。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。