Collaborative Proposal: MRA: Using NEON data to elucidate the ecological effects of global environmental change on phenology across time and space

合作提案：MRA：利用 NEON 数据阐明全球环境变化对跨时间和空间物候的生态影响

• 批准号: 2017463
• 负责人: Leah Johnson
• 金额: $ 10.9万
• 依托单位: Virginia Polytechnic Institute and State University
• 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: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017463&HistoricalAwards=false
• 关键词: Collaborative; Proposal; MRA; Using; NEON

Global environmental change is causing shifts in species’ phenologies (the timing of ecological processes) and rates of acclimation (physiological adjustments to environmental change), the physiological precursors to phenological shifts. These shifts are important because they can create 'mismatches' in the performance and timing of interacting species, such as predators and prey, hosts and parasites, competitors, and plants and pollinators, which can adversely affect biodiversity and the services that ecosystems provide to humans. Despite extensive data on the phenology and acclimation of individual species, no general framework exists that can predict how phenological responses of species – and by extension species interactions – will respond to environmental change. To address this knowledge gap and provide broader impacts to society, a research team has been assembled with expertise in global change and thermal biology, ecoinformatics, mathematical and statistical modeling, and geographic information systems. The broader impacts of the project include: training the next generation of STEM undergraduates and graduate students across diverse ethnic backgrounds and genders, a graduate course on large scales and ‘big data’ in biology, and new databases for posterity that will guide conservation and monitoring for species invasions and infectious diseases.From a scientific perspective, this team proposes to i) expand phenological datasets, ii) gather data from the literature on environmental change effects on species interactions, iii) develop a quantitative global framework for predicting the direction and magnitude of effects on individual species’ phenologies and species interactions based on latitude, climate, and organismal traits, and iv) validate present-day predictions of the model by working with at least 13 existing National Ecological Observatory Network (NEON) datasets. The specific objectives are to: 1) assemble a database of time series describing phenological shifts, local climatic drivers, latitude and elevation, and organismal body sizes; 2) develop a mathematical framework for predicting the phenological responses of species to environmental change, by quantifying how phylogeny, body size, habitat, latitude, phenological trait, and environment (temperature and precipitation) affect phenology; 3) use NEON data to validate this framework by testing whether it can accurately predict the phenological responses of individual species to variability in present-day climate, from local to continental scales; 4) use NEON data to evaluate the ability of this framework to predict how variability in present-day climate will affect the strength and outcome of species interactions and ecosystem functions; and 5) once validated, couple the framework to local environmental change projections to predict species and locations around the globe that will be particularly sensitive to changing environments.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.

全球环境变化正在导致物种物候(生态过程的时间)和适应速度(对环境变化的生理调整)的变化，这是物候变化的生理前兆。这些转变很重要，因为它们可能在相互作用的物种，如捕食者和猎物、宿主和寄生虫、竞争者以及植物和传粉者的表现和时间上造成“不匹配”，这可能对生物多样性和生态系统向人类提供的服务产生不利影响。尽管有大量关于个体物种物候和适应的数据，但没有一个通用的框架可以预测物种的物候反应--以及延伸到物种之间的相互作用--将如何应对环境变化。为了解决这一知识差距，并为社会提供更广泛的影响，组建了一个研究小组，其成员包括全球变化和热生物学、生态信息学、数学和统计建模以及地理信息系统方面的专业知识。该项目的更广泛影响包括：培训不同种族背景和性别的下一代STEM本科生和研究生，开设一门大规模的研究生课程，提供生物学方面的大数据，以及为后代建立新的数据库，以指导物种入侵和传染病的保护和监测。从科学角度来看，该团队建议：1)扩大物候数据集，2)从文献中收集关于环境变化对物种相互作用的影响的数据，3)开发一个基于纬度、气候和生物特征预测个体物种物候和物种互动影响的方向和大小的全球量化框架，以及iv)通过使用至少13个现有的国家生态观测网络(NEON)数据集来验证该模型的当前预测。具体目标是：1)建立描述物候变化、当地气候驱动因素、纬度和海拔以及生物体大小的时间序列数据库；2)通过量化系统发育、个体大小、栖息地、纬度、物候特征和环境(温度和降水)对物候的影响，建立预测物种对环境变化的物候反应的数学框架；3)使用霓虹灯数据验证该框架，测试它是否能够准确地预测个体物种对从局部到大陆尺度的当今气候变化的物候反应；4)使用霓虹灯数据评估该框架的能力，以预测当前气候的变化将如何影响物种相互作用和生态系统功能的强度和结果；以及5)一旦得到验证，将该框架与当地环境变化预测相结合，以预测全球对环境变化特别敏感的物种和地点。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。