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: 2017740
• 负责人: Anthony Dell
• 金额: $ 21.19万
• 依托单位: Lewis and Clark Community 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: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017740&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（生态过程的时机）和适应速率（生理调整环境变化）的转变，这是物候转移的物理前体。这些转变之所以重要，是因为它们可以在相互作用的物种的性能和时机中创建“不匹配”，例如捕食者和猎物，宿主和寄生虫，竞争者，植物和传粉剂，这可能会对生物多样性以及生态系统提供给人类提供的服务。尽管关于单个物种的物候和适应的广泛数据，但尚无一般框架，可以预测物种的物候反应以及扩展物种相互作用的方式会对环境变化做出反应。为了解决这一知识差距并为社会带来更广泛的影响，研究团队已在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拥有专业知识。该项目的更广泛影响包括：培训下一代的STEM大学生和研究生跨越种族背景和性别的研究生，一门关于大规模的研究生课程和生物学上的“大数据”的研究生课程，以及新的后代数据库，以指导保护和监视物种入侵和感染性疾病的保护和监测。对物种相互作用的变化影响，iii）开发一个定量的全球框架，用于预测基于纬度，气候和有机特征的物种物候和物种相互作用的影响的方向和幅度，以及iv）通过与至少13个现有的现有国家生态观测网络（NEON）数据合作来确认模型的当前预测。具体目标是：1）组装时间序列的数据库，描述了物候转移，当地的民用驱动因素，纬度和高程以及有机体大小； 2）开发一个数学框架，用于通过量化系统发育，身体大小，栖息地，纬度，物候特性和环境（温度和精度）影响物候的数学框架来预测物种对环境变化的物候反应； 3）使用霓虹灯数据通过测试是否可以准确预测物候响应来验证该框架4）使用霓虹灯数据来评估该框架的能力，以预测当今气候中的可变性如何影响物种相互作用和生态系统功能的强度和结果； 5）一旦经过验证，将框架与当地环境变化项目相结合，以预测全球范围内的物种和地点，这些物种和地点将对不断变化的环境特别敏感。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响来通过评估来获得的支持。