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Collaborative Research: MRA: Modeling and forecasting phenology across spatiotemporal and taxonomic scales using ecological observatory and mobilized digital herbarium data

合作研究：MRA：利用生态观测站和移动数字植物标本室数据对跨时空和分类尺度的物候进行建模和预测

基本信息

批准号：
2105932
负责人：
Susan Mazer
金额：
$ 52.84万
依托单位：
University of California-Santa Barbara
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-15 至 2026-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2105932&HistoricalAwards=false
关键词：
Collaborative Research MRA Modeling forecasting

项目摘要

Environmental change of all kinds – including climate change, urbanization, and wildfire – affects the seasonal timing of life cycle events in plants worldwide. Most notable are the effects of environmental conditions on the seasonal onset and duration of flowering. The timing of flowering within and among species is important for the persistence of natural populations because it affects interactions between plants, and the availability of flowers and fruits for the animals that depend on them. But the effects of environmental change on flowering differ among species and regions. This project aims to understand and forecast changes in flowering and fruiting among thousands of different plant species across the continental U.S.A. This project takes full advantage of millions of observations of flowering times collected by scientists working with the National Ecological Observation Network (NEON) and citizen-scientists contributing observations from their homes, neighborhoods, and public lands to the National Phenology Network (NPN). The researchers will augment these records of flowering times with the data from millions more herbarium specimens that are available on-line to detect the responses of flowering times to the past century of climate change. These observations will be combined with soil quality, plant cover, land use history, climate, and disturbance data to better understand how different environmental conditions influence species-specific and regional flowering times. Finally, the researchers will use statistical models to forecast short and long-term changes in future flowering times. The combined dataset will be a valuable resource available to other researchers examining the effects of environmental change on plant species and community traits. In addition, the research will provide educational opportunities for K-12, undergraduate and graduate students, and postdoctoral researchers. The project will also engage citizen-scientists who will contribute to a database of flowering times observed from herbarium collections through the CrowdCurio crowdsourcing platform.Plant phenology–the seasonal timing of key developmental events–is essential for species’ reproductive success. However, critical gaps remain in our understanding of phenology across space, time, and taxa. Increasingly, online herbaria and associated data are being mobilized to address these knowledge gaps because they provide extensive data that can be used to detect phenological responses to climatic change within and among biomes, functional groups, and taxonomic groups. In this project, the standardized, replicated, and focused phenological observations provided by NEON and the USA National Phenology Network will be harmonized for the first time with the taxonomic, spatial, and geographic breadth of herbarium data. First, flowering times derived from herbarium specimens will be assembled and augmented to include 4400 plant species that collectively span much of the continental US, with specific attention to key regions that have been digitized but overlooked: prairie, alpine, and urban biomes. Second, sources of variation in phenology within and among species, geographic regions, and higher taxa, and the effects of numerous understudied extrinsic factors (e.g., fire history, soil quality, disturbance) will be modeled. Third, forecasts of near- and long-term changes in the phenological behavior of populations, species, and communities will be modeled to better understand phenological responses at multiple ecological, phylogenetic, and temporal scales. Collectively, these efforts will help to elucidate plausible mechanistic responses to climatic and geographic factors that will determine species’ future phenology.This project is jointly funded by the Division of Environmental Biology/Macrosystems Biology and NEON-enabled Science Program and the Division of Biological Infrastructure/Capacity: Cyberinfrastructure Program.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.

各种环境变化--包括气候变化、城市化和野火--影响着世界各地植物生命周期事件的季节性时间。最值得注意的是环境条件对开花季节开始和持续时间的影响。物种内部和物种之间开花的时间对于自然种群的持久性非常重要，因为它影响植物之间的相互作用，以及依赖它们的动物是否能获得花朵和果实。但是环境变化对开花的影响在物种和地区之间是不同的。该项目旨在了解和预测美国大陆数千种不同植物物种开花和结果的变化。该项目充分利用了与国家生态观测网络（氖）合作的科学家和公民科学家收集的数百万次开花时间的观测，这些科学家从他们的家中，社区，以及国家物候网络（NPN）的公共土地。研究人员将用数百万个植物标本馆的数据来增加这些开花时间的记录，这些数据可以在线获得，以检测开花时间对过去世纪气候变化的反应。这些观测结果将与土壤质量、植被、土地利用历史、气候和干扰数据相结合，以更好地了解不同的环境条件如何影响物种特异性和区域开花时间。最后，研究人员将使用统计模型来预测未来开花时间的短期和长期变化。合并后的数据集将是一个宝贵的资源，可供其他研究人员研究环境变化对植物物种和群落特征的影响。此外，该研究将为K-12，本科生和研究生以及博士后研究人员提供教育机会。该项目还将邀请公民科学家参与，他们将通过CrowdCurio众包平台为植物标本馆收集的开花时间数据库做出贡献。植物物候学-关键发育事件的季节性时间-对于物种的繁殖成功至关重要。然而，关键的差距仍然存在于我们的物候跨越空间，时间和类群的理解。越来越多的在线植物标本库和相关数据正在被动员起来，以解决这些知识差距，因为它们提供了广泛的数据，可用于检测生物群落，功能群和分类群内部和之间对气候变化的物候反应。在这个项目中，由氖和美国国家物候学网络提供的标准化、可复制和有重点的物候观测将首次与植物标本馆数据的分类、空间和地理广度相协调。首先，从植物标本馆标本中获得的开花时间将被收集和扩增，以包括4400种植物物种，这些植物物种共同跨越美国大陆的大部分地区，特别关注已被数字化但被忽视的关键地区：草原，高山和城市生物群落。第二，种内和种间、地理区域和高等分类群的物候变化来源，以及许多未充分研究的外在因素（例如，火灾历史、土壤质量、干扰）将被建模。第三，对种群、物种和群落的物候行为的近期和长期变化进行预测，以更好地了解多个生态、系统发育和时间尺度上的物候响应。总的来说，这些努力将有助于阐明气候和地理因素的合理机械反应，这些因素将决定物种的未来物候。本项目由环境生物学/宏观系统生物学和NEON使能科学计划部门和生物基础设施/能力部门共同资助：网络基础设施计划。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准。