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

• 批准号: 2105907
• 负责人: Sydne Record
• 金额: $ 31.77万
• 依托单位: Bryn Mawr College
• 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 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2105907&HistoricalAwards=false
• 关键词: Collaborative; Research; MRA; Modeling; forecasting

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）会影响全球植物生命周期事件的季节性时机。最值得注意的是环境条件对季节性发作和开花持续时间的影响。物种内部和物种之间开花的时机对于自然种群的持久性很重要，因为它会影响植物之间的相互作用，以及依赖它们的动物的花和水果的可用性。但是环境变化对物种和地区之间开花不同的影响。该项目旨在理解和预测美国连续数千种不同植物物种的开花和果实变化。该项目充分利用了与国家生态观察网络（NEON）合作的科学家收集的数百万观察到的开花时间，并从他们的家园，邻里和公共土地上为国家生态学家（NEON）和公民 - 科学家贡献了观察，对国家和公共土地学网络（Necland Landsology Netrogntes）（N-Nectranology Network）（NPN Network）（NPN）（NPN）（PN）。研究人员将通过数百万种标本室物种的数据来扩大这些开花时间的记录，这些数据可在线可用，以检测开花时间对过去一个世纪的气候变化的反应。这些观察结果将与土壤质量，植物覆盖，土地使用历史，气候和灾难数据相结合，以更好地了解不同的环境条件如何影响规格特定和区域开花的时间。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。合并的数据集将是其他研究人员可用的宝贵资源，该研究人员研究了环境变化对植物物种和社区特征的影响。此外，该研究将为K-12，本科和研究生以及博士后研究人员提供教育机会。该项目还将吸引公民科学家，他们将通过Crowdcurio众包平台从植物标本室收集中观察到的开花时间数据库。Plant候位学 - 关键发展事件的季节性时机 - 物种的生殖成功至关重要。但是，我们对跨时空，时间和分类单元的物候学的理解仍然存在关键差距。越来越多的在线草药和相关数据被动员以解决这些知识差距，因为它们提供了广泛的数据，可用于检测对生物群体内部和生物群体，官能团和分类学组中晶体学变化的物候响应。在这个项目中，霓虹灯和美国国家物候网络提供的标准化，复制和集中的物候观察将首次与植物标本室数据的分类，空间和地理广度进行协调。首先，将衍生自标本标本的开花时间组装并增强，包括4400种植物物种，这些植物集体跨越了我们大部分连续的美国，并特别注意已被数字化但被忽略的关键区域：草原，高山和城市生物群。其次，物种内部和物种之间，地理区域和更高分类单元的差异来源，以及许多理解的外部因素（例如火灾历史，土壤质量，灾难）的影响。第三，将对种群，物种和社区的物候行为的近期和长期变化的森林进行建模，以更好地理解多种生态，系统发育和临时量表的物候反应。总的来说，这些努力将有助于阐明对气候和地理因素的合理机械响应，这些反应将决定物种的未来物候学。该项目由环境生物学/宏观系统生物学和支持霓虹灯的科学计划和基于生物依赖能力的部门共同资助。基金会的智力优点和更广泛的影响评论标准。