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

各种环境变化--包括气候变化、城市化和野火--都会影响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季节开花和开花持续时间的影响。物种内和物种间的开花时间对自然种群的持续很重要，因为它影响植物之间的相互作用，以及依赖植物的动物能否获得花卉和果实。但环境变化对开花的影响因物种和地区而异。该项目旨在了解和预测美国大陆数千种不同植物的开花和结果变化。该项目充分利用了国家生态观测网络(NEON)的科学家和公民科学家收集的数百万个开花时间的观测数据，这些科学家从他们的家中、社区和公共土地向国家物候学网络(NPN)贡献了观测。研究人员将用数以百万计的更多标本的数据来补充这些开花时间的记录，这些标本可以在线获得，以检测开花时间对过去一个世纪气候变化的反应。这些观测将与土壤质量、植物覆盖、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特定物种和地区的开花时间。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。合并后的数据集将为其他研究人员提供宝贵的资源，以研究环境变化对植物物种和群落特征的影响。此外，这项研究将为K-12、本科生和研究生以及博士后研究人员提供教育机会。该项目还将吸引公民科学家，他们将通过CrowdCurio众包平台，为从植物标本馆中观察到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--对物种的繁殖成功至关重要。然而，我们对物候学的理解仍然存在着跨越空间、时间和类群的严重差距。越来越多的在线草药和相关数据正在被用来填补这些知识空白，因为它们提供了大量数据，可用于检测生物群、功能组和分类组内部和之间对气候变化的物候反应。在这个项目中，由霓虹灯和美国国家物候学网络提供的标准化、重复和集中的物候观测将首次与植物标本馆数据的分类学、空间和地理广度相协调。首先，从植物标本中提取的开花时间将被组合并扩大到包括4400种植物，这些植物总共横跨美国大陆的大部分地区，并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。其次，将模拟物种、地理区域和高等类群内部和之间物候变化的来源，以及许多未被研究的外部因素(例如，火灾历史、土壤质量、干扰)的影响。第三，将对种群、物种和群落物候行为的短期和长期变化进行建模，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。总而言之，这些努力将有助于阐明对气候和地理因素的可信的机械响应，这些因素将决定物种未来的物候。该项目由环境生物学/大系统生物学和霓虹灯启动的科学计划司和生物基础设施/能力司：网络基础设施计划联合资助。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。

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.