Phenological sensitivity to climate across space and time: harnessing the diversity of digital herbarium data to generate and to test novel predictions

众所周知，植物会根据当地的气候条件改变其开花时间，但影响其反应的大小和方向的因素尚不清楚。此外，并不是所有物种都会根据相同的气候因素改变它们的季节性开花时间。因此，随着气候的变化，一些物种可能开花太早，导致遭受冬季霜冻，而另一些物种可能开花太晚，或者没有足够多的开花时间来成功繁殖。这个项目将提高我们对个别物种和植物种群的开花时间如何随着未来气候条件的反应而变化的理解。这项研究对于预测传粉者和其他以花蜜和花粉为食的动物未来花卉资源的可用性以及评估植物遭受霜冻损害、食草动物活动和其他季节性压力(如夏季干旱)的风险至关重要。然而，到目前为止，还没有对开花时间随气候变化而变化的方向和幅度进行全面的大陆研究。该项目将创建一个单一的大型数据库，并使所有数据在线向公众开放。此外，该项目将为本科生和研究生提供研究培训。初步证据表明，物候对气候变化的反应(或敏感性)的大小可能在密切相关和功能相似的类群中保守。因此，有可能通过对记录良好的密切相关分类群的检查来预测尚未被研究的物种的物候学。美国各地教育和研究机构存档的数十万份电子记录提供了有关美国各地植物学家在过去200年里收集的植物标本的标准化信息，包括收集每个标本的日期和地点，以及收集当天它是否开花。这项研究将这些不同的记录整合到一个单一的数据库中，并利用它们来评估影响1000个充分采样物种的历史和当代开花时间的因素。反过来，这些信息将被用来预测预测气候情景下季节性开花的变化。将使用数字标本馆记录和现场记录的观察来评估影响被子植物历史和当代开花时间的因素，这些因素涉及前所未有的多样性被子植物(1000个物种，每个物种代表100个标本；80个科，400个属)。将生成预测模型，使研究人员能够在特定气候条件下预测单个物种的物候变化。

It is well known that plants alter their flowering times in response to local climatic conditions, but the factors influencing the magnitude and direction of their responses are not well understood. Moreover, not all species change their seasonal flowering time in response to the same climate factors. Consequently, as climate changes, some species may flower too early, resulting in exposure to winter frosts, while others may flower too late or fail to shift their flowering enough to reproduce successfully. This project will improve our understanding of how the timing of flowering by individual species and groups of plant species shift in response to future climatic conditions. This research is essential for forecasting the future availability of floral resources for pollinators and other animals that feed on nectar and pollen, as well as for assessing plant risk of exposure to frost damage, herbivore activity, and other seasonal stresses (e.g., summer drought). To date, however, no comprehensive, continental study of the direction and magnitude of changes in flowering time in response to changes in climate has been conducted. This project will create a single, large database and make all data available online to the public. In addition, this project will provide research training to undergraduate and graduate students.Preliminary evidence suggests that the magnitude of phenological responsiveness (or sensitivity) to climate changes may be conserved among closely related and functionally similar taxa. Consequently, it may be possible to predict the phenology of species that have not been studied through examination of closely related taxa that are well-documented. Hundreds of thousands of electronic records archived in educational and research institutions throughout the United States provide standardized information about plant specimens collected by botanists across the U.S. over the past 200 years, including the date and location where each specimen was collected and whether it was flowering on the date of collection. This research integrates these disparate records into a single database, and leverages them to evaluate the factors influencing historical and contemporary flowering times across 1000 well-sampled species. In turn, this information will be used to forecast shifts in seasonal flowering under projected climate scenarios. Digital herbarium records and recorded in situ observations will be used to evaluate the factors influencing historical and contemporary flowering times across an unprecedented diversity of angiosperms (1000 species, each represented by 100 specimens; 400 genera; 80 families). Predictive models will be generated to enable researchers to forecast phenological changes of individual species given specific climatic conditions.