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

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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.