Even though flowering times are important indicators of how plants are responding to climate change, we still need to characterize the flowering patterns of a larger number of species. Only by doing so we will be able to have a better understanding of the extension of possible shifts in the phenological activities of plants in response to changes in climate. However, long-term time series demand an ongoing monitoring in the field and are, thus, difficult to compile. In order to fill this gap, researchers have been using biological collections as sources of phenological information. Specimens in herbaria have been collected for a long time and often include information on the phenology of the individual, making these collections invaluable sources of long-term datasets. Here, we plan on building a series of algorithms to gather information on the flowering times of specimens in virtual collections in Brazil. These algorithms will help us collect and process text and image data to determine if a given specimen was flowering when it was collected. We will select those species with distinctive flowers and records that span for long periods. This way, we will be able to determine the flowering patterns of a larger number of species. Next, we will match these patterns with climate cues, such as temperature and rainfall. After determining the periods of flowering activities of each selected species and to which, if any, climate variables they respond, we will look for evidence of shifts in species time series in response to shifts to changes in the climate.
News published in Agência FAPESP Newsletter about the scholarship: