High elevation plant communities are rapidly changing due to climate warming, with species potentially changing their ranges in elevation. Pollinators respond to changes in flowers' density and type, however it's difficult to anticipate future changes in the structure of alpine interaction networks. Currently, information on plant-pollinator interactions is often based on direct observations by researchers in the field, which often provides only limited data. The availability of affordable digital video recording devices and advances in computer vision has recently sparked the development of several automated pollinator monitoring systems. When coupled with powerful machine learning algorithms, these systems can enable the identification of floral visitors from images, but their application remains limited. In this project we will test and further develop methods for observing pollinators in the field, to study community changes, species interactions networks and ecosystem function.
2022 - 2023