Predicting climate driven shifts in the past and future of crop pollination synchrony

Climate change has affected the timing of many ecological events, from tree leaf out to bird migration. These changes in phenology can cause mismatched timing of life history events for multiple species, for example asynchrony in pollinator activity and flower blooming. For species interactions that underpin key ecosystem services, such as pollination, climate change induced ecological asynchrony presents another challenge to ensuring that agriculture is productive and resilient. If pollinator activity becomes increasingly decoupled with the blooming period of pollinator dependent crops then yield gaps may increase. However, it is unclear whether phenological asynchrony will affect agricultural production by disrupting the timing of pollination services in relation to the blooming of flowering crops. Will the timing of species interactions change in the future? And by how much?

This research proposes to address these questions and provide solutions for strategic climate adaptation through data-driven forecasts of future pollination under different climate scenarios. However, testing whether phenological shifts occur is a research challenge because of limited historical data on the timing of life history events. By combining field experiments and AI-based detection of individual body characteristics, this research offers a new approach for determining the age and activity period of an important crop pollinator. We apply this method to museum specimens to look back in time and see whether pollinator age and activity has changed, and if climate change explains these changes. We then use advanced statistical models to forecasts whether pollination may change in the future under different climate scenarios.