Automated flower monitoring with deep learning reveals fine-scale microclimate selection by pollinators

A central challenge in predicting biological responses to climate change is bridging the mismatch between coarse changes in climate and the fine-scale environments organisms experience.^1,2 Behavior plays a crucial, understudied role in bridging these scales. For small ectotherms like pollinating insects, behavioral responses to microclimate variation can buffer or amplify thermal exposure, generating temperature differences that meet or exceed mean climate warming.^3,4,5,6,7 Realized climate impacts on pollinators and pollination depend strongly on behavioral responses to thermal environments, response variation across taxa, and the dynamic microclimatic heterogeneity organisms experience. Yet, our understanding of microclimatic dynamics at insect-relevant scales-or how pollinators exploit them-remains limited. We combined a novel, automated, deep-learning-based pollinator monitoring system⁸ with physical operative temperature models to quantify pollinator responses to dynamic microclimate gradients at fine spatial (meters) and temporal (minutes) scales. In experimental shade microclimate manipulations, insect pollinators dynamically tracked thermal microclimates. In naturalistic plant communities, microclimate heterogeneity varied over time, driven by short-term shifts in temperature, solar radiation, and diurnal cycles, and increased seasonally, coinciding with vegetative growth. Pollinator taxa showed divergent responses to microclimatic changes, indicating potential thermal buffering and amplification, suggestive of differential thermal tolerance and life history constraints. Data-driven modeling suggests taxon-specific responses to microclimate could drive divergent thermal risk under identical environmental conditions, altering the spatial structure of plant-pollinator communities, and impacting pollination efficacy. Together, we show that climate impacts are shaped by pollinator behavior and microclimate dynamics, suggesting that managing for microclimatic variation may be impactful for pollinators and pollination.