Quantifying biotic interactions at scale is critical to understanding ecosystem functions, such as plant‐pollinator interactions. Here, we demonstrate how woody plant functional traits and vegetation structure gathered with remote sensing can aid in predicting plant‐pollinator network indices from fine to broad spatial extents. We analysed 209 tropical plant‐pollinator networks, where vegetation characteristics were generated using spectral and LiDAR data. We found that pollination network structures were correlated to plant traits reflective of drought‐adaptive strategies and nutrient availability. Networks were predicted to be more nested and less specialised with increasing leaf nitrogen content. Further, relationships between leaf thickness, photosynthetic capacity, and water content indicate that networks may be more modular and less connected under arid, high‐light conditions where plants invest in water‐conserving tissues yet maintain high photosynthetic rates. Our findings reveal plant functional strategies as underlying environmental mechanisms that structure plant‐pollinator networks, paving the way to predict interactions using remote sensing.

Plant-pollinator interactions are critical to terrestrial ecosystem functioning and global food production but are experiencing increasing pressures from land use and global environmental changes. Plant functional traits and vegetation structure reflect the responses of vegetation to local environmental pressures and relate directly to the nesting and floral resources available to pollinators. Yet, little is known about the role of vegetation traits and structure in determining the organisation of plant-pollinator networks, nor on methods to predict such networks at broad spatial scales. Here, we evaluate how plant functional traits and vegetation structure influence plant-pollinator interaction patterns and how satellite remote sensing can aid in predicting such patterns at scale. We analysed a total of 209 plant-pollinator networks from across the tropics. Plant functional traits and vegetation structure were generated using spectral and LiDAR remote sensing. We found that pollination networks responded to vegetation functional traits along a spectrum of acquisitive to conservative plant resource use strategies. Networks were more modular in areas with shorter vegetation and low leaf nutrient content, while higher leaf photosynthetic capacity and leaf water content were associated with higher network connectance. Vegetation structure metrics associated with canopy openness and more acquisitive functional traits (high leaf photosynthetic capacity and phosphorus content) were associated with greater network specialisation (H₂’). Additionally, networks were more nested with increasing trait variability. Our findings reveal that plant functional strategies play an important role in structuring biotic interactions such as those between plants and pollinators, paving the way to predict these interaction networks at scale using remote sensing approaches.