Using plant-pollinator interactions to identify key species for planning tropical forest restoration

There is still a lack of practical guidelines for understanding species roles and planning restoration strategies to enhance plant-pollinator interactions and support ecosystem functioning. We applied a network approach to understand the evolution of plant-pollinator restoration patterns and identify priority species, thus advancing restoration planning. Specifically, we compared species composition and network metrics along a gradient of time postdisturbance, from the initial stage of restoration to pristine forest in the Eastern Amazon. We found that mining type is a predictor of species composition. We observed the recovery of interaction diversity and pollinator specialization in the early stages of restoration. Mining type affected connectance, interactions, and species richness, and the restoration stage affected the number of links. From the interactions, we built a trait-based framework to select manageable native species for initial restoration. The species selection framework proposed here is useful not only for forest restoration but also for the restoration of other areas and case studies (e.g. agroecosystems, conservation units, and ecological corridors) and can be adapted depending on the goals of each project. Here, we provide practical information for the management of mined land restoration in the Eastern Amazon and for restoration planning across broader scales.