Abstract

Abstract With their large diversity of species, solitary bees are important pollinators of crops and native plant communities in agricultural landscapes. Stressors such as changing landscapes, climate and pesticide exposures may affect populations differently, dependent on each species' ecological traits. We developed a population model for solitary bees, SolBeePop, which can be applied to simulate a variety of species by using species‐specific traits, including the nesting strategies. Species' phenological traits are mechanistically combined with input time series capturing temporal and spatial variability in landscape compositions. Calibration and validation of the model with empirical study data demonstrate that the model can capture realistic dynamics in bee populations. In simulations conducted representing four species, Osmia bicornis, Megachile rotundata, Nomia melanderi and Eucera pruinosa, identical conditions and assumed nesting resource limitations resulted in different population‐level outcomes, indicating the importance of interactions between external factors and species‐specific traits including phenological, survival and reproductive traits. Synthesis and applications. The publicly available model is intended as a tool for the assessment of population‐level outcomes of stressors, for instance, the limitation of floral resources in agricultural landscapes, limitation of nesting habitat and the exposure to pesticides. Realistic landscape scenarios can be tested and available data for one species can be used to estimate outcomes in other solitary bee species, informing conservation plans and risk assessment approaches to support managed and natural populations in the field.

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