The influence of local and landscape scale on single response traits in bees: A meta-analysis

Abstract

Assessments of environmental drivers that regulate the functional composition of various organisms have become more frequent in the ecological literature, as this approach establishes a more direct connection between community structure and ecosystem functions. Bee response traits, such as sociality, body size, nest location, nest behaviour, and dietary specialization, have been reported in empirical studies that examine the role of land use intensity in functional diversity. However, empirical studies include different descriptors measured at different spatial scales, producing poor generalizations. Processes operating at different scales may have different effects depending on the response traits considered in the analysis. In this meta-analysis, we provide a quantitative assessment of the role that the structural complexity of habitats at local and landscape scales plays in the richness and abundance patterns of bees, considering different response traits. As indicated through this meta-analysis, the descriptors of structural complexity at the local scale explained more of the richness and abundance of bees with distinct response traits than the descriptors at the landscape scale. In addition, high management intensity has a negative effect on the different response traits. Below-ground nesting bees and social bees showed different abundance trends, which suggest a mechanism denominated ‘response diversity’. This result suggests that the adoption of hybrid management strategies at the local scale could support the richness and abundance of different bees with distinct response traits in agroecosystems. These distinct response traits can be an important ecological pattern that contributes to the development of management strategies that maintain, in space and time, bees with distinct response traits. However, we should analyse the communities in terms of clusters of response traits, considering the possible synergies and trade-offs between these traits.