Using wild bees as indicators of landscape composition and bee diversity: Insights from contrasting clustering approaches

Global insect declines and pronounced spatial and taxonomic sampling biases highlight the need for efficient biodiversity monitoring tools. Indicator species offer a promising solution, yet wild bees remain underexplored in this context. To address this gap, we evaluated the applicability of wild bees as indicators of landscape composition and bee diversity across urban and agricultural environments. Using standardised pan trap sampling, we collected 26,607 wild bees representing 283 species from 32 sites in and around Prague and Brno (Czech Republic), spanning two biogeographical regions. We compared two clustering approaches: a top-down method based on landscape composition and a bottom-up method based on bee community composition. Indicator species were identified for each cluster, and co-occurrence analyses were used to characterise typical wild bee communities. Both approaches produced moderately similar groupings but differed substantially in the indicator species identified. Clustering based on bee abundances yielded more ecologically coherent indicators and clearer differentiation between urban and agricultural landscapes, while capturing effects of habitat composition and regional species pools. Analyses revealed distinct bee communities associated with forests, urban greenspaces, agricultural landscapes, and both urban and agricultural wastelands. Most indicator species were specific to a region, but a select number of species proved effective as indicators on larger scales. Our results demonstrate that selected wild bee species can serve as effective indicators of landscape composition and bee diversity. We recommend bee-based clustering where comprehensive data are available, as it better incorporates species’ ecological requirements and supports efficient monitoring and conservation planning in heterogeneous anthropogenic landscapes.