Fragmented grasslands in different landscape structures provide different opportunities for cavity‐nesting Hymenoptera
Year: 2026
Type: article
Abstract: The global decline in insects threatens ecosystem functioning, but the drivers are region‐ and habitat‐specific. In the Hungarian Great Plain, loss of key habitats due to land‐use intensification has severely fragmented semi‐natural grasslands, yet their role in supporting cavity‐nesting Hymenoptera remains poorly understood. We studied 60 fragments (30 sand steppes in forest‐dominated landscapes, 30 loess steppes in agricultural landscapes) along size and isolation gradients. We used trap nests to investigate occupancy, brood‐cell abundance, species richness, parasitism and nesting materials. In sand steppes, brood‐cell abundance was higher in less connected fragments, whereas parasitoid species richness and parasitism showed size‐dependent relationships with connectivity. Large sand fragments hosted more soil‐based nesting‐material users than small ones. In loess steppes, small fragments had higher occupancy and greater spider‐hunting wasp brood‐cell abundance. Flowering‐species frequency increased brood‐cell abundance and parasitism ratios of bees and parasitoids. Bee brood‐cell abundance increased with connectivity in large, but not small, loess fragments. Community composition differed between habitat types, and fragmentation predictors showed contrasting associations across the systems: landscape configuration dominated in sand steppes, whereas fragment size and floral resources were most important in loess steppes. Conservation should recognize that small, isolated sand‐steppe fragments can support substantial nesting output and multitrophic interactions, whereas in loess steppes maintaining local floral resources and a network of fragments is key to sustaining cavity‐nesting Hymenoptera and ecosystem services.
DOI: 10.1111/icad.70117
Language: English
Topic: Plant and animal studies
Domain: Life Sciences
SDG: Life on land
Open Access status: hybrid
Estimated APC paid: $4,750
Funder: Magyar Tudományos Akadémia
Award: G7788839506
OpenAlex ID: W7168796506
