Blue Vane and Pan Traps Are More Effective for Profiling Multiple Facets of Bee Diversity in Subtropical Forests

Insects. 2024 Nov 20;15(11):909. doi: 10.3390/insects15110909.

Abstract

The choice of trap in entomological surveys affects the composition of captured insects, though previous comparative studies have been limited in the types of composition measured, and the effects of environmental context. We assessed the sampling bias of several traps commonly used in pollinator monitoring: blue, yellow, and white pan traps, and blue vane traps, towards different taxonomic and functional groups and their efficiency in measuring taxonomic, phylogenetic, and functional diversity. Analyses were performed in monoculture and mixed forests to understand the environmental context of trap efficiency. We found that blue pan traps generally outperformed other types in bee capture and exhibited a preference for Halictidae bees. Blue pan traps yielded the highest species richness and phylogenetic diversity, while blue vane traps captured the highest functional richness. Bias differences were frequently detected in mixed forests compared with monoculture forests. We also found the combination of blue vane and pan traps consistently correlated highest with a complete survey among two-method combinations. Based on our findings, we recommend a combination of blue vane and pan traps to obtain a more comprehensive bee collection in an efficient manner. Additionally, it is crucial to consider habitat type when designing bee trapping protocols to ensure an accurate representation of bee communities.

Keywords: DNA barcoding; bee diversity; biodiversity monitoring; blue vane traps; forest insects; pan traps; pollinator monitoring.

Grants and funding

This work was supported by grants (No. 32250610207) from the National Science Foundation of China and (No. 2020FSB0001) from CAS President’s International Fellowship Initiative (PIFI) to D.C.; a grant (No. 41972029) from National Science Foundation of China to J.S.H; and Sino BON Insect Diversity Monitoring Network (Sino BON-Insect).