Diversity Patterns of Pollinating Insect Communities in the Central Qinling Mountains and Their Responses to Environmental Change

This study investigated pollinator community structure and its environmental drivers across different habitats in the central Qinling Mountains, a key biodiversity hotspot in China. Field surveys were conducted at approximately 40 sampling sites from March to September during 2024–2025, covering multiple seasons, with concurrent measurements of climatic, topographic, and vegetation variables. Alpha diversity patterns revealed strong habitat-dependent differences, with natural habitats supporting higher species richness and Shannon diversity, whereas agricultural habitats exhibited lower diversity but higher dominance. Semi-natural habitats showed intermediate characteristics. Taxonomic groups responded differently, indicating uneven sensitivity to habitat change. Beta diversity analyses further demonstrated significant community differentiation among habitats, with natural and agricultural habitats showing the greatest dissimilarity and semi-natural habitats acting as transitional systems. Environmental analyses indicated that pollinator community structure and diversity were jointly shaped by landscape composition, climatic conditions, and plant resource availability. Forest cover was positively associated with diversity maintenance, whereas increasing agricultural proportion and wind disturbance generally exerted negative effects. Precipitation and humidity showed overall positive influences, but responses varied among taxonomic groups. Importantly, interaction analyses revealed that environmental effects were strongly context-dependent. Landscape structure and floral resource availability significantly mediated climatic influences on community structure, diversity, and abundance. Forest cover tended to buffer climatic stress, while agricultural expansion amplified adverse environmental effects. These findings highlight that pollinator community responses are governed by the combined and interactive effects of climate, landscape, and resource gradients, emphasizing the importance of multi-factor mechanisms in shaping community dynamics.