生物多样性

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生境类型与月份变化对热带蜂类昆虫多样性与群落结构的影响

唐航, 孙牧汎, 林小甜, 陈怡, 曹凤勤, 杨艳   

  1. 海南大学, 571737
    中国热带农业科学院三亚研究院, 572025
  • 收稿日期:2026-05-09 修回日期:2026-07-08
  • 通讯作者: 杨艳
  • 基金资助:
    资助项目Supported projects:海南省自然科学青年基金项目(323QN196); 海南省重点研发项目(ZDYF2026SXLH027)

Impact of Habitat Types and Monthly Variation on the Diversity of Tropical Bee and Wasp Communities

Hang Tang, Mufan Sun, Xiaotian Lin, Yi Chen, Fengqin Cao, 艳 杨   

  1. , Hainan University 571737,
    , Sanya Research Institute of the Chinese Academy of Tropical Agricultural Sciences 572025,
  • Received:2026-05-09 Revised:2026-07-08
  • Contact: Yan Yang

摘要: 蜂类昆虫是农业生态系统中的重要功能类群,既包括提供传粉服务的传粉蜂,也包括参与害虫控制的寄生蜂和捕食性蜂类群。明确其群落结构的时空变化规律及驱动机制,对传粉者多样性与农田天敌多样性保护具有重要意义。然而,在热带农业景观中,生境类型与月份变化对蜂类昆虫群落的相对作用仍缺乏系统认识。在海南大学儋州校区农业景观中选取道路、荒地、农田和林地四类生境开展为期一年的蜂类昆虫逐月调查,采用α多样性指数、非度量多维尺度分析(NMDS)、置换多元方差分析(PERMANOVA)、β多样性分解及指示种分析等方法,系统解析群落结构的时空变化特征及驱动机制。共记录蜂类昆虫2943头,隶属于17科75属120种。控制采样强度后,各生境群组间α多样性未检测到显著差异,其中位数呈现数值差异。PERMANOVA结果显示,生境和月份均与群落组成差异显著相关,其中月份对群落变异的解释率高于生境。β多样性分解结果显示,生境尺度和月份总体尺度上的群落差异均主要由物种周转过程驱动,嵌套性贡献较低。指示种分析表明,道路生境具有18种显著指示种(如Apis ceranaApis melliferaAmegilla sp. 1等),林地有1种显著指示种(Cremnops sp. 1),而农田与荒地未检出显著指示种。热带农业景观中蜂类昆虫群落组成差异主要由月份更替驱动(解释度 19.9%),生境类型的解释贡献更低(9.5%),群落空间与时间分化均以物种周转过程为核心。本研究揭示了时间过程在蜂类昆虫群落构建中的核心作用,为热带农业生态系统中蜂类昆虫多样性保护与生境管理提供理论依据。

关键词: 蜂类昆虫, 生境异质性, 月份动态, 群落结构, α多样性, β多样性, 物种周转

Abstract

Aim: Bee and wasp constitute an important functional group in agroecosystems, encompassing pollinators that provide pollination services, as well as parasitoid wasps and predatory wasp assemblages involved in pest regulation. Elucidating the spatiotemporal variation patterns and driving mechanisms of their community structures is of great significance for the conservation of pollinator diversity and farmland natural enemy diversity. However, the relative contributions of habitat types and monthly dynamics to bee and wasp communities remain poorly understood in tropical agricultural landscapes. 

Method: A one‑year monthly survey of bee and wasp taxa was conducted across four habitat types (roadside, wasteland, farmland, and woodland) in the agricultural landscape of Danzhou Campus, Hainan University. We applied α‑diversity indices, non‑metric multidimensional scaling (NMDS), permutational multivariate analysis of variance (PERMANOVA), β‑diversity partitioning, and indicator species analysis to systematically explore the spatiotemporal variation and driving mechanisms of bee and wasp community structure. 

Result:  A total of 2943 bee and wasp individuals were collected, belonging to 120 species, 75 genera, and 17 families. After controlling for sampling intensity (effective monthly sweep net sampling times), no significant differences in α-diversity were detected among habitat groups, although their median values differed numerically. PERMANOVA revealed that both habitat and month significantly affected community composition, with month explaining a higher proportion of community variation than habitat. β‑diversity partitioning indicated that community dissimilarity at both habitat and temporal scales was predominantly driven by species turnover, while the contribution of nestedness was low. Indicator species analysis showed that roadside habitats harbored the highest number of characteristic indicator species (18 species, including Apis cerana, Apis mellifera, and Amegilla sp. 1), forest habitat had one significant indicator species (Cremnops sp. 1), while farmland and wasteland had no significant indicator species. 

Conclusion: In tropical agricultural landscapes, temporal turnover across months is the primary driver of compositional variation in bee and wasp communities, accounting for 19.9% of the total variance, while habitat type contributes far less explanatory power at only 9.5%. Species turnover constitutes the core process underlying both spatial and temporal differentiation of bee and wasp taxa communities. Our findings highlight the crucial role of temporal processes in pollinator community assembly, and provide a theoretical basis for bee and wasp biodiversity conservation and habitat management in tropical agroecosystems.

Key words: bee and wasp, habitat heterogeneity, monthly dynamics, community structure, α-diversity, β-diversity, species turnover