昆虫学报 ›› 2020, Vol. 63 ›› Issue (10): 1242-1259.doi: 10.16380/j.kcxb.2020.10.010

• 研究论文 • 上一篇    下一篇

茶园周边景观格局对茶小绿叶蝉种群遗传结构的影响

李金玉1,2,3, 牛东升1,2,3, 陈杰1,2,3, 尤士骏1,2,3,*, 尤民生1,2,3,*   

  1. (1. 福建农林大学应用生态研究所, 闽台作物有害生物生态防控国家重点实验室, 福州 350002; 2. 福建农林大学, 教育部害虫生态防控国际合作联合实验室, 福州 350002; 3. 福建农林大学, 农业部闽台作物有害生物综合治理重点实验室, 福州 350002)
  • 出版日期:2020-10-20 发布日期:2020-11-06

Effects of landscape pattern around tea plantation on the population genetic structure of the tea green leafhopper, Empoasca onukii (Hemiptera: Cicadellidae)

LI Jin-Yu1,2,3, NIU Dong-Sheng1,2,3, CHEN Jie1,2,3, YOU Shi-Jun1,2,3,*, YOU Min-Sheng1,2,3,*   

  1.  (1. State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou 350002, China; 2. Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou 350002, China; 3. Key Laboratory of Integrated Pest Management for Fujian-Taiwan Crops, Ministry of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China)
  • Online:2020-10-20 Published:2020-11-06

摘要: 摘要: 【目的】研究不同茶园茶小绿叶蝉Empoasca onukii种群的遗传分化和基因流格局,探究其种群遗传结构差异和扩散特点及其与茶园景观格局的关系。【方法】以福建省安溪县为研究区域,在运用ArcMap10.5和R软件包raster分析研究区域景观组成和结构的基础上,选取周边景观格局不同的18个茶园采集茶小绿叶蝉(530个个体),基于23个微卫星位点对这些个体进行PCR扩增和基因型测定,采用ARLEQUIN 3.5.2, FSTAT 2.9.3和R软件包adegenet 2.0.0分析其遗传多样性和遗传分化情况;采用STRUCTURE 2.3.4和R软件包adegenet 2.0.0中的DAPC程序分析其种群遗传分化;利用BAYESASS 3.0.4估算种群间最近几代的迁移率;同时利用景观遗传学的统计方法Mantel、距离矩阵多元回归模型(MRM)和一般线性模型(GLMM)将茶小绿叶蝉种群遗传分化与景观组成和景观结构的空间数据进行关联分析。【结果】供试18个茶小绿叶蝉种群的23个微卫星位点的等位基因数为9~52,等位基因丰富度(AR)为3.686~4.397,基因多样性(DIV)为0.676~0.734,期望杂合度(He)为0.659~0.729。聚类分析显示,有大量森林生境的西北部5个相邻样点的种群组成一个类群,有大量居民点和其他作物田分布的东北部的5个相邻样点的种群分为两个类群,而集约化种植模式明显的南部样点的种群也分成两个类群。两两种群间的Nei氏遗传距离为0.042~0.984,Provesti氏遗传距离为0.207~0.650,遗传分化指数FST为0.002~0.222。BAYESASS分析显示,种群间的现时基因流(Nm)相对较低,介于0.007~0.180,而在种群内部的基因流介于0.674~0.854。在此基础上,Mantel和距离矩阵多元回归模型分析显示,地理距离和采样点周围1 000 m范围内草地面积占比是与茶小绿叶蝉种群遗传分化有关的两个关键因子;一般线性模型分析进一步证实茶小绿叶蝉种群遗传分化与这两个关键因子线性关系显著,茶小绿叶蝉种群遗传多样性与采样点周围半径1 000 m范围内草地面积占比线性关系显著。【结论】结果说明研究区域内茶小绿叶蝉种群形成了明显的遗传分化结构和地理距离隔离格局,异地种群间现时基因交流受限明显,因此推测茶小绿叶蝉其自主扩散能力比较有限,不具有远距离迁飞的习性。茶园周围1 000 m范围内草地生境对茶小绿叶蝉种群的遗传多样性具有积极作用,茶园周边景观组成和尺度范围可能通过影响茶小绿叶蝉种群的扩散和定殖过程而与其种群遗传结构相关联。

关键词:  茶小绿叶蝉, 茶园, 景观格局, 遗传结构, 基因流, 害虫可持续治理

Abstract: 【Aim】 This study aims to analyze the patterns of genetic differentiation and gene flow among different populations of the tea green leafhopper, Empoasca onukii, in different tea plantations, and to investigate the genetic structure difference and dispersion characteristics of E. onukii populations and their relationship with the landscape pattern around tea plantation. 【Methods】 A total of 530 E. onukii samples were collected from 18 tea plantations in Anxi County, Fujian Province, southeastern China. ArcMap 10.5 and raster of R package were used to analyze the landscape composition and configuration around each studied tea plantation. E. onukii samples were then individually amplified and individually genotyped at 23 microsatellite loci. The genetic diversity and genetic differentiation of E. onukii populations were measured using ARLEQUIN 3.5.2, FSTAT 2.9.3 and R package adegenet 2.0.0. Population genetic differentiation was analyzed using both STRUCTURE 2.3.4 and DAPC in R package adegenet 2.0.0. BAYESASS 3.0.4 was used to estimate the dispersal rates over the last few generations among populations. Meanwhile the correlation between the genetic differentiation of E. onukii populations and the spatial data of landscape composition and landscape configuration was analyzed by using Mantel tests, multiple regression on distance matrices (MRM) and generalized linear mixed models (GLMM). 【Results】 All the 23 microsatellite loci in 18 E. onukii populations were polymorphic, with alleles varying from 9 to 52, the allelic richness (AR) from 3.686 to 4.397, the gene diversity (DIV) from 0.676 to 0.734, and the expected heterozygosity (Hefrom 0.659 to 0.729. Cluster analysis showed that the populations of five sampling sites from the tea plantations surrounded by woodland habitats in the northwestern Anxi clustered into one distinct cluster, the populations of five sampling sites from the tea plantations surrounded by residential areas and croplands in the northeastern Anxi formed two separate clusters, and the populations of sampling sites from the intensified tea plantations in the southern Anxi formed two clusters. The Nei’s distance between two populations ranged from 0.042 to 0.984, Provesti’s genetic distance from 0.207 to 0.650, and the pairwise FST value from 0.002 to 0.222. BAYESASS analysis showed fairly low gene flow (Nm)(0.007-0.180) among populations, and the gene flow within population ranged from 0.674 to 0.854. The Mantel tests and MRM model demonstrated that geographical distance and the area percentage of grassland in the circular sector of 1 000 m radius around sampling site were two key factors in shaping genetic patterns of E. onukii populations. GLMM further confirmed a significant linear relationship between the genetic differentiation of E. onukii populations and these two key factors, and also between genetic diversity of E. onukii populations and the area percentage of grassland in the circular sector of 1 000 m radius around sampling site.【Conclusion】 The results provide direct evidence for significant population genetic differentiation and isolation by distance in E. onukii, and suggest that limited recent gene flow has occurred among populations sampled from different sites. These findings support the idea that E. onukii may have limited dispersal capacity and is unlikely to naturally undergo long-distance migration. The grassland habitat adjacent to tea plantation at the spatial scale of 1 000 m has positive effects on the genetic diversity of E. onukii populations. The landscape composition and scale around tea plantations may be related to the genetic structure of E. onukii by affecting the dispersal and colonization of E. onukii populations.

Key words: Empoasca onukii, tea plantation, landscape pattern, genetic structure, gene flow, sustainable pest management