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中国云南小兽寄生革螨的群落结构和空间分布
引用本文:黄丽琴,郭宪国,吴滇,王乔花.中国云南小兽寄生革螨的群落结构和空间分布[J].昆虫学报,2009,52(12):1328-1337.
作者姓名:黄丽琴  郭宪国  吴滇  王乔花
作者单位:大理学院病原与媒介生物研究所,云南大理,671000
摘    要:寄生在小兽体表的革螨可能是传播肾综合征出血热和立克次体痘等人兽共患病的媒介。本文报道了云南省28个县(市)小兽体表革螨的野外调查结果, 运用物种数、平均丰富度和Shannon多样性指数对小兽寄生革螨的群落特征和沿环境梯度的空间分布进行了研究, 并用系统聚类分析法 (SPSS 16.0软件)对18种主要小兽的革螨群落相似性进行了比较。在云南省28个县(市)共捕获到小兽14 544头, 隶属于5目(啮齿目、食虫目、攀鼩目、兔形目、食肉目)10科35属67种, 在捕获的小兽体表采集到革螨80 791头, 经鉴定属于10科33属112种。结果分析表明: 主要的宿主动物为黄胸鼠 Rattus tanezumi、齐氏姬鼠Apodemus chevrieri和大绒鼠Eothenomys miletus;纳氏厉螨Laelaps nuttalli、毒厉螨L. echidninus和贵州厉螨L. guizhouensis为革螨的优势种。齐氏姬鼠A. chevrieri、社鼠N. confucianus和黄胸鼠R. tanezumi体表寄生的革螨种类最多;臭鼩鼱Suncus murinus、齐氏姬鼠A. chevrieri和灰麝鼩Crocidura attenuata的革螨群落多样性最高。聚类分析结果表明, 大部分革螨群落的相似程度与相应小兽的亲缘关系及所处生态环境的相似性是基本一致的, 分类地位和生境选择相似的小兽, 它们的革螨群落也被聚为一类。革螨物种数沿纬度梯度的水平分布呈现两个峰值, 最大峰值出现在25°~26°N之间;沿海拔梯度的垂直分布呈单峰分布格局, 峰值在海拔2 000~2 500 m之间。革螨和小兽的多样性沿纬度梯度和海拔梯度的空间分布趋势也均表现出随着纬度和海拔的升高而先升高后降低的单峰型分布格局, 峰值分别出现在北纬25°~27°N和海拔2 000~2 500 m之间。结果提示云南革螨群落种类丰富, 多样性高。云南革螨物种数和多样性的分布格局可能直接受到古北和东洋两区系边缘效应的影响。

关 键 词:革螨  小兽  群落结构  空间分布  聚类分析  云南  

Community structure and spatial distribution of gamasid mites associated with small mammals in Yunnan, China
HUANG Li-Qin,GUO Xian-Guo,WU Dian,WANG Qiao-Hua.Community structure and spatial distribution of gamasid mites associated with small mammals in Yunnan, China[J].Acta Entomologica Sinica,2009,52(12):1328-1337.
Authors:HUANG Li-Qin  GUO Xian-Guo  WU Dian  WANG Qiao-Hua
Abstract:Ectoparasitic gamasid mites associated with small mammals have long been suspected to be the vectors of some zoonoses such as hemorrhagic fever with renal syndrome (HFRS) and rickettsialpox. In this paper, the results of wild investigations of the gamasid mites associated with small mammals in 28 counties of Yunnan, China is reported. The characteristics of community and describe the spatial distribution of gamasid mites along an environmental gradient are analyzed by using species richness, Shannon diversity index. In addition, the similarity of 18 mite infracommunities was compared by using hierarchical clustering analysis (SPSS 16.0) A total of 14 544 individuals of small mammals belonging to five orders (Rodentia, Insectivora, Scandentia, Lagomorpha and Carnivora), 10 families, 35 genera and 67 species were trapped, from which 80 791 individuals of gamasid mites representing 10 families, 33 genera and 112 species were collected. The results indicated that the dominant host species were Rattus tanezumi, Apodemm chevrieri, and Eothenomys miletus, while dominant gamasid mite species were Laelaps nuttalli, L echidninus and L guizhouensis. The mite infracommunities associated with A. Chevrieri, N. Confucianus and R. Tanezumi exhibited the highest species richness, while mite infracommunities on Suncus murinus, Apodemus chevrieri and Crocidura attenuata presented the highest diversity. The results of cluster analysis showed that the similarity of most mite communities in accordance with the taxonomic relationship and the habitat of their corresponding small mammal hosts. The mite communities are clustered into the same group when their hosts are similar in zoological taxonomy and habitat selection. The horizontal patterns of gamasid mite species richness along a latitudinal gradient showed two peaks, the highest richness was recorded at the latitude 25°N to 26°N, while the vertical patterns presented a single-peak curve along the elevation gradient, peaking at the elevation of 2 000 m to 2 500 m. The diversity spatial distribution patterns of gamasid mites and their small mammal hosts showed the similar trends of single-peak curves which gradually increased and then decreased with increasing of latitude and elevation, peaking at the latitude 26°N to 27°N and the elevation of 2 000 m to 2 500 m. The results suggest that the community structure of gamasid mites in Yunnan Province has high species richness and diversity. The spatial distribution patterns of gamasid mites in Yunnan Province may be the results of the edge effect between the Oriental and Palaearctic realms.
Keywords:Gamasid mites  small mammals  community structure  spatial distribution  cluster analysis  Yunnan
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