Welcome to Chinese Journal of Ecology! Today is Share:

cje

Previous Articles     Next Articles

Ant species diversity in northeastern Yunnan.

HUANG Zhao, XU Zheng-hui*, LIU Xia, LI Li-mei, WANG Ya-li, SHI Sheng-hui, SHI Yun, CHEN Zhi-feng   

  1. (Key Laboratory of Forest Disaster Warning and Control in Yunnan Province, College of Biodiversity Conservation, Southwest Forestry University, Kunming 650224, China).
  • Online:2019-12-10 Published:2019-12-10

Abstract: We surveyed ant species diversity of the northeast Yunnan with plot method. The results show that there are 120 species, 41 genera, and 6 subfamilies of Formicidae in the study area. Pheidole watsoni Forel and Paraparatrechina sakurae Ito are the dominant species. There were 6 common species, 14 relatively common species, 33 relatively rare species, and 65 rare species. The order of ant species richness on the five vertical zones is: north slope of Daxuecao (70 species) > west slope of Yaoshan (50 species) > north slope of Zhenxiong (47 species) > south slope of Daxuecao (39 species) > north slope of Xiaocaoba (36 species). Ant species richness, individual density, and diversity indices were generally decreasing with increasing altitude, suggesting that altitude and air temperature were the key factors driving species diversity of ant communities. The main indices of ant communities showed multi-domain effect, as they were affected by climatic factors and human disturbance, with a more important role of the latter one. Although the five vertical zones have been disturbed by human beings in varying degrees, large areas of natural forests are retained in the Wumengshan Nature Reserve with Daxuecao as the core zone and Yaoshan Nature Reserve with Mount Yaoshan as the core zone. Due to the fogy and humid climatic characteristics in the study area, ant fauna and diversity are at the average level of that in Yunnan Province. Ant communities vary vertically, with different ecological functions and conservation values.

Key words: spring vegetation phenology, spatio-temporal distribution, climate change, satellite data.