摘要:弹尾类是土壤动物中常见的优势类群，其作为土壤微食物网的重要组成部分，参与凋落物分解、土壤团聚体形成等重要生态过程。以往对弹尾类分布格局的研究通常关注其在不同海拔梯度或者不同生境类型下的分布情况，但在不同气候带下弹尾类多样性沿纬度分布格局仍不清楚。为讨论不同气候带下弹尾类沿纬度的分布格局及其潜在的环境影响机制，于2017年10月（雨季末期）在云南省同一经度（E 101°）分布的三种典型气候带设置海拔梯度样带：热带雨林（西双版纳，800 m、1000 m、1200 m、1400 m）、亚热带常绿阔叶林（哀牢山，2000 m、2200 m、2400 m、2600 m）、亚高山针叶林（丽江玉龙雪山，3200 m、3400 m、3600 m、3800 m），采集凋落物层弹尾类并调查分析土壤温度、土壤含水量、凋落物厚度、土壤pH、土壤容重及土壤孔隙度等环境因子。利用Berlese-Tullgren法收集土壤动物，共获得弹尾类19150只，隶属于10科29属，其中符属（39.9%，等节科）数量最多，其余优势属为棘属（21.7%，棘科）和球角属（10.1%，球角科），这3个属合计占总体的71.7%。凋落物层弹尾类的密度在亚高山针叶林明显高于热带雨林和亚热带常绿阔叶林，弹尾类的属数排序由多到少依次为热带雨林、亚高山针叶林、亚热带常绿阔叶林。通过最小二乘回归法对弹尾类多样性的海拔格局进行回归分析，得出弹尾类的丰富度指数（Margalef's指数、Menhinick's指数）、多样性指数（Shannon-Wiener多样性指数、Simpson多样性指数）和均匀度指数（Pielou均匀度指数）沿热带雨林、亚热带常绿阔叶林、亚高山针叶林呈单调递减格局。通过全模型子集回归筛选最佳环境模型表明，温度是影响弹尾类多样性沿不同气候带分布格局的主要环境因子。本研究为预测不同气候带下弹尾类多样性如何响应环境变化提供参考。



Abstract:As an important part of the soil microfood-web, Collembola is a dominant group in soil fauna, which participates in litter decomposition and promotes the formation of soil aggregates. Previous studies have focused on the distribution pattern of Collembola at different altitudes or habitats, but the distribution pattern of Collembola diversity along latitudes in different climatic zones is still unclear. There are three typical climatic zones in Yunnan Province, which are tropical, subtropical and subalpine. They are all located in the eastern margin of the Qinghai-Tibet Plateau. In order to explore the latitudinal distribution pattern and potentially environmental impact mechanism of Collembola in different climatic zones, the elevational gradient transects were set up in three typical climatic zones of Yunnan Province in October 2017 (at the end of the rainy season), namely the tropical rainforest (800 m, 1000 m, 1200 m, 1400 m), subtropical evergreen broad-leaved forest (2000 m, 2200 m, 2400 m, 2600 m), and subalpine coniferous forest (3200 m, 3400 m, 3600 m, 3800 m). The longitude of all transects is almost the same (E 101 degrees), which minimizes the impact of longitude, topographic differences and geological history on the results of the study. We collected soil fauna in litter layer per unit area and investigated the environmental factors such as soil temperature, soil water content, litter amount, soil pH, soil bulk density and soil porosity. Soil animals were extracted by Berlese-Tullgren method. We put Collembola sample in 75% alcohol solution and identified Collembola to genus level. A total of 19150 Collembola individuals were obtained, belonging to 29 genera and 10 families. At family level, the number of Isotomidae was the largest (59.9%), followed by Onychiuridae (21.8%) and Onychiuridae (10.1%). These three families accounted for 91.8% of the total individuals. At genus level, the most abundant genus was Folsomia (39.9%, Isotomidae). The secondary dominant genus was Onychiurus (21.7%, Onychiuridae) and then Hypogastrura (10.1%, Hypogastruridae). These three genera accounted for 71.7% of the total individuals. The density of Collembola in litter layer was significantly higher in sub-alpine coniferous forest than that in tropical rainforest and subtropical evergreen broad-leaved forest. The genus number of Collembola decreased as the following order: tropical rainforest, sub-alpine coniferous forest, and subtropical evergreen broad-leaved forest. Based on the regression analysis of the elevational diversity patterns of Collembola by least squares regression method, the richness index (Margalef's index, Menhinick's index), diversity index (Shannon-Wiener index, Simpson index), and evenness index (Pielou evenness index) of Collembola decreased monotonously along the tropical rainforest, subtropical evergreen broad-leaved forest and sub-alpine coniferous forest. Taking each diversity index as the response variable, with temperature (mean soil temperature, maximum soil temperature and minimum soil temperature in rainy season), litter amount, soil pH, soil water content, soil bulk density, and soil porosity as explanatory variables, the best environmental model (minimum AIC value) was selected by subset regressions from full model. We concluded that temperature was the main environmental factor affecting the distribution pattern of Collembola diversity (positively correlated) along different climatic zones. This study enhances our understanding on how the litter Collembola will respond to future environmental changes among different climatic zones, especially in the context of global climate change.





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