中国蛇类物种丰富度地理格局及其与生态因子的关系

物种丰富度地理格局成因是生态学和生物地理学研究重要目标之一。生态假说在解释物种丰富度地理格局的成因上受到广泛关注。该文基于100km×100km空间分辨率研究中国蛇类物种丰富度的地理分布格局,并结合生态假说探讨影响蛇类分布格局的因素。该研究采用主轴邻距法获得基于特征值的空域数据,并同生态因子进行多元回归分析,结果表明:(1)中国蛇类物种丰富度在经、纬度上呈现多峰分布格局,物种丰富度最高的地区位于东洋界亚热带、热带,丰富度较低的地区位于青藏高原、北方草原荒漠、黄淮平原、两湖平原及鄱阳湖平原等;(2)多元回归分析能解释56.5%的蛇类物种丰富度变化,分析得出蛇类物种丰富度格局的主要影响因子是归一化植被指数、最冷季降水量和年温差。(3)模型选择结果显示,在多元回归分析中,P<0.05的变量(归一化植被指数、最冷季降水量和年温差)组成的模型是解释蛇类物种丰富度格局的最优模型。这说明蛇类物种丰富度格局是由不同生态因子共同作用的结果。基于中国蛇类物种丰富度地理格局成因研究的复杂性,该文提出在进一步研究中,需重视各假说中影响因子的选择和人类活动的影响,并在不同空间尺度上对蛇类物种丰富度地理格局进行综合分析。

Geographic patterns and ecological factors correlates of snake species richness in China

Understanding large-scale geographic patterns of species richness as well its underlying mechanisms are among the most significant objectives of macroecology and biogeography. The ecological hypothesis is one of the most accepted explanations of this mechanism. Here, we studied the geographic patterns of snakes and investigated the relationships between species richness and ecological factors in China at a spatial resolution of 100 km×100 km. We obtained the eigenvector-based spatial filters by Principal Coordinates Neighbor Matrices, and then analyzed ecological factors by multiple regression analysis. The results indicated several things: (1) species richness of snakes showed multi-peak patterns along both the latitudinal and longitudinal gradient. The areas of highest richness of snake are tropics and subtropical areas of Oriental realm in China while the areas of lowest richness are Qinghai-Tibet Plateau, the grasslands and deserts in northern China, Yangtze-Huai Plain, Two-lake Plain, and the Poyang-lake Plain; (2) results of multiple regression analysis explained a total of 56.5% variance in snake richness. Among ecological factors used to explore the species richness patterns, we found the best factors were the normalized difference vegetation index, precipitation in the coldest quarter and temperature annual range ; (3) our results indicated that the model based on the significant variables that (P<0.05) uses a combination of precipitation of coldest quarter, normalized difference vegetation index and temperature annual range is the most parsimonious model for explaining the mechanism of snake richness in China. This finding demonstrates that different ecological factors work together to affect the geographic distribution of snakes in China. Studying the mechanisms that underlie these geographic patterns are complex, so we must carefully consider the choice of impact-factors and the influence of human activities.