Zhang Feng-Ying, Liao Zi-Yan, Pan Kai-Wen, Zhang Meng, Zhao Yu-Lin, Zhang Lin
Sichuan Forestry and Grassland Survey and Planning Institute, Chengdu 610081, China.
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China.
Ying Yong Sheng Tai Xue Bao. 2021 Jul;32(7):2290-2300. doi: 10.13287/j.1001-9332.202107.012.
How to accurately model species macro-richness patterns and endemism centers is a key focus of biodiversity conservation efforts and a hot biogeographical topic. Southwest China is one of regions with high Fagaceae species richness, the species diversity patterns and driving mechanisms are unclear. In this study, the distribution pattern of species richness (SR), weighted endemism (WE), and corrected weighted endemism (CWE) indices were estimated based on 7258 occurrence points of 161 Fagaceae species in Southwest China using both occurrence-to grid method and species distribution model (SDM). We used the spatial autoregressive (SAR) model to analyze the relationship between diversity indices and environmental factors. Overall, the three SDM-simulated diversity indices were more continuous in values than that of the occurrence-to grid method, though the distributions of those indices obtained by the two methods were similar. The areas with high SR value were mainly distributed in the south edge of Yunnan, north Guangxi and southwest Guangxi (62-89 species). The maximum of WE concentrated in south Yunnan and west Guangxi (1.77-5.02). The highest CWE (0.07-0.17) was found in southeast Tibet, Qinling-Daba Mountains, southwest Guangxi, and southeast Yunnan. The SAR models showed significant effect of precipita-tion in the driest month, standard deviations of seasonal temperature, altitude range and soil organic carbon content on SR. The effects of precipitation in the driest month, standard deviations of seaso-nal temperature, potential evaporation and altitude range on the WE were significant. The precipitation in the driest month, standard deviations of seasonal temperature, historical temperature change, coefficient of variation of enhanced vegetation index and altitude variation had significant effects on the CWE. The of SAR model for SR, WE and CWE was 0.857, 0.733, 0.593, respectively, being higher than that of ordinary least squares (OLS) (=0.689, 0.425, 0.422). In conclusion, water availability, climate seasonality, habitat heterogeneity, historical climate change and soil condition were the most important factors limiting the distribution of SR and WE of Fagaceae in Southwest China. The SR and WE centers of Fagaceae were located in south and southeast Yunnan, southwest Guangxi, west Guangxi, Qinling-Daba Mountains, and southeast Tibet, where should be adequately protected.
如何准确模拟物种丰富度格局和特有中心是生物多样性保护工作的重点和生物地理学的热点话题。中国西南地区是壳斗科物种丰富度较高的地区之一,但其物种多样性格局及驱动机制尚不清楚。本研究基于中国西南地区161种壳斗科植物的7258个分布点,采用分布点到网格法和物种分布模型(SDM),估算了物种丰富度(SR)、加权特有性(WE)和校正加权特有性(CWE)指数的分布格局。我们使用空间自回归(SAR)模型分析了多样性指数与环境因子之间的关系。总体而言,尽管两种方法得到的指数分布相似,但三种SDM模拟的多样性指数在数值上比分布点到网格法更连续。SR值高的区域主要分布在云南南部边缘、广西北部和广西西南部(62 - 89种)。WE的最大值集中在云南南部和广西西部(1.77 - 5.02)。最高的CWE(0.07 - 0.17)出现在西藏东南部、秦岭 - 大巴山、广西西南部和云南东南部。SAR模型显示,最干旱月份的降水量、季节温度标准差、海拔范围和土壤有机碳含量对SR有显著影响。最干旱月份的降水量、季节温度标准差、潜在蒸发量和海拔范围对WE有显著影响。最干旱月份的降水量、季节温度标准差、历史温度变化、增强植被指数变异系数和海拔变化对CWE有显著影响。SR、WE和CWE的SAR模型的R²分别为0.857、0.733、0.593,高于普通最小二乘法(OLS)(分别为0.689、0.425、0.422)。总之,水分有效性、气候季节性、生境异质性、历史气候变化和土壤条件是限制中国西南地区壳斗科植物SR和WE分布的最重要因素。壳斗科植物的SR和WE中心位于云南南部和东南部、广西西南部、广西西部(原文有误,应为广西西部)、秦岭 - 大巴山和西藏东南部,这些地区应得到充分保护。