北重楼潜在适生区对气候变化的响应及其主导气候因子

基于现有物种数据结合气候变量来预测物种的潜在地理分布,对于了解物种进化以及合理保护具有重要意义。本研究基于中国境内220个北重楼分布点和12个相关系数较低的气候因子,利用MaxEnt模型和ArcGIS软件预测了北重楼在当前时期和未来时期(2050s、2070s)的潜在适生区,并分析了影响其地理分布的主导气候因子。结果表明: MaxEnt模型AUC值为0.940,预测结果准确性较高;当前时期,北重楼的总适生区面积占整个研究区域面积的18.1%,其中,高适生区和低适生区分别占7.0%和11.1%,主要位于大兴安岭、小兴安岭、长白山山脉、秦岭-大巴山区、河北、山西以及山东北部等地区;未来时期在RCP 2.6、RCP 4.5、RCP 6.0、RCP 8.5气候情景下,2050s和2070s中国境内北重楼的总适生区面积均呈现缩减趋势,其中,高适生区面积均减少,而低适生区面积则全部有所增加,且北重楼适生区的范围和几何中心逐渐向东北方向的高海拔地区扩散;影响北重楼地理分布的主导气候因子分别为最湿月降水量、年平均温度、等温性和1月降水量,累积贡献率高达89.2%,其适宜范围分别为100～275 mm、-0.1～16 ℃、21～35和3～14 mm。

Responses of potential suitable area of Paris verticillata to climate change and its dominant climate factors

Prediction of the potential distribution of species based on the data of its current distribution in combination with climatic variables is important for understanding species evolution and reasonable conservation. Based on 220 distribution sites in China and 12 low-correlation climatic variables, we analyzed the potential distribution of Paris verticillata at present and future (2050s and 2070s) using the MaxEnt model and ArcGIS program. Further, we analyzed the dominant driving factors for its geographic distribution. The results showed that the area under the curve indices (AUC) was 0.940, with high prediction accuracy. The potential suitable regions of P. verticillata were mainly distributed in the Greater Xing’an Mountains, the Xiao Xing’an Mountains, the Changbai Mountains, the Qinling-Daba Mountains, Hebei, Shanxi and north Shandong under current climate scenario. Those regions accounted for 18.1% of the total suitable area in the country, of which the highly suitable areas accounted for 7.0% and the lowly suitable area 11.1%. The total suitable areas of P. verticillata in the 2050s and 2070s would decline under the climate change scenarios of RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The highly suitable area would decline, but the lowly suitable area would increase. With the global climate change, both the range and the geometric center of its distribution would gradually spread to higher altitude in the northeast. The cumulative contributions of four dominant factors reached as high as 89.2%, namely, precipitation of wettest month, mean annual temperature, isothermality, and precipitation of January. Their appropriate ranges were 100-275 mm, -0.1-16 ℃, 21-35 and 3-14 mm, respectively.