植物生态学报 ›› 2013, Vol. 37 ›› Issue (7): 631-640.doi: 10.3724/SP.J.1258.2013.00065

• 研究论文 • 上一篇    下一篇

基于物种分布模型评价土壤因子对我国毛竹潜在分布的影响

金佳鑫1, 江洪1,2*, 彭威1, 张林静1, 卢学鹤1, 徐建辉1,3, 张秀英1, 王颖1   

  1. 1南京大学国际地球系统科学研究所, 南京 210093;
    2浙江农林大学国际空间生态与生态系统生态研究中心, 杭州 311300;
    3滁州学院, 安徽滁州 239000
  • 收稿日期:2013-03-05 修回日期:2013-05-23 出版日期:2013-07-01 发布日期:2013-07-05
  • 通讯作者: 江洪 E-mail:jianghong.china@hotmail.com
  • 基金资助:

    国家自然科学基金项目;国家“973”重点基础研究发展规划项目基金;高等学校博士学科点专项科研基金

Evaluating the impact of soil factors on the potential distribution of Phyllostachys edulis (bamboo) in China based on the species distribution model

JIN Jia-Xin1, JIANG Hong1,2*, PENG Wei1, ZHANG Lin-Jing1, LU Xue-He1, XU Jian-Hui1,3, ZHANG Xiu-Ying1, and WANG Ying1   

  1. 1International Institute for Earth System Science, Nanjing University, Nanjing 210093, China;

    2International Center of Spatial Ecology and Ecosystem Ecology, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China;

    3Chuzhou University, Chuzhou, Anhui 239000, China
  • Received:2013-03-05 Revised:2013-05-23 Online:2013-07-01 Published:2013-07-05
  • Contact: JIANG Hong E-mail:jianghong.china@hotmail.com

摘要:

基于单类别支持向量机方法的物种分布模型, 利用政府间气候变化专门委员会(IPCC)气候情景模式和联合国粮食与农业组织(FAO)的全球土壤数据, 模拟1981–2099年我国毛竹(Phyllostachys edulis)的潜在空间分布及变化趋势, 比较考虑土壤因子前后模拟结果的差异, 旨在探究土壤因子对毛竹潜在空间分布模拟结果的影响。结果表明, 仅以气候因子为模拟变量和同时考虑气候与土壤因子为模拟变量的毛竹潜在空间分布模拟均具有较高精度, 毛竹潜在分布区表现为面积增加并向北扩张。模拟因子重要性分析表明表征温暖程度的气候因子在毛竹潜在分布模拟中起主导作用, 而表征土壤质地和酸碱性的土壤因子以限制性作用为主。同时考虑气候与土壤因子的模拟结果具有较高的模拟效率, 且在未来气候变化情景模式下毛竹潜在分布区面积增幅与向北迁移幅度均小于仅使用气候因子的模拟, 表明土壤要素对毛竹潜在分布具有明显的限制作用, 该结果对现在的毛竹潜在分布模拟研究具有重要的补充作用。

Abstract:
Aims We aimed to detect the impact of soil factors on predicting the potential distribution of Phyllostachys edulis (bamboo) by comparing the prediction accuracy and the spatio-temporal pattern of potential habitat of P. edulis.
Methods Using IPCC (Intergovernmental Panel on Climate Change) climate change scenario datasets and FAO (Food and Agriculture Organization) Soil Map of the World, the potential distribution of P. edulis in China was predicted from 1981 to 2099 based on species distribution models, one-class Support Vector Machine (SVM). We used two groups of predictors: one included climate factors only, and the other had both climate factors and soil factors.
Important findings The SVM based on both predictor groups predicted the potential distribution of P. edulis, and the potential habitat expended and migrated northward with time. Factor importance analysis showed that the climate factors correlated with warm conditions played a driving role in the simulation of the potential habitat of P. edulis, while soil factors associated with soil texture and pH mainly impacted the simulation as limiting factors. However, the prediction using both climate and soil predictors performed with higher efficiency, and the intensity of the potential habitat expending and migrating was less than that of the group of climate factors only. The finding suggested that the soil factors significantly constrain the potential habitat of P. edulis, and soil constraint should be considered in predicting species distribution in future.