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黄土丘陵区延河流域潜在植被分布预测与制图
引用本文:温仲明,焦峰,焦菊英.黄土丘陵区延河流域潜在植被分布预测与制图[J].应用生态学报,2008,19(9):1897-1904.
作者姓名:温仲明  焦峰  焦菊英
作者单位:西北农林科技大学中国科学院水利部水土保持研究所,陕西杨陵,712100
基金项目:国家科技支撑计划,国家重点基础研究发展计划(973计划),中国科学院"西部之光"人才培养计划,国家自然科学基金
摘    要:潜在植被的分布预测与制图对植被恢复规划具有重要的指导价值.利用广义相加模型(generalized additive model,GAM),结合GIS空间分析技术和环境梯度分层采样技术,为延河流域24个地带性物种建立了分布模型,并在考虑群落内部物种种间关系及其分布概率的基础上,对物种分布进行运算,模拟预测了延河流域37种植物群落的分布状况和延河流域的潜在植被分布.结果表明: 研究区植被分布预测值与实际调查值间的差异不显著,预测的植被空间分布较好地反映了延河流域潜在的植被分布状况,表明该模型具有较好的预测能力,对于区域植被恢复的目标设定和恢复规划具有重要意义.

关 键 词:潜在植被  植被  环境  广义相加模型  分布预测
收稿时间:2007-12-16

Prediction and mapping of potential vegetation distribution in Yanhe River catchment in hilly area of Loess Plateau
WEN Zhong-ming,JIAO Feng,JIAO Ju-ying.Prediction and mapping of potential vegetation distribution in Yanhe River catchment in hilly area of Loess Plateau[J].Chinese Journal of Applied Ecology,2008,19(9):1897-1904.
Authors:WEN Zhong-ming  JIAO Feng  JIAO Ju-ying
Institution:Institute of Soil and Water Conservation, Northwest A & F University, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, Shannxi, China
Abstract:The prediction and mapping of potential vegetation distribution is of instructive to the ecological restoration planning. By using generalized additive model (GAM) and in combining with GIS spatial analyst and environmental stratification sampling techniques, a distribution model for 24 dominant species in Yanhe River catchment was developed, and, based on the interspecific relationships in plant communities and the distribution probability, the spatial distribution of plant species was calculated, and the distribution of 37 plant communities and of the potential vegetation in Yanhe River catchment was predicted. The results showed that there were no significant differences between predictive values and actual data, and the predictive spatial distribution of vegetation could actually reflect the distribution of potential vegetation in Yanhe River catchment, suggesting that the established model had good ability for the vegetation distribution prediction, which was of significance to the goal setting and planning of vegetation restoration.
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