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空间异质性对样地数据空间外推的影响
引用本文:梁宇,贺红士,胡远满,布仁仓.空间异质性对样地数据空间外推的影响[J].应用生态学报,2012,23(1):185-192.
作者姓名:梁宇  贺红士  胡远满  布仁仓
作者单位:1. 中国科学院沈阳应用生态研究所,沈阳110016;中国科学院研究生院,北京100049
2. 中国科学院沈阳应用生态研究所,沈阳,110016
基金项目:中国科学院创新团队国际合作计划项目(KZCX2-YW-T06);中国科学院知识创新工程重要方向项目(KZCX2-YW-444)资助;国家重点基础研究发展计划项目(2009CB421101)
摘    要:应用模型结合的方法模拟了3个空间异质性等级预案下反应变量(气候变化下景观水平的树种分布面积)的变化情况,并分析模拟结果在预案之间的差异性,探讨了环境空间异质性对样地观测到的树种对气候变化响应向更大空间尺度外推的影响.结果表明:空间异质性在一般情况下对样地数据向土地类型尺度外推没有影响,而对样地尺度外推到海拔带尺度的影响则有较复杂的情况.对于对气候变化不敏感的树种以及非地带性树种,空间异质性对样地数据向海拔带尺度外推没有影响;对于大多数对气候变化敏感的地带性树种而言,空间异质性对样地数据向海拔带尺度外推则有影响.

关 键 词:气候变化  森林景观预测  空间异质性  空间外推  尺度  LANDIS  样地数据

Effects of spatial heterogeneity on spatial extrapolation of sampling plot data
Liang Yu,He Hong-Shi,Hu Yuan-Man,Bu Ren-Cang.Effects of spatial heterogeneity on spatial extrapolation of sampling plot data[J].Chinese Journal of Applied Ecology,2012,23(1):185-192.
Authors:Liang Yu  He Hong-Shi  Hu Yuan-Man  Bu Ren-Cang
Institution:Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China. liangysts@gmail.com
Abstract:By using model combination method, this paper simulated the changes of response variable (tree species distribution area at landscape level under climate change) under three scenarios of environmental spatial heterogeneous level, analyzed the differentiation of simulated results under different scenarios, and discussed the effects of environmental spatial heterogeneity on the larger spatial extrapolation of the tree species responses to climate change observed in sampling plots. For most tree species, spatial heterogeneity had little effects on the extrapolation from plot scale to class scale; for the tree species insensitive to climate warming and the azonal species, spatial heterogeneity also had little effects on the extrapolation from plot-scale to zonal scale. By contrast, for the tree species sensitive to climate warming, spatial heterogeneity had effects on the extrapolation from plot scale to zonal scale, and the effects could be varied under different scenarios.
Keywords:climate change  forest landscape prediction  spatial heterogeneity  spatial extrapolation  scale  LANDIS  sampling plot data  
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