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当前位置: 首页 > 文章 > 森林破碎化的社会经济驱动力分析——以美国阿拉巴马州为例 东北林业大学学报 2010,38 (6) 61-63
Position: Home > Articles > Assessment of Socio-economic Drivers Contributing to Forest Fragmentation: A Case Study from Alabama,USA Journal of Northeast Forestry University 2010,38 (6) 61-63

森林破碎化的社会经济驱动力分析——以美国阿拉巴马州为例

作  者：
李明诗;刘图强;潘洁
单  位：
南京林业大学
关键词：
森林破碎化;破碎化模型;驱动力;空间变异模型;阿拉巴马州
摘  要：
以基于植被变化追踪遥感模型所生成的1999年森林干扰产品为基础,采用森林破碎化分析模型在5×5窗口分析尺度下将美国阿拉巴马州森林归并为内部、孔洞、边界、斑块、过渡及未确定6种破碎化成分。同时,以行政县为单位采集森林像元的平均高程、森林像元的平均坡度、居民受教育程度、人口密度及人均收入等与破碎化成分建立统计关联。结果表明:除平均坡度外,其余4因子均与森林破碎化成分显著相关,人口密度、人均收入及受教育程度是阿拉巴马州森林破碎化重要的社会经济驱动力;所识别的驱动因子对不同的破碎化成分空间变动的解释能力不一,其中对于孔洞森林变异的解释能力最强,达65.8%。统计检验表明所建立的破碎化驱动力模型对于归纳阿拉巴马州森林破碎化成因是有效和可靠的。
译  名：
Assessment of Socio-economic Drivers Contributing to Forest Fragmentation: A Case Study from Alabama,USA
作  者：
Li Mingshi,Liu Tuqiang,Pan Jie( College of Forest Resources and Environment,Nanjing Forestry University,Nanjing 210037,P. R. China)
关键词：
Forest fragmentation; Fragmentation models; Driving forces; Spatial variability models; Alabama
摘  要：
This study adopted a forest fragmentation model other than landscape indices applying to Alabama’s forest change products for 1999,which were derived from a vegetation change tracker model ( VCT) ,to quantify and classify each forest pixel into one of the six fragmentation components ( interior,perforated,edge,patch,transitional and undetermined) ,at the analytical scale of 5 by 5 pixels. Meanwhile,socio-economic and environmental predictors including mean elevation of forest pixels,mean slope of forest pixels,population density,educated degree and per capita income by administrative county of Alabama were captured to correlate with the established forest fragmentation components to explain the spatial variability of driving forces responsible for forest fragmentation. Results show that the mean elevation,population density,educated degree and per capita income are all significantly correlated with the forest fragmentation components,and weak correlations were observed between the mean slope and the fragmentation conditions in this analysis. The established multivariant linear regression models yielded different capabilities in explaining the variance of the fragmentation components,ranging from 38. 4% for patch forest to 65. 8% for perforated forest. Additionally,statistical tests suggest that the established driving models for forest fragmentation are reliable and effective in exploring the processes and causes of forest fragmentation.

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