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大兴安岭呼中林区地表死可燃物载荷量空间格局
引用本文:刘志华,常禹,陈宏伟,周锐,荆国志,张红新,张长蒙.大兴安岭呼中林区地表死可燃物载荷量空间格局[J].应用生态学报,2008,19(3):487-493.
作者姓名:刘志华  常禹  陈宏伟  周锐  荆国志  张红新  张长蒙
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,北京,100039
2. 中国科学院沈阳应用生态研究所,沈阳,110016
3. 大兴安岭呼中林业局,黑龙江呼中,165036
摘    要:利用地统计学方法,依据时滞分类标准对大兴安岭呼中林区地表死可燃物进行了对比研究.结果表明:一级地表死可燃物表现为强烈的空间自相关性,占总地表死可燃物载荷量的55.54%,平均载荷量为762.35gm-2,其载荷量的决定因素是林分因子和立地年龄;二、三级地表死可燃物的平均载荷量之和为610.26g·m-2,具有较弱的空间自相关性,其载荷量的决定因素为干扰历史.地表死可燃物类型和数量影响因素的复杂性和空间异质性是造成插值精度不高的主要原因,但采用实地调查数据,并结合地统计学方法,可快速准确地计算出地表死可燃物载荷量的空间分布格局,可间接为林业管理提供依据.

关 键 词:地表死可燃物  可燃物载荷量  空间格局  地统计  呼中林区  大兴安岭  大兴安岭  林区  地表  可燃物类型  载荷量  空间格局  Xing  area  forest  load  fuel  dead  land  surface  pattern  林业管理  分布格局  地计算  快速  结合  调查数据
文章编号:1001-9332(2008)03-0487-07
修稿时间:2007年4月6日

Spatial pattern of land surface dead combustible fuel load in Huzhong forest area in Great Xing'an Mountains
LIU Zhi-hua,CHANG Yu,CHEN Hong-wei,ZHOU Rui,JING Guo-zhi,ZHANG Hong-xin,ZHANG Chang-meng.Spatial pattern of land surface dead combustible fuel load in Huzhong forest area in Great Xing''''an Mountains[J].Chinese Journal of Applied Ecology,2008,19(3):487-493.
Authors:LIU Zhi-hua  CHANG Yu  CHEN Hong-wei  ZHOU Rui  JING Guo-zhi  ZHANG Hong-xin  ZHANG Chang-meng
Institution:Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China. liuzh811@126.com
Abstract:By using geo-statistics and based on time-lag classification standard, a comparative study was made on the land surface dead combustible fuels in Huzhong forest area in Great Xing'an Mountains. The results indicated that the first level land surface dead combustible fuel, i. e., 1 h time-lag dead fuel, presented stronger spatial auto-correlation, with an average of 762.35 g x m(-2) and contributing to 55.54% of the total load. Its determining factors were species composition and stand age. The second and third levels land surface dead combustible fuel, i. e., 10 h and 100 h time-lag dead fuels, had a sum of 610.26 g x m(-2), and presented weaker spatial auto-correlation than 1 h time-lag dead fuel. Their determining factor was the disturbance history of forest stand. The complexity and heterogeneity of the factors determining the quality and quantity of forest land surface dead combustible fuels were the main reasons for the relatively inaccurate interpolation. However, the utilization of field survey data coupled with geo-statistics could easily and accurately interpolate the spatial pattern of forest land surface dead combustible fuel loads, and indirectly provide a practical basis for forest management.
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