期刊文献+

大兴安岭呼中林区地表死可燃物载荷量空间格局 被引量:23

Spatial pattern of land surface dead combustible fuel load in Huzhong forest area in Great Xing'an Mountains
下载PDF
导出
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762.35g·m-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. 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 ·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· 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.
出处 《应用生态学报》 CAS CSCD 北大核心 2008年第3期487-493,共7页 Chinese Journal of Applied Ecology
基金 国家自然科学基金资助项目(30670363)
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 land surface dead combustible fuel combustible fuel load spatial pattern geostatistics Huzhong forest area Great Xing' an Mountains.
  • 相关文献

参考文献32

  • 1云丽丽,张元宏,高国平.森林地被可燃物燃烧性的研究[J].辽宁林业科技,2001(5):15-16. 被引量:18
  • 2Zheng H-N (郑焕能). Forest Fire Prevention. Harbin: Northeast Forestry University Press, 1994
  • 3Chang Y, He HS, Bishop L, et al. Long-term forest landscape responses to fire suppression in Great Xing' an Mountains, China. International Journal of Wildland Fire, 2007, 16:34-44
  • 4Westin S. Wildfire in Missouri. Jefferson City: Missouri Department of Conservation, 1992
  • 5Guyette RP, Muzika RM, Dey DC. Dynamics of an anthropogenic fire regime. Ecosystems, 2002, 5:472-486
  • 6He HS, Shang BZ, Thomas RC, et al. Simulating forest fuel and fire risk dynamics across landscapes-LANDIS fuel module design. Ecological Modelling, 2004, 180: 135-151
  • 7冯益明,唐守正,李增元.空间统计分析在林业中的应用[J].林业科学,2004,40(3):149-155. 被引量:64
  • 8Samra JS, Gill HS, Bhatia VK. Spatial stochastic modeling of growth and forest resource evaluation. Forest Science, 1989, 35:663-676
  • 9Hock BK, Payn TW, Shirly TW. Using a geographic information system and geostatistics to estimate site index of Pinus radiata for Kaingaroa Forest. New Zealand Journal of Forest Science, 1993, 23:264-270
  • 10Zhou Y-L (周以良). Vegetation of Daxing' anling in China. Beijing: Science Press, 1991

二级参考文献68

共引文献305

同被引文献552

引证文献23

二级引证文献441

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部