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樟子松幼树在不同林分结构中的空间分布及其更新分析 被引量:12

Spatial patterns of young Pinus sylvestris var. mongolica saplings and their regeneration analysis in different stands of Inner Mongolia,northern China
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摘要 林分结构是影响天然樟子松林更新的重要因素,而樟子松幼树的空间分布又将决定未来的林分结构。该文以内蒙古红花尔基自然保护区内天然樟子松林为研究对象,采用Ripley的单变量K函数和Hamill&Wright的统计方法,分析了不同林分下樟子松幼树空间分布格局及更新情况。结果表明:①不同林分内,樟子松大树随尺度增加呈现随机分布,而樟子松幼树呈现较明显的聚集分布。②针阔混交林下,樟子松幼树多分布在阔叶树周围4 m范围内,且数量较多、发育较好,呈现出良好的更新趋势;樟子松纯林内,幼树则多分布在樟子松大树周围且数量极少,平均树高明显低于混交林内幼树,更新情况远不如针阔混交林理想。掌握樟子松幼树的空间分布格局和更新规律有助于揭示整个林分的更新过程,为合理经营樟子松林提供依据。 Forest structure is an important factor on regeneration of natural Pinus sylvestris var. mongolica forest and the spatial distribution of its saplings will determine the future forest structure. This study, conducted in natural P. sylvestris var. mongolica forest in Honghuaerji Natural Reserve in Inner Mongolia Autonomous Region of northern China, analyzes the spatial pattern and regeneration of its saplings in different forest stands using Ripley's K function and Hamill & Wright statistics. The results showed that all P. sylvestris var. mongolica adults were randomly distributed with the increase of scales in different forest stands, while P. sylvestris var. mongolica saplings were significantly clustered. The saplings grew within four meters from broadleaved trees and grew well in coniferous-broadleaved mixed forests. On the contrary, P. sylvestris var. mongolica saplings grew close to its adults in pure forest. Additionally, the average height of P. sylvestris var. mongolica saplings in pure forest was lower than that in coniferous-broadleaved mixed forests. Understanding the spatial pattern and regeneration rules of P. sylvestris var. mongolica saplings will help to understand its regeneration process and then make sound management decisions on the forest.
出处 《北京林业大学学报》 CAS CSCD 北大核心 2008年第6期71-77,共7页 Journal of Beijing Forestry University
基金 “十一五”国家科技支撑计划项目(2006BAD26B05) 国家自然科学基金项目(30571528、30671722)
关键词 樟子松 空间分布 林分更新 Ripley's K函数 Hamill&Wright统计方法 Pinus sylvestris var. mongolica spatial distribution stand regeneration Ripley' s K function Hamill & Wright statistical methods
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