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塞罕坝机械林场林内景观质量评价研究 被引量:8

Study on Scenic Beauty of Forest Interior Landscape in Saihanba Mechanized Forest Farm
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摘要 采用SBE法,以塞罕坝机械林场落叶松纯林、落叶松白桦混交林、樟子松纯林和桦树天然次生林等4种主要林分的林内景观为研究对象进行研究。结果表明:落叶松纯林和白桦落叶松混交林美景度较高,樟子松纯林次之,桦树次生林最低;平均胸径在15 cm以下、密度在1 250株/hm2以上、林分透视距离在1倍树高以下、乔灌草结构、灌木盖度高于90%、灌木高度在1m以上,都显著降低了林内美景度;密度、林分结构(乔灌草结构)、灌层盖度(≥90%)3个指标进入美景度与林分指标的回归模型,解释了55.1%的因变量,且均与美景度为负相关关系,说明这3个指标显著降低了林分的美景度;林分美景度与灌层的生物多样性无显著相关关系,降低灌木层的高度和盖度,既可以增加美景度也不会影响灌层生物多样性。 The article studied forest interior landscape quality of 4 typical forest stands in Saihanba using SBE method which include Larix principis rupprechtii plantation,Larix principis rupprechtii and Betula platyphylla mixed plantation,Pinus sylvestris var.mongholica lit.plantation and Betula platyphylla natural secondary forest.The results showed that SBE score of Larix principis-rupprechtii plantation,Larix princip-is-rupprechtii and Betula platyphylla mixed plantation were higher,followed by Pinus sylvestris var.mongholica Litv.,and Betula platyphylla natural secondary forest was the lowest;the SBE score was reduced significantly by some stand indicators including DBH below 15cm,stand density below 1250 plant/hm2 ,perspective distance below the tree height,vertical structure with tree,shrub and grass,shrub layer coverage greater than 90%,shrub average height greater than 1 m;3 indicators including density, stand structure (with tree,shrub and grass),shrub layer coverage(more than 90%)entered the regres-sion model,explaining 55.1%of the dependent variable,and had a negative correlation with SBE,indica-ting that the 3 indexes significantly reduced the scenic beauty of the stand;SBE score has no significant correlation with the biodiversity of shrub layer,so reducing height and coverage of shrub layer could in-crease the scenic beauty but not affect the biodiversity of shrub layer.
出处 《林业资源管理》 北大核心 2016年第3期98-103,111,共7页 Forest Resources Management
基金 国家林业局全国森林经营基础研究项目(169201531-4) 河北农业大学中青年骨干教师境外研修项目(1081006)
关键词 塞罕坝 林内景观 美景度 SBE法 Saihanba forest interior landscape scenic beauty SBE method
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