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施肥对落叶松二代林生长的影响 被引量:4

The influence of fertilization on growth of larch forest of second generation
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摘要 基于塞罕坝机械林场高海拔地区华北落叶松采伐迹地土壤出现的地力衰退、酸化、弱化等问题,为培育优质的二代林资源,根据土壤的立地情况及所需营养元素,对有代表性的迹地更新二代幼林进行了林地施肥对比试验。在试验混合肥区中,施肥30g的林地林木树高和地径年平均生长量均高出对照99.7%、施肥50g的年平均树高及地径生长量均高出对照1倍以上,分别达到158.5%、114.4%;在控释肥区中,施肥30g的林地林木树高年平均生长量高出对照43.6%、地径年平均生长量高出对照23.9%;施肥50g的林木树高年平均生长量高出对照77.3%、地径年平均生长量高出对照36.2%。试验结果表明,华北落叶松二代林地对氮肥的需求量较大,通过施肥使林木生长明显加快,可以为立地条件类似地区提供借鉴。 Based on the decline of soil fertility,soil acidification,and weakening of cut-over area high-altitude Larix principis-rupprechtii forest in Sihanba Mechanized Forestry Centre(SMFC)and other issues,to cultivate high quality the second generation of forest resources,a fertilizing contrast test of wood land was conducted according to the situation of soil site and the required nutrients for representative mark place to update the second generation young design.The result showed that the average annual growth of tree high in the mixed fertilizing area by 30g was 99.7%higher than CK,with the ground diameter annual growth of 99.7%higher than CK,while the average high and diameter with 50g treatment increased by over one time compared with CK reaching 158.5%and 114.4%,respectively.In the controlled releasing fertilizer tree site by fertilization 30g the average annual growth of tree high and ground diameter was 43.6%and 23.9%,while that in 50g treatment was 77.3%and36.2%.Additionaly,the second-generation forest land of Larix principis-rupprechtii highly demanded for nitrogen.Through scientific fertilization trees will grow faster,greatly improving its yield,quality and resistance,and providing a new road to explore site conditions and references for similar areas to cultivate high quality timber forest.
作者 高伟航
出处 《河北林果研究》 2014年第2期129-132,共4页 Hebei Journal of Forestry and Orchard Research
关键词 塞罕坝 高海拔地带 落叶松 二代林 施肥 影响 Saihanba high elevation land larch two generation forests soil fertility decline effect
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  • 1姚延祷,杨秀清,杜鹃,等.林学概论[M].北京:中国农业科学技术出版社,2008:263.
  • 2QIN S J, BADGWELL T A. A survey of industrial model predictive control technology [J]. Control Engineerin9 Practice, 2003, 11(7): 733-764.

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