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基于森林资源清查资料的盈江县森林生物量和生长量分析

Forest Biomass And Growth in Yingjiang County Based on Forest Resource Inventory Data
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摘要 为确定盈江县森林碳储量和碳汇潜力的变化特征及其影响因子,以便更好地分析盈江县森林生物量和生长量。基于盈江县2012年和2017年森林资源清查数据,利用生物量换算因子连续函数法和异速生长方程,评估盈江县森林碳储量和碳汇潜力的变化特征及其影响因子。结果显示:(1)盈江县森林生物量储量丰富,达85.55 t/hm^(2)。其中:栎类林最大,为168.3 t/hm^(2);核桃林最低,为7.10 t/hm^(2)。(2)不同林龄林分生物量差异较大,近熟林最高,其次分别为中龄林、成熟林、过熟林、幼龄林。(3)常绿阔叶林的林分生长量最大,其次是落叶阔叶林和针叶林。结果表明:盈江县森林生物量储量丰富且以阔叶林为主;林龄和年均气温是影响林分生长和生物量的主要因素。 This study is to analyze the change characteristics and influencing factors of forest carbon stock and carbon sink potential in Yingjiang County.Combining with the continuous forest inventory data of 2012 and 2017 in Yingjiang County,the change characteristics and influencing factors of forest carbon stock and carbon sink potential in Yingjiang County were assessed by using the continuous function method of biomass conversion factor and the anisotropic growth equation.The results show that:(1)Yingjiang County has rich forest biomass,amounting to 85.55 t/hm^(2),among which the oak forest is the largest,168.3 t/hm^(2);the lowest walnut forest is 7.10 t/hm^(2).(2)The distribution of biomass varies greatly among different forest ages,with submature forest being the highest,followed by middle-age forest,mature forest,overmature forest and young forest.(3)Evergreen broad-leaved forest has the highest stand growth,followed by deciduous broad-leaved forest and coniferous forest.The results indicate that stand age and annual average temperature are the main factors affecting stand biomass and growth distribution.
作者 汤明华 刘娟 高林 赵金发 樊骥善 余涛 TANG Minghua;LIU Juan;GAO Lin;ZHAO Jinfa;FAN Jishan;YU Tao(Ecological Branch of Yunnan Institute of Forest Inventory and Planning,Kunming Yunnan 650031,P.R.China;Yunnan Forestry Technological College,Kunming Yunnan 650224,P.R.China;Yunnan Institute of Forest Inventory and Planning,Kunming Yunnan 650051,P.R.China)
出处 《西部林业科学》 CAS 北大核心 2024年第1期129-137,共9页 Journal of West China Forestry Science
基金 “连清”成果应用专项研究课题。
关键词 森林资源清查 生物量评估 生长量 影响因子 随机森林模型 forest resource inventory biomass assessment forest growth influence factor random forest model
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