基于小班尺度的乔木林碳储量和碳密度估算——以宁都县为例

Estimation of carbon storage and carbon density based on the subcompartment scale-a case study of Ningdu County,Jiangxi Province

本文以宁都县为研究区,基于江西省宁都县森林资源二类调查小班数据,采用立木生物量模型估算乔木林小班的碳储量和碳密度。结果表明:宁都县乔木林小班碳储量和碳密度的分布范围分别为0.13~6 412.84 t和0.07~286.28 t·hm^(-2);乔木林总碳储量为7 863 804.76 t,平均碳密度为31.54 t·hm^(-2)。从林分类型来看,碳密度大小依次为栎类(102.45 t·hm^(-2))>其他硬阔类(69.93 t·hm^(-2))>阔叶混交类(48.61 t·hm^(-2))>枫香(41.14 t·hm^(-2))>木荷(38.75 t·hm^(-2))>针阔混交类(38.34 t·hm^(-2))>马尾松(31.43 t·hm^(-2))>针叶混交类(29.75 t·hm^(-2))>其他软阔类(22.71 t·hm^(-2))>杉木(14.26 t·hm^(-2))>湿地松(14.14 t·hm^(-2));总体上阔叶树种碳密度优于针叶树种,碳密度随龄组增长而增加。研究区森林固碳潜力较大,加强中幼龄林抚育以及针叶林针阔化改造能够有效提高森林固碳能力。

It was used the standing biomass model to estimate the carbon storage and carbon density of the sub class of arbor forest,this paper took Ningdu County as the study area,based on the sub class data of Class II forest resource survey in Ningdu County,Jiangxi Province.The results showed that the distribution range of carbon storage and carbon density in the subcompartment of arbor forest in Ningdu County was 0.13~6412.84 t and 0.07~286.28 t·hm^(-2),respectively.The total carbon storage of the tree forest was 7863804.76 t,with an average carbon density of 31.54 t·hm^(-2).In terms of stand types,the carbon density was in the order of Quercus(102.45 t·hm^(-2))>other hard broad-leaved species(69.93 t·hm^(-2))>broad-leaved mixed species(48.61 t·hm^(-2))>Liquidambar formosana(41.14 t·hm^(-2))>Schima superba(38.75 t·hm^(-2))>needle broad-leaved mixed species(38.34 t·hm^(-2))>Pinus massoniana(31.43 t·hm^(-2))>needle broad-leaved mixed species(29.75 t·hm^(-2))>other soft broad-leaved species(22.71 t·hm^(-2))>Cunninghamia lanceolata(14.26 t·hm^(-2))>Pinus elliottii(14.14 t·hm^(-2)).Generally,the carbon density of broad-leaved trees was better than that of coniferous trees,and the carbon density increases with the age group.The forest in the research area had a great potential for carbon sequestration,and strengthening the tending of young and middle-aged forests and the coniferous forest coniferous transformation could effectively improve the forest's carbon sequestration capacity.