Forest and Grassland Resources Research >
Evaluation on Forest Biomass and Carbon Storage in Pearl River Delta in Guangdong Province
Received date: 2022-04-29
Revised date: 2022-06-27
Online published: 2022-10-13
Based on the data of the ninth continuous inventory of forest resources in Guangdong,the single-element diameter at breast height (DBH)model was used to calculate the biomass of arbor forest in the Pearl River Delta.The carbon storage per plant in the arbor forest was calculated by the carbon content coefficient of trees.The biomass and carbon storage of the arbor forest in the sample plot were obtained from statistical summary.The biomass per hectare in the Pearl River Delta was 61.52 t/hm2,and the carbon density was 29.95t/hm2.In terms of the forest stands,the middle-aged and young-aged forests were dominant,the near-mature and mature forests had higher biomass and carbon density per unit area;The species of Schima superba,Pinus massoniana,Quercus,mixed broadleaf forests and mixed conifer and broadleaf forests had higher biomass and carbon density per unit area,while the Eucalyptus was lower;The spatial distribution pattern of biomass and carbon storage were high in the east and west and low in the south;And the biomass and carbon density per unit area increased with the increase of altitude.The sustainable carbon sink potential of arbor forests can be improved by adjusting the age structure,optimizing the tree species composition,strengthening the tending of young and middle-aged forests,and forest protection,which can provide guidance for the construction and promotion of forest city cluster in Pearl River Delta.
Key words: biomass; carbon density; Pearl River Delta
Kangjie LI , Zhongyue HU , Ping LIU , Zhengchun XU . Evaluation on Forest Biomass and Carbon Storage in Pearl River Delta in Guangdong Province[J]. Forest and Grassland Resources Research, 2022 , 0(4) : 54 -60 . DOI: 10.13466/j.cnki.lyzygl.2022.04.008
| [1] | 杨青川. 利用森林蓄积量生物量模型估算岫岩县森林碳储量[J]. 绿色科技, 2021, 23(8):20-22. |
| [2] | 孙忠秋, 吴发云, 胡杨, 等. 基于Landsat-8 OLI数据的马尾松林蓄积量饱和点确定及估测[J]. 林业资源管理, 2020(6):135-142. |
| [3] | 刘魏魏, 王效科, 逯非, 等. 全球森林生态系统碳储量、固碳能力估算及其区域特征[J]. 应用生态学报, 2015, 26(9):2881-2890. |
| [4] | 马泽清, 刘琪璟, 徐雯佳, 等. 基于TM遥感影像的湿地松林生物量研究[J]. 自然资源学报, 2008(3):467-478. |
| [5] | 庞勇, 黄克标, 李增元, 等. 基于遥感的湄公河次区域森林地上生物量分析[J]. 资源科学, 2011, 33(10):1863-1869. |
| [6] | 程丽芬. 山西霍山森林群落生物量与碳密度研究[J]. 林业资源管理, 2017(1):70-74. |
| [7] | 沈希, 张茂震, 祁祥斌. 基于回归与随机模拟的区域森林碳分布估计方法比较[J]. 林业科学, 2011, 47(6):1-8. |
| [8] | 刘浩然, 范伟伟, 徐永胜, 等. 基于无人机激光雷达点云的单木生物量估测[J]. 中南林业科技大学学报, 2021, 41(8):92-99. |
| [9] | 吴恒, 胥辉. 四川省主要乔木林类型碳汇速率及储量动态分析[J]. 林业资源管理, 2021(5):47-55. |
| [10] | 潘婧靓, 邢艳秋, 黄佳鹏, 等. 联合GF-3 PolSAR数据与Landsat-8 OLI数据的森林地上生物量估测[J]. 中南林业科技大学学报, 2020, 40(8):83-90. |
| [11] | Du Ling, Zhou Tao, Zou Zhenhua, et al. Mapping forest biomass using remote sensing and national forest inventory in China[J]. Forests, 2014, 5(6):1267-1283. |
| [12] | Hudak A T, Stand E K, Vierling L A, et al. Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys[J]. Remote Sensing of Environment, 2012, 123:25-40. |
| [13] | 刘萍, 邓鉴锋, 魏安世, 等. 广州市森林生物量及碳储量评估[J]. 西南林业大学学报, 2015, 35(4):62-65. |
| [14] | 左雪漫, 闫国东, 陈瑾, 等. 福建省林地覆盖变化及其海拔梯度效应的分析[J]. 林业资源管理, 2022(1):70-77. |
| [15] | 国家林业局. LY/T 2263-2014,立木生物量模型及碳计量参数——马尾松[S]. 北京: 中国标准出版社, 2014. |
| [16] | 国家林业局. LY/T 2261-2014,立木生物量模型及碳计量参数——湿地松[S]. 北京: 中国标准出版社, 2014. |
| [17] | 国家林业局. LY/T 2264-2014,立木生物量模型及碳计量参数——杉木[S]. 北京: 中国标准出版社, 2014. |
| [18] | 国家林业局. LY/T 2260-2016,立木生物量模型及碳计量参数——木荷[S]. 北京: 中国标准出版社, 2016. |
| [19] | 国家林业局. LY/T 2261-2016,立木生物量模型及碳计量参数——枫香[S]. 北京: 中国标准出版社, 2016. |
| [20] | 国家林业局. LY/T 2658-2016,立木生物量模型及碳计量参数——栎树[S]. 北京: 中国标准出版社, 2016. |
| [21] | 曾伟生. 基于木材密度的34个树种组一元立木生物量模型建立[J]. 林业资源管理, 2017(6):41-46. |
| [22] | 王念奎. 福建省乔木林碳储量估算及变化动态分析[J]. 林业勘察设计, 2017, 37(2):40-45. |
| [23] | 林玮, 梁东成, 唐昌亮, 等. 华南地区主要造林树种林分碳储量估算[J]. 林业与环境科学, 2019, 35(2):20-29. |
| [24] | 杨昆, 管东生. 珠江三角洲森林的生物量和生产力研究[J]. 生态环境, 2006(1):84-88. |
| [25] | Dixon R K, Brown S, Houghton R A, et al. Carbon pools and flux of global forest ecosystems[J]. Science, 1994, 263(5144):185-190. |
| [26] | 朱妍. 基于Landsat 8 OLI和ALOS-2 PALSAR-2数据的北京市森林生物量估测研究[D]. 北京: 北京林业大学, 2020. |
/
| 〈 |
|
〉 |