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林业资源管理 ›› 2022, Vol. 0 ›› Issue (6): 44-53.doi: 10.13466/j.cnki.lyzygl.2022.06.008

• 科学研究 • 上一篇    下一篇

基于CBM-CFS3模型的马尾松林碳密度特征及其影响因素

章敏1(), 王健2, 韩天一3, 欧阳勋志1, 潘萍1(), 刘冬冬1   

  1. 1.鄱阳湖流域森林生态系统保护与修复国家林业和草原局重点实验室 江西农业大学林学院,南昌 330045
    2.安福县明月山林场,江西 吉安 343200
    3.江西省林业资源监测中心,南昌 330046
  • 收稿日期:2022-10-14 修回日期:2022-10-28 出版日期:2022-12-28 发布日期:2023-01-16
  • 通讯作者: 潘萍
  • 作者简介:章敏(1997-),男,江西星子人,在读硕士,主要从事森林资源管理与监测研究。Email:1162787927@qq.com
  • 基金资助:
    国家自然科学基金项目(32260392);国家自然科学基金项目(31760207);江西省教育厅科技计划项目(GJJ200448)

Characteristics of Carbon Density and Its Influencing Factors of Pinus massoniana Forest Based on CBM-CFS3 Model

ZHANG Min1(), WANG Jian2, HAN Tianyi3, OUYANG Xunzhi1, PAN Ping1(), LIU Dongdong1   

  1. 1. Key Laboratory of National Forestry and Grassland Administration for the Protection and Restoration of Forest Ecosystem in Poyang Lake Basin,College of Forestry,Jiangxi Agricultural University,Nanchang 330045,China
    2. Ming Yue Mountain Forestry Centre of Anfu County,Ji’an,Jiangxi 343200,China
    3. Jiangxi Forestry Resources Monitoring Center,Nanchang 330046,China
  • Received:2022-10-14 Revised:2022-10-28 Online:2022-12-28 Published:2023-01-16
  • Contact: PAN Ping

摘要:

基于赣州市森林资源二类调查样地数据,通过区域尺度碳收支模型(CBM-CFS3)对马尾松林碳密度进行计算,并分别采用地统计学和多元逐步回归方法分析碳密度的空间分布及其影响因素。结果表明:不同森林类型、起源的马尾松林最优林龄-蓄积生长方程存在差异,总体上Logistic模型、Richards模型和Gompertz模型拟合的效果比Korf模型要好。林分总碳密度为135.08MgC/hm2,其中,植被层碳库、死亡有机质(DOM)碳库分别为41.51,93.57MgC/hm2,植被层碳库表现为树干>树枝>树根>树叶,DOM碳库为土壤层>枯落物>枯死木;林分总碳密度在空间上呈现一定的正相关性,主要集中在106.73~161.16MgC/hm2,低值区域面积大于高值区域,空间上没有表现出明显的规律性。龄组、平均胸径、郁闭度、年平均温度与林分总碳密度均存在极显著正相关(P<0.01),是影响碳密度的主要因子。通过森林资源样地调查数据构建生长模型用于CBM-CFS3模型中估算森林碳密度,有利于较全面和准确估算区域森林不同碳库,植被因子是影响其碳密度的主要因素。

关键词: 马尾松林, 森林碳密度, CBM-CFS3模型, 影响因素, 赣南

Abstract:

Based on the sample plot data from the forest resources inventory of Ganzhou City,the carbon density of Pinus massoniana forest was calculated by regional scale carbon budget model (CBM-CFS3),and the spatial distribution and influencing factors of carbon density were analyzed by geostatistics and multiple stepwise regression methods,respectively. The results showed that there were differences in the optimal stand age-accumulation equation for different forest types and origins of Pinus massoniana forests. In general,the Logistic model,Richards model and Gompertz model fit better than the Korf model. The total carbon density of the stand was 135.08MgC/hm2,in which the carbon densities of the vegetation layer carbon pool and the dead organic matter (DOM) carbon pool were 41.51MgC/hm2 and 93.57MgC/hm2,respectively. The vegetation layer carbon pool showed as trunk>branches>roots>leaves while DOM carbon pool showed as soil layer>litter>dead wood. The total carbon density of forest stands had a certain positive correlation in space,mainly concentrated in 106.73-161.16MgC/hm2. The area of the low-value carbon density area was larger than the high-value carbon density area,but there was no obvious regularity in space. Age group,average diameter at the breast height (DBH),canopy density and annual mean temperature were all highly significantly and positively correlated with the total carbon density of forest stands (P<0.01),so they were the main factors affecting carbon density. The growth model constructed by the sample plot data from the forest resources inventory was used to estimate forest carbon density in the CBM-CFS3 model,which was conducive to get a more comprehensive and accurate estimation of different carbon pools in regional forests. The vegetation factor was the main factor affecting its carbon density.

Key words: Pinus massoniana forest, forest carbon density, CBM-CFS3 model, influencing factors;southern Jiangxi Province

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