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基于连清数据的湖南森林碳密度估计及变化特征分析(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2017年04期
Page:
129-135
Column:
研究论文
column:
2017-07-31

Article Info:/Info

Title:
Estimation and analysis of variation characteristic of forest carbon density in Hunan Province using continuous forest inventory data
Article ID:
1000-2006(2017)04-0129-07
Author:
戴前石1胡 觉1 李建军2*
1. 国家林业局中南林业调查规划设计院,湖南 长沙 410014;
2. 中南林业科技大学计算机与信息工程学院, 湖南 长沙 410004
Author(s):
DAI Qianshi1 HU Jue1 LI Jianjun2*
1. Central South Forest Inventory and Planning Institute of State Forestry Administration, Changsha 410014, China;
2. College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China
Keywords:
森林碳密度 连清数据 时空分析 湖南省
Keywords:
forest carbon density continuous forest inventory data tempo-spatial analysis Hunan Province
Classification number :
S757.2
DOI:
10.3969/j.issn.1000-2006.2017.04.020
Document Code:
A
Abstract:
【目的】通过碳密度时空分析、驱动因素分析,探索科学适用的基于森林资源连续清查资料的大区域森林碳汇功能监测方法。【方法】以湖南省1999—2014年4期6 615块森林资源连续清查固定样地数据为主要信息源,采用Pearson相关系数,在5种理论半方差模型精度比较分析基础上,选取预测性能最高的模型进行森林碳密度克里金内插、时空分析、驱动因素分析。【结果】5种理论半方差模型预测精度按照从高到低排序为:球体模型>指数模型>圆形模型>线性模型>高斯模型。1999、2004、2009、2014年湖南省森林碳密度分别为17.156、17.938、18.491、20.489 t/hm2,标准差分别为13.309、15.499、16.211、17.141 t/hm2。1999—2014年,湖南省森林碳密度呈稳步上升趋势,空间聚集性减弱、破碎化趋势增强; 1999—2014年,湖南省森林碳密度在空间分布上整体呈现出西部、南部、东部较高(>20 t/hm2),北部、中部较低(5~20 t/hm2)的空间分布格局。1999—2014年,森林碳密度与植被覆盖度、坡度、土壤厚度始终保持正相关关系,与灯光亮度的相关性在1999、2004年为负相关,在2009、2014年则为正相关。【结论】湖南省碳密度的时空变化受林业政策调整和社会经济条件变化的双重影响,应加强退耕还林、公益林生态效益补偿的力度,巩固集体林权制度改革成果。
Abstract:
【Objective】Because forest carbon sequestration is an important component of forest ecosystem services, monitoring of forest carbon sequestration is a vitaltopic in the field of forest ecology research that can provide scientific basis for regional forest planning. 【Method】In this study, data of 6 615 fixed sampling plots from continuous national forest inventory of four periods from 1999 to 2014 were collected, and the Pearson correlation coefficient was calculated to evaluate the prediction performance of five theoretical semi-variance models. The model with the highest prediction accuracy was then chosen to do Kriging interpolation of forest carbon density, followed by analysis of tempo-spatial dynamics and driving factors of forest carbon density. 【Result】Among the five theoretical semi-variance models, the order of prediction accuracy from high to low is sphere model> exponential model> circular model> linear model> Gaussian model. The forest carbon density in Hunan Province in 1999, 2004, 2009 and 2014 was 17.156,17.938,18.491 and 20.489 t/hm2, respectively, whereas the standard deviation of forest carbon density was 13.309,15.499,16.211 and 17.141 t/hm2, respectively. From 1999 to 2014, forest carbon density in Hunan Province showed a steady upward trend in quantity, but a weakened spatial aggregation, and increased fragmentation trend in spatial distribution. From 1999 to 2014, the spatial distribution of forest carbon density in Hunan Province generally followed a pattern in which the carbon density in the west, south and east(>20 t/hm2)was higher than that in the north and central part(5-20 t/hm2). From 1999 to 2014, the forest carbon density was positively correlated with vegetation coverage, slope and soil thickness, and negatively correlated with light value in 1999 and 2004 but positively correlated in 2009 and 2014. 【Conclusion】It is necessary to improve the function of forest carbon sinks by strengthening the policies regarding conversion of cropland to forest, and the compensation for ecological benefit for public-welfare forests, as well as consolidating the achievements of collective forest tenure reform.

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Memo

Memo:
收稿日期:2016-08-11 修回日期:2016-12-01
基金项目:国家自然科学基金项目(31570627)
第一作者:戴前石(daiqianshi@126.com),高级工程师。*通信作者:李建军(lijianjun_21@163.com),教授,博士。
引文格式:戴前石,胡觉, 李建军. 基于连清数据的湖南森林碳密度估计及变化特征分析[J]. 南京林业大学学报(自然科学版),2017,41(4):129-135.
Last Update: 1900-01-01