江西省马尾松林生态系统碳密度空间变异特征

doi:10.13287/j.1001-9332.201906.040

应用生态学报 ›› 2019, Vol. 30 ›› Issue (6): 1885-1892.doi: 10.13287/j.1001-9332.201906.040

江西省马尾松林生态系统碳密度空间变异特征

潘萍¹, 孙玉军¹, 欧阳勋志^2,*, 饶金凤², 冯瑞琦², 杨子云²

¹北京林业大学林学院, 北京 100083;
²江西农业大学林学院, 南昌 330045

收稿日期:2019-01-14 出版日期:2019-06-15 发布日期:2019-06-15
通讯作者: * E-mail: oyxz_2003@hotmail.com
作者简介:潘萍,女,1988年生,博士. 主要从事森林资源管理与监测研究. E-mail: panping0306@163.com
基金资助:
国家自然科学基金项目(31760207,31360181,31160159)和中国科学院战略性先导科技专题项目(XDA05050205)资助

Spatial variation of carbon density in Pinus massoniana forest in Jiangxi Province, China

PAN Ping¹, SUN Yu-jun¹, OUYANG Xun-zhi^2,*, RAO Jin-feng², FENG Rui-qi², YANG Zi-yun²

¹College of Forestry, Beijing Forestry University, Beijing 100083, China;
²College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China

Received:2019-01-14 Online:2019-06-15 Published:2019-06-15
Supported by:
This work was supported by the National Natural Science Foundation of China (31760207, 31360181, 31160159) and the Chinese Academy of Sciences Strategic Prio-rity Research Program (XDA05050205)

摘要/Abstract

摘要： 森林碳密度是反映森林生态系统固碳能力的重要指标之一,分析其碳密度的空间变异可为碳汇林业的经营与管理提供科学依据.以江西省马尾松林生态系统为对象,基于样地调查及样品碳含量测定数据,利用全局和局域Moran I,分析其碳密度的空间自相关性,并采用地统计学方法,探讨其空间分布规律.全局Moran I表明,马尾松林生态系统碳密度的空间自相关性呈正相关,且其自相关性随着距离的增大而逐渐减弱,当距离超过400 km后不存在空间自相关性,其空间分布随距离的增大逐渐由聚类分布趋向于随机分布;局部Moran I值表明,马尾松林生态系统碳密度的局部空间分布不均匀,且随距离的增大,其局部空间分布的差异逐渐增大.半方差函数模型的拟合结果表明,球状模型对马尾松林生态系统碳密度的拟合效果最优,其块金值与基台值的比值为0.36,其在空间上存在中等程度的相关性.通过克里格空间插值,马尾松林生态系统碳密度主要集中在85.14～153.52 t·hm^-2,空间分布规律总体上均呈中间低、周边高的趋势,与研究区的周边高中间低的地势特征较为吻合.

Abstract: Carbon density is one of the important indicators for carbon sequestration capacity in forest ecosystems. The analysis of spatial variation in forest carbon density can provide scientific basis for management of forest carbon sink. We investigated the carbon density of Pinus massoniana forest in Jiangxi Province. Based on plot investigation and meaurement of sample carbon content, the spatial autocorrelation and distribution of carbon density were analyzed and explored respectively by using global Moran I, local Moran I and geostatistics. Results from the global Moran I showed that ecosystem carbon density had significant positive spatial autocorrelation and its autocorrelation decreased with the increase of distance. Ecosystem carbon density had no spatial autocorrelation when the distance exceeded 400 km. The spatial distribution of ecosystem carbon density changed from aggregated distribution to random distribution with the increase of distance. Results from the local Moran I showed that the local spatial distribution of ecosystem carbon density was not uniform, and the difference of local spatial distribution gradually increased with the increase of distance. The fitting results of semi-variogram models showed that the spherical model was the best fitting model for the estimation of ecosystem carbon density. The ratio of nugget to sill was 0.36, indicating mode-rate spatial correlation of carbon density. The ecosystem carbon density based on kriging spatial interpolation mainly concentrated in the range of 85.14-153.52 t·hm^-2. The spatial distribution regularity was generally low in middle region and high in peripheral region, which was consistent with the terrain characteristics of the study area.

潘萍, 孙玉军, 欧阳勋志, 饶金凤, 冯瑞琦, 杨子云. 江西省马尾松林生态系统碳密度空间变异特征[J]. 应用生态学报, 2019, 30(6): 1885-1892.

PAN Ping, SUN Yu-jun, OUYANG Xun-zhi, RAO Jin-feng, FENG Rui-qi, YANG Zi-yun. Spatial variation of carbon density in Pinus massoniana forest in Jiangxi Province, China[J]. Chinese Journal of Applied Ecology, 2019, 30(6): 1885-1892.

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江西省马尾松林生态系统碳密度空间变异特征

Spatial variation of carbon density in Pinus massoniana forest in Jiangxi Province, China

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