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【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/hm~2,标准差分别为13.309、15.499、16.211、17.141 t/hm~2。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/hm~2),北部、中部较低(5~20 t/hm~2)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。
【Objective】 Through the analysis of carbon density spatio-temporal analysis and driving factors, a large-scale forest carbon sequestration monitoring method based on the continuous inventory of forest resources was explored. 【Method】 The data of 6 615 forest resources in Hunan Province from 1999 to 2014 were used as the main source of information for continuous inventory of fixed forest resources. The Pearson correlation coefficient was used. Based on the comparative analysis of the accuracy of the five theoretical semi-variance models, the highest predictive performance Model of forest carbon density Kriging interpolation, spatio-temporal analysis, the driving factor analysis. 【Result】 The results showed that the accuracy of five theoretical semi-variance models ranked from high to low: spherical model> exponential model> circular model> linear model> Gaussian model. The forest carbon density of Hunan Province in 1999, 2004, 2009 and 2014 were respectively 17.156, 17.938, 18.491 and 20.489 t / hm ~ 2 with standard deviations of 13.309, 15.499, 16.211 and 17.141 t / The forest carbon density in Hunan Province showed a steady upward trend, the spatial aggregation decreased and the tendency of fragmentation increased. From 1999 to 2014, the spatial distribution of forest carbon density in Hunan showed an overall increase of more than 20 t / hm in the west, south and east ~ 2), the northern and central lower (5 ~ 20 t / hm ~ 2) spatial distribution pattern. In 1999-2014, there was a positive correlation between forest carbon density and vegetation coverage, slope and soil thickness. The correlation with light intensity was negatively correlated in 1999 and 2004, and positive in 2009 and 2014. 【Conclusion】 The spatial and temporal changes of carbon density in Hunan Province are both affected by the adjustment of forestry policies and the changes of social and economic conditions. We should step up the compensation for ecological benefits of returning farmland to forests and public welfare forests, and consolidate the achievements in the reform of collective forest rights system.