Analysis of spatio-temporal changes in forest biomass in China

Weiyi Xu , Xiaobin Jin , Jing Liu , Xuhong Yang , Jie Ren , Yinkang Zhou

Journal of Forestry Research ›› 2021, Vol. 33 ›› Issue (1) : 261 -278.

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Journal of Forestry Research ›› 2021, Vol. 33 ›› Issue (1) : 261 -278. DOI: 10.1007/s11676-021-01299-8
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Analysis of spatio-temporal changes in forest biomass in China

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Abstract

Forests play a central role in the global carbon cycle. China's forests have a high carbon sequestration potential owing to their wide distribution, young age and relatively low carbon density. Forest biomass is an essential variable for assessing carbon sequestration capacity, thus determining the spatio-temporal changes of forest biomass is critical to the national carbon budget and to contribute to sustainable forest management. Based on Chinese forest inventory data (1999–2013), this study explored spatial patterns of forest biomass at a grid resolution of 1 km by applying a downscaling method and further analyzed spatio-temporal changes of biomass at different spatial scales. The main findings are: (1) the regression relationship between forest biomass and the associated influencing factors at a provincial scale can be applied to estimate biomass at a pixel scale by employing a downscaling method; (2) forest biomass had a distinct spatial pattern with the greatest biomass occurring in the major mountain ranges; (3) forest biomass changes had a notable spatial distribution pattern; increase (i.e., carbon sinks) occurred in east and southeast China, decreases (i.e., carbon sources) were observed in the northeast to southwest, with the largest biomass losses in the Hengduan Mountains, Southern Hainan and Northern Da Hinggan Mountains; and, (4) forest vegetation functioned as a carbon sink during 1999–2013 with a net increase in biomass of 3.71 Pg.

Keywords

Forest vegetation biomass / Spatial distribution / Spatio-temporal changes

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Weiyi Xu, Xiaobin Jin, Jing Liu, Xuhong Yang, Jie Ren, Yinkang Zhou. Analysis of spatio-temporal changes in forest biomass in China. Journal of Forestry Research, 2021, 33(1): 261-278 DOI:10.1007/s11676-021-01299-8

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