Abstract

BackgroundThe accuracy in estimating forest ecosystem carbon storage has drawn extensive attention of researchers in the field of global climate change. However, incomparable data sources and various estimation methods have led to significant differences in the estimation of forest carbon storage at large scales.MethodsIn this study, we reviewed fundamental types of forest carbon storage estimation methods and their applications in China.ResultsResults showed that the major forest carbon storage estimation methods were classified into 3 major categories and 15 subcategories focusing on vegetation carbon storage estimation, soil carbon storage estimation, and litter carbon storage estimation, respectively. The application in China showed that there have been 3 development stages of research in China since the 1990s. Studies of forest carbon storage estimation in province scales were conducted more frequently in the northeastern, eastern and southwestern provinces such as Zhejiang, Heilongjiang and Sichuan with high forest coverage or large forest area. Inventory-based methods, soil type method, and biomass model were the main forest estimation methods used in China, focusing on vegetation, soil and litter carbon storage estimation respectively. Total forest carbon storage of China was approximate 28.90 Pg C, and the average vegetation carbon density (42.04 ± 5.39 Mg·ha− 1) was much lower than that of the whole world (71.60 Mg·ha− 1). Vegetation carbon density from average biomass method was the highest (57.07 Mg·ha− 1) through comparing nine types of vegetation carbon storage estimation methods applied during 1989 to 1993.ConclusionsMany studies on forest carbon storages have been carried out in China at patch scales or regional scales. These efforts enabled the research of forest carbon storage to reach a relatively advanced stage. Meanwhile, the accumulation of massive research data provides the basis for subsequent research work. Some challenges are also existing. This review could provide a reference for more accurate estimation of forest carbon storage in the future.

Highlights

  • The accuracy in estimating forest ecosystem carbon storage has drawn extensive attention of researchers in the field of global climate change

  • Chinese forests have served as a carbon sink over the past few decades (Piao et al 2005a, b; Ju et al 2007; Fang et al 2014; Zeng 2014; Zhang et al 2015), which was primarily due to large-scale afforestation efforts in China, where the forest area increased by 2 million hectares per year in the 1990s and by an average of 3 million hectares per year since 2000 (Fang et al 2018; Lu et al 2018)

  • We summarized and analyzed fundamental types of forest carbon storage estimation methods in recent decades, which were classified into 3 major categories and 15 subcategories focusing on vegetation carbon storage estimation, soil carbon storage estimation, and litter carbon storage estimation, respectively

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Summary

Introduction

The accuracy in estimating forest ecosystem carbon storage has drawn extensive attention of researchers in the field of global climate change. Forest ecosystem is one of the most important parts of terrestrial ecosystems and the largest carbon pool, occupying an integral position in global carbon cycle of terrestrial ecosystems (Liu et al 1997; Fang et al 1998; Wang et al 2001; Kuuluvainen and Gauthier 2018; Zhao et al 2019). Forest ecosystem has higher productivity than any other terrestrial ecosystems, with its fixed carbon accounting for more than two-thirds of the total amount in terrestrial ecosystems each year (Fang et al 2001a, b). The forest area of China is among the top five globally and covers 20.36% of the country’s total area (FAO 2016). Chinese forests have served as a carbon sink over the past few decades (Piao et al 2005a, b; Ju et al 2007; Fang et al 2014; Zeng 2014; Zhang et al 2015), which was primarily due to large-scale afforestation efforts in China, where the forest area increased by 2 million hectares per year in the 1990s and by an average of 3 million hectares per year since 2000 (Fang et al 2018; Lu et al 2018)

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