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Table 1 Different methods for estimating carbon storages of China’s forest (PgC). The first period is the start of the Returning Farmland to Forest Program

From: Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years

Volume-derivedStand-level linear volume-biomass equations, or continuous biomass expansion factor (CBEF), using variables of total area, volume per unit area. Data: NFIs.5.96.2 Fang et al. (2007; 2014); Guo et al. (2010)
Volume-derivedAge-grouped, stand-level linear volume-biomass equations based. Data: 6th NFI.5.5  Xu et al. (2007)
Volume-derivedMean ratio method, using variables of total volume and mean BEF. Data: 6th NFI.6.2  Guo et al. (2010)
Volume-derivedTree-level allometric biomass equations with DBH and height predictors. Provincial BEFs were calculated based on DBH and height information of plots (660,000 permanent plots established in 7th NFI). Data: 7th NFI. 6.7 Li et al. (2011)
Volume-derivedStand-level allometric volume-biomass equations (power functions); removing upscaling error. Data: NFIs. et al. (2016)
Carbon densityMean biomass density method, using variables of total area and mean biomass density. Data: 6th NFI.7.7  Guo et al. (2010)
Carbon densityDeriving carbon density from site measurements, and average carbon density from the provincial area-weighted average and its corresponding area; using Random Forest model to detail spatial patterns of carbon density. Data: Independent investigation, establishing total 7800 sites for field measurements in forests.  10.4Tang et al. (2018)
Remote sensingMultiple spectral bands of MODIS and forest inventory data with an empirical statistical model.6.3 6.8Sun et al. (2015)
Remote sensingA development of AGBmapping. Data: Geoscience Laser Altimeter System (GLAS)/Ice, Cloud, Land Elevation Satellite (ICESat) data, optical imagery, climate surfaces, and topographic data. 10.2a Su et al. (2016)
  1. aTotal biomass carbon, estimated from the reported AGB (7.5 Pg)