Abstract
Several comparative studies have reported that there can be great discrepancies between different methods used to estimate forest biomass. With the development of carbon markets, an accurate estimation at the regional scale (i.e. county level) is becoming increasingly important for local government. In this study, we applied five methodologies [continuous biomass expansion factor (CBEF) approach, mean biomass density (MB) approach, mean biomass expansion factor (MBEF) approach, national continuous biomass expansion factors (NCBEF) proposed by Fang et al (2002), standard IPCC approach] to estimate the total biomass for Shitai County, China. The CBEF is generally considered to provide the most realistic estimates in term of regional biomass because CBEF reflects the change of BEF to stand density, stand age and site conditions. The forests of the whole county were divided into four forest types, namely Chinese fir plantations (CF), hardwood broadleaved forests (HB), softwood–broadleaved forests (SB) and mason pine forests (MP) according to the local forest management inventory of 2004. Generally, the MBEF approach overestimated forest biomass while the IPCC approach underestimated forest biomass for all forest types when CBEF derived biomass was used as a control. The MB approach provided the most similar biomass estimates for all forest types and could be an alternative approach when a CBEF equation is lacking in the study area. The total biomass derived from MBEF was highest at 1.44×107 t, followed by 1.32 ×107 t from CBEF, 1.31 ×107 t from NCBEF, 1.25 ×107 t from MB and 1.16 ×107 t from IPCC. Our results facilitate method selection for regional forest biomass estimation and provide statistical evidence for local government planning to enter the potential carbon market.
Highlights
About 80% of terrestrial biomass is stored in forests (Dixon et al 1994), and forest biomass as well as methods for its estimation are of great interest due to the important role of forests with regards to mitigating global climate change (Guo et al 2010, Seo et al 2013)
Based on the national forest inventory in 1999-2003, China’s forest biomass carbon stock ranged from 5.7 Pg C (1 Pg C = 1015 g C) derived from the continuous biomass expansion factor (CBEF) approach to 7.7 Pg C derived from the mean biomass density (MB) approach (Guo et al 2010), and it is even higher from MODIS-based estimation (8.6 Pg C, Yin et al 2015)
The CBEF was considered the most realistic estimate because it estimated biomass as a function of stand volume, which incorporated the effects of forest age, stand density and site quality
Summary
About 80% of terrestrial biomass is stored in forests (Dixon et al 1994), and forest biomass as well as methods for its estimation are of great interest due to the important role of forests with regards to mitigating global climate change (Guo et al 2010, Seo et al 2013). In this study, five well-known methods, namely the continuous biomass expansion factor (CBEF) approach, the mean biomass density (MB) approach, the mean biomass expansion factor (MBEF) approach, national continuous biomass expansion factors (NCBEF) proposed by Fang et al (2002), and the standard IPCC approach, were used to estimate the forest biomass of four forest types.
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