Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

Abstract

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations.

Forest carbon storage along the north-south transect of eastern China: Spatial patterns, allocation, and influencing factors

“…Furthermore, there were 72 vegetation plots in cold humid regions, 257 plots in temperate humid and semi-humid regions, 84 plots in temperate arid and semi-arid regions, 226 plots in warm temperate humid and sub-humid regions, 179 plots in north subtropical humid regions, 428 plots in mid-subtropical humid regions, 162 plots in south subtropical humid regions, and 63 plots in tropical humid regions. For the plots with only forest biomass, a coefficient of 0.5 was used to convert vegetation biomass density to C storage (Mg C ha −1 ; Cook et al, 2014;Yu et al, 2014). Unless the data of SOC storage (Mg C ha −1 ) were reported in the original studies, they were calculated using Eq.…”

Review of regional carbon counting methods for the Chinese major ecological engineering programs

“…Implementing these large-scale programs not only improves the ecological environment, but also greatly helps local farmers and communities escape poverty in the program regions. Various case studies have demonstrated that these programs have substantially increased forest carbon stocks and sequestration rates at local levels (Chen and Hay 2009;Wang et al 2014;Yu et al 2014). However, there are few studies on quantification of the contributions of those large-scale programs to forest carbon stocks at regional and national levels.…”

Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods

“…However, more recent evidence shows that these constant BEFs are always the average values for a specific tree species, which are sometimes inaccurate given that stand age, stand density and site quality can change the BEFs (Lehtonen et al 2004, Teobaldelli et al 2009, Correia et al 2010. Thus, applying constant BEFs values across all age classes and site conditions within a forest type underestimates the forest biomass of younger or less productive stands or overestimates the forest biomass of older and more productive stands (Fang et al 1998, Goodale et al 2002, Yu et al 2014. In this study, the threshold stand volume where BEFs equal the constant BEF were 59, 39, 20 and 153 m 3 for CF, HB, SB and MP forests, respectively.…”

“…Sharp et al (1975) estimated the regional forest biomass for Northern Carolina in the USA using a constant BEF of 2.0 Mg m -3 . However, more recent studies have indicated that the BEF is not a constant value and varies with forest age, site class and stand density (Fang and Wang 2001, Lehtonen et al 2004, Teobaldelli et al 2009, Correia et al 2010, Yu et al 2014. Thus, applying constant BEFs across all age classes and site conditions within a given forest type underestimates the forest biomass of younger or less productive stands and overestimates the forest biomass of older or more productive stands (Fang et al 1998, Goodale et al 2002.…”