Aboveground biomass estimation at different scales for subtropical forests in China

Abstract

Background: The accurate estimation of forest biomass at different scales is the critical step in the assessment of forest carbon stocks. We used three models at increasing scales: allometric model at ecoregional scale (model 1), dummy variable allometric model at both ecoregion and regional scales (model 2), and allometric model at regional scale (model 3) to estimate the aboveground biomass of six subtropical forests in China. Furthermore, we also tested whether wood density can improve the accuracy of the allometric model at regional scale.

Results: Aboveground biomass estimates for six subtropical forests were significantly affected by the ecoregions (p < 0.05). Model 1 and model 2 had good fitness with higher values of R ², lower RSE (residual standard error) and MPSE (mean percent standard error) than model 3. The values of MPSE for model 1, model 2, and model 3 ranged from 2.79 to 30.40%, 5.15 to 40.94%, and 13.25 to 80.81% at ecoregion scale, respectively. At regional scale, MPSE of model 2 was very similar to that of model 1, and was less than model 3. New allometric models with wood density had greater R ², lower RSE and MPSE than the traditional allometric models without wood density variable for six subtropical forests at regional scale.

Conclusion: The dummy variable allometric models have better performances to estimate aboveground biomass for six subtropical forests in China, which provided an effective approach to improve the compatibility of forest biomass estimations from different scales. New allometric models with wood density substantially improved accuracies of aboveground biomass estimation for subtropical forests at regional scale.

Keywords: Aboveground biomass; Allometric equation; Dummy variable model; Scale; Wood density.

Fig. 1

The sampling plot locations for the six forest types in the subtropical region of China. See Table 1 for the abbreviations of the forest types and ecoregions

Fig. 2

Comparison measured AGB (aboveground tree biomass) and predicted AGB for six subtropical forests from three allometric models at different scales (model 1, model 2 and model 3) in China. Model 1: allometric model at ecoregion scale, model 2: dummy variable allometric model at both ecoregion scale and regional scale, and model 3: allometric model at regional scale. See Table 1 for the abbreviations of the six forest types

Fig. 3

Fitted curves for each forest type and all forest types at regional scale in subtropical region of China applied the allometric model with wood density variable, and the allometric model without wood density variable. See Table 1 for the abbreviations of the six forest types

Fig. 4

Compared the measured AGB (aboveground tree biomass) and the estimated AGB in subtropical forests by the allometric model with wood density, the allometric model without wood density, and the model widely used in tropical trees created by Chave et al. (2014) $\left({\text{AGB}}_{\text{est}}=0.0673\times {\left(\mathit{\rho }{D}^{2}H\right)}^{0.976}\right)$, respectively (a), and compared MPSE among these three allometric models (b)