Individual tree aboveground biomass for Castanopsis indica in the mid-hills of Nepal

Abstract

Quantitative information of tree biomass is useful for management planning and monitoring of the changes in carbon stock in both forest and agroforestry systems. An estimate of carbon stored in these systems can be useful for developing climate change mitigation strategies. A precise estimate of forest biomass is also important for other issues ranging from industrial forestry practices to scientific purposes. The individual tree-based biomass models serve as fundamental tools for precise estimates of carbon stock of species of interest in forest and agroforestry systems. We developed individual tree aboveground biomass models for Castanopsis indica using thirty-six destructively sampled tree data covering a wide range of tree size, site quality, growth stage, stand density, and topographic characteristics. We used diameter at breast height (DBH) as a main predictor and height-to-DBH ratio (a measure of tree slenderness) and wood density (a measure of stiffness and cohesiveness of wood fibres) as covariate predictors in modelling. We, hereafter, termed the biomass models with former two predictors as first category models (density independent models) and the models with all three predictors as second category models (density dependent models). Among various functions evaluated, a simple power function of the form $$y_{i} = b_{1} x_{i}^{{b_{2} }}$$ , in each category, showed the best fits to our data. This formulation, in each category, described most of the biomass variations ( $$R_{adj}^{2}$$ > 0.98 and RMSE < 72.2) with no significant trend in the residuals. Since both density dependent and density independent models exhibit almost similar fit statistics and graphical features, one of them can be applied for desired accuracy, depending on the access of the input information required by the model. Our biomass models are site-specific, and their applications should therefore be limited to the growth stage, stand density, site quality, stand condition, and species distribution similar to those that formed the basis of this study. Further research is recommended to validate and verify our model using a larger dataset with a wider range of values for site quality, climatic and topographic characteristics, stand density, growth stage, and species distribution across Nepal.