Forest carbon stock-based bioeconomy: Mixed models improve accuracy of tree biomass estimates

Abstract

Tree biomass and carbon stock continue to be the most important contributors to a forest-based bioeconomy. Accurate estimation of tree biomass and carbon stock therefore is crucial for planning a sustainable bioeconomy based on sustained forest bioresource production and harvest. Precise carbon accounting is also of fundamental importance for a green carbon market as well as for an improved model of quantitative global carbon cycle. However, estimating biomass and carbon at a large spatial scale without causing significant environmental disruption has been posing a methodological challenge necessitating to evolve a robust yet accurate estimation method. Although forest-specific generalized allometric models are the most widely used method to estimate forest tree biomass and carbon stock, these either under- or over-estimate the values, particularly in mixed-species forests. To address this challenge, we employed mixed equations that included species-specific models or available models for a sister species that provided a more conservative estimate of stand-level tree biomass and carbon compared to the generalized equations. We gathered primary data on tree girth and height at the stand level from sub-tropical and temperate forests of Tawang river basin, Arunachal Pradesh, India for validation. We compiled 32 equations comprising 27 species-specific and 5 forest-specific generalized models from a global dataset of allometric models. The outputs from the mixed models were comparable with the results of the harvest studies conducted by other researchers in similar forest types validating the efficacy of mixed models at a landscape scale.