Dendrometric traits for developing biomass equations of tree and shrub species in carbon sequestration projects

The advancement of carbon sequestration projects holds significant potential to deliver mutually beneficial outcomes for both the environment and the economy. In this context, biomass models have been extensively developed to estimate the aboveground biomass of woody plants - such as trees and shrubs - using dendrometric characteristics, like diameter and height. The datasets presented in this study compile dendrometric traits from multiple tree and shrub species, supporting the construction of robust biomass models. As a result, tree and shrub biomass can serve as integral indicators for evaluating the effectiveness of carbon sequestration projects, incorporating key factors such as diameter, height and plantation density. By establishing reliable biomass estimation models, it becomes possible to enhance the monitoring and verification of carbon storage, thereby providing a scientific basis for the planning, management and policy-making of carbon sink initiatives. This approach contributes significantly to ecological restoration and climate change mitigation efforts.

This study presents two dendrometric datasets of individual trees and shrub bushes from carbon sequestration projects in north-western China, covering sites in Xining and Haidong (Qinghai Province), Tianshui (Gansu Province) and Aba (Sichuan Province). Specifically, the tree dataset comprises measurements of canopy breadth (in two perpendicular directions), height, diameter at breast height (DBH) and base perimeter for 2084 individuals across 25 species. The shrub dataset includes crown diameter (in two perpendicular directions), height and basal perimeter for 998 bushes across 36 species. These dendrometric traits serve as key parameters in biomass estimation equations. Furthermore, as the diameter and height of trees and shrubs significantly influence understorey plant diversity - primarily through their effects on stand density, species interactions and community composition - these datasets are valuable for advancing biomass modelling and assessing plant diversity outcomes under conservation management.