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Position: Home > Articles > Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships Forest Ecosystems 2023,10

Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships

作  者：
Mingxia Yang;Xiaolu Zhou;Changhui Peng;Tong Li;Kexin Chen;Zelin Liu;Li Peng;Cicheng Zhang;Jiayi Tang;Ziying Zo
单  位：
Institute of Environment Sciences, Department of Biology Sciences, University of Quebec at Montreal, Case Postale 8888, Succursale Centre-Ville, Montreal, Quebec, H3C 3P8, Canada; School of Geographic Sciences, Hunan Normal University, Changsha, 410081, China;School of Geographic Sciences, Hunan Normal University, Changsha, 410081, China;School of Geographic Sciences, Hunan Normal University, Changsha, 410081, Chin
关键词：
Allometric equation;Forest biomass;National Forest Inventory;Species grouping;Tree architecture;Wood densit
摘  要：
The development of allometric biomass models is important process in biomass estimation because the reliability of forest biomass and carbon estimations largely depends on the accuracy and precision of such models. National Forest Inventories (NFI) are detailed assessments of forest resources at national and regional levels that provide valuable data for forest biomass estimation. However, the lack of biomass allometric equations for each tree species in the NFI currently hampers the estimation of national-scale forest biomass. The main objective of this study was to develop allometric biomass regression equations for each tree species in the NFI of China based on limited biomass observations. These equations optimally grouped NFI and biomass observation species according to their phylogenetic relationships. Significant phylogenetic signals demonstrated phylogenetic conservation of the crown-to-stem biomass ratio. Based on phylogenetic relationships, we grouped and matched NFI and biomass observation species into 22 categories. Allometric biomass regression models were developed for each of these 22 species categories, and the models performed successfully (R2 ​= ​0.97, root mean square error (RMSE) ​= ​12.9 ​t·ha–1, relative RMSE ​= ​11.5%). Furthermore, we found that phylogeny-based models performed more effectively than wood density-based models. The results suggest that grouping species based on their phylogenetic relationships is a reliable approach for the development and selection of accurate allometric equations.

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