Additive equations system to estimate aboveground biomass by structural component and total of three giant Bamboo species in Mexico

ABSTRACT

Background:

Bamboo species have a high potential to produce biomass and stock carbon. However, biometric tools are not available to estimate biomass production for most giant bamboo taxa. The aim was to develop an additive equation system to estimate the aboveground biomass by structural component and the total of the three bamboo species. Destructive sampling was applied, and a sample of 101 mature bamboo specimens was collected. The nonlinear power allometric model was used to integrate two additive equations systems, which were formed by the structural components of biomass: culm, branches and leaves as well as aboveground biomass total. The predictor variables were: diameter at breast height (D) for the S1 system, and D in combination with the total height (D²H) for the S2 system.

Results:

It was determined that the SUR method in combination with the dummy variables technique and the correction of heteroscedasticity is an adequate fit strategy. Given that the additivity property is fulfilled, specific values of the parameters of each system and by taxon are identified. In addition, the variance of the error stabilizes. The aboveground biomass of the culm constitutes 86.40%, 90.48%, and 93.94% for Bambusa oldhamii Munro, Guadua aculeata Rupr., and Guadua angustifolia Kunth, respectively. The S1 system was selected, and its statistics regarding the total aboveground biomass were 0.92, 4.9 kg, -0.35 kg, and 0.05 for the fit statistics R ² _adj , RMSE, S, and E, respectively.

Conclusion:

This biometric tool will easier to carry out aboveground biomass inventories, as well as to infer the carbon content and CO₂ equivalent at the specimen level.

Keywords:
Additivity property; Bambusa oldhamii Munro; Guadua aculeata Rupr; Guadua angustifolia Kunth; SUR method.

HIGHLIGHTS

Additive equation system estimates the biomass of culms, branches, leaves, and total aboveground biomass. Power allometric model, SUR method, and dummy variables technique were appropriate. The S1 system that uses diameter at breast height as a predictor variable is recommended. Additive equations systems developed for Guadua aculeata stands are the first record in the literature.