The potential of bamboo forests as a carbon sink and allometric equations for estimating their aboveground biomass

Juan Carlos Camargo García (), Angela Maria Arango Arango () and Long Trinh ()
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Juan Carlos Camargo García: Universidad Tecnológica de Pereira
Angela Maria Arango Arango: Universidad Tecnológica de Pereira
Long Trinh: International Bamboo and Rattan Organization

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 8, No 41, 20159-20187

Abstract: Abstract Bamboo forests in Colombia and the Andean region of South America represent high-value ecosystems that provide ecological and economic benefits with local and global impacts. One of the ecosystem services provided by these forests is associated with their capacity to store carbon. In this study, data collected from monitoring plots were used to estimate the carbon content in different pools. Bamboo biomass (Bba), tree biomass (Btree), litter (Cli) and soil organic carbon (SOC) were assessed. The approximate total ecosystem carbon stock (TECaprox) ranged from 198.4 Mg C ha−1 to 330.9 Mg C ha−1 and bamboo carbon Cba represents approximately 50%. In addition, considering the relevance of developing tools to facilitate bamboo inventory and biomass estimates, allometric equations (AE) to estimate bamboo aboveground biomass (AGB) were fitted using the diameter of culms at breast height (dbh) and the total culm length (l) as predictor variables. The fitted AEs included the weighted linear, weighted log-transformed and weighted nonlinear fixed effect models. To compliance the additivity of biomass components a simultaneous systems of biomass equations (seemingly unrelated regressions) were also fitted. The precision and accuracy were assessed considering the residual diagnostic plots and statistics, such as the root-mean-square error (RMSE), RMSE percentage error (RMSEPE) and the Furnival’s index (Fln) for weighted log-transformed models and cross-validation. The performance of the models was similar with an RMSE of approximately 10 kg and 26% of RMSEPE, with slightly lower error for the weighted log-transformed model for the fitting and validation phases. A proper performance was also evidenced for the simultaneous approach for predicting AGB. Bamboo forests showed high relevance as carbon sinks and therefore might be considered strategic tropical ecosystems for climate change mitigation. On the other hand, the fitted AE exhibited proper performance and therefore provided reliable possibilities for estimating the AGB of bamboo during inventories. For practical reasons, the use of models with dbh as a predictor variable is recommended.

Keywords: Climate change mitigation; Coffee region; Colombian Andes; Guadua angustifolia; Total ecosystem carbon; Regression analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03460-1

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