Which allometric models are the most appropriate for estimating aboveground biomass in secondary forests of Madagascar with Ravenala madagascariensis?

In Madagascar, allometric models have been developed only for the primary forests. There have been no specific models for the secondary forests. However, with a view to extending the geographic scope of the REDD+(1) mechanism, it deems important to consider the secondary forests of which the potential of carbon sequestration remains unknown. In eastern part of Madagascar, the secondary forests are mostly colonized by Ravenala madagascariensis, an endemic monocotyledonous plant. The main goal of this study was to develop local allometric models for secondary forests with Ravenala madagascariensis. Models for Ravenala madagascariensis were developed separately from those of other woody species. The second goal was to test the validity of the existing allometric equations for the woody species into the study sites, namely three pantropical models developed by Brown, Chave et al. and the best fitted local model developed by Vieilledent et al. for the dense humid forest in Madagascar. Using the destructive method, 120 stems of Ravenala madagascariensis and 115 trees were harvested, weighed and measured. As results, the best fitted local model for the woody species was AGB = EXP(-1.515 + 1.912 ln(D) + 0.471 ln(H) + 0.732 ln(rho)), where AGB is the aboveground biomass in kg, H the total height in m, D the diameter at the breast height in cm and rho the wood specific gravity. For Ravenala madagascariensis, the model which only considered total height was the most appropriate: AGB = EXP(-4.996 + 5.654 ln(H) - 0.772(ln(H))(2)). Comparing with the existing equations, errors of estimates were higher for the pantropical models and a slight overestimation was observed while applying that of Vieilledent et al. It is thus recommended to choose the local site specific models for estimating the aboveground biomass for the secondary forests with Ravenala madagascariensis in the eastern part of Madagascar. (C) 2019 The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative.