Linking growth models and allometric equations to estimate carbon sequestration potential of cocoa agroforestry systems in West Africa.

Abstract

Establishment of a tree canopy in Cocoa Agroforestry Systems (C-AFS) provides higher carbon stocks and other ecosystem services compared with other agricultural land uses. These systems are eligible for incentive schemes for carbon sequestration but need to be optimally designed to ensure that they meet intended future goals. In this study, we combined environmental-dependent growth models and allometric equations to forecast carbon sequestration in an innovative C-AFS trial in Côte d'Ivoire and compare the results with values estimated in other cocoa systems elsewhere. The polynomial regression and non-linear regression models provided the best fit models to predict total height and stem diameter in cocoa and associated shade tree species. Then, best species-specific allometric equations were selected and used to estimate biomass from stem diameter and/or tree height. Carbon stock in the trial ranged from 37.2 to 40.5 Mg C ha^-1 at 20 years, with abrupt changes due to the management activities during the study period. Timber trees stored more than 45% of aboveground carbon stocks across all agroforestry schemes. The models developed in this study hold clear applications and will serve as major platforms to design new cocoa agroforestry systems and make well-informed management decisions to maximize carbon sequestration.