Résumé
French Guiana’s Atlantic coastline is one of the world’s most dynamic and sediment-rich, shaped by the interplay of Amazon-derived mud banks, intense wave action, and shifting geomorphology. These wave-exposed muddy coasts host extensive mangrove ecosystems that experience rapid cycles of accretion and erosion. The resulting environmental changes drive forest establishment, retreat, and renewal at rates rarely seen elsewhere.
This repository provides R code and curated plot-level field data for analyzing stand growth and aboveground biomass in mangrove forests along the coast of French Guiana. Six parametric growth models (Weibull, Chapman Richards, Power, Gompertz, Logistic, and Monomolecular) are applied to Avicennia germinans and Rhizophora mangle, and Rhizophora racemosa chronosequence datasets age-structured plots to evaluate how these unique environmental pressures shape growth trajectories and biomass accumulation in mangrove stands. Deliverables include stand-level biomass estimates and model diagnostics coefficient of determination R squared, root mean square error RMSE, Akaike Information Criterion AIC, alongside bootstrapped prediction intervals for rigorous uncertainty quantification.