Data and code of the publication entitled: A common framework to model recovery in disturbed tropical forests

We developed an original Bayesian hierarchical model of recovery trajectories, considering disturbed forests in a common framework, through a disturbance intensity gradient, inferred with the loss of basal area due to disturbance. As a case study, we tested our modelling approach on above-ground biomass, Shannon taxonomic diversity and taxonomic composition similarity from two long-term experiments, Tirimbina (Costa Rica) and Paracou (French Guiana), where forest permanent sample plots have been set up following selective logging (63.25 ha), agriculture (4 ha), and clearcutting+fire (6.25 ha). <br> <strong>This dataset contains:</strong> <ul> <li><strong>1 dictionary data text file</strong></li> <li><strong>5 model scripts (run under the R package rstan version 2.26.13):</strong> <ul> <li>Stan codes for the vegetation attribute predictions: above-ground biomass (AGB), Shannon diversity, and composition similarity.</li> <li>Stan codes for the general models of long-term and long- + short-term processes presented in the publication.</li> </ul> </li> <li><strong>12 data sets:</strong> <ul> <li>Basal area in disturbed forests, and in old-growth forests (for above-ground biomass and Shannon diversity predictions)</li> <li>Above-ground biomass in disturbed forests, and in old-growth forests (for above-ground biomass predictions)</li> <li>Shannon diversity in disturbed forests, and in old-growth forests (for Shannon diversity predictions)</li> <li>Basal area in selectively logged forest, in clearcut+fire forest, and in old-growth forests (for composition similarity predictions)</li> <li>Composition similarity in selectively logged forest, in clearcut+fire forest, and in old-growth forests (for composition similarity predictions)</li> </ul> </li></ul>

Bibliographic Details

Main Authors:	Maurent, Eliott, Hérault, Bruno, Piponiot, Camille, Derroire, Géraldine, Delgado, Diego, Finegan, Bryan, Aubry-Kientz, Mélaine, Amani, Bienvenu H. K., Ngo Bieng, Marie Ange
Published:	CIRAD Dataverse
Subjects:	Earth and Environmental Sciences, anthropogenic disturbance, recovery, tropical forest conservation, vegetation attribute trajectories, ecosystem modelling,
Online Access:	https://doi.org/10.18167/DVN1/8KL5PC
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