Moving forward socio-economically focused models of deforestation

Dezécache Camille, Salles Jean Michel, Vieilledent Ghislain, Hérault Bruno. 2017. Moving forward socio-economically focused models of deforestation. Global Change Biology, 23 (9) : 3484-3500.

https://doi.org/10.1111/gcb.13611

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Quartile : Outlier, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Outlier, Sujet : BIODIVERSITY CONSERVATION / Quartile : Outlier, Sujet : ECOLOGY

Résumé : Whilst high-resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision-making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001–2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterization of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects.

Mots-clés Agrovoc : forêt, forêt tropicale humide, déboisement, démographie, population rurale, modèle de simulation, télédétection, méthode statistique, couvert forestier, dynamique des populations, sociologie rurale, aménagement forestier