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) : pp. 3484-3500.

Journal article ; 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

Abstract : 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. (Résumé d'auteur)

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

Mots-clés géographiques Agrovoc : Guyane française

Mots-clés libres : Demography, Guiana shield, REDD+, Scenarios, Spatially explicit modelling, Subsidies

Classification Agris : K70 - Forest injuries and protection
K01 - Forestry - General aspects
E51 - Rural population
E50 - Rural sociology
U40 - Surveying methods
U10 - Mathematical and statistical methods

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

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