Suchergebnisse

Les aménagements futurs nécessaires au développement rapide de la Guyane vont entraîner la conversion de terres forestières, participant ainsi au changement global. Les décideurs guyanais devront conjuguer ces aménagements avec la préservation des services écosystémiques forestiers. Le projet GuyaSim avait comme objectif l'approfondissement des connaissances sur ces services (stock de carbone, biodiversité et qualité du sol) et le transfert d'un logiciel aux décideurs pour faciliter l'intégration de ces connaissances dans les politiques d'aménagement du territoire. L'article présente les caractéristiques et les fonctionnalités de ce logiciel GuyaSim. Il s'agit d'un logiciel libre de type Sig, destiné a priori aux services d'aménagement des collectivités et du domaine forestier de Guyane. Le logiciel offre deux grands types de fonctionnalité : la mise à disposition d'informations et l'aide à l'aménagement. Les informations mises à disposition sont les scénarios de développement socio-économique, les scénarios climatiques et les valeurs des services écosystémiques. L'aide à l'aménagement consiste en des outils de construction des scénarios d'aménagement du territoire (changement d'usage des terres) et d'aménagement forestier (exploitation forestière), fournissant des informations sur l'impact environnemental. Les fonctionnalités du logiciel sont limitées par les connaissances sur les écosystèmes guyanais. Les avancées des projets de recherche en cours permettront de mettre à jour le logiciel à moyen terme.

Mapping the vegetation Carbon stocks is crucial to understand the global climate change. The Carbon stock maps have direct implications in economy and environmental policy. This is especially true in tropical forests where most of the uncertainties on carbon fluxes and stocks are concentrated. Substantial efforts have been done recently to map forest carbon in tropical areas, especially by using remote sensing-based approaches. However, there is no way to bypass a calibration step where biomass is locally measured through forest inventories. The great importance of this learning step and its possible issues has been documented, highlighting the importance of terrestrial datasets. In our work, we have gathered a very large dataset of forest inventories covering the Congo Basin. It consists of 73 000 0.5ha plots of commercial inventories covering 4 million hectares in Cameroon, Republic of Congo, Gabon, Central African Republic, and the Democratic Republic of the Congo. These terrestrial data are of great value to understand and model the spatial distribution of various forest properties, among which the Carbon stock. They can also make a great tool to control and improve the performance of the remote sensing methods. In our study, we rely on these plots to test the validity of previously published pantropical Carbon maps. After gathering the data with extra care due to the heterogeneous inventory methods, we used bioclimatic models, topography, and remote sensing observation to extrapolate the forest carbon estimates at the Congo basin scale. (Texte intégral)

International audience ; Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.

International audience ; Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.

International audience ; Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.

International audience ; Africa is forecasted to experience large and rapid climate change1 and population growth2 during the twenty-first century, which threatens the world's second largest rainforest. Protecting and sustainably managing these African forests requires an increased understanding of their compositional heterogeneity, the environmental drivers of forest composition and their vulnerability to ongoing changes. Here, using a very large dataset of 6 million trees in more than 180,000 field plots, we jointly model the distribution in abundance of the most dominant tree taxa in central Africa, and produce continuous maps of the floristic and functional composition of central African forests. Our results show that the uncertainty in taxon-specific distributions averages out at the community level, and reveal highly deterministic assemblages. We uncover contrasting floristic and functional compositions across climates, soil types and anthropogenic gradients, with functional convergence among types of forest that are floristically dissimilar. Combining these spatial predictions with scenarios of climatic and anthropogenic global change suggests a high vulnerability of the northern and southern forest margins, the Atlantic forests and most forests in the Democratic Republic of the Congo, where both climate and anthropogenic threats are expected to increase sharply by 2085. These results constitute key quantitative benchmarks for scientists and policymakers to shape transnational conservation and management strategies that aim to provide a sustainable future for central African forests.