The potential for global forest cover: The restoration of forested land at a global scale could help capture atmospheric carbon and mitigate climate change. Bastin et al. used direct measurements of forest cover to generate a model of forest restoration potential across the globe (see the Perspective by Chazdon and Brancalion). Their spatially explicit maps show how much additional tree cover could exist outside of existing forests and agricultural and urban land. Ecosystems could support an additional 0.9 billion hectares of continuous forest. This would represent a greater than 25% increase in forested area, including more than 200 gigatonnes of additional carbon at maturity.Such a change has the potential to store an equivalent of 25% of the current atmospheric carbon pool. Science , this issue p. 76 ; see also p. 24

There is strong interest in gaining an informed view of changes likely to occur in forest area and the impacts of these changes on production forestry and forest conservation. Despite the complexity of underlying causes, it is largely accepted that deforestation is mainly focused in the tropics and driven by conversion to agriculture. Similarly, energy demand and GDP are largely determining wood consumption and production. Based on these assumptions, we built a model predicting natural forests and planted forests’ evolution in the next 15years, and compared the results of the modelling with survey results from country expertise. The results suggest that on a global level, forest resources loss is likely to slow down. The forests that are most at risk of conversion were clearly identified within the tropical domain, while the forest under protected areas showed very little risk of being converted to other land uses in the near future

Our study quantified the global tree restoration potential and its associated carbon storage potential under existing climate conditions. We received multiple technical comments, both supporting and disputing our findings. We recognize that several issues raised in these comments are worthy of discussion. We therefore provide a detailed common answer where we show that our original estimations are accurate.

A third of the world’s ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO’s SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data.

This study explores how deforestation relates to biophysical and socio-economic variables in a quantitative, spatially explicit analysis. Both patterns of historical (approximately 4000 B.C. – 2000 A.D.) and recent (1990–2005) deforestation were explored and compared. The study uses location analysis, combining spatially explicit global databases of deforestation with variables hypothesized to relate to deforestation (e.g. rural livestock density, cost-distance). The results show that historical and recent deforestation show similar patterns when plotted against the selected variables suggesting the relations to be empirical. The strongest relations were between deforestation and rural population density, cost-distance and crop suitability respectively. These findings support the hypothesis that agricultural expansion was the largest direct cause of deforestation historically and it continues to be the largest direct cause today. While crop suitability showed a strong correlation with deforestation, pasture suitability showed no correlation. The study accordingly compares contemporary deforestation in the tropical domain against economic development (approximated by a combination of GDP value and growth rate) which resulted in a reproduction of the deforestation pattern predicted by the forest transition curve. In view of the apparent empirical relation, the variables which relate to deforestation in this study are expected to have predictive power to identify locations of likely future deforestation. To illustrate the application value of this analysis, the deforestation risk in African protected forest was assessed. This assessment revealed that protected areas are found on locations with below average pressure and the pressures vary greatly in the different regions. The findings underline the importance of considering national circumstances to understand the government's efforts to manage its forests sustainably and contribute to international mitigation by reducing forest-related emissions. Spanish Este estudio explora la relación entre deforestación y variables biofísicas y socioeconómicas en un análisis cuantitativo y espacialmente explícito. Se han explorado y comparado patrones de deforestación histórica (aproximadamente 4000 aC – 2000 A.D.) y reciente (1990–2005). El estudio utiliza el análisis de localización, combinando bases de datos globales de deforestación espacialmente explícitos con variables de hipótesis relacionadas con la deforestación (por ejemplo, carga ganadera rural, coste-distancia). Los resultados muestran que las deforestaciones histórica y reciente muestran patrones similares cuando se trazan con las variables seleccionadas sugiriendo relaciones empíricas. Las relaciones más fuertes se dieron entre la deforestación y la densidad de población rural, coste-distancia y la idoneidad de cultivo respectivamente. Estos hallazgos apoyan la hipótesis de que la expansión agrícola ha sido la principal causa directa de deforestación histórica y reciente. Si bien la idoneidad de cultivo mostró una fuerte correlación con la deforestación, la idoneidad de pasto no mostró correlación. En consecuencia, el estudio compara la deforestación contemporánea en el dominio tropical con el desarrollo económico (aproximada por una combinación del valor de PIB y su tasa de crecimiento) que resultó en una reproducción del patrón de deforestación predicho por la curva de transición forestal. A la vista de la aparente relación empírica, se espera que las variables relacionadas con la deforestación en este estudio tengan poder predictivo para identificar ubicaciones de probable deforestación futura. Para ilustrar el valor de aplicación de este análisis, se evaluó el riesgo de deforestación en bosques protegidos africanos. Esta evaluación reveló que las áreas protegidas se encuentran en lugares con presión por debajo de la media y que estas presiones varían mucho entre regiones. Los hallazgos subrayan la importancia de considerar las circunstancias nacionales para entender los esfuerzos del gobierno a la hora de manejar sus bosques de manera sostenible y contribuir a la mitigación internacional mediante la reducción de las emisiones relacionadas con los bosques. French Cette étude explore comment la déforestation est liée à des variables biophysique et socio-économiques à travers une étude quantitative et spatialement explicite. Les tendances de la déforestation historique (de -4000 av. JC à 2000) sont comparées à celles de la déforestation récente (1990–2005). L'étude repose sur une analyse spatiale, qui combine des bases de données mondiales de la déforestation avec des variables potentiellement liées à la déforestation (densité de bétail, distance-coût etc.). Les résultats montrent que les déforestations historique et récente suivent des tendances similaires, notamment à travers les relations graphiques des variables choisies. Les corrélations les plus fortes ont été observées entre la déforestation et la densité de population rurale, l'accessibilité (distance-coût) et le potentiel agricole des terres. Ces résultats supportent l'hypothèse que l'expansion de l'agriculture était et continue à être la principale cause directe de déforestation. Alors que le potentiel agricole a montré des corrélations fortes, l'aptitude au pâturage n'a montré aucune corrélation. En conséquence, cette étude a comparé la déforestation actuelle dans les tropiques avec le développement économique (approximé comme une combinaison du PIB et du taux de croissance): les tendances de la déforestation sont également prédites par la courbe de transition forestière. Etant donné les résultats empiriques apparents, les variables liées à la déforestation dans cette étude peuvent être considérées pour leur potentiel prédictif des emplacements de la déforestation future. A titre d'illustration, les risques de déforestation dans les forêts protégées d'Afrique ont été évalués. L'évaluation montre que les aires protégées se trouvent sur des zones avec une pression en-dessous de la moyenne du continent, mais avec de très fortes variabilités régionales. Les résultats montrent l'importance de considérer les circonstances nationales pour comprendre les efforts des gouvernements pour gérer les forêts de façon durable et contribuer à la mitigation internationale des émissions de gaz à effet de serre liées à la déforestation.