Katché Komlanvi Akoete

Although the green belt around Greater Lomé (GBGL) is a vital ecological buffer, it is currently facing significant degradation. This decline appears to be associated with a combination of various socioeconomic uses by the local community and formal operations of established businesses. Grounded in the cultural materialism framework, this study aims to contribute to a better understanding of the dynamics of the socioeconomic uses of the green belt around Greater Lomé in a context of degradation and investigates the dynamics of these socioeconomic uses and their environmental impacts through a multidisciplinary methodology. This approach combines anthropological analysis based on field observation, 53 semi-structured interviews and 5 focus groups, a quantitative questionnaire survey (n = 384) and an analysis of land use and land cover (LULC) dynamics derived from Landsat imagery (2003–2023). The results reveal six main types of socioeconomic uses of the GBGL (notably land transactions, agriculture, breeding and grazing, exploitation of wood energy, timber and utility wood, sand mining, and waste disposal), which lead to complex social dynamics ranging from conflicts to alliances among stakeholders. The LULC dynamics analysis indicates a staggering 468.26% expansion in built-up areas over the last 20 years, at the expense of swamp vegetation/gallery forest (−76.79%), tree-and-shrub savanna (−53.47%) and plantations (−49.43). This study provides a scientific basis supporting the urgent necessity to establish the GBGL as a legally protected entity and argues in favour of an inclusive management model that is designed to reconcile the socioeconomic survival needs of local populations with sustainable preservation of essential ecosystem services.

The degradation of forest landscapes in West Africa, particularly in Togo, threatens ecological and socio-economic sustainability. This study analyzes the spatio-temporal dynamics of land use in the central plains of Togo between 1991 and 2022, and projects its evolution for 2030 and 2050 to guide restoration strategies. The methodology integrates the interpretation of Landsat images (1991, 2005, 2022) and the analysis of indicators, including conversion rates and the anthropization index. Prospective modeling (Markov chains and neural networks) follows a trend scenario. The results reveal a sharp decline in natural forest formations: dense semi-deciduous and dense dry forests (−50.55%) and woodlands (−62.06%), converted mainly to cropland, plantations, and built-up areas. Shrub/tree savannas, the dominant class, represent a transitional stage resulting from forest degradation. The average annual deforestation rate is 0.75%. The ecological disturbance index increased from 0.24 (1991) to 0.45 (2005), and then to 0.56 (2022), reflecting increased human impact and fragmentation. Projections indicate that these trends will continue, highlighting the growing vulnerability of ecosystems and the need to integrate this dynamic into sustainable management and restoration policies.