Vegetation and Land Cover Change in the Context of Land Degradation in sub-Saharan West Africa

Land degradation has been a serious environmental problem in dryland areas where moisture supply is limited. This thesis aims to assess vegetation and land cover change in the context of land degradation in the sub-Saharan West Africa, a hotspot of environmental change. The study combines various approaches which include statistical trend analysis of satellite derived Normalized Difference Vegetation Index (NDVI) residuals, indigenous knowledge of vegetation changes, and land use land cover change analysis to determine the spatial and temporal changes in vegetation and land cover in the context of land degradation over a 30-year period. Results have shown that, in spite of the ongoing scientific debate around the greening trend observed by satellite data in the past three decades, evidence of land degradation is very pronounced in the region, particularly when a soil moisture index is used in the residual trend analysis to correct for vegetation productivity instead of instantaneous rainfall. They also indicate a declining rate of diversity and density of indigenous wood vegetation species at the study sampling sites (p < 0.05), with nearly 80% of all the identified species found to have become either completely extinct or migrated to a region with sufficient moisture conditions. A continued decrease of closed forest and an increase in croplands were found, with agricultural land use being the major driving force of land cover change, and across the region nearly all the areas found under severe land degradation are croplands. This thesis has shown the importance and relevance of an interdisciplinary approach for land degradation studies. Future studies should go beyond the analysis of NDVI trends based on rainfall as the major driver of vegetation change. Instead, an integrated method should be used which will combine soil moisture, indigenous knowledge of vegetation and land cover and land use conditions as it would provide much more comprehensive data that can be used to support the vulnerable communities in sub-Saharan West Africa whose livelihoods rely on ecological resources.