Assessment of population dynamics and forest cover change in Yumbe District, Uganda

Abstract

Sub-Saharan Africa is well endowed with both renewable and non-renewable natural resources critical in supporting several forms of development on the continent. Key among these is natural forest resources. However, the population explosion in sub-Saharan Africa in general and Uganda, in particular, is threatening the survival of these forests due to the associated increasing demand for food, fodder, energy, and land for settlement. The study was conducted in Yumbe district where the forests considered included woodland and bushland since tropical high forests have been depleted or degraded by human activities. We used a predictive model to map future forest cover loss amidst the rapidly increasing population in Yumbe district in Uganda. Specifically, the study analyzed the relationship between population dynamics and forest cover change to predict future forest cover changes. To analyze changes in forest cover, the study utilized Landsat satellite imagery for 1990, 2000, 2010, and 2021; while the population data for the respective years was obtained from the Uganda Bureau of Statistics (UBOS). To explain the role of anthropogenic forces on forest cover change, the study considered different land use types as explanatory variables: planted forests, subsistence farmland, built-up areas, and other land use types. It then explored the interactions between these variables and forest cover change in the study area. Population-forest cover change model was developed to evaluate three decades of population and trends of forest cover to predict forest cover for 2032. The results indicate that in the three decades, the population increased by more than sixfold, and land area under subsistence agriculture, a proxy of population increased by 195.2%, but the forest cover declined by 80.3%. It is predicted that the forest cover will be lost completely by 2032 when the population reaches an estimated 838,078 from the current 657,430 people. This study, therefore, recommends that off-land employment opportunities such as tourism, apiary, transport, and manufacturing industries should be expanded in order to save forest resources from spatially extensive agricultural land uses. Key words: Forest, Forest cover loss, Predictive modeling, Population dynamics, Land use