GIScience & Remote Sensing (Nov 2021)
Quantitative multi-factor characterization of eco-environmental vulnerability in the Mount Elgon ecosystem
Abstract
The Mount Elgon ecosystem (MEE), an important hydrological and socio-economic area in East Africa, has exhibited significant landscape changes. These are driven by both natural factors and human activities. Yet, the vulnerability of this ecosystem is poorly understood. This study characterizes ecological and environmental (eco-environmental) vulnerability for the MEE using freely available Earth observation, topographic, and socio-economic data. Spatial principal component analysis (SPCA) was used to compute a new eco-environmental vulnerability index (EEVI) by integrating natural, environmental, and socio-economic conditions. The final EEVI was then categorized into five classes (potential, slight, light, moderate, and severe). Temporal principal component analysis (TPCA) was also conducted to identify persistent changes in multi-year variables spanning the period 2001–2018. Further, the precipitation concentration index (PCI) was assessed to evaluate changes in the spatio-temporal distribution of precipitation in the MEE. The study found that EEVI indicates the most aggregate vulnerability on the Ugandan side, especially in savanna regions. Majority of the MEE was moderately vulnerable, and savannas and grasslands constituted the largest proportion of the severe vulnerability class. There was also a marked increase in vulnerability with decrease in elevation. Eco-environmental vulnerability was strongly associated with multi-year variables based on precipitation, temperature, and population density. The study also found that precipitation concentration is amplifying especially in the wet season, thus threatening agriculture and community livelihoods. Areas in the moderate and severe vulnerability classes were identified for prioritized conservation attention.
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