Persistent Vegetation Greening and Browning Trends Related to Natural and Human Activities in the Mount Elgon Ecosystem

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 13; p. 2113
• Main Authors: Wanyama, Dan, Moore, Nathan J., Dahlin, Kyla M.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2020
• Subjects: Agricultural land; Agriculture; bfast; breakpoint analysis; Browning; Carbon; Climate; Climate change; Climate variability; Deforestation; Developing countries; East Africa; Ecosystems; Environmental hazards; Food security; Grasslands; Greening; Land cover; Land use; LDCs; Mann–Kendall; Natural resources; NDVI; Normalized difference vegetative index; Population growth; Precipitation; Principal components analysis; Rainfed farming; Reforestation; Remote sensing; Savannahs; Sen’s slope; Spectroradiometers; Time; Time series; Trends; Vegetation; Vegetation changes; Vegetation index; Uganda; Kenya; East Africa; Mount Elgon
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12132113

Many developing nations are facing severe food insecurity partly because of their dependence on rainfed agriculture. Climate variability threatens agriculture-based community livelihoods. With booming population growth, agricultural land expands, and natural resource extraction increases, leading to changes in land use and land cover characterized by persistent vegetation greening and browning. This can modify local climate variability due to changing land–atmosphere interactions. Yet, for landscapes with significant interannual variability, such as the Mount Elgon ecosystem in Kenya and Uganda, characterizing these changes is a difficult task and more robust methods have been recommended. The current study combined trend (Mann–Kendall and Sen’s slope) and breakpoint (bfast) analysis methods to comprehensively examine recent vegetation greening and browning in Mount Elgon at multiple time scales. The study used both Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data and attempted to disentangle nature- versus human-driven vegetation greening and browning. Inferences from a 2019 field study were valuable in explaining some of the observed patterns. The results indicate that Mount Elgon vegetation is highly variable with both greening and browning observable at all time scales. Mann–Kendall and Sen’s slope revealed major changes (including deforestation and reforestation), while bfast detected most of the subtle vegetation changes (such as vegetation degradation), especially in the savanna and grasslands in the northeastern parts of Mount Elgon. Precipitation in the area had significantly changed (increased) in the post-2000 era than before, particularly in 2006–2010, thus influencing greening and browning during this period. The greenness–precipitation relationship was weak in other periods. The integration of Mann–Kendall and bfast proved useful in comprehensively characterizing vegetation greenness. Such a comprehensive description of Mount Elgon vegetation dynamics is an important first step to instigate policy changes for simultaneously conserving the environment and improving livelihoods that are dependent on it.