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Doctorat
États-Unis
2021
USING THE “KITE” FRAMEWORK FOR UNDERSTANDING LANDSCAPE CHANGE AND IMPROVING EAST AFRICAN AGRICULTURAL SYSTEMS UNDER CLIMATE CHANGE
Titre : USING THE “KITE” FRAMEWORK FOR UNDERSTANDING LANDSCAPE CHANGE AND IMPROVING EAST AFRICAN AGRICULTURAL SYSTEMS UNDER CLIMATE CHANGE
Auteur : Wanyama, Dan
Etablissement de soutenance : Michigan State University
Grade : Doctor of Philosophy (PhD) 2021
Résumé partiel
The Mount Elgon Ecosystem (MEE), an important hydrological and socio-economic area in East Africa, has exhibited significant landscape changes, driven by both natural factors and human activities, therefore leading to more frequent natural disasters (frequent and extended droughts, floods, and landslides). Yet, few studies have focused on the MEE socio-ecological system ; no comprehensive knowledge exists of how humans and nature interact, at multiple scales, to drive ecosystem-wide landscape changes. This dissertation focuses on three interrelated questions : (1.) What is the nature and magnitude of change in MEE greenness for the period 2001-2018, and how is this change related to long-term trends and variability in MEE precipitation ? (2.) How is ecological and environmental (eco-environmental) vulnerability distributed across the MEE, and what are the major factors driving these patterns ? and (3.) How will the MEE landscape change in the future, and what opportunities exist for streamlining livelihood improvement and environmental conservation efforts ?Study 1 characterized comprehensively, over multiple time scales, recent patterns and trends in MEE vegetation greening and browning. The MEE was found to exhibit significant variability in vegetation dynamics and precipitation regimes. There was persistent greening and browning at different time scales and this change was attributed to both natural factors (including changing precipitation) and anthropogenic factors (especially the vegetation-to-cropland conversion). The study also concluded that MEE precipitation had increased substantially in the post-2000 era, which influenced greening and browning patterns observed in the 2006-2010 period. The integration of Mann–Kendall, Sen’s slope and bfast (breaks for additive season and trend) proved useful in comprehensively characterizing recent changes in vegetation greenness within the MEE. Study 2 examined eco-environmental vulnerability for the MEE using freely available remote sensing (RS), topographic, and socio-economic data.
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