As part of its matchmaking approach that devises data-driven early action food security solutions for dry areas, the Jameel Observatory supports researchers looking for answers that pastoral communities can use to overcome climate changes. Observatory Students combine their academic studies with field work to produce development-oriented resources with practical applications.
John Mutua is a PhD student at the University of Edinburgh’s School of Geosciences and the Global Academy of Agriculture and Food Systems. He joins the university after working as a geospatial analyst at the Alliance of Bioversity International and CIAT in Kenya where he worked on various research topics including climate risk assessment, land degradation assessment, and and land cover mapping. He brings a good understanding of crop and livestock production systems, their functioning and response in East Africa, and how they can be transformed to be more productive and have a lower carbon footprint. In his previous job, he developed a wide range of forage suitability maps and contributed to a new method to map and assess heat stress in pigs. The results have been used to inform climate change policy for pigs in Uganda. Most importantly, the method has been further refined and applied in West Africa and across East Africa to highlight heat stress ‘hot spots’ for six livestock species.
John’s research focuses on how spatial analysis and environmental modelling can contribute to decision making in agri-food systems – specifically livestock nutrition and greenhouse gas (GHG) reduction assessment. Supported by the United Kingdom’s Engineering and Physical Sciences Research Council and the Food and Agriculture Organisation of the United Nations as well as Edinburgh University and the Jameel Observatory, he will combine earth observation data with local ground truth data to better estimate the composition of livestock feeds in East Africa. While livestock are a source of GHG emissions, the extent of their emissions is contested and often based on inaccurate estimates of feed composition. The aim is for outputs of this work to feed into the Global Livestock Environmental Assessment Model (GLEAM) as a first step towards revising the feed basket component.
Supervised by Gary Watmough, John’s research will build on existing work on feed availability in East Africa, exploring how machine learning algorithms and freely available satellite imagery can help generate predictions of livestock feed composition and its seasonal variability in East Africa. Combining earth observation with local survey data will provide a more holistic and wider-scale overview of the landscape that can help livestock keepers make real-time decisions about their livestock. Adding satellite data to conventional, but labour-intensive, survey techniques will produce intelligence that can be fed into early warning systems and used to help local communities and policy makers understand, and plan around, weather and climate trends and their implications for the livestock that most people in dry areas depend on for food security, nutrition and livelihoods.
Follow John on Twitter: @JohnYumbya
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