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Agent-based Modelling of Rangeland Health for Sustainable Dairy Production in Uganda's South-western Cattle Corridor

Agent-based Modelling of Rangeland Health for Sustainable Dairy Production in Uganda's South-western Cattle Corridor

Although milk production is a major source of livelihood amongst cattle keepers in Uganda's south-western (SW) corridor, the productivity is generally low, threatening the enterprise and the people that depend on it. The government of Uganda has recognised the need to enhance production to boost farmers' incomes and increase milk uptake in the next 5 years. Various interventions have been proposed, including: 1) tractor mechanisation, 2) pasture quality improvement, 3) fertiliser application to enhance pasture production, and 4) raising milk farm-gate prices. In this investigation, using a multidisciplinary approach, we propose to construct an Agent-based Model (ABM) premised on real-world bio-physical and socio-economic data, to assess the potential outcomes of these interventions on dairy production in the region. We will establish baselines of rangeland quality with a sample of 80 farms in three districts (in the cattle corridor): Mbarara, Ntungamo and Kiruhura to obtain data on animal breeds and stock, milk production levels, farmer livelihood characterisation, pasture and soil quality, gathered over a period of one year. The analysis will be based on mixed methods: remote sensing and GIS-based computations and rigorous statistics, culminating in the development of the first spatially explicit ABM in Uganda's cattle corridor. The modelling process, including the use of results and model runs will be undertaken in a participatory manner with the selected farmers, to enhance transparency of the model and inform decision making, as well as policy formulation.

Header image: A protoype land-scape model including herbivores (red), and humans, along with dynamic tree cover, grassland and surface water.

This project is supported by a grant from the Cambridge-Africa ALBORADA Research Fund and will run from October 2016 to April 2018