Herding resilience: Surveys and Bayesian spatial models for Africa’s livestock

This paper proposes a novel method for mapping livestock distribution in Africa using the Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA). Using a Bayesian spatial statistical model, we produce maps of livestock distribution at a resolution of 1 km 2 . Our case study in Malawi, covering 2010 and 2019, demonstrates the effectiveness of the method in mapping five livestock species. We compare our results with the Gridded Livestock of the World (GLW) database and use the maps to assess livestock vulnerability to climate-related flood risks under different climate scenarios. This approach provides a rapid, data-rich tool for policy makers to assess climate risks to livestock, which is critical for sustainable agricultural development and environmental management in data-poor regions.