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published 108945 1 329986 document 108945 indexcodes.txt text/x-c++ f46ea820efccb419344bdec79dc45041 MD5 14338 2025-02-13 07:15:52 https://pure.iiasa.ac.at/id/eprint/20402/2/indexcodes.txt 20402 2 2 text/x-c++ other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/108944 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/108944 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/108944 108949 2 329990 document 108949 small.jpg image/png e9a58afdbb580c4a4c3c075d25673b2a MD5 1839 2025-02-13 07:16:31 https://pure.iiasa.ac.at/id/eprint/20402/6/small.jpg 20402 6 6 image/png other Thumbnails conversion from text to thumbnail_small en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/108944 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/108944 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/108944 archive 353 disk0/00/02/04/02 2025-02-13 07:07:47 2025-02-13 07:07:47 2025-02-13 07:07:47 article show Krisztin T. 2088 0000-0002-9241-8628 van Dijk M. 2147 0000-0002-5207-7304 Piribauer P. pub BNR IBF Livestock distribution, INLA models, Climate resilience, Household surveys, African agriculture 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 km2. 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. 2025-06 published Elsevier doi:10.1016/j.envdev.2025.101141 167 2911 public Environmental Development 54 e101141 TRUE 2211-4599 no info:eu-repo/semantics/article