Mapping Poverty and Livestock in the Developing World
Philip K. Thornton, R.L. Kruska, Norbert Henninger, Patti Kristjanson, Robin S. Reid, F. Atieno, Angela Odero, T. Ndegwa
Abstract
Philip K. Thornton, R.L. Kruska, Norbert Henninger, Patti Kristjanson, Robin S. Reid, F. Atieno, Angela Odero, T. Ndegwa
Abstract
This study produces a set of maps and tables that locate significant populations of poor livestock keepers and has broadly assessed how poor livestock keeping populations are likely to change over the next 3-5 decades. The outputs of the study are based on innovative analysis using new global data sets. This includes mapping a global livestock production system classification, using definitions based on agroclimatology and human population density; mapping human population growth scenarios to 2050 for sub-Saharan Africa (SSA), Central and South America (CSA), and Asia; development of climate surfaces for Africa to 2050 as predicted from the downscaling of results from coarse-resolution global climate change models; mapping the livestock system classification for Africa to 2050 as driven by predicted changes in human population and climate; mapping district - and province - level poverty data for Kenya, Tanzania and Uganda as an example of high-resolution poverty data for more effective targeting of development assistance. Major conclusions of the analysis are outlined at the end of the document.
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This study produces a set of maps and tables that locate significant populations of poor livestock keepers and has broadly assessed how poor livestock keeping populations are likely to change over the next 3-5 decades. The outputs of the study are based on innovative analysis using new global data sets. This includes mapping a global livestock production system classification, using definitions based on agroclimatology and human population density; mapping human population growth scenarios to 2050 for sub-Saharan Africa (SSA), Central and South America (CSA), and Asia; development of climate surfaces for Africa to 2050 as predicted from the downscaling of results from coarse-resolution global climate change models; mapping the livestock system classification for Africa to 2050 as driven by predicted changes in human population and climate; mapping district - and province - level poverty data for Kenya, Tanzania and Uganda as an example of high-resolution poverty data for more effective targeting of development assistance. Major conclusions of the analysis are outlined at the end of the document.
Key concepts: Livestock, Poverty, Geography, Development economics, Political science, Economics, Economic growth, Forestry