The maps in Section 2.4 are based on the assumption that the national poverty rate is equally applicable across all systems or areas within the country. With a breakdown by livestock production system, it is possible to show numbers of poor by livestock production system, but this is only one step towards representing the distribution of poverty among livestock keepers. Poverty rates clearly differ within and between production systems. The proportional importance of livestock to household income streams differs from one culture to another and within production systems. For example, mixed crop–livestock farmers have multiple opportunities for obtaining income from a variety of sources; thus, income from livestock probably contributes a smaller proportion to their household food basket. By contrast, most pastoralists depend on livestock for a large proportion of their income, although this is changing. Thus, any map of poverty among livestock keepers needs to account for the importance of livestock to income at the household level.  At the national (or even regional) level, methods exist to deal with measurement of such issues. Some of these are illustrated with respect to Kenya in Section 3 below. At the global level, information on the importance of livestock to rural livelihoods is difficult to find. There are various approaches that could be taken to modify Map 7a, Map 7b, Map 7c and Map 7d to show differential poverty rates by production system. 
     One approach would be to use the density of TLUs per person as a proxy for the importance of livestock to income at the household level (this is shown globally in Map 8). The logic here would be that higher livestock numbers per person indicate that livestock are more important to household incomes, within a particular system. This assumption has some obvious flaws, including the possibility that areas with more livestock per person are areas that have more income opportunities of all kinds. However, an overlay of TLUs per person with the poverty map would give rise to differential poverty rates by system that could give an indication of numbers of poor livestock keepers. 
     A second approach would be to estimate the proportional importance of livestock to incomes in the 11 different production systems, and use this to weight the poverty rate by system. Information on this is very scanty, however; the approach using TLUs per person seems more objective, unless databases can be built up with country-level systems poverty rates (as for Kenya, see Section 3) from a wide variety of countries to the point where extrapolation could be done with some confidence. 
     A third approach would be to weight poverty rates by system with some notion of ‘vulnerability’ that might be related to such factors as, for example, rainfall variability, access to infrastructure and markets and soil degradation. The assumption here would be that areas with higher intrinsic vulnerability would be associated with higher poverty rates. The World Resources Institute (WRI), for example, is currently developing a global vulnerability layer that could possibly be used in this way in the future.
     A fourth approach is to use differential poverty rates associated with particular production systems defined in some way. Simply as an illustration of what could be done, and to highlight the need for future work on this element of the analysis, Map 9 shows (ostensibly) numbers of ‘poor livestock keepers’ by system by country (the numbers are tabulated by system in Table 7). These data were derived by applying differential proportions of poor livestock keepers as a percentage of the total poor by livestock production system. We used the revised estimates of the number of poor livestock keepers globally from Livestock In Development (LID, 1999). Using these data for extensive graziers (which we equated with the three livestock only, rangeland-based systems—LGA, LGH and LGT), poor rainfed mixed farmers (the three mixed rainfed systems, MRA, MRH and MRT), and landless livestock keepers (into which category we lumped all the remaining systems), we calculated global poverty rates for these systems using the data in Thornton et al. (2000), and then derived the proportion of the numbers of poor people in each system who are livestock keepers (76% for livestock-only systems, 68% for mixed rainfed systems and 26% for the remainder). These proportions were then applied to the numbers of poor in each system using the World Bank rural poverty rates (Table 6b). These numbers are very much illustrative only, but do show the type of analysis that is needed to refine the global poverty maps for maximum utility. 
     Map 9 indicates that the density of poor livestock keepers defined in this way is particularly high throughout SA (India, Pakistan and Bangladesh) and in parts of SSA (including Nigeria, Ethiopia, Uganda, Burundi, Rwanda, Malawi, and some systems in Kenya, South Africa and Niger, for example). These high densities appear to occur mostly in the mixed systems—these are the mixed irrigated  systems in parts of SA, and the mixed rainfed systems in parts of India and in most of SSA.

<< Previous    Next >>