Journal of Fisheries & Livestock Production
Open Access

Many organizations are involved in assembling and disseminating global spatial datasets that can be used for a wide variety of purposes. Such datasets are becoming increasingly important for priority setting and targeting by organizations with a global mandate for agriculture and agricultural research for development, such as the United Nations (UN) Food and Agriculture Organization (FAO), the international centres of the Consultative Group on International Agricultural Research (CGIAR), regional and sub-regional research organizations, and donors who need to target their investments and measure their impacts on beneficiaries.

Currently, one of the biggest gaps in the availability of global datasets is a spatial agricultural systems classification that provides appropriate detail on the distribution of crops and livestock in different places. This publication addresses this gap by bringing together some recent developments in agricultural production system mapping and highlighting some of the difficult problems involved. The work builds on considerable efforts that are made within the past decade and draws upon some case study systems classifications, from which general lessons could also be learned for application on a global scale.

A detailed knowledge of the distribution of livestock resources finds many applications, for example, in estimating production and off-take, the impacts of livestock on the environment, livestock disease risk and impact, and therefore the role that livestock plays in people’s livelihoods. But livestock is not all equal. In different contexts it serves quite different functions, plays different roles in people’s livelihoods, varies in herd structure and breed composition, and is fed and managed in different ways. For most applications some kind of practical stratification is needed: milk yields aren’t an equivalent from cows reared in extensive, low-input pastoral systems as they’re from specifically-bred dairy cows raised intensively.

The map of benefits from trypanosomosis removal in the Horn of Africa can assist decision-makers to prioritize interventions by highlighting areas where the financial return on investment is highest. The study also illustrates how information on livestock production systems can be combined with econometric and agro-ecological modelling in a spatially explicit framework. However, results also demonstrate that global maps of livestock production systems still fall short of distinguishing livestock production systems in sufficient detail for such modelling.