A geographical information approach for stratifying tropical Latin America to identify research problems and opportunities in sustainable agriculture
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Jones, Peter G.; Robison, Daniel Merritt; Carter, Simon E. 1990. A geographical information approach for stratifying tropical Latin America to identify research problems and opportunities in sustainable agriculture. Centro Internacional de Agricultura Tropical (CIAT), Cali, CO. 33 p.
Permanent link to cite or share this item: http://hdl.handle.net/10568/69770
Over the last 12 years a data base of climate, soils and crop distribution has been assembled for Latin America. Recently, socio-economic variables such as access and populations density and environmental variables such as the location of national parks, biological reserves and indian reserves have been added. Formerly this information was used primarily to make decisions on commodity research. Given the increasing awareness of long-term agroecological and socio-economic problems this database was used to systematize the search for the effective, specific courses of research into more sustainable agriculture. Given the premise that agroecological problems and solution vary with both the physical and social environments, the approach was divided in to phases. Phase I divided the continent into 124 classes in simple climatic and edaphic terms. The resulting classes were then overlaid with rural population density, rural income per capita, access and location of protected areas. Based on pre-determined criteria, a short list of environmental classes were chosen. Phase II involved a systematic assessment of actual land use in each subzone of the six selected classes. Subzones with similar environments and land uses were grouped in agroecological clusters. These in turn were evaluated for relevance to current and future CIAT research. By this method it was possible to quantify pre-determined aspects of sustainability problems based on both environmental and social variables. This formed an immediate basis for deciding between research problems. However, for the long term, it allows systematic comparison between the problems or areas that have researched and other areas with similar environment or land use problems.
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