Using similarity analyses to scale out research findings across Andean watershed basins
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Permanent link to this item: http://hdl.handle.net/10568/44212
Strategic research in agriculture and natural resources carried out by international research centers is deemed a public good and should, sooner or later, be put into the hands of development, governmental and non-governmental organizations. However, this research is usually done at specific pilot sites; there is a greater need to know how representative those sites are in relation to the diversity of contexts in other locations. Such is the case with the Challenge Program on Water and Food (CPWF), a global initiative in water research promoted by the Consultative Group on International Agricultural Research (CGIAR), which is developing and implementing strategic research in nine basins located in the tropics of Africa, Asia and South America. Given that resources are not available to collect data from the whole of the region, pilot sites are needed. It is hoped that research outputs obtained in the selected pilot sites can be the basis for scaling out solutions to similar situations in neighbouring or adjacent areas in same or different basins. In order to contribute to the scaling-out process, different classification methodologies were applied to determine how specific watershed basins are representative of larger areas. The Andean eco-region served as a case study but the methods can easily be applied in other regions. The spatial diversity of biophysical and social conditions across the Andes requires careful site selection. Two methods, a combination of Weight of Evidence (WofE) and Logistic Regression (LR) methods and Fast Cluster analysis, were used to determine the similarity of selected sites with those excluded. A 1-km study resolution covering most of the Andes eco-region included annual rainfall, elevation, length of growing period, land cover, roads and population density as the key variables. Results showed complementarities between the two methods in presenting a probability surface of similarity across the Andes and a clustering of similar sites inside and outside the pilot basins. The output information forms a strong basis for devising plans to scale out research findings from the pilot basins to the whole region.