UNCERTAINTIES IN INPUT-OUTPUT COEFFICIENTS FOR LAND-USE OPTIMIZATION STUDIES - AN ILLUSTRATION WITH FERTILIZER USE EFFICIENCY

Explorative land use optimization studies using linear programming req uire input-output coefficients of agricultural land use, which are bas ed on insight in the processes involved. However, insight in these pro cesses is not always sufficient, and often information on quantificati on of known processes is too limited to describe adequately all produc tion technologies in the soil and climate combinations that prevail in the region. This results in uncertainties in many coefficients, which might greatly affect the results and conclusions of the study. The cu rrent paper focusses on the problem of these uncertainties in input-ou tput coefficients, using the uncertainty in estimating the fertilizer use efficiency as an illustration. An example of uncertainty due to la ck of knowledge on processes involved is the use of different approach es for estimating fertilizer use efficiency in two land use optimizati on studies. A further problem is uncertainty due to lack of data, this is illustrated with an example from the Atlantic Zone of Costa Rica. Very few data are available to determine fertilizer use efficiency and data from regions with similar soil and climate type are not availabl e either. Data from non-similar regions may not give the right impress ion of the possibilities in the region. Different concepts and sources of information result in different estimates of coefficients, which m ight in turn greatly influence the results of the linear programming m odel. It is therefore concluded that, rather than using one fixed valu e for a particular input-output coefficient, the effect of uncertainty in coefficients on the final results of the model should be examined.