A DECISION-SUPPORT MODEL FOR MONITORING NUTRIENT BALANCES UNDER AGRICULTURAL LAND-USE (NUTMON)

A quantitative model of the balance between inputs and outputs of nitr ogen, phosphorus and potassium in African land use systems (NUTBAL) wa s recently developed at two scales: supra-national (38 sub-Saharan Afr ican countries) and regional (Kisii District, Kenya). Calculating inpu ts (mineral fertilizer, organic manure, wet and dry deposition, biolog ical nitrogen fixation, sedimentation) and outputs (removal of above-g round crop parts, leaching, denitrification, water erosion) led to the conclusion that there are considerable net fertility losses in each g rowing period. In this paper, NUTBAL is elaborated into a decision-sup port model (NUTMON) to monitor the effects of changing land use, and s uggest interventions that improve the nutrient balance. As input and o utput determinants cannot all be quantified equally well, the model re cognizes primary data, estimates, and assumptions. The NUTMON determin ants are mostly scale-neutral and can therefore be used to monitor nut rient balances at farm, regional, national and supra-national level. T his is essential since the hierarchical levels interact. A number of r ecent interventions at the regional level (Kisii District, Kenya) are elaborated, including national fertilizer and produce price policies, fertilizer supply in small packages, zero-grazing, agroforestry, soil conservation measures, and increasing fertilizer use efficiency. It is shown that a major nutrient conservation effort in Kisii reduces nutr ient depletion by approximately 50%, but does not entirely redress the N and K balance. To achieve the latter without reducing crop producti on, 75% of the district would have to be converted to a rotation syste m of maize and green manure cover crops, whereas 25% can remain under tea. NUTMON has the potential to become a dynamic tool for land use po licies, geared towards a balanced nutrient status in African land use systems. It can assist decision makers in determining the effects of c uffent and alternative land use scenarios, taking account of both the productivity as well as the long-term sustainability of agro-ecosystem s.