Chapter 4

Conclusions and caveats

Table 33 presents an overview of the nutrient balance of each of the cases reviewed in the preceding chapters. All the nutrient-balance methodologies used the sum of all inputs minus the sum of all outputs. Most approaches were derived from Stoorvogel and Smaling (1990), with five Inflows and five outflows. Nutrient balances have become spatially explicit at the macrolevel, the focus is on farming systems at the mesolevel, and participatory approaches and niche management have been introduced at the microlevel.

TABLE 33
Overview of nutrient-balance studies

* Nutrient balance ranged from -14 kg NPK/ha/year for South Africa to -136 kg NPK/ha/year for Rwanda

Macrolevel

At macrolevel, the nutrient-balance model raises awareness of soil fertility problems, indicates areas with nutrient depletion or accumulation, and gives a quantified picture of the nutrient flows. A macrolevel assessment can provide a basis for selecting areas for soil fertility improvement. A mesolevel study can then identify specific constraints, and it should reveal the best options.

Mesolevel

The introduction of mesolevel studies adds value to existing national- and farm-level approaches. Provided that sufficient data are available, mesolevel nutrient balances can be compiled properly. Mesolevel results provide information that cannot be deduced from macrolevel and or microlevel studies. The mesolevel offers a suitable entry point for policy-makers and private sector intervention, where macrolevel and microlevel are not appropriate for policy-making at the subnational level. Further methodological refinements are feasible through making them more spatially explicit (accounting for spatial variation in soils and climate) and through improving procedures for calculating nutrient flows and quantifying soil nutrient stocks.

Microlevel

Many microlevel soil fertility studies have examined different regions and farming systems using different approaches and focuses, such as participatory approach, socio-economic household groups, economic aspects and INM techniques. With the NUTMON-toolbox, a standardized approach for nutrient monitoring has been developed. This enables comparisons between different studies. Microlevel studies provide a picture of the variation within a mesolevel unit. Relevant management factors can be included, and monitoring can check whether changes in nutrient management have a bearing on the nutrient balance and farm income. A participatory approach for the development and validation of locally specific packages should be promoted. It needs to combine examples of soil fertility management technologies with socio-economic and institutional measures that improve the adoption rate of the technologies.

Caveats

Validation

A major issue is the lack of sufficient validation and high uncertainties of the different nutrient flows. Large-scale and data-demanding studies are difficult to validate because of the large areas and the large amount of different data involved. This makes validation in the field difficult and expensive. It is not possible to validate all the nutrient flows at the macrolevel because this would require a massive number of samples. It might be possible to validate each nutrient flow at the microlevel, but these validations would then need to be scaled up to the mesolevel and the macrolevel. Other large-scale studies in the context of climate change and biodiversity research have similar validation problems. Some nutrient flows, such as leaching, can be validated by experiments. However, other flows, such as erosion or mineral fertilizer application, are more difficult to validate. As it is almost impossible to validate the whole nutrient balance, one can choose to validate only those specific flows that are deemed most important. For example, one can measure erosion in the field where this is one of the main losses according to the nutrient balance. These field observations and measurements should be performed according to a sound sampling scheme. Connecting validations of process research, e.g. studies of N₂O losses, to system research, such as this study, is both practical and feasible.

Gaps

Although the nutrient balance includes the most important nutrient flows, it fails to take some aspects into account. At the macrolevel, it does not incorporate large-scale processes such as forest burning and river-basin sediment transport. At the livestock level, it does include urine specifically although its nutrient content is quite different from that of dung. In addition, nutrient losses of urine are very high because of leaching and volatilization. Some other aspects, although not directly linked with the nutrient balance, can be of importance for the functioning of the whole agro-ecosystem. For example, below ground biodiversity has a direct effect on soil structure and the release of nutrients from organic material. Off-site effects, such as sedimentation into reservoirs and excessive nitrate leaching to groundwater, can also be related to the nutrient balance. Depending on the definition of the system, transnational imports and exports of products can be important flows in the nutrient balance, e.g. export of cash crops and import of fertilizers. Economic dynamics, such as the withdrawal of subsidies or trade liberalization effects, provide the all-important context that needs to be known before suggesting any improved nutrient management. Finally, it may be necessary to examine nutrients other than N, P and K, such as Ca and S, or organic carbon to link up with carbon sequestration research groups.

Usefulness for policy-makers

It is important that policy-makers be aware of any gaps in the nutrient balance, so they know what the limitations of the nutrient-balance model are. This raises the question of whether present outputs can serve as tools for policy-makers or whether further research is required. The nutrient-balance model proved to be a useful indicator for informed policy-makers, but the results as presented so far offer no entry points for intervention. The model raises awareness of soil fertility problems, indicates areas with nutrient depletion or accumulation, and gives a quantified picture of the nutrient flows at the macrolevel. At the mesolevel, it is possible to: (i) identify specific constraints; (ii) use quantified nutrient flows for planning purposes; and (iii) extrapolate results to other similar areas. Furthermore, outcomes might convince policy-makers to make action plans to improve soil fertility.

Presentation of outcomes

Model results expressed in terms of kilograms of nutrient per hectare are not very meaningful for policy-makers. They prefer outcomes expressed in terms of yield loss or in monetary values. The nutrient balance should have links to other tools and data in order to make it more useful. Combining a simple soil fertility/crop production model, such as QUEFTS (Janssen et al., 1990), with the nutrient balance makes it possible to express nutrient depletion in terms of yield loss. Other attractive indicators to possibly attach to the nutrient flows and balance are the nutritive value of diets, food and cash needs, and equity indicators. Other options are to make use of decision-support systems and scenario studies. One way of making the nutrient-balance model more interactive is to link it to a model such as that of the conversion of land use and its effects (CLUE) (Veldkamp and Fresco, 1996), which simulates land use changes and its effects. It is also possible to combine the results with other GIS data, such as food security or poverty maps.

Specific problems for each scale level

In nutrient-balance calculations, each scale level has its own specific problems. At the macrolevel, the most important problems are: data quality; map interpretation; resolution differences; and groundtruthing. Intensive field checks in accordance with a sound sampling scheme can provide a partial solution. Soil properties and nutrient stocks might also be collected with new techniques for rapid estimation by reflectance spectroscopy (Shepherd and Walsh, 2002). At the mesolevel, the main problems are: lack of spatial data; incorporation of different management systems; and the absence of socio-economic explanatory factors, e.g. credit facilities and marketing. Spatial data will be increasingly available in the future. A classified satellite image and a DEM will improve the mesolevel nutrient balance significantly. At the microlevel, much research has already been done. The NUTMON-toolbox is a useful application, which also includes the monetary part. The issues at this level are: how to deal with diversity between and within farms; how to incorporate INM and integrated soil fertility management techniques; and how to scale up results. Possible options are: stratification in sampling methods; INM techniques in farmer field schools; and the use of GIS for upscaling.