Agro-ecological indicators of field-farming systems sustainability : 2. Nutrients and pesticides

Evaluation of cropping and farming sustainability can be carried out with direct measurements, simulation models or indicators the latter have the advantage of requiring a small amount of inputs, being fast to calculate and easy to interpret, allowing comparisons in space and time, and representing a synthesis of processes in complex systems. In a previous paper, we proposed a list of indicators related to the use of fossil energy and landscape and soil management. In this paper, we discuss indicators related to the use of nutrients and pesticides. We selected indicators that can be applied on a field and farm scale, based on data obtainable from the farmer and/or from existing agricultural databases; we excluded indicators based on direct measurements. A nutrient balance is the difference between inputs and outputs of a farm or field (surplus if positive, deficit if negative). Its advantage is its simplicity, the relatively small data requirement, the identification of different inputs, and its applicability to different mineral elements. However, nutrient balances do not indicate how much surplus can actually be lost from the system and in which way. The water quality risk indicator integrates the surplus calculated at field level with simple climatic and pedological information. We also describe two nitrogen management indicators that have been proposed for arable crops and grasslands to overcome the limitations of nutrient balances, and the phosphorus management (P) indicator, which compares the applied P amount with the recommended dose, identifying the risks of spoiling non–renewable resources or depleting soil reserves. Compared to nutrients, the use of risk indicators for pesticides is more problematic. As a matter of fact, pesticides show a greater variety of potential effects on human health and on different ecosystems; consequently, the analysis of their potential risk requires very complex and varied procedures depending on the environmental compartment considered (ground water, surface water, air and soil). This has led to the development of several pesticide risk indicators that differ greatly in terms of variables considered, field of activity, scale of analysis and methodologies utilized (interactive decision–tree, risk ratio approach, scoring table, fuzzy system). Some indicators use simple algorithms to estimate the risk, others make use of more complicated models. The simplest and generic indicators require very few data (such as the application rate), but in general they do not consider the fate on the environment and the distribution of the chemicals. On the contrary, more complex indicators require the use of predictive models to evaluate potential exposure of non target organisms to different active ingredients. We present some pesticide risk indicators with different levels of complexity that can be utilized at farm and field level, in order to obtain a picture of the different approaches available in literature and to point out their values and limitations.