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ABSTRACT Real life is often too complex to be understood by means of simple measurements or simulations by models. The purpose of indicators is to simplify the system so as to make this reality accessible to the users, in the form of a diagnostic or decision aid tool. These indicators represent a compromise between the scientific knowledge of the moment, the need to be concise, simplicity of use, and the availability of data. A procedure for developing such indicators in 7 stages is proposed. These are always defined according to an objective. They are either measured, estimated, or calculated by aggregation of data. Their values are assessed relative to a reference. We proposed to evaluate their relevance by a “probability test.” The validation of indicators, i.e., the fact that they fulfil the objective for which they were intended, is done through a “usefulness test” by surveys of end-users. Their scientific value stems from the rigour of the procedure and the degree of consensus which is established as to their method of elaboration. Even when user-friendly models will be available, indicators will remain a privileged tool to understand complex systems, for example, to estimate the impact of agricultural systems on the environment.
Girardin et al. (Mon,) studied this question.
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