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A new analytical framework of indicators sensitive to crop diversification

DiverIMPACTS aims to develop an adapted analytical framework to evaluate crop diversification sustainability and performance. The final list of the identified criteria and the related indicators is composed of 19 criteria and 29 performance indicators, described in the "indicator fact sheets". As a next step, a tool was developed to facilitate the collection of data needed for the indicator computation across the 25 DiverIMPACTS case studies.

Measuring and benchmarking success or failure is crucial in determining how well food systems are functioning and how effective specific interventions have been. However, classical agricultural productivity measurements do not always accurately portray the benefits and the drawbacks of diversified food systems. These mainly rely on total yields from specific crops, productivity per worker, and/or total factor productivity (total outputs relative to total land and labour inputs) and rarely reflect what matters for the longer term and for society at large.

It is, therefore, important to develop integrated performances indicators, which consider factors such as:

  • the long-term ecosystem health
  • impacts on biodiversity and the provision of ecosystem services
  • total resource flows
  • food and nutritional quality and security
  • economic viability of farms with respect to debt and climate shocks
  • overall impacts on livelihoods and equity

Accordingly, the overall goal of the DiverIMPACTS work package 4 is to conduct a sustainability assessment of crop diversification schemes, at the field, farm, value chain and territory levels, using a range of improved indicators and adapted multi-criteria assessment methods. The impacts of diversification will be evaluated by implementing already existing multi-criteria methods and expanding them to fully capture the different impacts of diversification in time (from single year to rotation) and space (from field to territory). Indicator choices within the different methods are made to ensure the assessment results are comparable in a multi-level analysis.

Specifically, the work package develops an adapted analytical framework of indicators sensitive to crop diversification, which are able to evaluate potential synergies and trade-offs of complex agricultural systems at different scales. At each level, subsets of indicators sensitive to diversification have been selected, following both a top-down and a bottom-up approach, mobilising the scientific community in interaction with the actors who operate within the project consortium.

The final list of the identified criteria and the related indicators is composed of 19 criteria and 29 performance indicators and is presented in Table 1. In particular, identified criteria were selected to cover the following sustainability dimensions: 6 criteria for the economic pillar, 11 criteria for the environmental dimension, and 2 criteria for the social dimension. Each criterion was matched according to both the expected impacts of the DiverIMPACTS project and the relative SAFA theme/sub-themes.

Each indicator is accompanied by a descriptive factsheet, which provides a wide range of information, including instructions for the specific indicator computation, some suggestions and recommendations for its use and the most pertinent literature references (see "Further information" below). As an example, factsheets about Crop Diversity Index and Short food supply chain and local distribution are available on Zenodo. 

This set of indicators will be used for the evaluation of the economic, social and environmental sustainability performance of the diversified agricultural strategies implemented in case studies selected by the DiverIMPACTS project and located across Europe.

    The DiverIMPACTS team has now developed a spreadsheet tool to collect data across the different case studies. This tool will facilitate the collection of the data needed for the indicator computation by the case study teams. It will also allow the data to be stored securely and checked for errors before it is used in the assessment. In order to demonstrate its functioning and to provide some preliminary results to the case study teams, the spreadsheet also allows some of the indicators to be automatically calculated.

    The tool will then be tested by selected case study and field experiment and, on the basis of their comments and suggestion, further improved. Once fine-tuned and finalised, this tool will be made available for the sustainability assessment in all the other case studies involved in the DiverIMPACTS project.

    Further information

    Elements and information reported in the indicators fact sheets

    • the sustainability dimension to which the indicator belongs
    • the indicator type (i.e. causal or effect)
    • the SAFA theme and sub-themes to which the indicator is matched
    • the WP4 internal reference of the indicator that is composed by the ID number preceded by the criterion name to which the indicator is nested
    • a general overview and the objective of the indicator
    • the spatial and the temporal scale to which the indicator is applied
    • the computation and the needed input data for each indicator
    • the reference values (if they are available) for the evaluation of the obtained results. In many case the reference values have to be yet defined as most indicators have never been applied for the crop diversification assessment
    • additional suggestions and recommendations (optional) for each proposed indicator
    • literature references

    Authors

    Stefano Canali, CREA - Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria, Italy
    Christian Bockstaller, INRA - French National Institute for Agricultural Research, France
    Michael Curran, FiBL - Research Institue of Organic Agriculture, Switzerland
    Ileana Iocola, CREA - Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria, Italy
    Christian Schader, FiBL - Research Institue of Organic Agriculture, Switzerland
    Didier Stilmant, CRA-W - Walloon Agricultural Research Center, Belgium
    Florence Van Stappen, CRA-W - Walloon Agricultural Research Center, Belgium
    Frédérique Angevin, INRA - French National Institute for Agricultural Research, France

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