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2009
- handle: 10670/1.i8qphs
- hal: hal-00455433
- doi: 10.1016/j.jenvman.2008.11.030
- IRSTEA: PUB00025369
- PRODINRA: 248450
- WOS: 000266651100006
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jenvman.2008.11.030
info:eu-repo/semantics/OpenAccess
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SOLUTION SPACE MODELLING MULTIFONCTIONNALITE DE L'AGRICULTURE MULTIFUNCTIONALITY MODELISATION POLITIQUE AGRICULTURE POLICY EXPLORATION SCALE -bio]/Agricultural sciences/Agriculture, economy and politicsCiter ce document
J.C.J. Groot et al., « On the contribution of modelling to multifunctional agriculture: Learning from comparisons », HAL-SHS : économie et finance, ID : 10.1016/j.jenvman.2008.11.030
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Résumé
In this paper a set of criteria is proposed for the evaluation of the potential contribution of modelling tools to strengthening the multifunctionality of agriculture. The four main areas of evaluation are (1) policy relevance, (2) the temporal resolution and scope, (3) the degree to which spatial and socio-institutional scales and heterogeneity are addressed and (4) the level of integration in the assessment of scientific dimensions and of the multiple functions of agriculture. The evaluative criteria are applied to the portfolio of modelling approaches developed and applied in a joint project of the French research institute INRA and the Dutch Wageningen University & Research Centre. The CLUE-S model focuses on prediction of changes in multifunctional land-use at regional scale, given a set of predetermined scenarios or policy variants, e.g. for ex-ante policy assessment and initiation of discussions on regional development. The two other modelling approaches are complementary and aim to address multifunctional farming activities. The Landscape IMAGES framework generates a range of static images of possible but sometimes distant futures for multifunctional farming activities in a small region or landscape. It supports the exploration of trade-offs between financial returns from agriculture, landscape quality, nature conservation and restoration, and environmental quality. Co-Viability Analysis generates trajectories of states and farming decisions fulfilling a given set of ecological and productive constraints representing a desired and sustainable future. The three modelling approaches differ in their policy relevance, in the ways that spatial and socio-institutional scales are addressed and in their degree of explicitation of interaction between the various functions of agriculture, but jointly cover most of the desired capabilities for assessment of multifunctionality. Caveats were particularly identified in the integration of the socio-institutional dimension and the related heterogeneity. Although the model portfolio did not completely satisfy the demands of the set of evaluative criteria, it is concluded that, due to their complementarities, in combination the three models could significantly contribute to further development and strengthening of multifunctionality.