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Background

On 31 October 2017, the European Commission opened a call for projects (RUR-04-2018) aiming to improve the modelling capabilities for agriculture which would ultimately support evidence-based policymaking in the sector. The specific request from the EC was:

Society assigns an increasing number of objectives to the policies influencing the agricultural sector and rural areas that it expects to see fulfilled. Therefore, justifications for policies extend well beyond mere food production. Evidence-based policy making implies the development and maintenance of appropriate instruments for use in the design of these policies and for the monitoring of their effects, taking advantage of new socio-economic approaches and increased possibilities opened up by progress in the ICT area.

Modelling policies dealing with agriculture and the related management of renewable resources at various geographic scales implies the development of a new architecture taking advantage of progress in modelling approaches and ICT. Given the focus on local effects of global events and EU policies, new approaches should take into account the individual decision-making unit (e.g. agent-based or machine learning-based approaches). Modelling will include such aspects as the environmental and climatic impacts of farming, delivery of ecosystem services modelling of aspects ranging from product / sector to farming systems, structural change including the transfer of production factors such as land, the integration of agriculture in rural society and will allow the establishment of links with biophysical models and geo-referenced datasets. Proposals will develop modelling at various geographic scales – from regional to global. They will build a highly modular and customisable suite of tools which will allow flexible use and further improvements as needs arise.

 

The projects

As a response to this call, three projects proposed innovative approaches to increase modelling capabilities in the agriculture sector. These projects have coordinated together forming the AGRIMODELS cluster in order to coordinate the potential synergies between them. Please find below the description for each one of them.

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Events