ARPHA Preprints, doi: 10.3897/arphapreprints.e115387
D3.5 Farming System Archetypes for each CS
expand article infoFanny Langerwisch, Tomáš Václavík‡, Marek Bednář‡, Guy Ziv§, Jodi Gunning§, Arjan Gosal§, Anne Paulus|, Sanja Brdar, Predrag Lugonja, Stefanija Stojkovic, Stephanie Roilo#, Anna Cord#
‡ Palacký University Olomouc, Olomouc, Czech Republic§ University of Leeds, Leeds, United Kingdom| Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany¶ BioSense Institute, Novi Sad, Serbia# Technische Universität Dresden, Dresden, Germany

Corresponding author: Fanny Langerwisch ( fanny.langerwisch@upol.cz )

Corresponding author: Tomáš Václavík ( tomas.vaclavik@upol.cz )

© Fanny Langerwisch, Tomáš Václavík, Marek Bednář, Guy Ziv, Jodi Gunning, Arjan Gosal, Anne Paulus, Sanja Brdar, Predrag Lugonja, Stefanija Stojkovic, Stephanie Roilo, Anna Cord.
This is an open access preprint distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Langerwisch F, Václavík T, Bednář M, Ziv G, Gunning J, Gosal A, Paulus A, Brdar S, Lugonja P, Stojkovic S, Roilo S, Cord A (2023) D3.5 Farming System Archetypes for each CS. ARPHA Preprints. https://doi.org/10.3897/arphapreprints.e115387
Open Access
Abstract
This deliverable provides an overview of the methods and data used for developing the Farming System Archetypes (FSAs) in the five case studies - Humber, Mulde, SouthMoravia, Bačka and Catalonia. Additionally, it discusses limitations as well as problems and presents solutions. The FSAs are a generalized typology of farming systems that are assumed to have similar response to policy change. FSAs are a major component of the BESTMAP modelling architecture because they provide linkages between many aspects of the project, especially connecting the biophysical and agent-based modelling in the case studies (CS), based on local data (e.g. IACS/LPIS, for explanation see Methodology), with the modelling of policy effects at the EU level, based on FADN micro-data within the FADN regions. The FSA framework defines the main farm characteristics determined by two main dimensions: firstly farm specialization and secondly economic size, both calculated and mapped for each farm in the CSs. ‘Farmer agents’ who belong to the same FSA are then assumed to have similar decision patterns regarding the adoption of agri-environmental schemes, based on the relationships revealed in the CS agent-based models.
Keywords
farming, policy, needs, agriculture, environment