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Behavioural, Ecological and Socio-economic Tools for Modelling Agricultural Policy

Periodic Reporting for period 1 - BESTMAP (Behavioural, Ecological and Socio-economic Tools for Modelling Agricultural Policy)

Periodo di rendicontazione: 2019-09-01 al 2021-02-28

BESTMAP (Behavioural, Ecological & Socio-Economic Tools for Modelling Agricultural Policy) addresses the topic RUR-04-2018 “Analytical tools and models to support policies related to agriculture and food”, the “Socio-economic science and humanities” cross-cutting priority and the “Rural Renaissance” call.
Around 40% of European Union land is agricultural. Processes like land-use intensification and climate change threaten the ecosystem services provided by these agro-ecosystems. Policy makers at all levels face the challenge of enhancing agricultural sustainability whilst maintaining farmers’ livelihoods. Current policy impact assessment models (PIAMs) used by the Commission largely ignore the complexity of farmers’ decision making, and existing models focus on economics, mostly ignoring policy impacts on rural natural, social and cultural assets.
BESTMAP is developing a new modelling framework utilising behavioural theory and linking economic modelling with individual-farm Agent-Based Models (ABM). These new modular and customizable tools will allow BESTMAP to quantitatively model, monitor and map policy change impacts on the environment, biodiversity, ecosystem services, and socio-economic conditions.
BESTMAP aims to improve and contribute to existing tools used by the Commission, national and regional decision-makers and expert personnel. Finally, BESTMAP will use a range of external communication and dissemination activities to build capacity for researchers, national and EU Directorate-General staff and parliamentarians, to model policy impacts and improve policy design and monitoring.
Work Package 1, ‘Project management’, consortium coordination team established, project manager hired, project website launched, project communication system set up (G-Suite for Education), versions 1 and 2 of data management plan completed, guidelines and protocols harmonizing activities across case studies completed, first version of exploitation plan including business model and market analyses completed.

Work Package 2, ‘Co-design and co-development’, conceptual framework design & architecture completed, telephone interviews with Brussels-based stakeholders conducted, initial version of DART-BIO outputs for one baseline and one policy scenario completed.

Work Package 3, ‘Farming System Archetypes’, farmer interview campaign conducted, developed prototype Farming System Archetypes (proto-FSAs), final FSA mapping underway, directives for modelling approach written, modelling workshop with DGs and JRC held, case study base layer and European base layer set up, ecosystem services (ESS) modelling underway.

Work Package 4, ‘Agent-based modelling and analysis’, commenced July 2020, first deliverables due January 2022. Preliminary agent-based modelling and development of methodology underway.

Work Package 5, ‘Upscaling’, commenced November 2020, first deliverables due October 2021. Work on European ABM and upscaling ESS models underway. Planning for remote sensing mapping of FSAs underway.

Work Package 6, ‘Capacity building and dissemination’, communication tools produced including project visual identity, communication materials and templates, project website, social media profiles. Plan of engagement written and updated, communication & dissemination plan written, analysis of the needs and capacity of policy makers, expert practitioners and other modellers conducted.

Work Package 7, ‘Ethics’, has delivered all three ethics requirements of the project.
A farmer interview campaign was conducted in Spring 2020. We held 124 semi-structured interviews, with a stratified range of farmer types, across the 5 case studies that consisted of two parts, a qualitative interview, and a quantitative questionnaire. The interviews focused on farmer’s motivations for participating in agri-environmental schemes and found that overall, the relative importance of economic aspects is very high and that farmers tend to consider AES on land that is less productive. Analysis of the data continues.

BESTMAP also conducted 12 in-depth interviews with Brussels-based stakeholder groups representing a cross-section of agents in the European agriculture sector. Feedback shows support for a move away from direct payments and income support to compensating only public goods, whilst increasing food pricing to reflect real costs. Respondents also expressed the need for policy that considers the food system as a whole with less uncertainty and better understanding of trade-offs, especially with regard to land use. A report on these interviews has been created and will be made available to the Commission and Directorate-Generals.

In order to help addressing the current lack of knowledge on new CAP policy impacts on the environment and society, BESTMAP has quantified a first version of a baseline and a policy scenario (the Renewable Energy Directive RED2) using the DART-BIO model, which carries forward current trends and policies until 2030 by calibrating the gross domestic product and CO2 emissions. The results show that, given current fossil fuel prices, biofuels are not cost competitive, and without policies, such as the RED2, biofuel consumption in the EU would return to a negligible level.

To address the current disparity and lack of homogenization in geospatial data sources, which are distributed in different formats and lack a consistent temporal and spatial reference system, BESTMAP has combined multiple data sources including IACS and LPIS to create a Case Study base layers and a European base layer. This will ensure unified use and analyses across all CS and at European scale.

BESTMAP have also developed an approach for identifying ‘farming system archetypes’ and mapped these across the case studies. This is a novel development of the existing ‘land systems’ approach and will serve predominantly for linking and upscaling the CS results at the European level.
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