D3.5 Farming System Archetypes for each CS

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

D2.3 Dashboard design prototype

Dashboards for data visualisation and decision-making are information management tools that visually display, analyse and provide metrics of data, for better decisions and understanding improvement.Dashboards provide critical reporting of spatialised data and associated metrics information and are essential for displaying model results, guiding decisions and better navigating the landscape. The main aim of the dashboards is to quickly gain insights into the most relevant results of the data displayed. The main added value for users is that information is transformed into knowledge which is useful for decisions on policy making

D2.3 Dashboard design prototype

Dashboards for data visualisation and decision-making are information management tools that visually display, analyse and provide metrics of data, for better decisions and understanding improvement.Dashboards provide critical reporting of spatialised data and associated metrics information and are essential for displaying model results, guiding decisions and better navigating the landscape. The main aim of the dashboards is to quickly gain insights into the most relevant results of the data displayed. The main added value for users is that information is transformed into knowledge which is useful for decisions on policy making

D1.1 BESTMAP website and web-based within-project communication system

To promote and disseminate the BESTMAP research across stakeholders and the general public, and to raise awareness of the project findings, BESTMAP launched a website at the initial phase of the project. This report describes in detail the purpose, creation process and content of the BESTMAP website – the project’s key tool for successful dissemination, communication and knowledge transfer. The deliverable also describes the current and future implementation and maintenance of the website

D6.3 Communication Plan and Dissemination Plan

Deliverable 6.3 Communication and Dissemination plan comprises actions, tools and channels to be used throughout the BESTMAP project scope. The purpose of this document is to outline the strategy, to define means of communication, tools and actions that will be done within the BESTMAP project in order to reach a wide range of stakeholders. This plan is a living document and will be officially updated in month 24 (D6.8). The first chapter of the Communication and Dissemination Plan explains the wider context of the project and highlights how the project duration and geographical scope impact the communication and dissemination activities. The second chapter presents communication and dissemination strategy including definition of objectives and target audiences, communication tools and key messages. The third chapter presents AGRIMODELS cluster, while the fourth chapter explains Social Media Strategy. The aim of the fifth chapter is to emphasize the importance of project partners’ involvement in communication and dissemination activities, and the sixth chapter showcases the list of relevant conferences for presentation of the BESTMAP project. Seventh chapter presents an action plan for communication and dissemination activities while a list of references can be found in chapter eight

D6.5 Integration guide for using common CGE/PE models with BESTMAP models

This deliverable report provides an integration guide on how information gained in BESTMAP’s agent-based model can be used in the standard economic model to improve the assessment of agricultural policies in the European Union. First, the models used in the BESTMAP are explained. The integration guide discusses in detail the preconditions and challenges when linking agent-based models with standard economic models such as partial and general equilibrium models. As a result of an expert workshop, six challenges are identified. The report also presents suggestions on how to make use of the finding and presents a way forward to integrate the two types of models

D6.1 Analysis of needs and capacity of different audiences including policy makers, expert practitioners and other modellers

This document has five main sections: the first one, “Developing the needs assessment protocol” which explains how we approached to different stakeholders in order to define and analyse their needs and capacities; the second section contains the report of of the interviews conducted by RISE and present the needs of Policy Makers; section three explains the needs of expert practitioners identified during the online workshop (14th and 15th of July 2020);  section four presents the needs of biophysical modeling community and section five explains the needs of ABM modellers identified from recent scholarly workshops. The results of this analysis will be taken under consideration and co-design and co-development processes

D1.2 Data Management Plan

This document is the first version of the Data Management Plan of the H2020 BESMAP project. The Data Management Plan is intended as a living document and updated versions of this document will be produced in month 18 (D1.4) and month 36 (D1.6). The scope of the Data Management Plan is to describe the data management life cycle of all data sets that will be collected, processed or generated by the BESTMAP project. This document outlines how research data will be handled during the BESTMAP project, and after the project is completed. This Data Management Plan describes what data will be collected, processed or generated and what methodology and standards will be applied, whether and how this data will be shared and/or made open, and how it will be curated and preserved

D5.4 Mapping of vegetation indices and metrics, and their utility in FSA mapping at CS scale

This deliverable provides an overview of all work conducted in the context of Activity 5.3.1 (Developing remote sensing indicators) with respect to Farming System Archetype (FSA) Mapping (Task 5.3). This work is based on the FSA definition and mapping in ‘D2.2 - Conceptual Framework’ and ‘D3.5 - Farming System Archetypes for each CS’ and investigates the potential of remote sensing methods to inform different dimensions of FSAs. Findings from this analysis will contribute to the BESTMAP roadmap (Task 5.4). Specifically, methodologies for crop type mapping, crop yield estimation, and field boundary mapping are investigated in different case study regions and their relevance for FSAs are shown

D4.2 Trade-off/synthesis analyses including spatial co-occurrence of ESS / biodiversity socio-economic

This document describes the interrelationships between the ecosystem services, biodiversity and socio-economic outputs modelled in the Work Package 3 (WP3), to identify bundles of co-occurring services. Furthermore, this document presents an analysis of how different types of Agri-Environmental Measures (AEM) drive trade-offs and synergies among different services. The analysis spans two AEM adoption scenarios, one without AEM and one reflecting the current AEM adoption levels, for all five Case Studies (CS) of BESTMAP