H2020 BESTMAP Project: Behavioral, Ecological, and Socioeconomic Tools for Modeling Agricultural Policies

Work Package 1, “Project Management,” focused on monitoring project progress and risk management and mitigation. The data management plan was regularly updated, and model codes/results, as well as results of modeling exercises and analyses, were stored in Zenodo, GitLab (https://git.ufz.de/), GeoNetwork (https://geonetwork.ufz.de), and the project dashboard. Guidelines and protocols were created and developed to harmonize activities across the case studies (CS). Work Package 1 also ensured the completion of exploitation activities, including the approval of a Memorandum of Understanding (MoU) for the future exploitation of the experience and modeling tools developed during the project. Work Package 2, “Co-design and co-development,” was responsible for developing a co-design approach with stakeholders to identify relevant policy scenarios for ECs to model their impacts. Five agri-environment schemes and their implementation/non-implementation scenarios were selected. The sessions were also key to co-designing the interactive dashboard (https://www.ogc.grumets.cat/bestmap/) with future users, by carrying out a user requirement of the functionalities that stakeholders would need. In addition, an economic reference scenario was developed using the CGE DART-Bio model, which focused on synergies between the EU Renewable Energy Directive (RED 2) policy, global biofuel quotas, and international climate policies under the Paris Agreement. The study revealed that the implementation of biofuel policies in non-EU regions leads to an overall shift toward more cropland used for biofuel feedstock, which affects pastures and crops not used for biofuel production. This task also highlights the fact that climate policies influence land-use changes differently depending on whether they target CO2 emissions or all greenhouse gas emissions. Work Package 3, 'Farming Systems Archetypes' (FSA), was responsible for collecting all the geospatial data needed to create the models. A suite of customizable, open-source, and spatially explicit biophysical models was developed and/or adapted to estimate the effects of selected Agri-Environmental Practices (AEPs) on ESSs. The models were used to map ESS provision, biodiversity, and socioeconomic outcomes under different AEP adoption scenarios across the five project ESCs. WP3 also developed AAFs, a categorization of farms according to their specialization and economic size, which were mapped for each ESC and can be consulted on the dashboard. Work Package 4, “Agent-based Modeling and Analysis,” focused on the development and implementation of ABMs in each SC. The main structure of the ABMs was consistent across SCs, but they were tailored to local specificities due to differences in data availability and existing policies and regulations. The ABMs were applied to different agri-environment scheme (SEA) scenarios to investigate the effects of SEA parameters on SEA adoption rates, compared to current adoption rates. Work Package 4 also examined how SEA adoption drives trade-offs and synergies between SEAs, biodiversity, and socioeconomic outcomes, focusing on two different scenarios, with and without SEAs. Furthermore, Work Package 4 reviewed policy indicators from different sources linked to agricultural practices, and the most relevant indicators were selected and analyzed to determine their degree of association with BESTMAP model outcomes. Finally, Work Package 4 synthesized and compared the main findings of the regional SCs, which served as a basis for the BESTMAP policy briefs. Work Package 5, "Scaling," used SC-level ESS results to predict average farm-level ESS outcomes at NUTS3 level in the remaining NUTS3 regions of the EU and other European countries. Scaling was carried out using European-level environmental and economic predictors, used in metamodels to predict European-level outcomes, determined through cross-regional SC predictions. The European-level asset market model (AMM) predicted AES adoption in the EU using a generalized linear model approach, which showed how such adoption varied across countries. Work Package 5 also piloted a project to investigate remote sensing methods for crop type mapping, crop yield mapping, and plot boundary mapping. The results, in summary, demonstrate the potential of remote sensing techniques to generate complementary datasets for mapping FSA dimensions, but lack precision for metrics such as crop yield or composition. A roadmap for expanding BESTMAP into an operational pan-European modeling platform was developed, in addition to exploring, through pilot analyses, various areas for improvement and future research. Work Package 6, "Capacity Building and Dissemination," addressed integration with other projects by developing an engagement plan to establish a strategic pipeline of relationship-building processes with identified stakeholders, including joint participation in the AGRIMODELS cluster at various events. Project information and results were disseminated through various channels, and policy briefs were also produced, covering proposals for the new EU statistical regulation and the Common Agricultural Policy, along with specific scenarios. Work Package 7, "Ethics," ensured compliance with the project's ethical requirements.