Despite numerous studies demonstrating the positive interactions between ecosystems and agricultural production, a redesign of the agricultural landscape to minimize negative feedback loops has proven difficult. The concept of agroecological resilience offers the opportunity to integrate agricultural production and agroecosystem functions at the landscape level. We used a mixed-methods approach to (i) identify key indicators of agroecological resilience in an intensive, large-scale agricultural landscape in Germany based on semi-structured expert interviews and (ii) quantify agroecological resilience using a participatory expert modeling approach, specifically a Bayesian network (BN). The BN quantifies resilience capacities based on key resilience indicators, taking into account other ecological, social, and economic variables as well as feedbacks between them. We found that transformability can be predicted with a certainty of 63.6 %, while predicting robustness and adaptability is more uncertain. Furthermore, we identified the variable agricultural approach as barrier separating the BN between the socio-economic, cultural and participatory cluster and the conditionally dependent management, landscape, and vulnerability cluster, as well as the resilience key indicators and resilience capacities. Scenario analysis revealed that, in contrast to status quo and sustainable intensification approaches, only an agroecological approach leads to significant changes in the system and improves transformability. Further development into a spatially explicit BN could provide detailed information on the resilience of agricultural landscapes and enable comparisons between regions on a broader scale.

The implementation of Agri-Environment-Climate Measures (AECM), a component of the European Unions’ Common Agricultural Policy promoting sustainable farming practices, is often driven by economic and management factors rather than environmental effectiveness. Agricultural Decision Support Systems (ADSS) could support spatial targeting of AECM, but challenges related to usability, usefulness and interoperability may hinder their adoption.This paper presents a pilot ADSS, the AECM-Navigator, and evaluates these characteristics through stakeholder consultation. The tool enables users to test selected AECM typologies in field plots and reports model-based effects on biodiversity and ecosystem services. The evaluation included identifying ADSS requirements for AECM planning, user testing and a questionnaire.Results suggest that stakeholders found the AECM-Navigator intuitive and easy to use and recognized its potential to support more effective and efficient spatial targeting of AECM, although several requirements were not met. Findings support its iterative improvement to better meet stakeholders’ needs and encourage its adoption.