From digital decision-support to policy implementation: An operational framework for agri-environmental schemes

Advances in digital technologies have the potential to address shortcomings of current agri-environment schemes (AES) designed to promote biodiversity conservation and ecosystem health in agricultural landscapes. We identify three major barriers that currently hinder broader implementation of AES: gaps in the current understanding and reflections of locally-specific agro-ecological complexities; spatial scale mismatches between ecological scales of change and individual and administrative scales of implementation; and administrative and logistical hurdles. The Digital Agricultural Knowledge and Information System (DAKIS) is an integrated decision support system (DSS) which generates localised land management recommendations designed to simultaneously support sustainable agricultural production, biodiversity conservation and ecosystem resilience. We here draw on core concepts and components of the DAKIS to formulate a guiding framework for leveraging digital technologies to support the implementation, monitoring and valorisation of sustainable agricultural practices across farm and landscape scales. We present the five central steps of the framework and illustrate its technical application through a case study examining the implementation of the EU's Nature Restoration Regulation in Brandenburg, Germany. We then discuss its advantages and challenges, its potential to overcome multi-scalar barriers to AES planning and implementation, and potential contributions to scaling up sustainable agricultural land management beyond individual farms. • We identify three major barriers to broader uptake of agro-environmental schemes. • We discuss how digital technologies can help scale up sustainable practices. • We present a framework to guide the use of digital tools for environmental policy. • It can streamline monitoring capacities and support complex data interpretation. • Our framework is context-specific and can be applied at different spatial scales.