Scaling agroecology for food system transformation in metropolitan areas: Agroecological characterization and role of knowledge in community-supported agriculture farms connected to a food hub in Berlin, Germany

ABSTRACT

We investigated an already existing agri-food network connecting ten regional community-supported agriculture farms with a food hub in the city of Berlin. The overall aim of the study was to conduct an agroecological characterization of the farms by using the Agroecology Criteria Tool and focusing on the role of knowledge (co-)creation and sharing. We conducted walking interviews with ten farmers and applied participatory research techniques. We found that, first, the farmers either have already transformed the farm into an advanced agroecological model (level 3) or are transitioning from organic to agroecological (level 2–3). Second, the interactions between the farms and regional agri-food system actors foster the reconnection between eaters and regional growers (level 4). The actors of this transformation belong, thus, to grassroots self-organized and solidarity-based initiatives, which have built an agroecology-based regional agri-food network. And third, the diversity of activities and formats identified for engaging a broad range of stakeholders provides resources for redefining power relationships and co-creating knowledge. However, there are important barriers that must be addressed to scale this network, such as the lack of structures, platforms and collaborations fostering the knowledge (co-)creation and sharing, access to affordable and secure land, and the lack of governmental support.

GRAPHICAL ABSTRACT

KEYWORDS:

• alternative food networks (AFN)
• local and traditional knowledge
• food system transformation
• agroecology criteria tool
• Berlin-Brandenburg region
• food hub
• living lab

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study is framed within the ‘FOODSHIFT2030’ project, and received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 862716.