To assess the potential impacts of Mixed Farming and Agroforestry Systems (MiFAS) at the landscape scale, we analyse selected case studies from two perspectives: bottom-up and top-down.

The bottom-up approach considers a landscape as formed by farmers and their interactions among themselves and other actors. Indeed, farmers exchange feed, manure, and even information: therefore, even if single farms are specialized, the interactions among them can make the landscape mixed. Once these interactions are understood, a so-called ‘agent-based’ model is developed to provide new insights into landscape-level efficiency and resilience. Dynamic simulations of the agent-based approach help to identify the roles of the farms in the landscape, e.g. the most vulnerable farms in the landscape (i.e. the ones more at risk of nitrogen accumulation), or can show the importance of developing connections for increasing landscape efficiency and resilience.

The top-down approach considers a landscape as a set of different land uses and aggregated variables. It draws on EU EUROSTAT and FADN data to identify the regions in Europe most adapted to mixed system (greatest existing mixed farming and highest potential for developing it). Through this approach farm or regional typologies are constructed, based on land cover variables (e.g. percentage of grassland or maize fodder cultivation in a region), livestock density (e.g. number of cattle per surface unit), or other types of variables (e.g., average size of the farm).

All the above bottom-up and top-down results will be compared for the selected MIXED networks, with lessons to be learned for the upscaling and generalization across Europe. This landscape modelling work will be complemented by a review of relevant literature and project studies addressing mixed systems.

The landscape level research will deliver:

• a literature study and review of relevant research projects addressing MiFAS
• a report with a description of a graph-based modelling approach for farm interactions
• a report on the potential for expansion of mixed farming in European regions
• a Landscape scale impact assessment and solution scenarios for resilient mixed farming systems

☘️ Mixedness at the level of landscape requires interactions among farmers

At the landscape level, specialized farms can contribute to nutrient recycling and integration if they interact in some way with other specialized – complementary – farms (Martin et al., 2016). For instance, the exchange of manure between livestock farmers and feed between crop farmers exemplifies how interactions can promote nutrient recycling and integration among landscape components.

☘️ It is important to note that not all the interactions lead to mixedness

Not all interactions lead to mixedness. Some interactions are dedicated to improve food productivity but their benefit for landscape resilience need to be assessed.

☘️ There are different types of interactions and among the case studies of the project. An inventory was made:

• Exchanges between specialised crop and specialised livestock farmers in the form of feed/straw-vs-manure exchanges (FR, UK, NL). This helps regional self-sufficiency, reduction of imported feed and synthetic nitrogen; local closure of nutrient cycle.
• Livestock transfers from one place to another, so that animals benefit from better nutritional/climate conditions in certain periods of the year and provide benefits (i.e., pasture maintenance, weed control, nutrient recycling) (PT, UK).
• Other types of interactions: e.g. parcel exchanges in NL for optimizing rotations, collaboration between diversified farms with agro-tourism facilities in RO.

☘️ The main importance of intermediaries and cooperatives

Our analysis over the different case studies and the more in-depth analysis in the Ariège (FR) case study revealed that a factor encouraging interaction is the need for farming diversification, improve the quality of the production and engage into business partnership. These interactions are often informal relationships evolving into long-term partnerships. The lack of formal structures can sometimes create challenges in terms of scalability and resilience.

☘️ Going mixed at the level of landscape poses challenges

In the case studies, bureaucratic constraints and regulatory restrictions were consistently identified as major barriers to fostering interactions between farmers. Climate change was mentioned as a barrier for interaction. Indeed, climate events can negatively affect production, leading to a decreased quantity of goods to exchange. Not all areas are equally suitable for MIFAS, it is worth focusing on areas with high potential and avoid those with little potential, these low potential areas are mainly grassland dominated, where other approaches to resilience/diversity need to be looked for.