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The agricultural sector faces serious environmental, social and economic challenges. In response, there has been a proliferation of labels and certifications aiming to ensure minimum farm sustainability performance. Organic agriculture (OA) a prominent example, having received substantial research attention relating to agronomic and environmental performance. While international OA movements are evolving to include broader sustainability aspirations, limited research exists on the social and economic performance of OA. To address this, we conducted a representative farm-based assessment of the Swiss organic sector to evaluate its contribution to sustainability across a wide range of themes based on the FAO Sustainability of Agriculture and Food Assessment (SAFA) Guidelines. We assessed 185 farms using the Sustainability Assessment and Monitoring RouTine (SMART) Farm Tool, chosen through stratified random sampling by farm type and agricultural zone. The results indicate that the Swiss organic sector makes a substantially positive contribution to sustainability, with average scores for theme goal achievement of 62% (Good Governance), 77% (Environmental Integrity), 70% (Economic Resilience), and 87% (Social Well-being). A set of 45 influential indicators (28 for plant production/mix farms and 30 for livestock farms) were selected based on the ability to explain variance (using Principal Component Analysis) and importance for goal achievement. The indicator sets explained a large amount of variation (ca. 70% for both farm types) and revealed a snapshot of management topics relevant to sustainability performance across the sector. These covered socio-political engagement, emissions to air and water, biodiversity, animal welfare, profitability, vulnerability, product quality, local economy, capacity building, and workplace risks. The spread of results across the sample, and comparisons to secondary data (literature and official statistics), revealed the importance of both well-studied issues (e.g., wide spread of energy consumption, variable yield levels/stability, local value chain dynamics) and more novel insights (e.g., strong political engagement, variable price premiums, lacking social security of farming families, insecure land tenure). We propose these topics as a basis for deeper analysis, designing improvement measures and conducting comparative research. This would bring much-needed breadth into the typically narrow debate surrounding the relative merits of OA.

This paper is based on results from the research project UNISECO, which is funded by European Union's Horizon 2020 research and innovation programme under grant agreement No. 773901.We would like to thank all the farmers, farm organisations and stakeholders of the multi-actor platforms of the UNISECO project who contributed to the data collection. We also like to thank Andreas Basler whose corrections improved the comprehensibility of the paper. ; Peer reviewed ; Publisher PDF

The overall aim of the UNISECO project is to provide recommendations on how the sustainability of agro-ecological farming systems (AEFS) in Europe can be promoted. These recommendations build upon multi-actor engagement and practice-validated strategies. The project explores both of these approaches in 15 case studies across Europe. Every case study reflects an AEFS at a certain point of transition towards agro-ecological farming systems. A first step in all of the case studies was to characterize the status quo of the farm systems. Along with other methods to describe the status quo, three decision support tools (DST) were applied in the case studies to provide information on the environmental, economic and social performance of current AEFS. The tools applied were COMPAS, an economic performance assessment tool, Cool Farm Tool, a greenhouse gas inventory tool, and SMART, a multidimensional sustainability tool. This deliverable presents the overall approach taken to assess the farms along the agro-ecological transition, describes the tools, and presents results from their application in the case studies. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N° 773901.