Agroforestry systems have multifunctional roles in enhancing agronomic productivity, co-production of diversity of food and non-food products and provision of ecosystem services. The knowledge of the performance of agroforestry systems compared with monoculture is scarce and scattered. Hence, the objective of the study was to analyze the agronomic productivity and economic viability of diverse agroforestry systems in Europe. A network of five agroforestry systems integrating arable crops, livestock and biomass trees was investigated to assess the range of agricultural products in each agroforestry system. Land Equivalent Ratio (LER) was used to measure the agronomic productivity, whereas gross margin was used as an indicator for economic viability assessment. LER values ranged from 1.36–2.00, indicating that agroforestry systems were more productive by 36–100% compared to monocultures. Agroforestry gross margin was lower in Denmark (€112 ha⁻¹ year⁻¹) compared to United Kingdom (€5083 ha⁻¹ year⁻¹) and the crop component yielded higher returns compared to negative returns from the tree component in agroforestry. Hence, the study provided robust field-based evidence on agronomic productivity and economic viability assessment of agroforestry systems in diverse contexts for informed decision making by land managers, advisory services, farmers and policymakers.

Reducing soil tillage can lead to many benefits, but this practice often increases weed abundance and thus the need for herbicides, especially during the transition phase from inversion tillage to non-inversion tillage. We evaluated if subsidiary crops (SCs, e.g., cover crops) can mitigate the effects of non-inversion tillage on weed abundance. Two-year experiments studying SC use, tillage intensity, and nitrogen (N) fertilization level were carried out twice at six sites throughout northern and central Europe. SCs significantly reduced weed cover throughout the intercrop period (−55% to −1% depending on site), but only slightly during the main crops. Overall weed abundance and weed biomass were higher when using non-inversion tillage with SCs compared to inversion tillage without SCs. The effects differed due to site-specific weed pressure and management. With increasing weed pressure, the effect of SCs decreased, and the advantage of inversion over non-inversion tillage increased. N fertilization level did not affect weed abundance. The results suggest that SCs can contribute by controlling weeds but cannot fully compensate for reduced weed control of non-inversion tillage in the transition phase. Using non-inversion tillage together with SCs is primarily recommended in low weed pressure environments.

Background In this study, we introduce the application of ensemble averages, a concept rooted in statistical mechanics, to the analysis of Fuzzy Cognitive Maps (FCMs). This novel approach is employed to investigate stakeholder perceptions of the organic and sustainable food chain across Europe and identify leverage points for its improvement. The FCMs were constructed through workshops held in seven countries participating in the European project Foodlevers, using diverse methodologies to ensure comprehensive and regionally relevant data collection. Methods By leveraging ensemble averages, we aggregate the outcomes of FCMs initialised with random conditions, ensuring robust and stable representations of the systems under study. This approach allows us to mitigate the variability inherent in individual initialisations and highlight the underlying structure and dynamics of the maps. Through this analysis, we identify the key variables and their roles within each country’s food system, providing insights into the factors perceived as most critical by stakeholders for promoting sustainability and organic practices. Results Our findings reveal both commonalities and country-specific differences in the perceived leverage points, reflecting the diverse socio-economic and cultural contexts within Europe. The ensemble averaging method proved particularly effective in achieving consistent rankings of variables, enabling a clearer comparison across the countries. This methodological advancement enhances the utility of FCMs in multi-country studies, offering a reliable tool for analysing complex systems and informing policy interventions. The results contribute to a deeper understanding of the systemic dynamics of the European organic food chain and provide actionable insights for policymakers and stakeholders aiming to strengthen sustainable practices. Conclusion Our study highlights the potential of integrating statistical mechanics techniques with cognitive mapping methodologies to address pressing challenges in food systems research and beyond.