• Energy Research

Crop diversification represents a key lever to support the development of sustainable agri-food systems. Knowledge on trade-offs and carry over effects from different crop diversification strategies is essential to inform agricultural stakeholders of potential costs and benefits. This knowledge is limited by existing data and performance measures predominantly focused on single crops, rather than complete rotations. Moreover, sustainability performance indicators are often used for assessment purposes, rather than supporting stakeholder learning and actions. A new set of 32 indicators was developed to address these needs, and used to evaluate the environmental, economic and social sustainability of the diversified agricultural systems highlighted in the case studies, which are often characterized by data availability constraints. This approach was tested in France, Germany and Italy to determine a critical ex-post diagnosis of the existing systems, and for the assessment of ex-ante innovative scenarios. The results will be used to support these case studies in the identification and design of more sustainable agricultural systems. Although the framework is based on feasible and proxy indicators, the assessment outcomes have allowed local actors to reflect on the effects generated by the implemented crop diversification strategies. Key issues include trade-offs occurring between optimizing economic and environmental performance.

The modeling of land use impacts on biodiversity is considered a priority in life cycle assessment (LCA). Many diverging approaches have been proposed in an expanding literature on the topic. The UNEP/SETAC Life Cycle Initiative is engaged in building consensus on a shared modeling framework to highlight best-practice and guide model application by practitioners. In this paper, we evaluated the performance of 31 models from both the LCA and the ecology/conservation literature (20 from LCA, 11 from non-LCA fields) according to a set of criteria reflecting (i) model completeness, (ii) biodiversity representation, (iii) impact pathway coverage, (iv) scientific quality, and (v) stakeholder acceptance. We show that LCA models tend to perform worse than those from ecology and conservation (although not significantly), implying room for improvement. We identify seven best-practice recommendations that can be implemented immediately to improve LCA models based on existing approaches in the literature. We further propose building a "consensus model" through weighted averaging of existing information, to complement future development. While our research focuses on conceptual model design, further quantitative comparison of promising models in shared case studies is an essential prerequisite for future informed model choice.

Abstract There is an urgent need to change the current extractive and resource-intensive agricultural practices. Adopting circular practices within the agricultural system could provide multiple benefits of slowing global climate change, reducing extractive practices and helping farmers to adapt to a changing climate. However, there are still many barriers for farmers to adopt these desired circular agriculture (CA) practices, among others, a lack of information about on-farm circular practices. There is a need to support farmers in recognising which strategies can increase the circularity of their farm and what this means in terms of their farms’ climate neutrality and its long-term sustainability. Therefore, the aim of this paper is to develop a novel conceptual framework to facilitate a broader and integrated understanding of how on-farm CA strategies and practices contribute to the goals of climate change mitigation and on-farm sustainability, thus supporting farmers in transitioning their farms towards greater circularity.