Resource-use archetypes in contrasting agrosilvopastoral systems: An emergy study of Portuguese Montado and Scottish grasslands

CONTEXT Mixed farming systems are often classified into broad typologies that mask differences between management logics and sustainability trade-offs. This limits the diagnostic capacity of sustainability assessments and reduces the effectiveness of agri-environmental policies targeting system-specific dynamics. OBJECTIVE This study aims to identify dominant resource-use configurations in contrasting mixed farming systems, quantify their key drivers, and develop a diagnostic framework to analyse how management variability shapes system performance and sustainability outcomes. METHODS We combined emergy accounting with Latin Hypercube Sampling (LHS) to analyse two contrasting systems: Portuguese Montado silvopastoral systems (PT) and Scottish crop–livestock systems (SCT). Farm-level resource flows for one production year were converted into solar emergy joules (sej). For each system, 10,000 management scenarios were generated using LHS to explore input variability. Emergy indicators were analysed as distributions rather than point estimates, and k-means clustering was applied to identify recurring resource-use profiles. RESULTS AND CONCLUSIONS Across both systems, emergy indicators did not converge towards a single optimal configuration but consistently formed three resource-use archetypes: eco-embedded, input-moderate, and input-intensive. Scottish systems were predominantly associated with input-intensive and input-moderate configurations, driven by variability in fertiliser use and mechanisation. In contrast, Montado systems more frequently exhibited eco-embedded profiles, shaped by renewable resource flows, particularly evapotranspiration, and limited external inputs such as phosphorus fertiliser. The analysis also revealed contrasting system response dynamics: SCT performance is largely influenced by short-term management decisions, whereas PT systems are constrained by longer-term ecological processes. These findings highlight distinct leverage points and temporal dynamics governing system behaviour. SIGNIFICANCE This study demonstrates that combining emergy analysis with uncertainty exploration provides a robust framework for diagnosing system behaviour beyond static sustainability metrics. By identifying system-specific resource-use patterns and leverage points, the approach supports the design of targeted policies aligned with the ecological and management dynamics of different agricultural systems.