Although cocoa production addresses the livelihoods of several rural households, there is a global concern about its negative impact on the physical environment. How does this trade-off play out in different farming systems? This paper examined the social and environmental trade-offs and synergies of organic and conventional cocoa farming systems. Using the ‘SMART Farm-tool’ and principal component analysis approach, data collected from 398 cocoa farmers in five communities in the Atwima Mponua District of Ghana were analysed. We found that social and environmental trade-offs in the organic cocoa farming system are labour-related (EV = −0.38). The social and environmental trade-offs in the conventional cocoa farming system are health and safety and biodiversity-related (EV = −0.64). The organic farming system recognises indigenous knowledge in promoting biodiversity conservation and land degradation reduction (EV = −0.57). There can be more synergy than trade-off in both systems if support for capacity building and credit is provided and indigenous knowledge sharing is prioritised among low-income and vulnerable farmers. In this way, the labour conditions, biodiversity conservation, and health and safety-related concerns will be addressed. Addressing labour concerns in organic cocoa farming involves improving efficiency and working conditions. Strategies include training programs for organic techniques, introducing technology for tasks, and adhering to fair labour standards. This ensures labour concerns are addressed across the supply chain.

Agricultural landscapes are multifunctional and closely connected to the much wider food system. In our review, we explore three specific aspects of modelling approaches for agricultural landscape assessments: (a) how multifunctionality is commonly analysed to support decision-making for sustainable agricultural land management; (b) how the modelling approaches relate to the wider food systems; and (c) how gaps in the existing modelling approaches might be addressed. For this, we identified key elements of agricultural landscape assessments, including ecosystem services (ESS) provided, driving factors, and linkages between crop and livestock production, and to the wider food system. We reviewed 238 publications with respect to these elements. While biodiversity and the ESS ‘water conditions’ and ‘atmospheric composition/conditions’ are widely covered, they are rarely used in combination. Other ESS, such as ‘pest and disease control’, are largely missing. Our results further indicate strong differences between individual approaches regarding model parameterisation and consideration of abiotic, biotic, and management driving factors. Our analysis also shows that the interconnectedness of crop and livestock production is rarely considered and that return flows from the food system are not considered. Furthermore, impacts from the production of external inputs and off-site effects are not considered. Consequently, existing models might overlook trade-offs and synergies between landscape functions. Failure to consider variations in relevant driving factors and food system linkages likely results in studying incorrect levers for change and failing to show decision-makers the full scope of available action. We thus suggest adopting more encompassing modelling approaches to ensure coverage of the full scope of potential actions, whilst hedging against overly costly data requirements by, e.g. employing well-designed sensitivity analyses. In this way, the most relevant components and thus the most important leverage points for interventions can be identified.

Livestock production is a major driver of phosphorus (P) surpluses, threatening nutrient-sensitive regions, such as the watershed of Lake Sempach in Switzerland. While reducing livestock density may alleviate these impacts, it risks undermining food production and rural livelihoods. This study investigates regionally adapted strategies to reduce livestock-related P excretion while maintaining animal-source protein production. Using the dynamic LEAF.livestock model, we simulated nearly five million combinations of herd structures and management practices. Each scenario was assessed across five key indicators: P excretion, animal-source protein output, land use, food-feed competition, and manure fertilizing potential. Region-specific ecological and production constraints were applied, including limits on P excretion, maintenance of animal-source protein (ASP) output, and adherence to available land. No scenario fulfilled all constraints simultaneously. When the land-use constraint was relaxed, over 514’000 viable and 7’174 Pareto-optimal scenarios emerged, showing clear trade-offs between livestock density, herd composition, feed sourcing, and nutrient outputs. Pareto-optimal scenarios consistently required reduced livestock density (65–90% of Business-as-usual (BAU)), pig shares ≥20%, and fewer suckler cows. Pig-dominated scenarios performed best on P excretion and ASP output but required more arable land and intensified feed-food competition. Dairy-dominated scenarios used less arable land and had better N:P ratios, but produced less ASP, though equal or greater than BAU. Similar results emerged therefore from different strategies, highlighting the importance to identify local optima rather than rely on a single global solution. In all scenarios, more plant-source protein than ASP could be produced if the same land were used directly for food production. To maintain the current ASP production, many scenarios relied on external land for feed production, manure export, or off-site rearing, shifting environmental burdens beyond the catchment. This study provides a model-based foundation for designing ecologically sound and socially acceptable livestock transition pathways, highlighting region-specific trade-offs and actionable strategies to reduce P surpluses while maintaining food production within environmental limits.