Abstract: Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.

Abstract: To comply with complexity in farming and social demands with respect to farming practices, to remain competitive in and resilient to an ever changing decision environment, today’s farm managers need to develop an extensive portfolio of activities, made coherent by an overall strategic vision. This paper focusses on dairy farming, which shows complexity by integrating crop and livestock processes and faces nowadays important challenges from its social and market environment. The aim is twofold: first, what does strategic thinking mean in dairy farming and what kind of strategic decisions are eligible for a sustainable development, second, what kind of methodological framework can be built to support the farmer’s strategic thinking and decision making. The novel strategy exploration implies not only the mere crop-livestock organization alternatives, but also creatively looks for resilience increasing activities that allow for flexible food nonfood substitutions, multiple valorization trajectories and alternative multi-agents arrangements. Concrete examples include agroforestry, alternative nutrient throughputs or composting. The methodological support focusses on four principles: (i) integrative, considering the whole-farm scale, (iii) normative, leading to improved decision making, (iii)participatory, compiling transdisciplinary knowledge and (iv) communicative, using typical farm benchmarking. Findings are brought together from  literature, own research experiences on dairy farm management and interaction with stakeholders, amongst other the technical sciences researchers in the MACSUR knowledge hub. No Label