Abstract: Livestock farming is the world’s largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource-and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction.

Abstract: As models become increasingly complex and integrated, uncertainty among model  parameters, variables and processes become critical for evaluating model outcomes and  predictions. A framework for understanding uncertainty in climate modelling has been  developed by the IPCC and EEA which provides a framework for discussion of uncertainty  in models in general. Here we report on a review of this framework along with the results  of a survey of sources of uncertainty in livestock and grassland models. Along with the  identification of key sources of uncertainty in livestock and grassland modelling, the  survey highlighted the need for a development of a common typology for uncertainty.  When collaborating across traditionally separate research fields, or when communicating  with stakeholders, differences in understanding, interpretation or emphasis can cause  confusion. Further work in MACSUR should focus on improving model intercomparison  methods to better understand model uncertainties, and improve availability of high  quality datasets which can reduce model uncertainties. No Label