Abstract: • First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects.

Abstract: The imposition of a carbon tax in the economy will have indirect impacts on dairy farmers in Australia. Although there is a great deal of information available regarding mitigation strategies both in Australia and internationally, there seems to be a lack of research investigating the variable prices of carbon-based emissions on dairy farm operating profits in Australia. In this study, a stochastic analysis comparing the uncertainty in income in response to different prices on carbon-based emissions was conducted. The impact of variability in pasture consumption and variable prices of concentrates and hay on farm profitability was also investigated. The two different feeding systems examined were a ryegrass pasture-based system (RM) and a complementary forage-based system (CF). Imposing a carbon price ($20-$60) and not changing the systems reduced the farm operating profits by 28.4% and 25.6% in the RM and CF systems, respectively compared to a scenario where no carbon price was imposed. Different farming businesses will respond to variability in the rapidly changing operating environment such as fluctuations in pasture availability, price of purchased feeds and price of milk or carbon emissions differently. Further, in case there is a carbon price imposed for GHG emissions emanated from dairy farming systems, changing from pasture-based to more complex feeding systems incorporating home-grown double crops may reduce the reductions in farm operating profits. There is opportunity for future studies to focus on the impacts of different mitigation strategies and policy applications on farm operating profits. (C) 2015 Elsevier Ltd. All rights reserved.