Abstract: Climate and socio-economic change will affect the land use and the economic viability of Dutch dairy farms. Explorations of future scenarios, which include different drivers and impacts, are needed to perform ex-ante policy assessment. This study uses a bio-economic farm model to assess impacts of climate and socio-economic change on dairy farms in a sandy area in the Netherlands. Farm data from the Farm Accountancy Data Network provided information on the current production levels and available farm resources. First, the farm plans of individual farms were optimized in the current situation to benchmark farms and assess the current scope for improvement. Secondly, simulations for two scenarios were included: a Global Economy with 2 °C global temperature rise (GE/W+) and a Regional Community with 1 °C global temperature rise (RC/G). The impacts of climate change, extreme events, juridical change (including abolishment of milk quota), technological change and price changes were evaluated in separate model runs within the predefined scenarios. We found that farms can increase profit both by intensification and land expansion; the latter especially for medium sized farms (less than 70 cows). Climate change including the effect of increased occurrence of extreme events may negatively affect farm gross margin in the GE/W+ scenario. Lower gross margins are compensated for by the effects of technology and price changes. In contrast with the GE/W+ scenario, climate change has positive impacts on farm profit in RC/G, but less favourable farm input-output price ratios have a negative effect. Technological change is needed to compensate for revenue losses due to higher input prices. In both GE/W+ and RC/G scenarios, dairy farms increase production and the use of artificial fertilizer. Medium sized farms have more options to increase profit than the large farms: they benefit more from the abolishment of the milk quota and better adapt to negative and positive impacts of climate change. While the exact impact of different drivers will always remain uncertain, this study showed that changes in prices, technology and markets have a relatively larger impact than climate change, even when extreme events are taken into account. By using whole farm plans as activities that can be selected, the model is grounded in observations, and it was shown that half of the farms are gross margin maximizers as assumed in the model. The model therefore indicates ‘what could happen if’, and gives insights in drivers and impacts of dairy farming in the region.

Abstract: Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections. Erratum: doi: 10.1038/nplants.2017.125