Abstract: Impact response surfaces (IRSs) of spring and winter wheat yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect in Europe. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of 1981–2010 baseline weather.In spite of large differences in simulated yield responses to both baseline and changed climate between models, sites, crops and years, several common messages emerged. Ensemble average yields decline with higher temperatures (3–7% per 1°C) and decreased precipitation  (3–9% per 10% decrease), but benefit from increased precipitation (0-8% per 10% increase). Yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the German and Spanish sites. Precipitation effects diminish under higher temperature changes. Inter-model variability is highest for baseline climate at the Spanish site, but relatively insensitive to changed climate. Modelled responses diverge most at the Finnish and German sites for winter wheat under temperature change. The IRS pattern of yield reliability tracks average yield levels. Inter-annual yield variability is more sensitive to precipitation than temperature, except at the Spanish site for spring wheat.Optimal temperatures for present-day cultivars are close to the baseline under Finnish conditions but below the baseline at the German and Spanish sites. This suggests that adoption of later maturing cultivars with higher temperature requirements might already be advantageous, and increasingly so under future warming. No Label

Abstract: Greenhouse gas (GHG) mitigation is one of the main challenges faced by agriculture sector especially under an increasing demand for food. Production expansion needs to be accompanied by reductions in the GHG emission intensity of agricultural products. However, any uptakes of mitigation options by the farmers depend on the cost effectiveness of adopting such options as well as the farm characteristics. A highly effective mitigation option might not be practical for a farmer if the associated costs are high. A list of mitigation option implemented on different farm types with their cost effectiveness on farms would therefore be very useful for farmers as well as policy makers to make a decision. This paper aims to explore the use of three GHG mitigation options on different dairy farm groups in Scotland and determine the cost effectiveness of each of the options in those farm groups. The mitigation options considered for this paper are; i) use of sexed semen, ii) installing and using anaerobic digester and iii) increasing the share of concentrate diet. Farm level data from the Scottish Farm Accountancy dataset (FAS) was used and a cluster analysis was carried on to identify different dairy farm groups. The potential reduction of GHG emission per farm, including emissions arising from inputs used on the farm, under each of the option is then calculated using the GLEAM life cycle assessment model. An optimising farm level model, ScotFarm, was used on each of the farm groups to determine the optimum farm net margins under a baseline situation (with no options implemented) and three mitigation scenarios. The cost effectiveness of all three mitigation options are then determined based on reduction in GHG emission per farm and change in farm net margins under those options. Initial results for the sexed semen scenario suggest that this option can be cost effective for both efficient dairy farms (-£6.26/tCO2e) and medium-sized dairy farms (-£12.56/tCO2e). No Label

Abstract: Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations.