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Shrestha, S. (2015). Comparing the cost effectiveness of GHG mitigation options on different Scottish dairy farm groups (Vol. 5).
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
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Sharif, B. (2015). Inter-comparison of statistical models for projecting winter oilseed rape yield in Europe under climate change (Vol. 5).
Abstract: While intercomparison of process-based crop models for projections under climate change is being intensively studied at European as well as at the global scale, little effort has been made for comparing statistical models. In this study, several regression techniques (ordinary least squares, stepwise, shrinkage methods, principle components and partial least squares) were combined with different types of climate input variables (with different temporal resolution) in order to define a large range of statistical models. Each model was fitted to winter oilseed rape data collected in 689, 325 and 173 field experiments carried out in Denmark, Germany, and Czech Republic, respectively. The fitted models were then used to predict yield of winter oilseed rape in the field experiments during more than 20 years, up to 2013. Interpretability of the estimated climate variable effects and accuracy of yield predictions were both analysed. Results suggest that recent statistical methods (e.g., shrinkage methods) may have considerable capabilities to complement traditional statistical methods in yield prediction. The selection of the most influential variables was strongly influenced by the statistical method used to analyse the data. Among the most recent statistical methods, the uncertainties in projecting yield of winter oilseed rape under climate change were mainly due to residual errors and uncertainty in estimated parameter values, and not to model choice. No Label
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Schönhart, M. (2015). Integrated Assessment of Climate Change Mitigation and Adaptation Impacts at Landscape Level in the Austrian Mostviertel Region (Vol. 5).
Abstract: Climate change poses fundamental challenges on agriculture. It triggers autonomous adaptation responses of famers and thereby impacts the success of climate change mitigation. Integrated modelling frameworks (IMF) on land use serve as decision support instruments under such conditions by considering climate signals and accounting for combined mitigation and adaptation policies. We apply an IMF at the farm level in two contrasting grassland and cropland dominated landscapes in Austria to analyze climate change impacts on land use as well as impacts from mitigation and adaptation policies on the abiotic and biotic environment and the landscape. Results show that the impacts on farm gross margins and the abiotic and biotic environment are substantial either directly from climate change (e.g. changing erosion levels) or triggered via adaptation responses (i.e. land use and management change). Average gross margins increase between 1% and 12% depending on the case study landscape, the climate change scenario, and the policy scenario. With respect to biodiversity indicators, land use changes in the adaptation scenario decrease plant species diversity on farmland by 13% on average and losses are up to 80% for some farms. These changes are driven by policies in the adaptation scenario as responses on climate change in the absence of policies are modest with minor impacts on biodiversity. Results indicate the effectiveness of climate change adaptation in increasing farm incomes and the need to coordinate mitigation and adaptation policies to manage environmental outcomes. The IMF turns out to be effective in revealing heterogeneity of climate change impacts among farms and regions and linkages among adaptation and mitigation policies. No Label
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Semenov, M. A. (2015). Heat tolerance in wheat identified as a key trait for increased yield potential in Europe under climate change (Vol. 5).
Abstract: To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Predicted climate change emphasises the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost or severe drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, we refined the Sirius wheat model and incorporated effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. We used Sirius to design wheat ideotypes optimised for CMIP5-based climate scenarios for 2050 at 6 wheat growing areas in Europe. The yield potential for heat-tolerant ideotypes can be substantially increased compared with the current cultivars in the future by selecting optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, grain yield of heat-sensitive ideotypes was substantially lower and more variable in Hungary and Spain, because extending grain filling for increased yield potential was in conflict with high temperature episodes during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. No Label
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Schönhart, M. (2015). Analysis of climate change adaptation with bio-economic farm models: lessons from MACSUR regional pilot studies (Vol. 5).
Abstract: Integrated land use models (ILM) featuring agronomic and economic drivers of land use are frequently applied to serve the high information demand of stakeholders. This presentation results from collaboration among bio-economic farm modelers across the MACSUR regional pilot studies (www.macsur.eu) and shall compare and finally reveal good practice examples on the representation of climate change adaptation in bio-economic farm models. First results show a considerable diversity of approaches employed in the MACSUR regional pilot studies. All are programming models that optimize more or less elaborated forms of utility. All consider or plan to consider crop yield impacts from bio-physical crop models based on daily-resolution climate data. While some models include pest and diseases or livestock impacts, none take climate change impacts on market prices or interactions among farms into account so far. Clearly, adaptation options determine the solution space and are mainly expert-based in the regional case studies. Overall, the models are normative and analyze economically rational and optimal land use and management at the farm level, capable of showing the likely direction of differences in future management as a response to exogenous parameter changes (prices, yields, disease pressure, changed policy conditions, etc.). Such detailed models and their results may be applied in stakeholder interaction. Integrating the different direct and indirect effects of climate change, including the policy dimension, is the main contribution of farm level modelling of agricultural systems in the domain of climate change adaptation research. No Label
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