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Dalgaard, T., Hutchings, N., & Noe, E. (2014). Methods for regional scale farming systems modelling and uncertainty assessment – sustainability assessment case studies of production, nutrient losses and greenhouse gas emissions from grassland based systems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: In the EU Joint-Programming-Initiative: Modelling European Agriculturewith Climate Change for Food Security (MACSUR, LiveM: http://www.macsur.eu/index.php/livestock-modelling) we develop a research frameworkfor the modelling and sustainability assessment of livestock and grasslandbased farming systems at farm and regional scales.Based on results from related research and model development in Denmark,methodologies used for regional scaling, the description of data requirementsand sources, and methods to predict the effect and effectiveness of climate-and environment related policy measures are developed. In this study we present results from farm modelling in a study areaaround Viborg, Western Denmark using the http://www.Farm-N.dk/ model (Env.Pol. 159 3183-3192), including thedistribution of N-surpluses into different types of losses, and a comparisonwith empirical studies of farm nitrogen balances in the Danish study and fiveadditional European landscapes (Biogeosciences 9, 5303–5321). Based on this,methods and development needs for the mapping and uncertainty assessment ofnutrient losses and greenhouse gas emissions are discussed, referring to the presentdevelopment of the Farm-AC model and ongoing scenario studies in e.g. the www.dNmark.org project. In these scenarios, regional-scale policy measures areimplemented via the responses of a range of stakeholders, such as farmers,public interest groups, regulators and politicians. When modelling the outcomeof the policy measures implementation, it is often assumed that stakeholdersrespond as economically rational entities. However, social and cultural factorsare also known to play a role and modelling methods that permit these factorsto be taken into account will also be discussed.
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Saetnan, E. R., & Veneman, J. B. (2014). MitiGate: an On-line Meta-Analysis Database of Mitigation Strategies for Enteric Methane Emissions. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The animal science sector has seen a proliferation of potential mitigation strategies, aimed at tackling emissions from enteric fermentation in ruminant livestock production. By bringing together data from studies on the many mitigation options available through a structured meta-analytical approach, it is possible to evaluate the overall mitigation potential for these broad strategies as well as exploring the many factors influencing the potential of CH4 mitigation strategies. Such quantification of the different mitigation strategies will allow for better estimation of mitigation potential on different levels (animal, farm and sector scale) in modelling efforts. Also quantification is important to determine the strategies that show the best potential in lowering methane emissions and hence can be instrumental in policy recommendations. A database has been established through an initial extensive structured search of published literature on the topic. For each relevant paper identified, a range of meta-data have been extracted including information on the study design, mitigation strategy, animal husbandry, diet and methane emissions. By creating a database with multiple levels of moderator coding, we have provided a flexible platform for future meta-analyses at many levels of aggregation. Studies can then in future be aggregated at the level most appropriate for specific modelling or policy recommendations. This comprehensive database is being made available on-line through a user-friendly web interface. The web-site provides a facility for open access to the database, as well as future updates of the database as more research is published on the topic.
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Kersebaum, K. C., Kollas, C., Bindi, M., Palosuo, T., Wu, L., Sharif, B., et al. (2014). Model inter-comparison on crop rotation effects – an intermediate report. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed.
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Olesen, J. E., Vignjevic, M., & Wollenweber, B. (2014). Modelling adaptation of wheat cultivar to increasing temperatures and heat stress. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Climate change is expected to lead to yield reductions in cereals due to effects on both growth duration and physiological processes affecting assimilation and translocation to grains. However, some of these negative effects may be alleviated through plant breeding. A pot experiment with selected spring wheat varieties exposed to post anthesis heat stress (35 oC for 5 days) showed that the major factor affecting variety differences in heat tolerance was related to effects on green leaf area duration after heat stress. A field experiment with the same selected spring wheat varieties showed large differences between the varieties in crop development and in biomass. The data were used to calibrate the FASSET and Sirius crop models using a sequenced calibration procedure. Both models simulated crop growth and yield well. A sensitivity analysis with increasing temperature showed declining yields for both models with higher rates of yield reduction at temperature increases above 3oC. The models agreed on the pattern of yield decline between cultivars, with larger yield declines being related to earliness. The FASSET model was further modified to simulate effects of cultivar differences in remobilization of water soluble carbohydrates and effects of post-anthesis heat stress on crop yield. Effects of variation in threshold temperature for heat stress as well as response rate are tested.
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Zander, P., Schuler, J., Porwollik, V., & Hecker, J. - M. (2014). Modelling approach and first results on irrigation as climate change adaptation strategy of the project NaLaMa-nT. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The project NaLaMa-nT examines in the context of climate change sustainable development paths of land use in four different rural districts in Northern Germany. These districts were chosen along a soil-climate gradient from west to east with increasing water deficit for plant growth caused by both: decreasing rain fall and decreasing soil quality. In front of this background different trends and developments of agricultural production can be derived from analysing, modelling and comparing existing production systems and conditions of the different regions. One assumption developed from existing climate projections is that climate change will cause increasing water deficits for plant growth – especially in the eastern part of Germany. An obvious solution is to intensify agricultural production using existing irrigation methods that can reduce the yield risk and thus stabilize income from agriculture by avoiding yield failures and increasing the overall yield level. Therefore we build a modelling approach which allows an economic analysis both on the crop production activity level as well on the farm level. The data base comprises data representing recent production techniques and added optional irrigation techniques. The yields and input level changes are derived from literature studies and expert interviews. The farm structure is represented and modeled based on typical farms chosen from an IACS-data farm typology with different production potentials and patterns. First results will be presented in April.
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