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Kässi, P., Niskanen, O., & Känkänen, H. (2014). Farm level approach to manage grass yield variation in changing climate in Jokioinen and St. Petersburg. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Cattle’s feeding is based on grass silage in Northern Europe, but grass growth is highly dependent on weather conditions. In farms decision making, grass area is usually determined by the variation of yield. To be adequate in every situation, the lowest expected yield level determines the cultivated area. Other way to manage the grass yield risk is to increase silage storage capacity over annual consumption. Variation of grass yield in climate data from years 1961-1990 was compared with 15 different climate scenario models simulating years 2046-2065. A model was developed for evaluating the inadequacy risk in terms of cultivated area and storing capacity. The cost of risk is presented and discussed. In northern Europe a typical farm has storage for roughage consumption of almost one year. In addition, there can be a buffer storage. The extra storage is to be used before and during the harvest season. New harvest will be fed to animals only after the buffer empty. Shortage in the buffer storage is possible to be filled, when the yield exceeds the target level. For risk management, two alternative mechanisms are given: forage buffer and possibility to alter the field area. According to our results, there are no significant adverse effects in the cost of risk and implied farm profitability due to climate change. Selecting the risk management scenario of 30 % grass yield risk turned out to be the least cost solution.
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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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Rötter, R. P. (2014). Cross-cutting uncertainties in MACSUR impact projections. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Projections into the future, such as climate change impact projections on crop production for a given region, or, on global food prices and trade are inherently uncertain. Uncertainty does not fall within a single discipline but is dealt with by a wide variety of disciplines, themes and problem domains. Model uncertainty pertaining to the impact modelling chain from climate via crop and livestock to economic and trade modelling is only part of the overall uncertainty*. There is also scenario uncertainty and many other known and unknown “unknowns”1 to be considered in efforts such as MACSUR and its themes (CropM, LiveM, TradeM) to advance model-based integrated assessment of climate change risk assessment for agriculture and food security. Propagation of uncertainties along the climate change impact modelling chain has been portrayed as “uncertainty cascade” 2. We will present different basic approaches for evaluating uncertainty in models. So far, studies addressing quantification and reporting of uncertainties in impact projections still largely focus on two major sources, i.e. the shares originating from climate modelling and from crop modelling. However, a more comprehensive treatment of uncertainty and how it is reported is urgently needed.
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Schönhart, M., Schauppenlehner, T., Schmid, E., & Sinabell, F. (2014). Regional Pilot Case Study Mostviertel – AT: Preliminary Results. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: An integrated modelling framework (IMF) is developed to analyse impacts of climate andpolicy changes on farm welfare and the environment. The IMF is applied on two contrasting grassland (south) and cropland (north) dominated Austrian landscapes. The IMF combines the crop rotation model CropRota, the bio-physical process model EPIC and the bio-economic farm model FAMOS[space] and applies combined climate change and policy scenarios. Changing policies reduce farm gross margins by -36% and -5% in the two landscapes respectively. Climate change increases gross margins and farms can reach pre-reform levels on average. Climate induced intensification such as removing of landscape elements andincreasing fertilization can be moderated by an agri-environmental program (AEP). However, productivity gains from climate change increase the opportunity costs for AEP participation.
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Lehtonen, H. S., Kässi, P., Korhonen, P., Niskanen, O., Rötter, R., Palosuo, T., et al. (2014). Problems and opportunities in climate change adaptation in North Savo region. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Crop production for feed dominates land use in North Savo in eastern Finland. The value of dairy and beef production is appr. 70 % of the total value of agricultural production of the region. In climate change adaptation research we are especially interested in dairy and meat sectors, which are directly dependent on the development of productivity of crop production. Climate change implies changes in cereals and forage crop yields and nutritive quality. There are most likely increasing problems and risks related to overwintering and growing periods. Grass silage is mainly self-produced on farms and most often there is no market for silage. Silage production and use are vulnerable to changes in local climate, because lost yield cannot be easily replaced from market. Risks and costs due to increasing inter-annual yield volatility can be reduced by good management practices, such as crop rotation, plant protection, soil improvements and better crop protection against plant diseases.However the profitability of such measures is dependent on market and policy conditions. Nevertheless new cultivars and species, as well as various options for production and risk management, are most likely needed in future climate. Some adaptations may have multiple benefits which however may realize only in medium or long run. It is important to safeguard the most important and obviously needed adaptations, and identify market and socio-economic conditions which inhibit farmers from necessary adaptations and lead to reduced productivity and increased production costs.
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