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Virkajärvi, P., Lehtonen, H., & Järvenranta, K. (2015). Regional impacts of climate change, observations and projections. Finnish Pilot study: North Savo region. (Vol. 6, pp. SP6–5). Brussels.
Abstract: Regional adjustment of regulation is important (eg. water protection) Due to expected growing yield potential fertilisation restrictions need adjustmentNitrate directive restricts efficient and sustainable grass productionGreening practices have only slight – and partly negative – impact on ruminant production (permanent grassland not suitable for northern conditions)Inefficient markets for agricultural land cause difficulties for farms that are increasing their productionCapitalisation of area payments to land prices + incentives for extensification (e.g. nature management and other set aside schemes under pillar 2) fit better part-time crop farms, not full-time livestock farmsthey express frustration on weak land supplyProduction based support for suckler cows and (dairy originated) beef production is vital for producersNo significant increase in production expected, budgetary limits of coupled supports No Label
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Brouwer, F., & Sinabell, F. (2015). Three years of collaboration in TradeM – Agricultural markets and prices. In FACCE MACSUR Reports (Vol. 6, pp. SP6–4). Brussels.
Abstract: Some farmers may claim that climate change adaptation is easy compared to the difficulties caused by policiesAction based on weather observations only, is insufficient for farmers to respond to climate change. Researchers need support from farmers in understanding the responses in practice.Policies might be too slow to respond to needs for change in agriculture. Winners and losers seem to be observed everywhere.The impacts of climate change is heterogeneous among farm types and regionsEffects beyond 2050 remain largely unclear, mainly because the effects of extreme events are not consideredVariability of yields is important to farm incomes, but most studies only consider average changesFarmers are ready to design their site-specific adaptation response providing that new knowledge and learning spaces are available. A learning process based on integrated models, assessment of short- and long-term effects, is needed for farmers to adapt to climate change, price fluctuations and policy change. No Label
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Scholten, M. C. T. (2015). Research and innovation for a competitive and sustainable animal production sector in a climate changing Europe: linking up MACSUR with Animal Task Force. Advances in Animal Biosciences, 6(01), 1–2.
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Köchy, M., Jorgenson, J., & Braunmiller, K. (2015). Overview of case studies (Vol. 6).
Abstract: MACSUR comprises 18 regional case studies for analysing the effects of climate change on agriculture with integrated inter-disciplinary models. Three case studies in Finland, Austria, and Italy have been selected as pilot studies because of their advancement in integration and representation of European farming systems and regions. No Label
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Hoveid, Ø. (2015). Prototype of stochastic equilibrium model of the food system (Vol. 6).
Abstract: Food security is an issue of risk. If climate change is not responded to with diet, technology and/or policy changes, it may lead to reduced food security for the world population, in particular the poorer part which in longer periods may not afford to purchase food in sufficient quantity and quality. In order to improve the situation, certain policy changes may be required. In some cases are policy recommendations relatively obvious, while in other cases a deeper insight in the stochastic dynamics of food supply and storage is required to assess the consequences of policy proposals. The relatively obvious part is that farmers need be responsive in periods of low total production, so that sufficient supply restores quickly. Moreover, trade should allow local shortages to be covered. Many national policies with the goal of self-sufficiency aim in the opposite direction with stable prices and production and relatively less flexibility in production. The stochastic dynamics of food supply can be analysed in more detail with a dynamic stochastic general equilibrium model (DSGE). Although agriculture by nature is about taking decisions under uncertainty, quantitative stochastic dynamic models for policy analysis in agriculture have not yet emerged. The contribution in MACSUR is a formalization of a class of DSGE-s based on representation of biological processes managed with regard to outcomes due to uncertain nature. No Label
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