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Kipling, R.P.; Bannink, A.; Bellocchi, G.; Dalgaard, T.; Fox, N.J.; Hutchings, N.J.; Kjeldsen, C.; Lacetera, N.; Sinabell, F.; Topp, C.F.E.; van Oijen, M.; Virkajärvi, P.; Scollan, N.D. |
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Modelling European ruminant production systems: Facing the challenges of climate change |
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2017 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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10 |
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L1.1-D1 |
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Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks |
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LiveM |
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no |
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MA @ admin @ |
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4947 |
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Schönhart, M.; Schauppenlehner, T.; Schmid, E.; Sinabell, F. |
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Title |
Regional Pilot Case Study Mostviertel – AT: Preliminary Results |
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2014 |
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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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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5120 |
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Schönhart, M.; Sinabell, F. |
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Scenarios for the Austrian agricultural sector until 2025 considering greenhouse gas mitigation |
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2015 |
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Jahrbuch der ÖGA |
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25 |
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231-240 |
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Agrarian Perspectives XXIV, 25th Annual Conference of the Austrian Society of Agricultural Economics, 2015-09-16 to 2015-09-18, Prague |
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TradeM |
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no |
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MA @ admin @ |
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5028 |
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Banse, M.; Brouwer, F.; Palatnik, R.R.; Sinabell, F. |
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The Economics of European Agriculture under Conditions of Climate Change (Editorial) |
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2014 |
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German Journal of Agricultural Economics |
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German Journal of Agricultural Economics |
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63 |
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3 |
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131-132 |
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This Special Issue on “The Economics of European Agriculture under Conditions of Climate Change” brings together a selection of papers that contribute to the understanding of recent developments related to agriculture and climate change in four European coun- tries. The focus of the Special Issue is on quantitative modeling and empirical analyses. The papers presented here not only cover the heterogeneity of agriculture in Europe with case studies from the Mediterranean (Italy), central (Austria) and north-western Europe (Ireland and Scotland) but also give insights into the diversity of quantitative modeling approaches in agriculture. |
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English |
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Editorial material |
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TradeM, ft_macsur |
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no |
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MA @ admin @ |
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4763 |
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Brouwer, F.; Sinabell, F. |
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Three years of collaboration in TradeM – Agricultural markets and prices |
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2015 |
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FACCE MACSUR Reports |
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6 |
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SP6-4 |
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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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Brussels |
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Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A FACCE MACSUR workshop for policymakers |
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MA @ admin @ |
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2343 |
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