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Virkajärvi, P.; Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Young, D. |
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Modeling grassland with CATIMO – focus on the second cut |
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Conference Article |
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2013 |
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9(1) |
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9-13 |
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CropM |
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MA @ admin @ |
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2881 |
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Siebert, S.; Ewert, F. |
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Title |
Future crop production threatened by extreme heat |
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Journal Article |
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Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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9 |
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4 |
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climate-change; simulation-models; wheat yields; day length; temperature; growth; impact; co2; phenology; patterns |
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Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation. |
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2016-10-31 |
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English |
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1748-9326 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4813 |
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Author |
Hoveid, Ø. |
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Title |
What are the risks of food price changes? A time series analysis |
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Report |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-2 |
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It is a widely held belief (IPCC) that climate change bringsmore risks to the worldI Since the start of MACSUR, TradeM has had risk on theagenda, but few results have so far come out. It has beenclaimed though, that there is no evidence for more risk in theglobal wheat market (Steen and Gjølberg 2014) (TradeMworkshop at Hurdalssjøen)I I have myself had the ambition of creating a dynamicstochastic model of the food system in which risk would be anintegral part, but time has been too shortI I have also pointed to methods from finance to reveal insights,and that is the road to be followed here, guided by Bølviken &Benth (2000) Buyer’s risk larger than seller’s risk — due to asymmetricdistribution of returns. Large price jumps are more likely thanequally sized price falls.I Long term positions much more risky than short term ones —as expectedI Agricultural commodities much less risky than crude oilI Price risk are related to volatility, and their changes over timewill have similar causal explanationsI Risks of producers and consumers of agricultural commoditieswill to some extent be related to the price risk, and also totheir portfolios and the co-variance between returns |
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MA @ admin @ |
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4831 |
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Author |
Sinabell, F. |
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Title |
Yield potentials and yield gaps in soybean production in Austria – a biophysical and economic assessment |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-11 |
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context of analysis:• stakeholders. policy relevance: CC and protein crops• research problem:• how large is the yield gap and what can be done• data• approaches• findings• discussion and outlook yield gap analysis is a daunting task• what can be learned• economics matters: prices of crop and other crops• land expansion: more land becoming more marginal• management matters a lot but – not directly observable in data• significant knowledge gaps still there• way forward:• look at other crops• explore options to improve management |
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MA @ admin @ |
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4829 |
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Schönhart, M. |
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Uncertainties from Climate Change on Farms and Ecosystem Services of a Grassland Dominated Austrian Landscape |
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Report |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-9 |
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MACSUR 1: development of a method to analysefarm and landscape scale impacts of CC, mitigationand adaptation effects– cropland dominated landscape, crop choice and soilmanagement– climate model uncertainty• Now: test and improve the robustness of the method– grassland landscape, cropland expansion and livestock– uncertainty analysis– variability of weather conditions High spatial resolution creates interfaces to disciplinarymodels and indicators• Challenging data & modelling demand• Increasing productivity can increase intensification pressures• Threatened permanent (extensive) grasslands and landscape elements, but• subject to resource constraints, costs and prices• Future RDP and environmental policy design (e.g. WFD) may need to takechanging productivity into account• Future research: analyze uncertainties & environmentalimpacts• Ensembles of crop and grassland models• Sensitivity analysis on economic input parameters• Qualitative surveys with agricultural experts and farmers |
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MA @ admin @ |
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4832 |
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