| Records |
Author  |
Biewald, A. |
| Title |
Representative Agricultural Pathways for Europe |
Type |
Report |
| Year |
2016 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
9 C6 - |
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Pages |
Sp9-1 |
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| Abstract |
Agricultural aspects have been covered in the scenario process on shared socio-economic pathways (SSPs), but only to a limited extent. In order to analyze the future dynamics of agricultural development they need to be complemented and specified by Representative Agricultural Pathways (RAPs), which cover different aspects of agricultural development as for example European agricultural and domestic policy, environmental policies, different livestock management systems, cropping systems or irrigation efficiencies.In this paper we will develop a general framework for RAPs where we define for each SSP the corresponding specific agricultural development. Some aspects of the above mentioned specifics can be derived from the definitions in the SSPs, as for example irrigation efficiencies which are linked to technological development. Agricultural policies on the other hand are not included in the SSP definitions. Here we will define agricultural and environmental policies, including the available funding in each area of the common agricultural policy (CAP) (pillars 1 and 2). As RAPs can only to a small degree be developed as European guidelines and implemented unilaterally, it is important to translate the overall storylines into specific scenario parameterization at national levels. Concerned by this are 1. national policies, as well as the agri-environmental schemes of the CAP in Pillar II, 2. livestock efficiencies and the development of extensive and intensive farm management, and 3. crop management systems.Additionally we will define which respresentative concentration pathways (RCPs) will match best the future agricultural and agro-economic trajectories. The following 5 preliminary RAPs for Europe will be further developed in our analysis:EU-RAP1 (Sustainable Europe) : strong CAP, strong shift on environmental regulation, no producer support, green CAP with strong mititgation componentEU-RAP2 (Middle of the road): BAU or things will stay as they are.EU-RAP3 (Fragmented Europe): Europe breaks up, rich countries support farmers with national subsidies, poor countries do not. There is no CAP anymoreEU-RAP4 (Two Europes): Europe is divided in a poor and a rich part. In the rich part a green and environmental friendly CAP will be implemented, in the poor part of Europe, the CAP will cease to existEU-RAP5(Fossil fueled Europe): free market world, strong institutions, weak on enviromental regulations, low domestic polices? Local green CAP without mitigation |
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MA @ admin @ |
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4836 |
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Blanco-Penedo et al. |
| Title |
Data driven dairy decision for farmers |
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Report |
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2016 |
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FACCE MACSUR Reports |
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8 |
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SP8-2 |
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Conference poster PDF |
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MA @ admin @ |
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4855 |
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Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. |
| Title |
Integrated assessment of crop productivity based on the food supply forecasting |
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Journal Article |
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2016 |
Publication |
Agricultural Economics – Czech |
Abbreviated Journal |
Agricultural Economics – Czech |
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61 |
Issue |
11 |
Pages |
502-510 |
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climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water |
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Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies. |
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English |
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0139-570x |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
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4644 |
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Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G. |
| Title |
Markov Chain as a Model of Daily Total Precipitation and a Prediction of Future Natural Events |
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Conference Article |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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no |
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MA @ admin @ |
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4911 |
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Boote, K.J.; Porter, C.; Jones, J.W.; Thorburn, P.J.; Kersebaum, K.C.; Hoogenboom, G.; White, J.W.; Hatfield, J.L. |
| Title |
Sentinel site data for crop model improvement—definition and characterization |
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Book Chapter |
| Year |
2016 |
Publication |
Improving Modeling Tools to Assess Climate Change Effects on Crop Response |
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Crop models are increasingly being used to assess the impacts of future climate change on production and food security. High quality, site-specific data on weather, soils, management, and cultivar are needed for those model applications. Also important is that model development, evaluation, improvement, and calibration require additional high quality, site-specific measurements on crop yield, growth, phenology, and ancillary traits. We review the evolution of minimum data set requirements for agroecosystem modeling and then describe the characteristics and ranking of sentinel site data needed for crop model improvement, calibration, and application. We in the Agricultural Model Intercomparison and Improvement Project (AgMIP), propose to rank sentinel site data sets as platinum, gold, silver, and copper, based on the degree of true site-specific measurement of weather, soils, management, crop yield, as well as the quality, comprehensiveness, quantity, accuracy, and value. For example, to be ranked platinum, the weather and soil characterization must be measured on-site, and all management inputs must be known. Dataset ranking will be lower for weather measured off-site or soil traits estimated from soil mapping. Ranking also depends on the intended purposes for data use. If the purpose is to improve a crop model for response to water or N, then additional observations are necessary, such as initial soil water, initial soil inorganic N, and plant N uptake during the growing season to be ranked platinum. Rankings are enhanced by presence of multiple treatments and sites. Examples of platinum-, gold-, and silver-quality data sets for model improvement and calibration uses are illustrated. |
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Hatfield, J.L.; Fleisher, D. |
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Advances in Agricultural Systems Modeling |
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7 |
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CropM |
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no |
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MA @ admin @ |
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4980 |
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