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| Author |
Lehtonen, H. |
| Title |
Evaluating competitiveness of clover-grass as a resilient feed production option in Finland |
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Report |
| Year |
2016 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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9 C6 - |
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Pages |
Sp9-4 |
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Abstract  |
Clover-grasses address the following objectives:– Decreased input use (N-fertilization), reduced dependency ofinorganic N => reduced GHG emissions– Possibility for increased protein content of silage, reduceddependency on purchased protein feed supplement (homegrown proteins, resilience)© Natural Resources Institute Finland– Better utilisation of farmland in the context of climate changein the north: Higher T – improved N fixation– Compatible with sustainable agriculture and sustainableintensification: more output with the same inputs / the sameoutput with reduced (non-renewable) inputs• In contrast: Shifting to silage maize increases N fertilisation– Major shift from grasslands to silage maize in e.g. Denmark 1. Small cost reductions in clover-grass cultivation, or clover-grasspremiums, may or may not increase clover cultivation- Their effectiveness is uncertain and subject to prices2. N tax is effective, but is not a suitable policy action in currentfinancial situation of farms (milk crisis 2015-2016)3. However, the results suggest that a 25% higher N price lead to© Natural Resources Institute Finlandsignificantly higher clover grass area and a small reduction ínmilk output – with no cost reductions or extra premiums!4. To increase clover cultivation, price ratios should be adjusted!5. If increasing clover -grass yield, a robust increase in clovergrass areas may realise, with small benefits for farm economyand overall production – How much more clover grass yieldcould be attained at low costs? A topic for further discussionand analysis |
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4853 |
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Semenov, M.A.; Stratonovitch, P. |
| Title |
Local-scale CMIP5-based climate scenarios for MACSUR2 |
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Report |
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2016 |
Publication |
FACCE MACSUR Reports |
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8 |
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Pages |
C2.2-D |
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CropM |
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Climate sensitivity of GCMs was used to select 5 GCMs from the CMIP5 ensemble for impact studies in MACSUR2. Selected GCMs for MACSUR2 are EC-EARTH (7), GFDL-CM3 (8) HadGEM2-ES (10), MIROC5 (13), and MPI-ESM-MR (15). These GCMs are evenly distributed among CMIP5 (Fig 1) and should capture, in principal, climate uncertainty of the CMIP5 ensemble. Using 5 GCMs will enable us to assess uncertainties in impacts related to uncertainty in climate projections. The selection of GCMs in MACSUR2 has a good overlap with selections of GCMs used in CORDEX and AgMIP projects. We used the LARS-WG generator to construct local-scale CMIP5-based climate scenarios for Europe (Semenov & Stratonovitch, 2015). Fifteen sites were selected in Europe for MACSUR2. For each site and each selected GCM, 100 yrs climate daily data were generated by LARS-WG for RCP4.5 and RCP8.5 emission scenarios and for baseline and 3 future periods: near-term (2021-2040), mid-term (2041-2060) and long-term (2081-2100). |
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MA @ admin @ |
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2270 |
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Stevanović, M.; Popp, A.; Lotze-Campen, H.; Dietrich, J.P.; Müller, C.; Bonsch, M.; Schmitz, C.; Bodirsky, B.L.; Humpenöder, F.; Weindl, I. |
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The impact of high-end climate change on agricultural welfare |
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Journal Article |
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2016 |
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Science Advances |
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Sci. Adv. |
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2 |
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8 |
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e1501452 |
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ftnotmacsur |
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Climate change threatens agricultural productivity worldwide, resulting in higher food prices. Associated economic gains and losses differ not only by region but also between producers and consumers and are affected by market dynamics. On the basis of an impact modeling chain, starting with 19 different climate projections that drive plant biophysical process simulations and ending with agro-economic decisions, this analysis focuses on distributional effects of high-end climate change impacts across geographic regions and across economic agents. By estimating the changes in surpluses of consumers and producers, we find that climate change can have detrimental impacts on global agricultural welfare, especially after 2050, because losses in consumer surplus generally outweigh gains in producer surplus. Damage in agriculture may reach the annual loss of 0.3% of future total gross domestic product at the end of the century globally, assuming further opening of trade in agricultural products, which typically leads to interregional production shifts to higher latitudes. Those estimated global losses could increase substantially if international trade is more restricted. If beneficial effects of atmospheric carbon dioxide fertilization can be realized in agricultural production, much of the damage could be avoided. Although trade policy reforms toward further liberalization help alleviate climate change impacts, additional compensation mechanisms for associated environmental and development concerns have to be considered. |
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MA @ admin @ |
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5003 |
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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 |
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11 |
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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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MA @ admin @ |
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4644 |
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Jancic, M. |
| Title |
Climate change adaptation in maize production in Serbia |
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Report |
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2016 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
9 C6 - |
Issue |
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Pages |
Sp9-3 |
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Climate change is noticed and well established phenomenon, described as change in the statistical properties of the climate system, considered over long period of time, regardless of cause (Houghton, 1996). This change has been monitored on global (Rosenzweig et al., 1994; Harrison et al., 1995; Wolf et al., 1995; Watson et al., 1996; Downing et al., 2000; Sathaye et al., 1997; Sirotenko et al., 1997) and regional scale (Alexandrov et al., 2002; Lalic et al., 2012; Vučetić, 2011) by researchers, organizations and part of various programmes (IPCC, UNESCO Climate Change Initiative). In a same time, it was analysed change in agroclimatic indices, soil and water balance, crop development and yield, that quantify climate change impact on agricultural production. In recent regional studies and research projects (COST 734, 2008; ADAGIO, 2009), it was estimated and quantified climate change impact on yield and development in crop production of Central and Eastern European countries and Mediterranean region. The research showed a decrease in yield in several major crops, important in national food production and part of economy. A high variability in yield from year to year and decrease in yield was showed for most cereals. |
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4856 |
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