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Author Özkan, Ş.; Ahmadi, B.V.; Bonesmo, H.; Østerås, O.; Stott, A.; Harstad, O.M.
Title Impact of animal health on greenhouse gas emissions Type Journal Article
Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal (up) Advances in Animal Biosciences
Volume 6 Issue 01 Pages 24-25
Keywords dairy; GHG emissions; cull rate; health; HolosNor
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Language English Summary Language Original Title
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ISSN 2040-4700 ISBN Medium Article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4573
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Author Lotze-Campen, H.; von Lampe, M.; Kyle, P.; Fujimori, S.; Havlik, P.; van Meijl, H.; Hasegawa, T.; Popp, A.; Schmitz, C.; Tabeau, A.; Valin, H.; Willenbockel, D.; Wise, M.
Title Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal (up) Agric. Econ.
Volume 45 Issue 1 Pages 103-116
Keywords energy demand; agricultural markets; general equilibrium modeling; partial equilibrium modeling; model comparison; greenhouse-gas emissions; land-use; energy; productivity; scenarios; policies; capture; storage; system
Abstract Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high-emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM Approved no
Call Number MA @ admin @ Serial 4532
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Author Müller, C.; Robertson, R.D.
Title Projecting future crop productivity for global economic modeling Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal (up) Agric. Econ.
Volume 45 Issue 1 Pages 37-50
Keywords climate change; crop modeling; agricultural productivity; land use; greenhouse-gas emissions; soil organic-carbon; sub-saharan africa; climate-change; elevated co2; land-use; system model; wheat yields; maize yields; agriculture
Abstract Assessments of climate change impacts on agricultural markets and land-use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land-use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10-38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.
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Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4533
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Author Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G.
Title Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany Type Journal Article
Year 2015 Publication Agricultural Systems Abbreviated Journal (up) Agric. Syst.
Volume 136 Issue Pages 79-84
Keywords Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy
Abstract Highlights • We analyze the economic effects of plant breeding research in Germany. • Effects of reduced CO2 emissions due to productivity increases are being quantified. • Expansion of global agricultural area has been reduced by 1–1.5 million ha. • CO2 emissions have been reduced by 160–235 million tons. • German plant breeding research has an economic value of 10.8–15.6 billion EUR. Abstract We analyze the economic effects of plant breeding research in Germany. In addition to market effects, for the first time also effects of reduced CO2 emissions due to productivity increases are being quantified. The analysis shows that investments in German plant breeding research in the period 1991–2010 have reduced the global expansion of agricultural area by 1–1.5 million hectares. This has led to reduced CO2 emissions of 160–235 million tons. The economic value generated by plant breeding research, through increased production and reduced greenhouse gas emissions, is estimated at 10.8–15.6 billion EUR in the same period. This can be translated into a social rate of return on research investment in the range of 40–80% per year. Projections for the period 2011–2030 generate a return rate in the range of 65–140% per year. Investments into plant breeding research in Germany are highly profitable from a societal point of view. At the same time, our results show significant under-investments in agricultural research in Germany. These results provide a good justification for policy-makers to reverse funding cuts for public agricultural research over the last decades and to improve institutional conditions for private research, e.g. through better protection of intellectual property rights.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308521x ISBN Medium
Area Expedition Conference
Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4999
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Author Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R.
Title Integrated assessment of crop productivity based on the food supply forecasting Type Journal Article
Year 2016 Publication Agricultural Economics – Czech Abbreviated Journal (up) Agricultural Economics – Czech
Volume 61 Issue 11 Pages 502-510
Keywords 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
Abstract 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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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0139-570x ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4644
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