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Author Shrestha, S.; Ciaian, P.; Himics, M.; van Doorslaer, B.
Title Impacts of climate change on EU agriculture Type Journal Article
Year 2013 Publication Review of Agricultural and Applied Economics Abbreviated Journal Review of Agricultural and Applied Economics
Volume 16 Issue 2 Pages 24-39
Keywords (up) climate change; agricultural productivity; adaptation; Europe
Abstract The current paper investigates the medium term economic impact of climate changes on the EU agriculture. The yield change data under climate change scenarios are taken from the BIOMA (Biophysical Models Application) simulation environment. We employ CAPRI modelling framework to identify the EU aggregate economic effects as well as regional impacts. We take into account supply and market price adjustments of the EU agricultural sector as well as technical adaptation of crops to climate change. Overall results indicate an increase in yields and production level in the EU agricultural sector due to the climate change. In general, there are relatively small effects at the EU aggregate. For example, the value of land use and welfare change by approximately between -2% and 0.2%. However, there is a stronger impact at regional level with some stronger effects prevailing particularly in the Central and Northern EU and smaller impacts are observed in Southern Europe. Regional impacts of climate change vary by a factor higher up to 10 relative to the aggregate EU impacts. The price adjustments reduce the response of agricultural sector to climate change in particular with respect to production and income changes. The technical adaption of crops to climate change may result in a change production and land use by a factor between 1.4 and 6 relative to no-adaptation situation.
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Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4615
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Author Patil, R.H.; Laegdsmand, M.; Olesen, J.E.; Porter, J.R.
Title Soil temperature manipulation to study global warming effects in arable land: performance of buried heating-cable method Type Journal Article
Year 2014 Publication Environment and Ecology Research Abbreviated Journal Environment and Ecology Research
Volume 1 Issue 4 Pages 196-204
Keywords (up) Climate Change; Climate Manipulation; Soil Warming; Heating Cables; Soil Temperature; Agro-Ecosystems
Abstract Buried heating-cable method for manipulating soil temperature was designed and tested its performance in large concrete lysimeters grown with the wheat crop in Denmark. Soil temperature in heated plots was elevated by 5℃ compared with that in control by burying heating-cable at 0.1 m depth in a plough layer. Temperature sensors were placed at 0.05, 0.1 and 0.25 m depths in soil, and 0.1 m above the soil surface in all plots, which were connected to an automated data logger. Soil-warming setup was able to maintain a mean seasonal temperature difference of 5.0 ± 0.005℃ between heated and control plots at 0.1 m depth while the mean seasonal rise in soil temperature in the top 0.25 m depth (plough layer) was 3℃. Soil temperature in control plots froze (≤ 0℃) for 15 and 13 days respectively at 0.05 and 0.1 m depths while it did not in heated plots during the coldest period (Nov-Apr). This study clearly showed the efficacy of buried heating-cable technique in simulating soil temperature, and thus offers a simple, effective and alternative technique to study soil biogeochemical processes under warmer climates. This technique, however, decouples below-ground soil responses from that of above-ground vegetation response as this method heats only the soil. Therefore, using infrared heaters seems to represent natural climate warming (both air and soil) much more closely and may be used for future climate manipulation field studies.
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Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4632
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Author Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Li, T.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Bouman, B.; Bregaglio, S.; Brisson, N.; Buis, S.; Cammarano, D.; Challinor, A.J.; Confalonieri, R.; Conijn, J.G.; Corbeels, M.; Deryng, D.; De Sanctis, G.; Doltra, J.; Fumoto, T.; Gaydon, D.; Gayler, S.; Goldberg, R.; Grant, R.F.; Grassini, P.; Hatfield, J.L.; Hasegawa, T.; Heng, L.; Hoek, S.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.-H.; Lizaso, J.; Marcaida, M.; Müller, C.; Nakagawa, H.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.J.; Olesen, J.E.; Oriol, P.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Ruget, F.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Singh, B.; Singh, U.; Soo, H.K.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tang, L.; Tao, F.; Teixeira, E.I.; Thorburn, P.; Timlin, D.; Travasso, M.; Rötter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Wilkens, P.; Williams, J.R.; Wolf, J.; Yin, X.; Yoshida, H.; Zhang, Z.; Zhu, Y.
Title A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 214-215 Issue Pages 483-493
Keywords (up) climate change; crop model; emulator; meta-model; statistical model; yield; climate-change; wheat yields; metaanalysis; uncertainty; simulation; impacts
Abstract Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4714
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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 Agric. Econ.
Volume 45 Issue 1 Pages 37-50
Keywords (up) 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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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN 0169-5150 ISBN Medium Article
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Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4533
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Author Dockter, C.; Hansson, M.
Title Improving barley culm robustness for secured crop yield in a changing climate Type Journal Article
Year 2015 Publication Journal of Experimental Botany Abbreviated Journal J. Experim. Bot.
Volume 66 Issue 12 Pages 3499-3509
Keywords (up) Climate Change; Crops, Agricultural/*anatomy & histology/genetics/*growth & development; Edible Grain/anatomy & histology/genetics/growth & development; Genes, Plant; Hordeum/*anatomy & histology/genetics/*growth & development; Phenotype; Barley (Hordeum vulgare); Green Revolution; brassinosteroid; gibberellin; lodging; plant architecture; short culm
Abstract The Green Revolution combined advancements in breeding and agricultural practice, and provided food security to millions of people. Daily food supply is still a major issue in many parts of the world and is further challenged by future climate change. Fortunately, life science research is currently making huge progress, and the development of future crop plants will be explored. Today, plant breeding typically follows one gene per trait. However, new scientific achievements have revealed that many of these traits depend on different genes and complex interactions of proteins reacting to various external stimuli. These findings open up new possibilities for breeding where variations in several genes can be combined to enhance productivity and quality. In this review we present an overview of genes determining plant architecture in barley, with a special focus on culm length. Many genes are currently known only through their mutant phenotypes, but emerging genomic sequence information will accelerate their identification. More than 1000 different short-culm barley mutants have been isolated and classified in different phenotypic groups according to culm length and additional pleiotropic characters. Some mutants have been connected to deficiencies in biosynthesis and reception of brassinosteroids and gibberellic acids. Still other mutants are unlikely to be connected to these hormones. The genes and corresponding mutations are of potential interest for development of stiff-straw crop plants tolerant to lodging, which occurs in extreme weather conditions with strong winds and heavy precipitation.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN 0022-0957 1460-2431 ISBN Medium Review
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4556
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