| Records |
| Author |
Nelson, G.C.; Valin, H.; Sands, R.D.; Havlík, P.; Ahammad, H.; Deryng, D.; Elliott, J.; Fujimori, S.; Hasegawa, T.; Heyhoe, E.; Kyle, P.; Von Lampe, M.; Lotze-Campen, H.; Mason d’Croz, D.; van Meijl, H.; van der Mensbrugghe, D.; Müller, C.; Popp, A.; Robertson, R.; Robinson, S.; Schmid, E.; Schmitz, C.; Tabeau, A.; Willenbockel, D. |
| Title |
Climate change effects on agriculture: economic responses to biophysical shocks |
Type |
Journal Article |
| Year |
2014 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
| Volume |
111 |
Issue |
9 |
Pages |
3274-3279 |
| Keywords |
Agriculture/*economics; Carbon Dioxide/analysis; *Climate Change; Commerce/statistics & numerical data; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Humans; *Models, Economic; agricultural productivity; climate change adaptation; integrated assessment; model intercomparison |
Abstract  |
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. |
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| Language |
English |
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| ISSN |
0027-8424 1091-6490 |
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Article |
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| Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4535 |
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| Author |
Müller, C. |
| Title |
African lessons on climate change risks for agriculture |
Type |
Journal Article |
| Year |
2013 |
Publication |
Annual Review of Nutrition |
Abbreviated Journal |
Ann. Rev. Nutr. |
| Volume |
33 |
Issue |
1 |
Pages |
395-411 |
| Keywords |
Africa/epidemiology; *Climate Change/economics; Crops, Agricultural/economics/*growth & development; Diet/adverse effects/economics; Forecasting; *Global Health/economics/trends; Humans; Malnutrition/economics/epidemiology/prevention & control; *Models, Theoretical; Risk; Soil/chemistry; Water Resources/economics |
| Abstract |
Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited. |
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English |
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| ISSN |
0199-9885 1545-4312 |
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Article |
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CropM |
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no |
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MA @ admin @ |
Serial |
4496 |
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| Author |
Elsgaard, L.; Børgesen, C.D.; Olesen, J.E.; Siebert, S.; Ewert, F.; Peltonen-Sainio, P.; Rötter, R.P.; Skjelvåg, A.O. |
| Title |
Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe |
Type |
Journal Article |
| Year |
2012 |
Publication |
Food Additives & Contaminants: Part A |
Abbreviated Journal |
Food Addit. Contam. Part A |
| Volume |
29 |
Issue |
10 |
Pages |
1514-1526 |
| Keywords |
Agriculture/*economics/trends; Animals; Avena/chemistry/economics/*growth & development/microbiology; *Climate Change/economics; Crops, Agricultural/chemistry/economics/*growth & development/microbiology; Europe; *Food Safety; Forecasting/methods; Fungi/growth & development/metabolism; Humans; Models, Biological; Models, Economic; Mycotoxins/analysis/biosynthesis; Soil Pollutants/adverse effects/analysis; Spatio-Temporal Analysis; Triticum/chemistry/economics/*growth & development/microbiology; Uncertainty; Weather; Zea mays/chemistry/economics/*growth & development/microbiology |
| Abstract |
Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops. |
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English |
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Edition |
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1944-0049 1944-0057 |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4585 |
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| Author |
Rosenzweig, C.; Elliott, J.; Deryng, D.; Ruane, A.C.; Müller, C.; Arneth, A.; Boote, K.J.; Folberth, C.; Glotter, M.; Khabarov, N.; Neumann, K.; Piontek, F.; Pugh, T.A.; Schmid, E.; Stehfest, E.; Yang, H.; Jones, J.W. |
| Title |
Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison |
Type |
Journal Article |
| Year |
2014 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
| Volume |
111 |
Issue |
9 |
Pages |
3268-3273 |
| Keywords |
Agriculture/*methods/statistics & numerical data; *Climate Change; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Geography; *Models, Theoretical; Nitrogen/*analysis; Risk Assessment; Temperature; AgMIP; Isi-mip; agriculture; climate impacts; food security |
| Abstract |
Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. |
| Address |
2016-10-31 |
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English |
Summary Language |
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1091-6490 (Electronic) 0027-8424 (Linking) |
ISBN |
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Article |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4801 |
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| Author |
Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P. |
| Title |
Statistical modelling of agrometeorological time series by exponential smoothing |
Type |
Journal Article |
| Year |
2016 |
Publication |
International Agrophysics |
Abbreviated Journal |
International Agrophysics |
| Volume |
30 |
Issue |
1 |
Pages |
57-65 |
| Keywords |
exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather |
| Abstract |
Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error. |
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English |
Summary Language |
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Edition |
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| ISSN |
0236-8722 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4728 |
| Permanent link to this record |
