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Author |
Müller, C., Elliott J |
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Title  |
AgMIP’s Global Gridded Crop Model Intercomparison |
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Conference Article |
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Year |
2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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no |
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Call Number |
MA @ admin @ |
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2668 |
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Author |
Schmitz, C.; Kreidenweis, U.; Lotze-Campen, H.; Popp, A.; Krause, M.; Dietrich, J.P.; Müller, C. |
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Title |
Agricultural trade and tropical deforestation: interactions and related policy options |
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Journal Article |
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Year |
2014 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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Volume |
15 |
Issue |
8 |
Pages |
1757-1772 |
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Keywords |
Land-use change; Trade liberalisation; Tropical deforestation; Forest; protection; Agricultural productivity growth; land-use; brazilian amazon; co2 concentrations; carbon emissions; conservation; climate; mitigation; forests; impact; growth; Environmental Sciences & Ecology |
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Abstract |
The extensive clearing of tropical forests throughout past decades has been partly assigned to increased trade in agricultural goods. Since further trade liberalisation can be expected, remaining rainforests are likely to face additional threats with negative implications for climate mitigation and the local environment. We apply a spatially explicit economic land-use model coupled to a biophysical vegetation model to examine linkages and associated policies between trade and tropical deforestation in the future. Results indicate that further trade liberalisation leads to an expansion of deforestation in Amazonia due to comparative advantages of agriculture in South America. Globally, between 30 and 60 million ha (5-10 %) of tropical rainforests would be cleared additionally, leading to 20-40 Gt additional emissions by 2050. By applying different forest protection policies, those values could be reduced substantially. Most effective would be the inclusion of avoided deforestation into a global emissions trading scheme. Carbon prices corresponding to the concentration target of 550 ppm would prevent deforestation after 2020. Investing in agricultural productivity reduces pressure on tropical forests without the necessity of direct protection. In general, additional trade-induced demand from developed and emerging countries should be compensated by international efforts to protect natural resources in tropical regions. |
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2016-10-31 |
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English |
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1436-3798 1436-378x |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4810 |
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Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D. |
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Title |
Agriculture and climate change in global scenarios: why don’t the models agree |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
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45 |
Issue |
1 |
Pages |
85-85 |
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Keywords |
climate change impacts; economic models of agriculture; scenarios; system model; demand; cmip5 |
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Abstract |
Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty. |
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2016-10-31 |
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0169-5150 |
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Notes |
CropM, TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4796 |
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Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D. |
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Title |
Agriculture and climate change in global scenarios: why don’t the models agree |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
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45 |
Issue |
1 |
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85-101 |
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Keywords |
climate change impacts; economic models of agriculture; scenarios; system model; demand; CMIP5 |
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Abstract |
Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty. |
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0169-5150 |
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Notes |
CropM, TradeM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
4536 |
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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. |
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Title |
Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison |
Type |
Journal Article |
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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. |
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Volume |
111 |
Issue |
9 |
Pages |
3268-3273 |
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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 |
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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. |
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2016-10-31 |
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1091-6490 (Electronic) 0027-8424 (Linking) |
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CropM |
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Call Number |
MA @ admin @ |
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4801 |
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