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Author 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.
Title Agriculture and climate change in global scenarios: why don’t the models agree Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 85-85
Keywords climate change impacts; economic models of agriculture; scenarios; system model; demand; cmip5
Abstract (up) 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.
Address 2016-10-31
Corporate Author Thesis
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 4796
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Author 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.
Title Agriculture and climate change in global scenarios: why don’t the models agree Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 85-101
Keywords climate change impacts; economic models of agriculture; scenarios; system model; demand; CMIP5
Abstract (up) 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.
Address
Corporate Author Thesis
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 4536
Permanent link to this record
 

 
Author Rivington, M.
Title Agrimod: The Agricultural Modelling Knowledge Hub Website Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract (up) Agrimod is a new web-based Agricultural Modelling Knowledge Hub covering crop, livestock and trade models and the data they require, plus a wide range of supporting tools and resources. The purpose is to address the growing need, particularly in developing countries, of building national capabilities for researching agriculture and food security using models. To support research in this area, Agrimod provides a facility enabling users to access information and data needed to more successfully develop and employ agricultural modelling. Registered users can add new information about models, data, case studies, training, funding sources etc., whilst also being able to edit existing content  and contribute to discussion threads on key modelling issues. It will serve as a model, data and case study inventory. The vision is to unite the existing agricultural modelling community by providing a platform whereby models can be showcased, their applications discussed and new collaborations built, streamlining the process by which new model activities are developed. Moreover, Agrimod is intended to be a user–friendly information portal to people in other areas of research or new to agricultural modelling, looking to develop skills and acquire first-hand knowledge on agricultural modelling research. Thus Agrimod serves as a central knowledge hub for information on agricultural modelling activities worldwide and can be used by MACSUR as a complimentary information dissemination tool.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5051
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Author Weihermüller, L.
Title AgroC – Development and first evaluation of a model for carbon fluxes in agroecosystems Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract (up) Agroecosystems are highly sensitive to climate change. To predict and describe the processes, interactions and feedbacks in the plant-soil-system a model accounting for both compartments at an appropriate level of complexity is required.To describe the processes of crop development, crop growth, water flux, heat transport, and carbon cycling three process models were coupled and adjusted to each other: the one-dimensional soil water, heat and CO2 transport model SOILCO2, the carbon turnover model RothC, and the plant growth model SUCROS. Thereby, the main focus was on the full description of the CO2 flux into the atmosphere via plant and soil processes and finally on simulating the net ecosystem exchange. Additionally, the model was modified to work at the temporal resolution between 0.5 and 24 hours.For a first model evaluation a winter wheat data set obtained within the TERENO Rur catchment (North Rhine-Westphalia, Germany) during 2009 was used. For model initialisation soil carbon fractions were available. Plant specific parameters and soil properties were taken from literature. Measured soil water contents, soil temperatures, crop measurements, autotrophic, and heterotrophic chamber-based respiration measurements were used for validation and calibration.The coupled agroecosystem model AgroC described the crop development and heat transport well. Minor adjustments had to be made for carbon cycling, and to adapt the model to site specific conditions the soil hydraulic coefficients for soil water transport had to be determined by inverse modelling.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5052
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Author Porter, J.R.; Wratten, S.
Title National carbon stocks: Move on to a carbon currency standard Type Journal Article
Year 2014 Publication Nature Abbreviated Journal Nature
Volume 506 Issue Pages 295
Keywords
Abstract (up) Alongside Robert Costanza and colleagues’ plea to abandon gross domestic product as a measure of national success (see Nature 505, 283–285; 2014), we believe that there is an urgent need to change the way currencies are valued — by using a new ‘carbon standard’ that links economy to ecology. This would work in a similar way to the old gold-exchange standard, except that a country’s currency value would instead be determined by its saved and standing stocks of fossil and non-fossil carbon. Governments would need to decide whether to risk devaluing their currency by depleting carbon stocks — while still honouring a commitment to keep fossil-carbon stocks at 80% as a safeguard against extreme climate change. After the Second World War, huge investments radically altered the economies of the United States, the Soviet Union and the United Kingdom. In the face of climate change, it is now the global energy system that needs reinvention.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4635
Permanent link to this record