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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.C.; Olesen, J.E.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Title  |
Crop modelling for integrated assessment of risk to food production from climate change |
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Journal Article |
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Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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72 |
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Pages |
287-303 |
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Keywords |
uncertainty; scaling; integrated assessment; risk assessment; adaptation; crop models; agricultural land-use; change adaptation strategies; farming systems simulation; agri-environmental systems; enrichment face experiment; high-temperature stress; change impacts; nitrogen dynamics; atmospheric co2; spring wheat |
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Abstract |
The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. |
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1364-8152 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
4521 |
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Author |
Porter, J.R.; Christensen, S. |
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Title |
Deconstructing crop processes and models via identities |
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Journal Article |
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Year |
2013 |
Publication |
Plant Cell and Environment |
Abbreviated Journal |
Plant Cell and Environment |
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36 |
Issue |
11 |
Pages |
1919-1925 |
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Keywords |
Biomass; Carbon Dioxide/pharmacology; Climate Change; Crops, Agricultural/drug effects/*physiology; *Models, Biological; Kaya-Porter identity; crop models; deconstruction; resource use efficiency |
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Abstract |
This paper is part review and part opinion piece; it has three parts of increasing novelty and speculation in approach. The first presents an overview of how some of the major crop simulation models approach the issue of simulating the responses of crops to changing climatic and weather variables, mainly atmospheric CO2 concentration and increased and/or varying temperatures. It illustrates an important principle in models of a single cause having alternative effects and vice versa. The second part suggests some features, mostly missing in current crop models, that need to be included in the future, focussing on extreme events such as high temperature or extreme drought. The final opinion part is speculative but novel. It describes an approach to deconstruct resource use efficiencies into their constituent identities or elements based on the Kaya-Porter identity, each of which can be examined for responses to climate and climatic change. We give no promise that the final part is correct’, but we hope it can be a stimulation to thought, hypothesis and experiment, and perhaps a new modelling approach. |
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2016-10-31 |
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0140-7791 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4799 |
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Author |
Bennetzen, E.H.; Smith, P.; Porter, J.R. |
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Title |
Decoupling of greenhouse gas emissions from global agricultural production: 1970-2050 |
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Journal Article |
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Year |
2016 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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22 |
Issue |
2 |
Pages |
763-781 |
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Keywords |
climate change; energy use; global agriculture; greenhouse gas emissions; land use; mitigation; sustainable intensification |
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Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land-use change and project potential future emissions. The novel Kaya-Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO2 -eq. yr(-1) and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop- and livestock-production, respectively. Except for the energy-use component of farming, emissions from all sources have increased less than agricultural production. Our projected business-as-usual range suggests that emissions may be further decoupled by 20-55% giving absolute agricultural emissions of 8.2-14.5 Pg CO2 -eq. yr(-1) by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food-system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis. |
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ISSN |
1354-1013 |
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CropM, ftnotmacsur |
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Call Number |
MA @ admin @ |
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4706 |
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Author |
Ghaley, B.B.; Porter, J.R. |
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Determination of biomass accumulation in mixed belts of Salix, Corylus and Alnus species in combined food and energy production system |
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Journal Article |
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2014 |
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Biomass and Bioenergy |
Abbreviated Journal |
Biomass and Bioenergy |
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63 |
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86-91 |
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allometric equation; destructive and non-destructive method; stool and biomass yield; bio-energy belts; food and fodder crops; short rotation woody crops; short-rotation forestry; willow; plantations; sweden; coppice; equations; growth; poplar; trees; yield |
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Given the energetic, demographic and the climatic challenges faced today, we designed a combined food and energy (CFE) production system integrating food, fodder and mixed belts of Salix, Alnus and Corylus sp. as bioenergy belts. The objective was to assess the shoot dry weight-stem diameter allometric relationship based on stem diameter at 10 (SD10) and 55 cm (SD55) from the shoot base in the mixed bioenergy belts. Allometric relations based on SD10 and SD55 explained 90-96% and 90-98% of the variation in shoot dry weights respectively with no differences between the destructive and the non-destructive methods. The individual stool yields varied widely among the species and within willow species with biomass yield range of 37.60-92.00 oven dry tons (ODT) ha (1) in 4-year growth cycle. The biomass yield of the bioenergy belt, predicted by allometric relations was 48.84 ODT ha 1 in 4-year growth cycle corresponding to 12.21 ODT ha (1) year (1). The relatively high biomass yield is attributed to the border effects and the ‘fertilizing effect’ of alder due to nitrogen fixation, benefitting other SWRC components. On termination of 4-year growth cycle, the bioenergy belts were harvested and the biomass yield recorded was 12.54 ODT ha (1) year (1), in close proximity to the biomass yield predicted by the allometric equations, lending confidence and robustness of the model for biomass yield determination in such integrated agro-ecosystem. (C) 2014 Elsevier Ltd. All rights reserved. |
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0961-9534 |
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CropM |
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MA @ admin @ |
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4624 |
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Author |
Toscano, P.; Ranieri, R.; Matese, A.; Vaccari, F.P.; Gioli, B.; Zaldei, A.; Silvestri, M.; Ronchi, C.; La Cava, P.; Porter, J.R.; Miglietta, F. |
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Title |
Durum wheat modeling: The Delphi system, 11 years of observations in Italy |
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Journal Article |
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Year |
2012 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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43 |
Issue |
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108-118 |
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Keywords |
durum wheat; crop modeling; yield forecasting; calibration; scenarios; decision-support-system; crop simulation-model; ceres-wheat; mediterranean environment; winter-wheat; scaling-up; variability; quality; growth; water |
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► Delphi system, based on AFRCWHEAT2 model, for durum wheat forecast. ► AFRCWHEAT2 model was calibrated and validated for three years. ► A scenario approach was applied to simulation of durum wheat yield. ► Operational mode for eleven years in rainfed and water limiting conditions. ► Accurate forecast as an useful planning tool. Crop models are frequently used in ecology, agronomy and environmental sciences for simulating crop and environmental variables at a discrete time step. The aim of this work was to test the predictive capacity of the Delphi system, calibrated and determined for each pedoclimatic factor affecting durum wheat during phenological development. at regional scale. We present an innovative system capable of predicting spatial yield variation and temporal yield fluctuation in long-term analysis, that are the main purposes of regional crop simulation study. The Delphi system was applied to simulate growth and yield of durum wheat in the major Italian supply basins (Basilicata, Capitanata, Marche, Tuscany). The model was validated and evaluated for three years (1995-1997) at 11 experimental fields and then used in operational mode for eleven years (1999-2009), showing an excellent/good accuracy in predicting grain yield even before maturity for a wide range of growing conditions in the Mediterranean climate, governed by different annual weather patterns. The results were evaluated on the basis of regression and normalized root mean squared error with known crop yield statistics at regional level. (c) 2012 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ftnotmacsur |
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MA @ admin @ |
Serial |
4596 |
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