Methodologies for simulating impacts of climate change on crop production
► We reviewed 221 papers that used crop models to assess impacts of climate change. ► Crops most frequently assessed were wheat, maize, soybean and rice. ► Models predominantly used radiation use efficiency-based approaches. ► Assumed low baseline [CO 2] may exaggerate projected impacts of increased...
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| Published in | Field crops research Vol. 124; no. 3; pp. 357 - 368 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
20.12.2011
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| Subjects | |
| Online Access | Get full text |
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| Abstract | ► We reviewed 221 papers that used crop models to assess impacts of climate change. ► Crops most frequently assessed were wheat, maize, soybean and rice. ► Models predominantly used radiation use efficiency-based approaches. ► Assumed low baseline [CO
2] may exaggerate projected impacts of increased [CO
2]. ► Coordinated data resources and model intercomparisons may enhance impact studies.
Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO
2] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO
2 involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO
2, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO
2] typically corresponded to conditions 10–30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO
2]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO
2] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation. |
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| AbstractList | Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO₂] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO₂ involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO₂, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO₂] typically corresponded to conditions 10–30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO₂]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO₂] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation. Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO sub(2] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO) sub(2) involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO sub(2, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO) sub(2)] typically corresponded to conditions 10-30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO sub(2]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO) sub(2)] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation. Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO(2)] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO(2) involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO(2), stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO(2)] typically corresponded to conditions 10-30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO(2)]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO(2)] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation. ► We reviewed 221 papers that used crop models to assess impacts of climate change. ► Crops most frequently assessed were wheat, maize, soybean and rice. ► Models predominantly used radiation use efficiency-based approaches. ► Assumed low baseline [CO 2] may exaggerate projected impacts of increased [CO 2]. ► Coordinated data resources and model intercomparisons may enhance impact studies. Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO 2] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO 2 involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO 2, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO 2] typically corresponded to conditions 10–30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO 2]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO 2] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation. |
| Author | Wall, Gerard W. White, Jeffrey W. Hoogenboom, Gerrit Kimball, Bruce A. |
| Author_xml | – sequence: 1 givenname: Jeffrey W. surname: White fullname: White, Jeffrey W. email: jeffrey.white@ars.usda.gov organization: ALARC, USDA-ARS, 21881 North Cardon Lane, Maricopa, AZ 85138, United States – sequence: 2 givenname: Gerrit surname: Hoogenboom fullname: Hoogenboom, Gerrit organization: Department of Biological and Agricultural Engineering, University of Georgia, Griffin, GA 30223-1797, United States – sequence: 3 givenname: Bruce A. surname: Kimball fullname: Kimball, Bruce A. organization: ALARC, USDA-ARS, 21881 North Cardon Lane, Maricopa, AZ 85138, United States – sequence: 4 givenname: Gerard W. surname: Wall fullname: Wall, Gerard W. organization: ALARC, USDA-ARS, 21881 North Cardon Lane, Maricopa, AZ 85138, United States |
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| Snippet | ► We reviewed 221 papers that used crop models to assess impacts of climate change. ► Crops most frequently assessed were wheat, maize, soybean and rice. ►... Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for... |
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| SubjectTerms | adaptation Adaptation, Agricultural impacts, Climate change, Crop growth simulation, Global warming, Modeling agricultural forecasts canopy carbon dioxide climate computer software corn crop models crop production crop rotation crops cultivars Europe food production food security global warming greenhouse gas emissions issues and policy Oryza sativa planting date prediction radiation use efficiency researchers rice risk risk factors Ruta graveolens soil resources soybeans stakeholders stomatal conductance temperature tillage Triticum aestivum United States wheat Zea mays |
| Title | Methodologies for simulating impacts of climate change on crop production |
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