Effect of climate change on field crop production in California’s Central Valley
Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical...
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| Autor*in: |
Lee, Juhwan [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Systematik: |
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| Anmerkung: |
© Springer Science+Business Media B.V. 2011 |
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| Übergeordnetes Werk: |
Enthalten in: Climatic change - Springer Netherlands, 1977, 109(2011), Suppl 1 vom: 24. Nov., Seite 335-353 |
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| Übergeordnetes Werk: |
volume:109 ; year:2011 ; number:Suppl 1 ; day:24 ; month:11 ; pages:335-353 |
| Links: |
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| DOI / URN: |
10.1007/s10584-011-0305-4 |
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| Katalog-ID: |
OLC2062605471 |
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| 520 | |a Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. | ||
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10.1007/s10584-011-0305-4 doi (DE-627)OLC2062605471 (DE-He213)s10584-011-0305-4-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Lee, Juhwan verfasserin aut Effect of climate change on field crop production in California’s Central Valley 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2011 Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. Crop Yield Emission Scenario Wheat Yield Yield Change Biogeochemical Model De Gryze, Steven aut Six, Johan aut Enthalten in Climatic change Springer Netherlands, 1977 109(2011), Suppl 1 vom: 24. Nov., Seite 335-353 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:109 year:2011 number:Suppl 1 day:24 month:11 pages:335-353 https://doi.org/10.1007/s10584-011-0305-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_62 GBV_ILN_70 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4305 GBV_ILN_4325 RA 1000 AR 109 2011 Suppl 1 24 11 335-353 |
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10.1007/s10584-011-0305-4 doi (DE-627)OLC2062605471 (DE-He213)s10584-011-0305-4-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Lee, Juhwan verfasserin aut Effect of climate change on field crop production in California’s Central Valley 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2011 Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. Crop Yield Emission Scenario Wheat Yield Yield Change Biogeochemical Model De Gryze, Steven aut Six, Johan aut Enthalten in Climatic change Springer Netherlands, 1977 109(2011), Suppl 1 vom: 24. Nov., Seite 335-353 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:109 year:2011 number:Suppl 1 day:24 month:11 pages:335-353 https://doi.org/10.1007/s10584-011-0305-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_62 GBV_ILN_70 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4305 GBV_ILN_4325 RA 1000 AR 109 2011 Suppl 1 24 11 335-353 |
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effect of climate change on field crop production in california’s central valley |
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Effect of climate change on field crop production in California’s Central Valley |
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Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. © Springer Science+Business Media B.V. 2011 |
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Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. © Springer Science+Business Media B.V. 2011 |
| abstract_unstemmed |
Abstract Climate change under various emission scenarios is highly uncertain but is expected to affect agricultural crop production in the 21st century. However, we know very little about future changes in specific cropping systems under climate change in California’s Central Valley. Biogeochemical models are a useful tool to predict yields as it integrates crop growth, nutrient dynamics, hydrology, management and climate. For this study, we used DAYCENT to simulate changes in yield under A2 (medium-high) and B1 (low) emission scenarios. In total, 18 climate change predictions for the two scenarios were considered by applying different climate models and downscaling methods. The following crops were selected: alfalfa (hay), cotton, maize, winter wheat, tomato, and rice. Sunflower was also selected because it is commonly included in rotations with the other crops. By comparing the 11-year moving averages for the period 1956 to 2094, changes in yield were highly variable depending on the climate change scenarios across times. Furthermore, yield variance for the crops increased toward the end of the century due to the various degrees of climate model sensitivity. This shows that future climate, suggested by each of the emission scenarios, has a broad range of impacts on crop yields. Nevertheless, there was a general agreement in trends of yield changes. Under both A2 and B1, average modeled cotton, sunflower, and wheat yields decreased by approximately 2% to 9% by 2050 compared to the 2009 average yields. The other crops showed apparently no decreases in yield for the period 2010–2050. In comparison, all crop yields except for alfalfa significantly declined by 2094 under A2, but less under B1. Under A2, yields decreased in the following order: cotton (25%) > sunflower (24%) > wheat (14%) > rice (10%) > tomato and maize (9%). Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. Our results suggest that climate change will decrease California crop yields in the long-term, except for alfalfa, unless greenhouse gas emissions and resulting climate change is curbed and/or adaptation of new management practices and improved cultivars occurs. © Springer Science+Business Media B.V. 2011 |
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Under A2 compared to B1, the crop yield further decreased by a range of 2% (alfalfa) to 17% (cotton) by 2094, with more variation in yield change in the southern counties than the northern counties. The $ CO_{2} $ fertilization effects were predicted to potentially offset these yield declines (>30%) but may be overestimated. 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