How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?

被引:62
|
作者
Durand, Jean-Louis [1 ]
Delusca, Kenel [1 ]
Boote, Ken [2 ]
Lizaso, Jon [3 ]
Manderscheid, Remy [4 ]
Weigel, Hans Johachim [4 ]
Ruane, Alex C. [5 ]
Rosenzweig, Cynthia [5 ]
Jones, Jim [2 ]
Ahuja, Laj [6 ]
Anapalli, Saseendran [6 ]
Basso, Bruno [7 ]
Baron, Christian [8 ]
Bertuzzi, Patrick [9 ]
Biernath, Christian [10 ]
Deryng, Delphine [11 ]
Ewert, Frank [12 ]
Gaiser, Thomas [12 ]
Gayler, Sebastian [13 ]
Heinlein, Florian [10 ]
Kersebaum, Kurt Christian [14 ]
Kim, Soo-Hyung [15 ]
Mueller, Christoph [16 ]
Nendel, Claas [14 ]
Olioso, Albert [17 ]
Priesack, Eckart [10 ]
Ramirez Villegas, Julian [18 ,19 ]
Ripoche, Dominique [9 ]
Rottert, Reimund P. [20 ]
Seidel, Sabine I. [12 ]
Srivastava, Amit [12 ]
Tao, Fulu [20 ,21 ]
Timlin, Dennis [22 ]
Twine, Tracy [23 ]
Wang, Enli [24 ]
Webber, Heidi [12 ]
Zhao, Zhigan [25 ]
机构
[1] INRA, URP3F, Lusignan, France
[2] Univ Florida, Gainesville, FL USA
[3] Tech Univ Madrid, CEIGRAM, Madrid, Spain
[4] Thunen Inst, Braunschweig, Germany
[5] NASA, Goddard Inst Space Studies, New York, NY 10025 USA
[6] USDA ARS, CPSRU, Stoneville, MS 38776 USA
[7] Michigan State Univ, Dept Geol Sci, E Lansing, MI 48824 USA
[8] CIRAD, UMR TETIS, Montpellier, France
[9] INRA, Agroclim, Avignon, France
[10] Helmholtz Zentrum Munchen, Inst Biochem Plant Pathol, Neuherberg, Germany
[11] Univ Chicago, Computat Inst, Chicago, IL 60637 USA
[12] Univ Bonn, Inst Crop Sci & Resource Conservat INRES, Bonn, Germany
[13] Univ Hohenheim, Sect Biogeophys, Inst Soil Sci & Land Evaluat, Stuttgart, Germany
[14] Leibniz Ctr Agr Landscape Res ZALF, Inst Landscape Syst Anal, Muncheberg, Germany
[15] Univ Washington, Sch Environm & Forest Sci, Seattle, WA 98195 USA
[16] Potsdam Inst Climate Impact Res, Potsdam, Germany
[17] INRA, EMMAH, Avignon, France
[18] Univ Leeds, Sch Earth & Environm, Leeds, W Yorkshire, England
[19] Colombia Int Ctr Trop Agr CIAT, CGIAR Res Program Climate Change Agr & Food Secur, Cali, Colombia
[20] Nat Resources Inst, Luke, Finland
[21] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
[22] USDA ARS, Crop Syst & Global Change Lab, Beltsville, MD USA
[23] Univ Minnesota, Dept Soil Water & Climate, Minneapolis, MN 55455 USA
[24] CSIRO, Land & Water, Black Mt, Australia
[25] China Agr Univ, Beijing, Peoples R China
关键词
Zea mays; Atmospheric carbon dioxide concentration; Multi-model ensemble; Stomata conductance; Grain number; Water use; CLIMATE-CHANGE; ELEVATED CO2; FOOD SECURITY; PHOTOSYNTHESIS; RESPONSES; IMPACTS; PRODUCTIVITY; ADAPTATION; GROWTH; LEAVES;
D O I
10.1016/j.eja.2017.01.002
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO2]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al., 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50% of models within a range of +/-1 Mg ha(-1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(-1). However under water deficit in one of the two years, the models captured only 30% of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:67 / 75
页数:9
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