TY - JOUR
T1 - How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?
AU - Durand, Jean Louis
AU - Delusca, Kenel
AU - Boote, Ken
AU - Lizaso, Jon
AU - Manderscheid, Remy
AU - Weigel, Hans Johachim
AU - Ruane, Alex C.
AU - Rosenzweig, Cynthia
AU - Jones, Jim
AU - Ahuja, Laj
AU - Anapalli, Saseendran
AU - Basso, Bruno
AU - Baron, Christian
AU - Bertuzzi, Patrick
AU - Biernath, Christian
AU - Deryng, Delphine
AU - Ewert, Frank
AU - Gaiser, Thomas
AU - Gayler, Sebastian
AU - Heinlein, Florian
AU - Kersebaum, Kurt Christian
AU - Kim, Soo Hyung
AU - Müller, Christoph
AU - Nendel, Claas
AU - Olioso, Albert
AU - Priesack, Eckart
AU - Villegas, Julian Ramirez
AU - Ripoche, Dominique
AU - Rötter, Reimund P.
AU - Seidel, Sabine I.
AU - Srivastava, Amit
AU - Tao, Fulu
AU - Timlin, Dennis
AU - Twine, Tracy
AU - Wang, Enli
AU - Webber, Heidi
AU - Zhao, Zhigan
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/10
Y1 - 2018/10
N2 - 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 Thünen 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.
AB - 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 Thünen 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.
KW - Atmospheric carbon dioxide concentration
KW - Grain number
KW - Multi-model ensemble
KW - Stomatal conductance
KW - Water use
KW - Zea mays
UR - http://www.scopus.com/inward/record.url?scp=85010214519&partnerID=8YFLogxK
U2 - 10.1016/j.eja.2017.01.002
DO - 10.1016/j.eja.2017.01.002
M3 - Article
AN - SCOPUS:85010214519
SN - 1161-0301
VL - 100
SP - 67
EP - 75
JO - European Journal of Agronomy
JF - European Journal of Agronomy
ER -