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Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity
Elevated carbon-dioxide concentration [eCO(2)] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO(2). It is conjectured that a novel multimodal ensemble approach ma...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534615/ https://www.ncbi.nlm.nih.gov/pubmed/31127159 http://dx.doi.org/10.1038/s41598-019-44251-x |
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author | Ahmed, Mukhtar Stöckle, Claudio O. Nelson, Roger Higgins, Stewart Ahmad, Shakeel Raza, Muhammad Ali |
author_facet | Ahmed, Mukhtar Stöckle, Claudio O. Nelson, Roger Higgins, Stewart Ahmad, Shakeel Raza, Muhammad Ali |
author_sort | Ahmed, Mukhtar |
collection | PubMed |
description | Elevated carbon-dioxide concentration [eCO(2)] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO(2). It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO(2). To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO(2), APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO(2)] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO(2)]. |
format | Online Article Text |
id | pubmed-6534615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65346152019-06-03 Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity Ahmed, Mukhtar Stöckle, Claudio O. Nelson, Roger Higgins, Stewart Ahmad, Shakeel Raza, Muhammad Ali Sci Rep Article Elevated carbon-dioxide concentration [eCO(2)] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO(2). It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO(2). To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO(2), APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO(2)] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO(2)]. Nature Publishing Group UK 2019-05-24 /pmc/articles/PMC6534615/ /pubmed/31127159 http://dx.doi.org/10.1038/s41598-019-44251-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ahmed, Mukhtar Stöckle, Claudio O. Nelson, Roger Higgins, Stewart Ahmad, Shakeel Raza, Muhammad Ali Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title | Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title_full | Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title_fullStr | Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title_full_unstemmed | Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title_short | Novel multimodel ensemble approach to evaluate the sole effect of elevated CO(2) on winter wheat productivity |
title_sort | novel multimodel ensemble approach to evaluate the sole effect of elevated co(2) on winter wheat productivity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534615/ https://www.ncbi.nlm.nih.gov/pubmed/31127159 http://dx.doi.org/10.1038/s41598-019-44251-x |
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