Cargando…
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: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
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 |
Sumario: | 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)]. |
---|