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Novel multimodel ensemble approach to evaluate the sole effect of elevated CO2 on winter wheat productivity

机译：新颖的多模型集成方法评估CO2升高对冬小麦生产力的唯一影响

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摘要

Elevated carbon-dioxide concentration [eCO2] 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 CO2. It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO2. To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO2, 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 [eCO2] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO2].
机译：二氧化碳浓度升高[eCO2]是影响植物生长和产量的关键气候变化因素。传统上，作物建模工作已经在不考虑二氧化碳的情况下评估了气候参数对作物生长的影响。可以推测，新颖的多峰集成方法可以提高对eCO2的建模响应的准确性。为了证明作物模型的多模型集合在模拟eCO2方面的适用性，将APSIM，CropSyst，DSSAT，EPIC和STICS校准为观察数据，以了解作物物候，生物量和单产。在模型中，特别是在旱地（44％）与灌溉点（22％）相比，模拟生物量生产存在显着差异。在EPIC，干旱地区的平均产量最高（49％），在灌溉条件下最低（17％），APSIM和CropSyst观察到所有模型的产量均增加。对于合奏，旱地最大产量为45％，灌溉最大产量为最小22％。从我们的研究中得出的结论是，基于过程的作物模型在模拟作物对[eCO2]的响应时具有变异性，在水分胁迫条件下差异更大。我们建议使用集成来提高对[eCO2]的建模响应的准确性。

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