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首页> 外文期刊>Global change biology >Responses to atmospheric CO2 concentrations in crop simulation models: a review of current simple and semicomplex representations and options for model development
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Responses to atmospheric CO2 concentrations in crop simulation models: a review of current simple and semicomplex representations and options for model development

机译:作物仿真模型对大气二氧化碳浓度的反应 - 对当前简单和半相色谱介绍及模型开发选项的综述

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Elevated atmospheric CO2 concentrations ([CO2]) cause direct changes in crop physiological processes (e. g. photosynthesis and stomatal conductance). To represent these CO2 responses, commonly used crop simulation models have been amended, using simple and semicomplex representations of the processes involved. Yet, there is no standard approach to and often poor documentation of these developments. This study used a bottom-up approach (starting with the APSIM framework as case study) to evaluate modelled responses in a consortium of commonly used crop models and illuminate whether variation in responses reflects true uncertainty in our understanding compared to arbitrary choices of model developers. Diversity in simulated CO2 responses and limited validation were common among models, both within the APSIM framework and more generally. Whereas production responses show some consistency up to moderately high [CO2] (around 700 ppm), transpiration and stomatal responses vary more widely in nature and magnitude (e. g. a decrease in stomatal conductance varying between 35% and 90% among models was found for [CO2] doubling to 700 ppm). Most notably, nitrogen responses were found to be included in few crop models despite being commonly observed and critical for the simulation of photosynthetic acclimation, crop nutritional quality and carbon allocation. We suggest harmonization and consideration of more mechanistic concepts in particular subroutines, for example, for the simulation of N dynamics, as a way to improve our predictive understanding of CO2 responses and capture secondary processes. Intercomparison studies could assist in this aim, provided that they go beyond simple output comparison and explicitly identify the representations and assumptions that are causal for intermodel differences. Additionally, validation and proper documentation of the representation of CO2 responses within models should be prioritized.
机译:升高的大气二氧化碳浓度([CO2])导致作物生理过程的直接变化(例如,光合作用和气孔电导)。要代表这些CO2响应,使用涉及的过程的简单和半相色谱表示,已经修改了常用的作物仿真模型。然而,没有标准的方法,通常差的这些发展的文件。本研究使用了自下而上的方法(从APSIM框架开始作为案例研究),以评估常用作物模型的联盟中的建模响应,并照亮响应的变化是否反映了我们的理解中的真正不确定性,而与模型开发人员的任意选择相比,我们的理解反映了真正的不确定性。模拟CO2响应的多样性和有限的验证在亚航空框架内的模型中是常见的。而生产响应显示出一致性高度高[CO2](约700ppm),蒸发和气孔响应在自然界中更广泛变化,并且发现了对[ CO2]加倍至700 ppm)。最值得注意的是,尽管常见地观察和对模拟光合作用,作物营养质量和碳分配致力于,但发现氮响应包括在几种作物模型中。我们建议统一和考虑特定子程序的更多机械概念,例如,用于模拟N动态,作为提高对CO2响应的预测理解和捕获二级过程的方法。互通的研究可以协助这一目标,只要他们超出了简单的产出比较,并明确识别对不同差异发生因果的表示和假设。此外,应优先考虑模型内的CO2响应表示的验证和正确文档。

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