三维叶片解析模型中准确表示植物冠层结构与功能相互作用的分辨率要求

IF 2.6 Q1 AGRONOMY in silico Plants Pub Date : 2021-07-01 DOI:10.1093/insilicoplants/diab023
B. Bailey, E. Kent
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引用次数: 2

摘要

尽管功能-结构植物模型(FSPM)已被提议作为更好地分析和预测植物结构和功能之间相互作用的工具,但仍不清楚需要什么空间分辨率来充分解决这种相互作用。植物冠层中相邻叶片投射的阴影在亚叶尺度上产生了极大的吸收辐射空间梯度,而在“叶片解析”植物模型中通常无法完全解析。这种未能解决尖锐辐射梯度的情况可能会传播到其他依赖的生物物理模型中,并导致对整个植物和冠层通量的过度预测,其误差明显高于统计“大叶”或混浊介质模型。低分辨率辐射梯度在吸收辐射的概率分布中产生扩散效应,并抹杀了冠层结构的影响,有效地破坏了叶片分辨率模型的原始目标。光合作用全冠层通量的误差随着LAI、投影面积分数G的增加而近似线性增加,并且随着入射漫射辐射分数的增加而对数减少。当每片叶子只使用一个离散元素时,整个冠层净CO2通量的误差可能超过100%。由于子叶分辨率引起的误差随着每个叶的元素数量的增加而呈指数级下降。这些结果促使人们更仔细地考虑子叶分辨率对模型误差的影响,这可能会促使分辨率相对于当前的常见做法有所提高。
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On the resolution requirements for accurately representing interactions between plant canopy structure and function in three-dimensional leaf-resolving models
While functional–structural plant models (FSPMs) have been proposed as a tool for better analysing and predicting interactions between plant structure and function, it is still unclear as to what spatial resolution is required to adequately resolve such interactions. Shadows cast by neighbouring leaves in a plant canopy create extremely large spatial gradients in absorbed radiation at the sub-leaf scale, which are usually not fully resolved in ‘leaf-resolving’ plant models. This failure to resolve sharp radiative gradients can propagate to other dependent biophysical models, and result in dramatic overprediction of whole-plant and -canopy fluxes with errors significantly higher than that of a statistical ‘big leaf’ or turbid medium model. Under-resolving radiative gradients creates a diffusive effect in the probability distribution of absorbed radiation, and smears out the effect of canopy structure, effectively undermining the original goal of a leaf-resolving model. Errors in whole-canopy fluxes of photosynthesis increased approximately linearly with increasing LAI, projected area fraction G, and decreased logarithmically as the fraction of incoming diffuse radiation was increased. When only one discrete element per leaf was used, errors in whole-canopy net CO2 flux could be in excess of 100 %. Errors due to sub-leaf resolution decreased exponentially as the number of elements per leaf was increased. These results prompt closer consideration of the impact of sub-leaf resolution on model errors, which is likely to prompt an increase in resolution relative to current common practice.
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来源期刊
in silico Plants
in silico Plants Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
4.70
自引率
9.70%
发文量
21
审稿时长
10 weeks
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