On the resolution requirements for accurately representing interactions between plant canopy structure and function in three-dimensional leaf-resolving models. Issue 2 (27th August 2021)

• Record Type: Journal Article
• Authors: Bailey, Brian N; Kent, Eric R
• Editors: Prusinkiewicz, Przemyslaw
• Is Part Of: In silico plants. Volume 3: Issue 2(2021)
• Publication Date: 2021-08-27
• Subjects: Entropy -- FSPM -- leaf-resolving model -- photosynthesis -- radiation; Plant physiology -- Periodicals; Botany -- Periodicals; Botany -- Mathematical models -- Periodicals; Crop science -- Periodicals; 580
• DOI: 10.1093/insilicoplants/diab023
• Languages: English
• ISSNs: 2517-5025

Abstract

Abstract: 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.