MuSCA: a multi-scale model to explore carbon allocation in plants
F. ReyesiD, B. Pallas, C. Pradal, F. Vaggi, D. Zanotelli, M. Tagliavini, D. Gianelle, E. Costes
Abstract
Background and aimsCarbon allocation in plants is usually represented at a specific spatial scale, peculiar to each model. This makes the results obtained by different models, and the impact of their scale of representation, difficult to compare. In this work we developed a Multi Scale Carbon Allocation model (MuSCA) that can be applied at different, user-defined, topological scales of a plant, and used to assess the impact of each spatial scale on simulated results and computation time.\n\nMethodsModel multi-scale consistency and behavior were tested by applications on three realistic apple tree structures. Carbon allocation was computed at five spatial scales, spanning from the metamer (the finest scale, used as a reference) up to 1st order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data.\n\nKey ResultsThe model showed physiological coherence in representing competition for carbon assimilates. Results from intermediate values of the friction parameter best fitted the field data. For these, fruit growth simulated at the metamer scale (considered as a reference) differed from about 1% at growth unit scale up to 35% at first order branch scale. Generally, the coarser the spatial scale the more fruit growth diverged from the reference and the lower the obtained within-tree fruit growth variability. Coherence in the carbon allocated across scales was also differently impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time up to four orders of magnitude.\n\nConclusionsMuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation, suggesting that this factor should be carefully evaluated when using different carbon allocation models or comparing their results. Trades-off between computation time and prediction accuracy can be evaluated by changing topological scales.
02 /Specification & Classification
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