Ming Wang1, Neil White1,2, Volker Grimm3,4,5, Helen Hofman6, David Doley7, Grant Thorp8, Bronwen Cribb9,10, Ella Wherritt1, Liqi Han1, John Wilkie5, Jim Hanan1. 1. The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD, Australia. 2. Department of Agriculture and Fisheries, Toowoomba, QLD, Australia. 3. Helmholtz Centre for Environmental Research-UFZ, Department of Ecological Modelling, Leipzig, Germany. 4. University of Potsdam, Institute for Biochemistry and Biology, Potsdam, Germany. 5. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany. 6. Department of Agriculture and Fisheries, Bundaberg Research Facility, Kalkie, QLD, Australia. 7. The University of Queensland, Sustainable Minerals Institute, Brisbane, QLD, Australia. 8. Plant & Food Research Australia Pty Ltd, Melbourne, VIC, Australia. 9. The University of Queensland, Centre for Microscopy and Microanalysis, Brisbane, QLD, Australia. 10. The University of Queensland, School of Biological Sciences, Brisbane, QLD, Australia.
Abstract
Background and Aims: Functional-structural plant (FSP) models have been widely used to understand the complex interactions between plant architecture and underlying developmental mechanisms. However, to obtain evidence that a model captures these mechanisms correctly, a clear distinction must be made between model outputs used for calibration and thus verification, and outputs used for validation. In pattern-oriented modelling (POM), multiple verification patterns are used as filters for rejecting unrealistic model structures and parameter combinations, while a second, independent set of patterns is used for validation. Methods: To test the potential of POM for FSP modelling, a model of avocado (Persea americana 'Hass') was developed. The model of shoot growth is based on a conceptual model, the annual growth module (AGM), and simulates photosynthesis and adaptive carbon allocation at the organ level. The model was first calibrated using a set of observed patterns from a published article. Then, for validation, model predictions were compared with a different set of empirical patterns from various field studies that were not used for calibration. Key Results: After calibration, our model simultaneously reproduced multiple observed architectural patterns. The model then successfully predicted, without further calibration, the validation patterns. The model supports the hypothesis that carbon allocation can be modelled as being dependent on current organ biomass and sink strength of each organ type, and also predicted the observed developmental timing of the leaf sink-source transition stage. Conclusions: These findings suggest that POM can help to improve the 'structural realism' of FSP models, i.e. the likelihood that a model reproduces observed patterns for the right reasons. Structural realism increases predictive power so that the response of an AGM to changing environmental conditions can be predicted. Accordingly, our FSP model provides a better but still parsimonious understanding of the mechanisms underlying known patterns of AGM growth.
Background and Aims: Functional-structural plant (FSP) models have been widely used to understand the complex interactions between plant architecture and underlying developmental mechanisms. However, to obtain evidence that a model captures these mechanisms correctly, a clear distinction must be made between model outputs used for calibration and thus verification, and outputs used for validation. In pattern-oriented modelling (POM), multiple verification patterns are used as filters for rejecting unrealistic model structures and parameter combinations, while a second, independent set of patterns is used for validation. Methods: To test the potential of POM for FSP modelling, a model of avocado (Persea americana 'Hass') was developed. The model of shoot growth is based on a conceptual model, the annual growth module (AGM), and simulates photosynthesis and adaptive carbon allocation at the organ level. The model was first calibrated using a set of observed patterns from a published article. Then, for validation, model predictions were compared with a different set of empirical patterns from various field studies that were not used for calibration. Key Results: After calibration, our model simultaneously reproduced multiple observed architectural patterns. The model then successfully predicted, without further calibration, the validation patterns. The model supports the hypothesis that carbon allocation can be modelled as being dependent on current organ biomass and sink strength of each organ type, and also predicted the observed developmental timing of the leaf sink-source transition stage. Conclusions: These findings suggest that POM can help to improve the 'structural realism' of FSP models, i.e. the likelihood that a model reproduces observed patterns for the right reasons. Structural realism increases predictive power so that the response of an AGM to changing environmental conditions can be predicted. Accordingly, our FSP model provides a better but still parsimonious understanding of the mechanisms underlying known patterns of AGM growth.
Authors: Volker Grimm; Eloy Revilla; Uta Berger; Florian Jeltsch; Wolf M Mooij; Steven F Railsback; Hans-Hermann Thulke; Jacob Weiner; Thorsten Wiegand; Donald L DeAngelis Journal: Science Date: 2005-11-11 Impact factor: 47.728
Authors: Ming Wang; Neil White; Jim Hanan; Di He; Enli Wang; Bronwen Cribb; Darren J Kriticos; Dean Paini; Volker Grimm Journal: Ann Bot Date: 2020-09-14 Impact factor: 4.357