A multi-model framework for the Arabidopsis life cycle

© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Bibliographische Detailangaben
Veröffentlicht in:Journal of experimental botany. - 1985. - 70(2019), 9 vom: 29. Apr., Seite 2463-2477
1. Verfasser: Zardilis, Argyris (VerfasserIn)
Weitere Verfasser: Hume, Alastair, Millar, Andrew J
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:Journal of experimental botany
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Agent-based modelling Arabidopsis computational modelling ecophysiology growth model life history population ecology systems biology
Beschreibung
Zusammenfassung:© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Linking our understanding of biological processes at different scales is a major conceptual challenge in biology and aggravated by differences in research methods. Modelling can be a useful approach to consolidating our understanding across traditional research domains. The laboratory model species Arabidopsis is very widely used to study plant growth processes and has also been tested more recently in ecophysiology and population genetics. However, approaches from crop modelling that might link these domains are rarely applied to Arabidopsis. Here, we combine plant growth models with phenology models from ecophysiology, using the agent-based modelling language Chromar. We introduce a simpler Framework Model of vegetative growth for Arabidopsis, FM-lite. By extending this model to include inflorescence and fruit growth and seed dormancy, we present a whole-life-cycle, multi-model FM-life, which allows us to simulate at the population level in various genotype × environment scenarios. Environmental effects on plant growth distinguish between the simulated life history strategies that were compatible with previously described Arabidopsis phenology. Our results simulate reproductive success that is founded on the broad range of physiological processes familiar from crop models and suggest an approach to simulating evolution directly in future
Beschreibung:Date Completed 13.07.2020
Date Revised 11.10.2023
published: Print
Citation Status MEDLINE
ISSN:1460-2431
DOI:10.1093/jxb/ery394