ArticleJournal of experimental botany2019
A multi-model framework for the Arabidopsis life cycle.
Article in Journal of experimental botany, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Abundant clock proteins point to missing molecular regulation in the plant circadian clock.Molecular systems biology · 2025Article
- Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat.Genes · 2021Article
- Multiscale plant modeling: from genome to phenome and beyond.Emerging topics in life sciences · 2021Review
- Phenotyping in Arabidopsis and Crops-Are We Addressing the Same Traits? A Case Study in Tomato.Genes · 2020Review
- Molecular bases of responses to abiotic stress in trees.Journal of experimental botany · 2020Review
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Authors and funding
3 authors.
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Abstract
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.
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