Model-checking ecological state-transition graphs - Université d'Évry Access content directly
Journal Articles PLoS Computational Biology Year : 2022

Model-checking ecological state-transition graphs


Model-checking is a methodology developed in computer science to automatically assess the dynamics of discrete systems, by checking if a system modelled as a state-transition graph satisfies a dynamical property written as a temporal logic formula. The dynamics of ecosystems have been drawn as state-transition graphs for more than a century, ranging from state-and-transition models to assembly graphs. Model-checking can provide insights into both empirical data and theoretical models, as long as they sum up into state-transition graphs. While model-checking proved to be a valuable tool in systems biology, it remains largely underused in ecology apart from precursory applications. This article proposes to address this situation, through an inventory of existing ecological STGs and an accessible presentation of the model-checking methodology. This overview is illustrated by the application of model-checking to assess the dynamics of a vegetation pathways model. We select management scenarios by model-checking Computation Tree Logic formulas representing management goals and built from a proposed catalogue of patterns. In discussion, we sketch bridges between existing studies in ecology and available model-checking frameworks. In addition to the automated analysis of ecological state-transition graphs, we believe that defining ecological concepts with temporal logics could help clarify and compare them.
Fichier principal
Vignette du fichier
Thomas_etal_PLOS_computational_biol_2022_18_6.pdf (1.44 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

hal-03719082 , version 1 (13-07-2022)





Colin Thomas, Maximilien Cosme, Cédric Gaucherel, Franck Pommereau. Model-checking ecological state-transition graphs. PLoS Computational Biology, 2022, 18 (6), pp.e1009657. ⟨10.1371/journal.pcbi.1009657⟩. ⟨hal-03719082⟩
127 View
64 Download



Gmail Facebook X LinkedIn More