Modelling and parameter inference of predator-prey dynamics in heterogeneous environments using the direct integral approach

Itai Dattner*, Ezer Miller, Margarita Petrenko, Daniel E. Kadouri, Edouard Jurkevitch, Amit Huppert

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Most bacterial habitats are topographically complex in the micro scale. Important examples include the gastrointestinal and tracheal tracts, and the soil. Although there are myriad theoretical studies that explore the role of spatial structures on antagonistic interactions (predation, competition) among animals, there are many fewer experimental studies that have explored, validated and quantified their predictions. In this study, we experimentally monitored the temporal dynamic of the predatory bacterium Bdellovibrio bacteriovorus, and its prey, the bacterium Burkholderia stabilis in a structured habitat consisting of sand under various regimes of wetness. We constructed a dynamic model, and estimated its parameters by further developing the direct integral method, a novel estimation procedure that exploits the separability of the states and parameters in the model. We also verified that one of our parameter estimates was consistent with its known, directly measured value from the literature. The ability of the model to fit the data combined with realistic parameter estimates indicate that bacterial predation in the sand can be described by a relatively simple model, and stress the importance of prey refuge on predation dynamics in heterogeneous environments.

Original languageEnglish
Article number20160525
JournalJournal of the Royal Society Interface
Volume14
Issue number126
DOIs
StatePublished - 1 Jan 2017

Funding

FundersFunder number
Army Research Office
Defense Advanced Research Projects AgencyW911NF-15-2-0036
German-Israeli Foundation for Scientific Research and DevelopmentI-2390-304.6/2015
Israel Science Foundation387/15, 1583/12

    Keywords

    • Estimation
    • Heterogeneous environments
    • Optimization
    • Predator-prey model

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