Mechanistic modelling of daphnid-algae dynamics within a laboratory microcosm

Abstract : Our study describes the functioning of a 2-L laboratory microcosm of two species, daphnids (Daphnia magna) and microalgae (Pseudokirchneriella subcapitata), in two abiotic phases (water column and sedi- ment). We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae and growth, survival and grazing of daph- nids. We estimated model parameters by Bayesian inference, using simultaneously all data from multiple experiments specifically conducted for this study. Two types of model verifications were performed: (1) internal verification to validate model structure and parameter estimation method using all data simul- taneously; and (2) external verification to validate the ability of the model to be applied under new sediment conditions. For all parameters, we obtained biologically realistic values and reasonable uncer- tainties. The first verification step allowed us to confirm the modelled processes and the benefits of our parameter estimation method. The second one confirmed the ability of the model to describe microcosm functioning under different abiotic conditions. This innovative combination of mechanistic modelling and model-guided experiments revealed successful to understand the algae-daphnid microcosm func- tioning. This approach appears promising and can be applied to various issues in the ecological and ecotoxicological fields.
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Article dans une revue
Ecological Modelling, Elsevier, 2016, 320, pp.213-230. 〈10.1016/j.ecolmodel.2015.09.020〉
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Soumis le : mercredi 2 mars 2016 - 15:24:24
Dernière modification le : jeudi 19 avril 2018 - 14:49:47

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Dominique Lamonica, Ulysse Herbach, Frédéric Orias, Clément Bernard, Sandrine Charles, et al.. Mechanistic modelling of daphnid-algae dynamics within a laboratory microcosm. Ecological Modelling, Elsevier, 2016, 320, pp.213-230. 〈10.1016/j.ecolmodel.2015.09.020〉. 〈hal-01281672〉

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