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Thesis . 2022
License: CC BY
Data sources: Datacite
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Doctoral thesis . 2022
License: CC BY
Data sources: ZENODO
https://doi.org/10.70675/08383...
Doctoral thesis . 2026 . Peer-reviewed
Data sources: Crossref
ZENODO
Thesis . 2022
License: CC BY
Data sources: Datacite
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Dealing with uncertainty in complex models ˸ an application to the OSMOSE ecosystem model of the northern Humboldt current system

Authors: Doris Criscely LUJÁN PAREDES;

Dealing with uncertainty in complex models ˸ an application to the OSMOSE ecosystem model of the northern Humboldt current system

Abstract

Faire face à l'incertitude dans les modèles complexes ˸ une application au modèle écosystémique OSMOSE dans l'écosystème nord du courant de Humboldt L'augmentation de la complexité des modèles permet d'obtenir une représentation plus réaliste des systèmes naturels. Cela peut également conduire à la création d'outils très complexes, dont il est nécessaire d'étudier les sources d'incertitudes, ainsi que le degré de confiance que nous pouvons accorder à leurs prédictions. Cette thèse porte sur l'étude de l'incertitude dans le modèle d'écosystème marin OSMOSE appliqué à l'écosystème nord du courant de Humboldt. Ce travail explore les différentes méthodes et outils disponibles pour les études d'incertitude. Nous avons mis en œuvre une analyse d'incertitude, dont les principaux résultats ont montré que l'incertitude d'un modèle complexe dépend de l'incertitude de quelques paramètres d'entrée, qu'elle se propage dans le temps et que, selon les sorties du modèle sélectionnées, celles-ci peuvent atténuer ou amplifier le niveau d'incertitude de ses résultats. Nous présentons également un protocole basé sur le critère de fiabilité des paramètres.Cela nous permet de classer les paramètres du modèle en fonction de la source d'information utilisée pour estimer leurs valeurs et d'attribuer un niveau d'incertitude aux paramètres du modèle. Enfin, nous proposons une série de recommandations pour les futures études d'incertitude utilisant des modèles complexes.

Keywords

sensitivity analysis, uncertainty quantification, biodiversity models, uncertainty analysis

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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