Publications des scientifiques de l'IRD

Oliveros-Ramos R., Verley Philippe, Echevin Vincent, Shin Yunne-Jai. (2017). A sequential approach to calibrate ecosystem models with multiple time series data. Progress in Oceanography, 151, p. 227-244. ISSN 0079-6611.

Titre du document
A sequential approach to calibrate ecosystem models with multiple time series data
Année de publication
2017
Type de document
Article référencé dans le Web of Science WOS:000395609900015
Auteurs
Oliveros-Ramos R., Verley Philippe, Echevin Vincent, Shin Yunne-Jai
Source
Progress in Oceanography, 2017, 151, p. 227-244 ISSN 0079-6611
When models are aimed to support decision-making, their credibility is essential to consider. Model fitting to observed data is one major criterion to assess such credibility. However, due to the complexity of ecosystem models making their calibration more challenging, the scientific community has given more attention to the exploration of model behavior than to a rigorous comparison to observations. This work highlights some issues related to the comparison of complex ecosystem models to data and proposes a methodology for a sequential multi-phases calibration (or parameter estimation) of ecosystem models. We first propose two criteria to classify the parameters of a model: the model dependency and the time variability of the parameters. Then, these criteria and the availability of approximate initial estimates are used as decision rules to determine which parameters need to be estimated, and their precedence order in the sequential calibration process. The end-to-end (E2E) ecosystem model ROMS-PISCES-OSMOSE applied to the Northern Humboldt Current Ecosystem is used as an illustrative case study. The model is calibrated using an evolutionary algorithm and a likelihood approach to fit time series data of landings, abundance indices and catch at length distributions from 1992 to 2008. Testing different calibration schemes regarding the number of phases, the precedence of the parameters' estimation, and the consideration of time varying parameters, the results show that the multiple-phase calibration conducted under our criteria allowed to improve the model fit.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Ecologie, systèmes aquatiques [036]
Description Géographique
PEROU ; PACIFIQUE SUD ; HUMBOLDT COURANT
Localisation
Fonds IRD [F B010069394]
Identifiant IRD
fdi:010069394
Contact