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Oliveros-Ramos, R., Verley, P., Echevin, V., & Shin, Y. - J. (2017). A sequential approach to calibrate ecosystem models with multiple time series data. Progress in Oceanography, 151, 227–244. Résumé: 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. Mots-Clés: Data time series; ecosystem model; Humboldt Current Ecosystem; Inverse problems; Model calibration; Model fitting; Parameter estimation; Peru; Stochastic models http://www.umr-marbec.fr/r3fbas3/show.php?record=2057
Xing, L., Zhang, C., Chen, Y., Shin, Y. - J., Verley, P., Yu, H., et al. (2017). An individual-based model for simulating the ecosystem dynamics of Jiaozhou Bay, China. Ecological Modelling, 360(Supplement C), 120–131. Résumé: The Object-oriented Simulator of Marine ecoSystem Exploitation (OSMOSE) is one of the end-to-end models developed for ecosystem dynamic simulation and management strategy evaluation (MSE) in support of ecosystem-based fishery management (EBFM). However, the implementation of such integrated models has been limited due to lack of data, and their performance in advising fisheries management has been rarely evaluated. We developed an end-to-end model (OSMOSE-JZB) representing organisms of high and low trophic levels in the Jiaozhou Bay, a temperate bay in China with limited available data. We evaluated the performance of the model for simulating the ecosystem dynamics by comparing the model-predicted species biomass, size structure, trophic level, and mortality with relevant data derived from scientific surveys and literature. In general, the model-predicted species biomass and size ranges were consistent with observations. However, the size structure of the two dominant fish species showed some discrepancies between the model simulations and observations. The predicted mean trophic levels from OSMOSE-JZB were closer to the values derived from an Ecopath model of the same region, compared to the values derived from empirical isotope analysis. The model's output suggested that predation mortality appeared to be the main source of mortality for younger individuals compared to starvation and fishing mortality. This study suggests that the OSMOSE-JZB performs well under a data-poor situation and can be considered as a baseline ecosystem model for developing EBFM. Mots-Clés: end-to-end model; Jiaozhou Bay; Model calibration; Osmose; Performance evaluation http://www.umr-marbec.fr/r3fbas3/show.php?record=2186

Résumé: 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.

Mots-Clés: Data time series; ecosystem model; Humboldt Current Ecosystem; Inverse problems; Model calibration; Model fitting; Parameter estimation; Peru; Stochastic models

http://www.umr-marbec.fr/r3fbas3/show.php?record=2057

Résumé: The Object-oriented Simulator of Marine ecoSystem Exploitation (OSMOSE) is one of the end-to-end models developed for ecosystem dynamic simulation and management strategy evaluation (MSE) in support of ecosystem-based fishery management (EBFM). However, the implementation of such integrated models has been limited due to lack of data, and their performance in advising fisheries management has been rarely evaluated. We developed an end-to-end model (OSMOSE-JZB) representing organisms of high and low trophic levels in the Jiaozhou Bay, a temperate bay in China with limited available data. We evaluated the performance of the model for simulating the ecosystem dynamics by comparing the model-predicted species biomass, size structure, trophic level, and mortality with relevant data derived from scientific surveys and literature. In general, the model-predicted species biomass and size ranges were consistent with observations. However, the size structure of the two dominant fish species showed some discrepancies between the model simulations and observations. The predicted mean trophic levels from OSMOSE-JZB were closer to the values derived from an Ecopath model of the same region, compared to the values derived from empirical isotope analysis. The model's output suggested that predation mortality appeared to be the main source of mortality for younger individuals compared to starvation and fishing mortality. This study suggests that the OSMOSE-JZB performs well under a data-poor situation and can be considered as a baseline ecosystem model for developing EBFM.