A sequential approach to calibrate ecosystem models with multiple time series data
Authored by Yunne-Jai Shin, Vincent Echevin, Ricardo Oliveros-Ramos, Philippe Verley
Date Published: 2017
DOI: 10.1016/j.pocean.2017.01.002
Sponsors:
European Union
Platforms:
R
Model Documentation:
Other Narrative
Model Code URLs:
Model code not found
Abstract
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. (C) 2017
Elsevier Ltd. All rights reserved.
Tags
Dynamics
Fishery management
Parameter estimation
Model Calibration
stochastic models
Sensitivity-analysis
Individual-based
model
Parameter-estimation
Ecosystem model
Peru
Southern benguela
Mackerel trachurus-murphyi
Humboldt current ecosystem
Growth-parameters
Inverse problems
Model fitting
Data time series
Humboldt
current ecosystem