An end-to-end coupled model ROMS-N(2)P(2)Z(2)D(2)-OSMOSE of the southern Benguela foodweb: parameterisation, calibration and pattern-oriented validation

Type Article
Date 2014
Language English
Author(s) Travers-Trolet MorganeORCID1, Shin Yunne-Jai2, 3, Field J. G.3
Affiliation(s) 1 : IFREMER, Fishery Resources Lab, Boulogne Sur Mer, France.
2 : IRD, Res Inst Dev, CRH Ctr Mediterranean & Trop Fisheries Res, UMR Joint Res Unit EME Exploited Marine Ecosyst, Sete, France.
3 : Univ Cape Town, Marine Res Inst, ZA-7925 Cape Town, South Africa.
Source African Journal Of Marine Science (1814-232X) (Natl Inquiry Services Centre Pty Ltd), 2014 , Vol. 36 , N. 1 , P. 11-29
DOI 10.2989/1814232X.2014.883326
WOS© Times Cited 38
Note Online supplementary material: (1) Additional ROMS-N2P2Z2D2 equations and parameters, (2) maps of the spatial distribution of species modelled in OSMOSE, (3) graphs of the seasonality of fishing pressure and spawning for species modelled in OSMOSE, and (4) literature references of parameter values used for HTL (high trophic level) organisms in OSMOSE, are available as Supplementary Appendices S1–S4 to the online publication at
Keyword(s) individual-based model, model validation, pattern-oriented modelling, trophic interactions, two-way coupling
Abstract In order to better understand ecosystem functioning under simultaneous pressures (e.g. both climate change and fishing pressures), integrated modelling approaches are advocated. We developed an end-to-end model of the southern Benguela ecosystem by coupling the high trophic level model OSMOSE with a biophysical model (ROMS-N(2)P(2)Z(2)D(2)). OSMOSE is a spatial, multispecies, individual-based model simulating the whole life cycle of fish with fish schools interacting through opportunistic and size-based predation. It is linked to the biogeochemical model through the predation process; plankton groups are food for fish and fish apply a predation mortality on plankton. Here we describe the two-way coupling between the models and follow a pattern-oriented modelling approach to validate the simulations. At the individual level, model outputs are consistent with observed diets for several species from small pelagic fish to top predatory fish, although biases emerge from underestimation of macrozooplankton and lack of vertical structure. At the population level, the seasonality of the size structure is similar between the model and data. At the community level, the modelled trophic structure is consistent with the knowledge available for this ecosystem. The structure of the foodweb is an emergent property of the model, showing trophic links between species, their strength and the strong connectivity observed. We also highlight the capacity of this model for tracking indicators at various hierarchical levels.
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