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Coupling ecosystem and individual‐based models to simulate the influence of environmental variability on potential growth and survival of larval sprat (Sprattus sprattus L.) in the North Sea
Authors:UTE DAEWEL  MYRON A PECK  WILFRIED KÜHN  MICHAEL A ST JOHN  IRINA ALEKSEEVA  CORINNA SCHRUM
Institution:1. Institute of Hydrobiology and Fisheries Science, University of Hamburg, Olbersweg 24, D‐22767 Hamburg, Germany;2. Institute of Oceanography, University of Hamburg, Bundesstr. 53, D‐20146 Hamburg, Germany;3. Geophysical Institute, University of Bergen, Allégaten 70, N‐5007 Bergen, Norway;4. Bjerknes Centre for Climate Research, Allégaten 70, N‐5007 Bergen, Norway;5. Department of Marine Fisheries, Danish Institute for Fisheries Research, Charlottenlund Castle, DK‐2920 Charlottenlund, Denmark
Abstract:To investigate the impact of changing environmental conditions in the North Sea on the distribution and survival of early life stages of a marine fish species, we employed a suite of coupled model components: (i) an Eulerian coupled hydrodynamic/ecosystem (Nutrients, Phyto‐, Zooplankton, Detritus) model to provide both 3‐D fields of hydrographical properties, and spatially and temporally variable prey fields; (ii) a Lagrangian transport model to simulate temporal changes in cohort distribution; and (iii) an individual‐based model (IBM) to depict foraging, growth and survival of fish early life stages. In this application, the IBM was parameterized for sprat (Sprattus sprattus L.) and included non‐feeding (egg and yolk‐sac larval) stages as well as foraging and growth subroutines for feeding (post‐yolk sac) larvae. Sensitivity analyses indicated that the angle of visual acuity, assimilation efficiency and the maximum food consumption rate were the most critical intrinsic model parameters. As an example, we applied this model system for 1990 in the North Sea. Results included not only information concerning the interplay of temperature and prey availability on larval fish survival and growth but also information on mechanisms underlying larval fish aggregation within frontal zones. The good agreement between modelled and in situ estimates of sprat distribution and growth rates in the German Bight suggested that interconnecting these different models provided an expedient tool to scrutinize basic processes in fish population dynamics.
Keywords:ECOSMO  North Sea  spatially‐explicit IBM  sprat
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