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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
Author(s) -
DAEWEL UTE,
PECK MYRON A.,
KÜHN WILFRIED,
ST. JOHN MICHAEL A.,
ALEKSEEVA IRINA,
SCHRUM CORINNA
Publication year - 2008
Publication title -
fisheries oceanography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 80
eISSN - 1365-2419
pISSN - 1054-6006
DOI - 10.1111/j.1365-2419.2008.00482.x
Subject(s) - sprat , biology , juvenile fish , foraging , population , vital rates , zooplankton , predation , ichthyoplankton , oceanography , ecology , environmental science , fishery , larva , population growth , fish <actinopterygii> , juvenile , demography , herring , sociology , geology
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.