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We employed a coupled biological–physical, individual-based model (IBM) to estimate spatial and temporal changes in larval fish habitat suitability (the potential for areas to support survival and high rates of growth) of the German Bight, southern North Sea. In this Lagrangian approach, larvae were released into a size-structured prey field that was constructed from in situ measurements of the abundance and prosome lengths of stages of three copepods (Acartia spp., Temora longicornis, Pseudocalanus elongatus) collected on a station grid repeatedly sampled from February to October 2004. The choice of prey species and the model parameterisations for larval fish foraging and growth were based on field data collected for sprat (Sprattus sprattus) and other clupeid larvae. A series of 10-day simulations were conducted using 20 release locations to quantify spatial–temporal differences in projected larval sprat growth rates (mm d− 1) for mid-April, mid-May and mid-June 2004. Based upon an optimal foraging approach, modeled sprat growth rates agreed well with those measured in situ using larval fish ototliths. On the German GLOBEC station grid, our model predicted areas that were mostly unsuitable habitats (areas of low growth potential), e.g. north of the Frisian Islands, and others that were consistently suitable habitats (areas that had high growth potential), e.g. in the inner German Bight. In some instances, modelled larvae responded rapidly (~ 5 days) to changing environmental characteristics experienced along their drift trajectory, a result that appears reasonable given the dynamic nature of frontal regions such as our study area in the southern North Sea.

We employed a coupled biological–physical, individual-based model (IBM) to estimate spatial and temporal changes in larval fish habitat suitability (the potential for areas to support survival and high rates of growth) of the German Bight, southern North Sea. In this Lagrangian approach, larvae were released into a size-structured prey field that was constructed from in situ measurements of the abundance and prosome lengths of stages of three copepods (Acartia spp., Temora longicornis, Pseudocalanus elongatus) collected on a station grid repeatedly sampled from February to October 2004. The choice of prey species and the model parameterisations for larval fish foraging and growth were based on field data collected for sprat (Sprattus sprattus) and other clupeid larvae. A series of 10-day simulations were conducted using 20 release locations to quantify spatial–temporal differences in projected larval sprat growth rates (mm d− 1) for mid-April, mid-May and mid-June 2004. Based upon an optimal foraging approach, modeled sprat growth rates agreed well with those measured in situ using larval fish ototliths. On the German GLOBEC station grid, our model predicted areas that were mostly unsuitable habitats (areas of low growth potential), e.g. north of the Frisian Islands, and others that were consistently suitable habitats (areas that had high growth potential), e.g. in the inner German Bight. In some instances, modelled larvae responded rapidly (~ 5 days) to changing environmental characteristics experienced along their drift trajectory, a result that appears reasonable given the dynamic nature of frontal regions such as our study area in the southern North Sea.