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Integration of environmental drivers of fish early life stage survival within changing marine food webs
Stefan Koenigstein1,2, Stefan Gößling-Reisemann1, Felix Mark2, Hauke Reuter1,3, and Hans-Otto Pörtner1,2
University of Bremen, Bremen, Germany. E-mail: [email protected]
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Leibniz Center for Tropical Marine Ecology (ZMT), Bremen, Germany
Recruitment of marine fish stocks is affected by environmental factors, driving natural variations in stock
productivity and changes anticipated under climate change. While the effects of environmental drivers on fish early
life stages can be quantified in laboratory experiments, responses in real marine ecosystems will be influenced by
food availability, predation and other ecological factors. Integrative and process–based models can integrate these
different factors and help to understand their interactions.
We developed an integrative model of marine fish early life stages, incorporating detailed biological knowledge
about ontogenetic development, thermal response curves, and interactions with additional physiological stressors.
We incorporate experimentally quantified effects of different temperature and pCO2 regimes on fertilization, egg
and larval mortalities and development, and calibrate the model to oceanographic and ecological data to reproduce
empirical recruitment time series.
The model is parameterized for the Barents Sea cod, herring and capelin stocks. Confidence limits of projected
recruitment success under future ocean warming and acidification are given based on inter-individual variability in
experiments. Different scenarios of future food web changes and population adaptation are used to investigate to
which extent negative direct stressor effects may be compensated by higher-level processes. Finally, the
incorporation of mechanistic links between food uptake, growth, and survival is discussed.
This work demonstrates how models can incorporate experimentally quantified rates and empirical data, integrating
effects of multiple drivers among life stages, and estimating uncertainty associated with inter-individual and
ecological variation. It thus links individual effects to stock recruitment relevant for fisheries and ecosystem