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Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring

BACKGROUND: Individual-based biophysical larval models, initialized and parameterized by observations, enable numerical investigations of various factors regulating survival of young fish until they recruit into the adult population. Exponentially decreasing numbers in Northeast Arctic cod and Norwe...

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Autores principales: Vikebø, Frode B., Ådlandsvik, Bjørn, Albretsen, Jon, Sundby, Svein, Stenevik, Erling Kåre, Huse, Geir, Svendsen, Einar, Kristiansen, Trond, Eriksen, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3217961/
https://www.ncbi.nlm.nih.gov/pubmed/22110633
http://dx.doi.org/10.1371/journal.pone.0027367
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author Vikebø, Frode B.
Ådlandsvik, Bjørn
Albretsen, Jon
Sundby, Svein
Stenevik, Erling Kåre
Huse, Geir
Svendsen, Einar
Kristiansen, Trond
Eriksen, Elena
author_facet Vikebø, Frode B.
Ådlandsvik, Bjørn
Albretsen, Jon
Sundby, Svein
Stenevik, Erling Kåre
Huse, Geir
Svendsen, Einar
Kristiansen, Trond
Eriksen, Elena
author_sort Vikebø, Frode B.
collection PubMed
description BACKGROUND: Individual-based biophysical larval models, initialized and parameterized by observations, enable numerical investigations of various factors regulating survival of young fish until they recruit into the adult population. Exponentially decreasing numbers in Northeast Arctic cod and Norwegian Spring Spawning herring early changes emphasizes the importance of early life history, when ichthyoplankton exhibit pelagic free drift. However, while most studies are concerned with past recruitment variability it is also important to establish real-time predictions of ichthyoplankton distributions due to the increasing human activity in fish habitats and the need for distribution predictions that could potentially improve field coverage of ichthyoplankton. METHODOLOGY/PRINCIPAL FINDINGS: A system has been developed for operational simulation of ichthyoplankton distributions. We have coupled a two-day ocean forecasts from the Norwegian Meteorological Institute with an individual-based ichthyoplankton model for Northeast Arctic cod and Norwegian Spring Spawning herring producing daily updated maps of ichthyoplankton distributions. Recent years observed spawning distribution and intensity have been used as input to the model system. The system has been running in an operational mode since 2008. Surveys are expensive and distributions of early stages are therefore only covered once or twice a year. Comparison between model and observations are therefore limited in time. However, the observed and simulated distributions of juvenile fish tend to agree well during early fall. Area-overlap between modeled and observed juveniles September 1(st) range from 61 to 73%, and 61 to 71% when weighted by concentrations. CONCLUSIONS/SIGNIFICANCE: The model system may be used to evaluate the design of ongoing surveys, to quantify the overlap with harmful substances in the ocean after accidental spills, as well as management planning of particular risky operations at sea. The modeled distributions are already utilized during research surveys to estimate coverage success of sampled biota and immediately after spills from ships at sea.
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spelling pubmed-32179612011-11-21 Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring Vikebø, Frode B. Ådlandsvik, Bjørn Albretsen, Jon Sundby, Svein Stenevik, Erling Kåre Huse, Geir Svendsen, Einar Kristiansen, Trond Eriksen, Elena PLoS One Research Article BACKGROUND: Individual-based biophysical larval models, initialized and parameterized by observations, enable numerical investigations of various factors regulating survival of young fish until they recruit into the adult population. Exponentially decreasing numbers in Northeast Arctic cod and Norwegian Spring Spawning herring early changes emphasizes the importance of early life history, when ichthyoplankton exhibit pelagic free drift. However, while most studies are concerned with past recruitment variability it is also important to establish real-time predictions of ichthyoplankton distributions due to the increasing human activity in fish habitats and the need for distribution predictions that could potentially improve field coverage of ichthyoplankton. METHODOLOGY/PRINCIPAL FINDINGS: A system has been developed for operational simulation of ichthyoplankton distributions. We have coupled a two-day ocean forecasts from the Norwegian Meteorological Institute with an individual-based ichthyoplankton model for Northeast Arctic cod and Norwegian Spring Spawning herring producing daily updated maps of ichthyoplankton distributions. Recent years observed spawning distribution and intensity have been used as input to the model system. The system has been running in an operational mode since 2008. Surveys are expensive and distributions of early stages are therefore only covered once or twice a year. Comparison between model and observations are therefore limited in time. However, the observed and simulated distributions of juvenile fish tend to agree well during early fall. Area-overlap between modeled and observed juveniles September 1(st) range from 61 to 73%, and 61 to 71% when weighted by concentrations. CONCLUSIONS/SIGNIFICANCE: The model system may be used to evaluate the design of ongoing surveys, to quantify the overlap with harmful substances in the ocean after accidental spills, as well as management planning of particular risky operations at sea. The modeled distributions are already utilized during research surveys to estimate coverage success of sampled biota and immediately after spills from ships at sea. Public Library of Science 2011-11-16 /pmc/articles/PMC3217961/ /pubmed/22110633 http://dx.doi.org/10.1371/journal.pone.0027367 Text en Vikebø et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Vikebø, Frode B.
Ådlandsvik, Bjørn
Albretsen, Jon
Sundby, Svein
Stenevik, Erling Kåre
Huse, Geir
Svendsen, Einar
Kristiansen, Trond
Eriksen, Elena
Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title_full Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title_fullStr Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title_full_unstemmed Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title_short Real-Time Ichthyoplankton Drift in Northeast Arctic Cod and Norwegian Spring-Spawning Herring
title_sort real-time ichthyoplankton drift in northeast arctic cod and norwegian spring-spawning herring
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3217961/
https://www.ncbi.nlm.nih.gov/pubmed/22110633
http://dx.doi.org/10.1371/journal.pone.0027367
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