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Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific

The quantification and description of sea surface temperature (SST) is critically important because it can influence the distribution, migration, and invasion of marine species; furthermore, SSTs are expected to be affected by climate change. To better understand present temperature regimes, we asse...

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Detalles Bibliográficos
Autores principales: Payne, Meredith C., Brown, Cheryl A., Reusser, Deborah A., Lee, Henry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3256220/
https://www.ncbi.nlm.nih.gov/pubmed/22253893
http://dx.doi.org/10.1371/journal.pone.0030105
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author Payne, Meredith C.
Brown, Cheryl A.
Reusser, Deborah A.
Lee, Henry
author_facet Payne, Meredith C.
Brown, Cheryl A.
Reusser, Deborah A.
Lee, Henry
author_sort Payne, Meredith C.
collection PubMed
description The quantification and description of sea surface temperature (SST) is critically important because it can influence the distribution, migration, and invasion of marine species; furthermore, SSTs are expected to be affected by climate change. To better understand present temperature regimes, we assembled a 29-year nearshore time series of mean monthly SSTs along the North Pacific coastline using remotely-sensed satellite data collected with the Advanced Very High Resolution Radiometer (AVHRR) instrument. We then used the dataset to describe nearshore (<20 km offshore) SST patterns of 16 North Pacific ecoregions delineated by the Marine Ecoregions of the World (MEOW) hierarchical schema. Annual mean temperature varied from 3.8°C along the Kamchatka ecoregion to 24.8°C in the Cortezian ecoregion. There are smaller annual ranges and less variability in SST in the Northeast Pacific relative to the Northwest Pacific. Within the 16 ecoregions, 31–94% of the variance in SST is explained by the annual cycle, with the annual cycle explaining the least variation in the Northern California ecoregion and the most variation in the Yellow Sea ecoregion. Clustering on mean monthly SSTs of each ecoregion showed a clear break between the ecoregions within the Warm and Cold Temperate provinces of the MEOW schema, though several of the ecoregions contained within the provinces did not show a significant difference in mean seasonal temperature patterns. Comparison of these temperature patterns shared some similarities and differences with previous biogeographic classifications and the Large Marine Ecosystems (LMEs). Finally, we provide a web link to the processed data for use by other researchers.
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spelling pubmed-32562202012-01-17 Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific Payne, Meredith C. Brown, Cheryl A. Reusser, Deborah A. Lee, Henry PLoS One Research Article The quantification and description of sea surface temperature (SST) is critically important because it can influence the distribution, migration, and invasion of marine species; furthermore, SSTs are expected to be affected by climate change. To better understand present temperature regimes, we assembled a 29-year nearshore time series of mean monthly SSTs along the North Pacific coastline using remotely-sensed satellite data collected with the Advanced Very High Resolution Radiometer (AVHRR) instrument. We then used the dataset to describe nearshore (<20 km offshore) SST patterns of 16 North Pacific ecoregions delineated by the Marine Ecoregions of the World (MEOW) hierarchical schema. Annual mean temperature varied from 3.8°C along the Kamchatka ecoregion to 24.8°C in the Cortezian ecoregion. There are smaller annual ranges and less variability in SST in the Northeast Pacific relative to the Northwest Pacific. Within the 16 ecoregions, 31–94% of the variance in SST is explained by the annual cycle, with the annual cycle explaining the least variation in the Northern California ecoregion and the most variation in the Yellow Sea ecoregion. Clustering on mean monthly SSTs of each ecoregion showed a clear break between the ecoregions within the Warm and Cold Temperate provinces of the MEOW schema, though several of the ecoregions contained within the provinces did not show a significant difference in mean seasonal temperature patterns. Comparison of these temperature patterns shared some similarities and differences with previous biogeographic classifications and the Large Marine Ecosystems (LMEs). Finally, we provide a web link to the processed data for use by other researchers. Public Library of Science 2012-01-11 /pmc/articles/PMC3256220/ /pubmed/22253893 http://dx.doi.org/10.1371/journal.pone.0030105 Text en This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Payne, Meredith C.
Brown, Cheryl A.
Reusser, Deborah A.
Lee, Henry
Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title_full Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title_fullStr Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title_full_unstemmed Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title_short Ecoregional Analysis of Nearshore Sea-Surface Temperature in the North Pacific
title_sort ecoregional analysis of nearshore sea-surface temperature in the north pacific
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3256220/
https://www.ncbi.nlm.nih.gov/pubmed/22253893
http://dx.doi.org/10.1371/journal.pone.0030105
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