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Ecoregional analysis of nearshore sea-surface temperature in the north Pacific
Payne, M.C.; Brown, C.A.; Reusser, D.A.; Lee, H. (2012). Ecoregional analysis of nearshore sea-surface temperature in the north Pacific. PLoS One 7(1): e30105. dx.doi.org/10.1371/journal.pone.0030105
In: PLoS One. Public Library of Science: San Francisco. ISSN 1932-6203, more
Peer reviewed article  

Available in Authors 

Keyword
    Marine

Authors  Top 
  • Payne, M.C.
  • Brown, C.A.
  • Reusser, D.A.
  • Lee, H.

Abstract
    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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