Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model
Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 121 (2016): 1476–1501, doi:10.1002/2015JC011449. A new...
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Language: | English |
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ftwhoas:oai:darchive.mblwhoilibrary.org:1912/7994 2023-05-15T15:43:14+02:00 Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model Banas, Neil S. Zhang, Jinlun Campbell, Robert G. Sambrotto, Raymond N. Lomas, Michael W. Sherr, Evelyn B. Sherr, Barry F. Ashjian, Carin J. Stoecker, Diane K. Lessard, Evelyn J. 2016-02-20 https://hdl.handle.net/1912/7994 en_US eng John Wiley & Sons https://doi.org/10.1002/2015JC011449 Journal of Geophysical Research: Oceans 121 (2016): 1476–1501 https://hdl.handle.net/1912/7994 doi:10.1002/2015JC011449 Journal of Geophysical Research: Oceans 121 (2016): 1476–1501 doi:10.1002/2015JC011449 Phytoplankton bloom Climate change Bering Sea Microzooplankton Ecosystem model Phenology Article 2016 ftwhoas https://doi.org/10.1002/2015JC011449 2022-05-28T22:59:34Z Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 121 (2016): 1476–1501, doi:10.1002/2015JC011449. A new planktonic ecosystem model was constructed for the Eastern Bering Sea based on observations from the 2007–2010 BEST/BSIERP (Bering Ecosystem Study/Bering Sea Integrated Ecosystem Research Program) field program. When run with forcing from a data-assimilative ice-ocean hindcast of 1971–2012, the model performs well against observations of spring bloom time evolution (phytoplankton and microzooplankton biomass, growth and grazing rates, and ratios among new, regenerated, and export production). On the southern middle shelf (57°N, station M2), the model replicates the generally inverse relationship between ice-retreat timing and spring bloom timing known from observations, and the simpler direct relationship between the two that has been observed on the northern middle shelf (62°N, station M8). The relationship between simulated mean primary production and mean temperature in spring (15 February to 15 July) is generally positive, although this was found to be an indirect relationship which does not continue to apply across a future projection of temperature and ice cover in the 2040s. At M2, the leading direct controls on total spring primary production are found to be advective and turbulent nutrient supply, suggesting that mesoscale, wind-driven processes—advective transport and storminess—may be crucial to long-term trends in spring primary production in the southeastern Bering Sea, with temperature and ice cover playing only indirect roles. Sensitivity experiments suggest that direct dependence of planktonic growth and metabolic rates on temperature is less significant overall than the other drivers correlated with temperature described above. This work was supported by the National Science Foundation through ... Article in Journal/Newspaper Bering Sea Woods Hole Scientific Community: WHOAS (Woods Hole Open Access Server) Bering Sea Journal of Geophysical Research: Oceans 121 2 1476 1501 |
institution |
Open Polar |
collection |
Woods Hole Scientific Community: WHOAS (Woods Hole Open Access Server) |
op_collection_id |
ftwhoas |
language |
English |
topic |
Phytoplankton bloom Climate change Bering Sea Microzooplankton Ecosystem model Phenology |
spellingShingle |
Phytoplankton bloom Climate change Bering Sea Microzooplankton Ecosystem model Phenology Banas, Neil S. Zhang, Jinlun Campbell, Robert G. Sambrotto, Raymond N. Lomas, Michael W. Sherr, Evelyn B. Sherr, Barry F. Ashjian, Carin J. Stoecker, Diane K. Lessard, Evelyn J. Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
topic_facet |
Phytoplankton bloom Climate change Bering Sea Microzooplankton Ecosystem model Phenology |
description |
Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 121 (2016): 1476–1501, doi:10.1002/2015JC011449. A new planktonic ecosystem model was constructed for the Eastern Bering Sea based on observations from the 2007–2010 BEST/BSIERP (Bering Ecosystem Study/Bering Sea Integrated Ecosystem Research Program) field program. When run with forcing from a data-assimilative ice-ocean hindcast of 1971–2012, the model performs well against observations of spring bloom time evolution (phytoplankton and microzooplankton biomass, growth and grazing rates, and ratios among new, regenerated, and export production). On the southern middle shelf (57°N, station M2), the model replicates the generally inverse relationship between ice-retreat timing and spring bloom timing known from observations, and the simpler direct relationship between the two that has been observed on the northern middle shelf (62°N, station M8). The relationship between simulated mean primary production and mean temperature in spring (15 February to 15 July) is generally positive, although this was found to be an indirect relationship which does not continue to apply across a future projection of temperature and ice cover in the 2040s. At M2, the leading direct controls on total spring primary production are found to be advective and turbulent nutrient supply, suggesting that mesoscale, wind-driven processes—advective transport and storminess—may be crucial to long-term trends in spring primary production in the southeastern Bering Sea, with temperature and ice cover playing only indirect roles. Sensitivity experiments suggest that direct dependence of planktonic growth and metabolic rates on temperature is less significant overall than the other drivers correlated with temperature described above. This work was supported by the National Science Foundation through ... |
format |
Article in Journal/Newspaper |
author |
Banas, Neil S. Zhang, Jinlun Campbell, Robert G. Sambrotto, Raymond N. Lomas, Michael W. Sherr, Evelyn B. Sherr, Barry F. Ashjian, Carin J. Stoecker, Diane K. Lessard, Evelyn J. |
author_facet |
Banas, Neil S. Zhang, Jinlun Campbell, Robert G. Sambrotto, Raymond N. Lomas, Michael W. Sherr, Evelyn B. Sherr, Barry F. Ashjian, Carin J. Stoecker, Diane K. Lessard, Evelyn J. |
author_sort |
Banas, Neil S. |
title |
Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
title_short |
Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
title_full |
Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
title_fullStr |
Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
title_full_unstemmed |
Spring plankton dynamics in the Eastern Bering Sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
title_sort |
spring plankton dynamics in the eastern bering sea, 1971–2050 : mechanisms of interannual variability diagnosed with a numerical model |
publisher |
John Wiley & Sons |
publishDate |
2016 |
url |
https://hdl.handle.net/1912/7994 |
geographic |
Bering Sea |
geographic_facet |
Bering Sea |
genre |
Bering Sea |
genre_facet |
Bering Sea |
op_source |
Journal of Geophysical Research: Oceans 121 (2016): 1476–1501 doi:10.1002/2015JC011449 |
op_relation |
https://doi.org/10.1002/2015JC011449 Journal of Geophysical Research: Oceans 121 (2016): 1476–1501 https://hdl.handle.net/1912/7994 doi:10.1002/2015JC011449 |
op_doi |
https://doi.org/10.1002/2015JC011449 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
121 |
container_issue |
2 |
container_start_page |
1476 |
op_container_end_page |
1501 |
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1766377294179336192 |