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Departamento Gestión de Conocimiento, Monitoreo y Prospección
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Depth dependent relationships between temperature and ocean heterotrophic prokaryotic production
Indexado
WoS WOS:000457358000089
Scopus SCOPUS_ID:85008957428
DOI 10.3389/FMARS.2016.00090
Año 2016
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Marine prokaryotes play a key role in cycling of organic matter and nutrients in the ocean. Using a unique dataset (>14,500 samples), we applied a space-for-time substitution analysis to assess the temperature dependence of prokaryotic heterotrophic production (PHP) in epi- (0-200 m), meso- (201-1000 m) and bathypelagic waters (1001-4000 m) of the global ocean. Here, we show that the temperature dependence of PHP is fundamentally different between these major oceanic depth layers, with an estimated ecosystem-level activation energy (E-a) of 36 +/- 7 kJ mol(-1) for the epipelagic, 72 +/- 15 kJ mol(-1) for the mesopelagic and 274 +/- 65 kJ mol(-1) for the bathypelagic realm. We suggest that the increasing temperature dependence with depth is related to the parallel vertical gradient in the proportion of recalcitrant organic compounds. These E-a predict an increased PHP of about 5, 12, and 55% in the epi-, meso-, and bathypelagic ocean, respectively, in response to a water temperature increase by 1 degrees C. Hence, there is indication that a major thus far underestimated feedback mechanism exists between future bathypelagic ocean warming and heterotrophic prokaryotic activity.

Revista



Revista ISSN
Frontiers In Marine Science 2296-7745

Métricas Externas



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Disciplinas de Investigación



WOS
Marine & Freshwater Biology
Scopus
Oceanography
Aquatic Science
Global And Planetary Change
Water Science And Technology
Environmental Science (Miscellaneous)
Ocean Engineering
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Lonborg, Christian Hombre Australian Inst Marine Sci - Australia
Australian Institute of Marine Science - Australia
2 Cuevas, L. Antonio Hombre Universidad de Concepción - Chile
3 Reinthaler, Thomas Hombre Univ Vienna - Austria
Universität Wien - Austria
4 Herndl, Gerhard J. Hombre Univ Vienna - Austria
Royal Netherlands Inst Sea Res - Países Bajos
Universität Wien - Austria
Royal Netherlands Institute for Sea Research - NIOZ - Países Bajos
Royal Netherlands Institute for Sea Research - Países Bajos
5 Gasol, Josep M. Hombre ICM - España
CSIC - Instituto de Ciencias del Mar (ICM) - España
6 Moran, Xose Anxelu G. - King Abdullah Univ Sci & Technol - Arabia Saudí
King Abdullah University of Science and Technology - Arabia Saudí
7 Bates, Nicholas R. Hombre Bermuda Inst Ocean Sci - Bermudas
Bermuda Institute of Ocean Sciences - Bermudas
8 Alvarez-Salgado, Xose A. Hombre IIM - España
CSIC - Instituto de Investigaciones Marinas (IIM) - España

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Origen de Citas Identificadas



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Citas identificadas: Las citas provienen de documentos incluidos en la base de datos de DATACIENCIA

Citas Identificadas: 2.78 %
Citas No-identificadas: 97.22 %

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Citas identificadas: Las citas provienen de documentos incluidos en la base de datos de DATACIENCIA

Citas Identificadas: 2.78 %
Citas No-identificadas: 97.22 %

Financiamiento



Fuente
European Research Council
FP7/2007
Seventh Framework Programme
Carlsberg Foundation
Austrian Science Fund
Austrian Science Fund (FWF) Project
CNRS-INSU
PADOM project (Austrian Science Fund)
Malaspina expedition 2010
HOTMIX
European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC
Australian Institute of Marine Science (AIMS)
Australian Institute of Marine Science
Carlsbergfondet
Cariaco Basin Time-Series
Institut National des Sciences de l'Univers
Fiona Wood Foundation

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Agradecimientos



Agradecimiento
Financial support for this project was provided by the Australian Institute of Marine Science (AIMS) and a grant from the Carlsberg Foundation to CL. XA, XM and JG were funded by the Malaspina expedition 2010 (grant no CSD2008-00077) and HOTMIX (grant no CTM2011-30010-C02-02) projects. TR was supported by the PADOM project (Austrian Science Fund grant no P23221-B11). GH was funded by the Austrian Science Fund (FWF) project 14861309 and by the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC, grant agreement No. 268595 (MEDEA project). We thank A. Comes and the scientists and technicians on board Malaspina for their help. The British Oceanographic Data Centre (BODC) is acknowledged for supplying data for this analysis. We also acknowledge the large efforts made by thigh Ducldow and David L. Kirchman and their teams in generating the data of the US JGFOS program. "The data providers at the Bermuda Atlantic Time-Series Study (BATS) and Cariaco Basin Time-Series (CARIACO) are also acknowledged. A part of the Mediterranean data was obtained through the Biosope project funded through CNRS-INSU grants. Murray Logan is thanked for his input on using linear regression in R.
Financial support for this project was provided by the Australian Institute of Marine Science (AIMS) and a grant from the Carlsberg Foundation to CL. XA, XM and JG were funded by the Malaspina expedition 2010 (grant n° CSD2008-00077) and HOTMIX (grant n° CTM2011-30010-C02-02) projects. TR was supported by the PADOM project (Austrian Science Fund grant n° P23221-B11). GH was funded by the Austrian Science Fund (FWF) project I486-B09 and by the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement No. 268595 (MEDEA project). We thank A. Gomes and the scientists and technicians on board Malaspina for their help. The British Oceanographic Data Centre (BODC) is acknowledged for supplying data for this analysis. We also acknowledge the large efforts made by Hugh Ducklow and David L. Kirchman and their teams in generating the data of the US JGFOS program. The data providers at the Bermuda Atlantic Time-Series Study (BATS) and Cariaco Basin Time-Series (CARIACO) are also acknowledged. A part of the Mediterranean data was obtained through the Biosope project funded through CNRS-INSU grants. Murray Logan is thanked for his input on using linear regression in R.

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