Depth Dependent Relationships between Temperature and Ocean Heterotrophic Prokaryotic Production
Type
ArticleAuthors
Lønborg, ChristianCuevas, L. Antonio
Reinthaler, Thomas
Herndl, Gerhard J.
Gasol, Josep M.
Moran, Xose Anxelu G.

Bates, Nicholas R.
álvarez-Salgado, Xosé A.
KAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionMarine Science Program
Red Sea Research Center (RSRC)
Date
2016-06-07Permanent link to this record
http://hdl.handle.net/10754/622704
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Show full item recordAbstract
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) of 36 ± 7 kJ mol for the epipelagic, 72 ± 15 kJ mol for the mesopelagic and 274 ± 65 kJ mol 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 Ea 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°C. Hence, there is indication that a major thus far underestimated feedback mechanism exists between future bathypelagic ocean warming and heterotrophic prokaryotic activity.Citation
Lønborg C, Cuevas LA, Reinthaler T, Herndl GJ, Gasol JM, et al. (2016) Depth Dependent Relationships between Temperature and Ocean Heterotrophic Prokaryotic Production. Frontiers in Marine Science 3. Available: http://dx.doi.org/10.3389/fmars.2016.00090.Sponsors
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.Publisher
Frontiers Media SAJournal
Frontiers in Marine ScienceAdditional Links
http://journal.frontiersin.org/article/10.3389/fmars.2016.00090/fullae974a485f413a2113503eed53cd6c53
10.3389/fmars.2016.00090
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