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Difference between revisions of "Eichinger 2010 Biogeosciences"

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{{Publication
{{Publication
|title=Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D (2010) Increased bacterial growth efficiency with environmental variability: Results from DOC degradation by bacteria in pure culture experiments. Biogeosciences  7:1861–76.
|title=Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D (2010) Increased bacterial growth efficiency with environmental variability: Results from DOC degradation by bacteria in pure culture experiments. Biogeosciences  7:1861–76.
|info=[http://www.biogeosciences.net/7/1861/2010/bg-7-1861-2010.pdf Biogeosciences]
|info=[http://www.biogeosciences.net/7/1861/2010/bg-7-1861-2010.html Biogeosciences Open Access]
|authors=Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D
|authors=Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D
|year=2010
|year=2010

Revision as of 12:31, 26 May 2015

Publications in the MiPMap
Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D (2010) Increased bacterial growth efficiency with environmental variability: Results from DOC degradation by bacteria in pure culture experiments. Biogeosciences 7:1861–76.

» Biogeosciences Open Access

Eichinger M, Sempere R, Gregori G, Charriere B, Poggiale JC, Lefevre D (2010) Biogeosciences

Abstract: This paper assesses how considering variation in DOC availability and cell maintenance in bacterial models affects Bacterial Growth Efficiency (BGE) estimations. For this purpose, we conducted two biodegradation experiments simultaneously. In experiment one, a given amount of substrate was added to the culture at the start of the experiment whilst in experiment two, the same amount of substrate was added, but using periodic pulses over the time course of the experiment. Three bacterial models, with different levels of complexity, (the Monod, Marr-Pirt and the dynamic energy budget – DEB – models), were used and calibrated using the above experiments. BGE has been estimated using the experimental values obtained from discrete samples and from model generated data. Cell maintenance was derived experimentally, from respiration rate measurements. The results showed that the Monod model did not reproduce the experimental data accurately, whereas the Marr-Pirt and DEB models demonstrated a good level of reproducibility, probably because cell maintenance was built into their formula. Whatever estimation method was used, the BGE value was always higher in experiment two (the periodically pulsed substrate) as compared to the initially one-pulsed-substrate experiment. Moreover, BGE values estimated without considering cell maintenance (Monod model and empirical formula) were always smaller than BGE values obtained from models taking cell maintenance into account. Since BGE is commonly estimated using constant experimental systems and ignore maintenance, we conclude that these typical methods underestimate BGE values. On a larger scale, and for biogeochemical cycles, this would lead to the conclusion that, for a given DOC supply rate and a given DOC consumption rate, these BGE estimation methods overestimate the role of bacterioplankton as CO2 producers.


O2k-Network Lab: FR Marseille Denis M, FR Marseille Gregori G


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Regulation: Substrate;glucose;TCA cycle"Substrate;glucose;TCA cycle" is not in the list (Aerobic glycolysis, ADP, ATP, ATP production, AMP, Calcium, Coupling efficiency;uncoupling, Cyt c, Flux control, Inhibitor, ...) of allowed values for the "Respiration and regulation" property. 


HRR: Oxygraph-2k