A mechanistic explanation of the Sargasso Sea DMS “summer paradox” View Full Text


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Article Info

DATE

2011-11-10

AUTHORS

Luca Polimene, Stephen D. Archer, Momme Butenschön, J. Icarus Allen

ABSTRACT

In the Sargasso Sea, maximum dimethylsulfide (DMS) accumulation occurs in summer, concomitant with the minimum of chlorophyll and 2 months later than its precursor, dimethylsulfoniopropionate (DMSP). This phenomenon is often referred to as the DMS “summer paradox”. It has been previously suggested that the main agent triggering this pattern is increasing irradiance leading to light stress-induced DMS release from phytoplankton cells. We have developed a new model describing DMS(P) dynamics in the water column and used it to investigate how and to what extent processes other than light induced DMS exudation from phytoplankton, may contribute to the DMS summer paradox. To do this, we have conceptually divided the DMS “summer paradox” into two components: (1) the temporal decoupling between chlorophyll and DMSP and (2) the temporal decoupling between DMSP and DMS. Our results suggest that it is possible to explain the above cited patterns by means of two different dynamics, respectively: (1) a succession of phytoplankton types in the surface water and (2) the bacterially mediated DMSP(d) to DMS conversion, seasonally varying as a function of nutrient limitation. This work differs from previous modelling studies in that the presented model suggests that phytoplankton light-stress induced processes may only partially explain the summer paradox, not being able to explain the decoupling between DMSP and DMS, which is possibly the more challenging aspect of this phenomenon. Our study, therefore, provides an “alternative” explanation to the summer paradox further underlining the major role that bacteria potentially play in DMS production and fate. More... »

PAGES

243-255

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10533-011-9674-z

DOI

http://dx.doi.org/10.1007/s10533-011-9674-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1032612483


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