Abstract

Dimethylsulfide (DMS) is an important sulfur‐containing atmospheric trace gas of marine biogenic origin. DMS emitted from the oceans may be a precursor of tropospheric aerosols and cloud condensation nuclei (CCN), thereby affecting the Earth's radiative balance and possibly constituting a negative feedback to global warming, although this hypothesis is still somewhat controversial. The revised conceptual model of the marine pelagic food web gives a central role to planktonic bacteria. Recent experiments have shown that consumption of dissolved DMS by microbial metabolism may be more important than atmospheric exchange in controlling its concentration in surface waters and hence its ventilation to the atmosphere. In this paper we investigate the effect of the marine food web on cycling of dissolved DMS in surface waters during a phytoplankton bloom episode. A nitrogen‐based flow network simulation model has been used to analyze the relative importance of the various biological and chemical processes involved. The model predictions suggest that the concentration of DMS in marine surface waters is indeed governed by bacterial metabolism. Environmental factors that affect the bacterial compartment are thus likely to have a relatively large influence on dissolved DMS concentrations. The ecological succession is particularly sensitive to the ratio of phytoplankton to bacterial nutrient uptake rates as well the interaction between herbivore food chain and the microbial loop. Importantly for the design of field studies, the model predicts that peak DMS concentrations are achieved during the decline of the phytoplankton bloom with a typical time lag between peak DMS and peak phytoplankton biomass of 1 to 2 days. Significantly, the model predicts a relatively high DMS concentration persisting after the phytoplankton bloom due to excretion from large protozoa and zooplankton, which may be an additional explanation for the lack of correlation between DMS and chlorophyll a field measurements. Comparison of the model predictions has been made with tank algal bloom experiments.

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