DMS Production And Its Potential For A Bio-Feedback On Interdecadal Time Scales
Al Gabric
Faculty of Environmental Studies
Griffith University, Nathan, Australia, 4111
Dimethylsulfide is the most abundant form of volatile sulfur (S) in the ocean and is the main source of
biogenic reduced S to the global atmosphere (Andreae and Crutzen, 1997). The sea-to-air flux of S due
to DMS is currently estimated to be in the range (15 –33) Tg S yr-1 which constitutes about 40% of the
total atmospheric sulfate burden (Chin and Jacob, 1996). Once ventilated to the atmosphere, DMS is
rapidly oxidized to form non-sea-salt sulfate (nss-SO42- ) and methanesulfonate (MSA) aerosols.
Various species of phytoplankton produce differing amounts of dimethylsulfoniopropionate (DMSP),
the precursor to DMS. In general, coccolithophorids and small flagellates have higher intracellular
concentrations of DMSP, which is thought to act as an osmolyte in the algal cell. Shaw (1983) and then
Charlson et al. (1987) postulated links between DMS, atmospheric sulfate aerosols and global climate.
It was hypothesized that an increase in biogenically produced sulfate aerosols would lead to formation
of more cloud condensation nuclei (CCN), and brighter clouds. This change in cloud microphysics
could cool the earth’s surface and thus stabilize climate against perturbations due to greenhouse
warming. While phytoplankton are protagonists in this feed-back loop, recent advances in
understanding suggest that it is the entire food web that determines net DMS production and not just
algal taxonomy (Simo, 2001).
The proposed DMS-climate link, later called the CLAW hypothesis after the authors of the Charlson et
al. (1987) paper, stimulated a flurry of research in the 1990’s and several hundred scientific
publications, but is still to be verified. Attempts to assess the direction and magnitude of the DMSclimate feedback (Foley et al., 1991; Lawrence, 1993; Gabric et al., 1998) suggest the likelihood of a
small, negative feedback (stabilizing), with magnitude of order 10%, and considerable uncertainty.
These studies have all concluded that a feedback would occur at multi-decadal time-scales.
Unfortunately, seawater DMS time series long enough to enable an evaluation of the CLAW
hypothesis on interdecadal time scales are non-existent. Typically, oceanic data are collected over a
short-term (weeks) while the ship is under way. Blooms of marine phytoplankton are relatively short
lived, so assessing seasonality brings problems with respect to spatial coverage (vertical and horizontal)
and frequency of sampling.
Notable medium-term studies include the following: Leck et al. (1990) followed the changes in DMS
concentration and plankton abundance in the Baltic Sea during 18 months. Turner et al. (1996) took
near-surface samples at 120 geographically defined stations in the southern North Sea from a ship at
monthly intervals for a 9-month period. In contrast, Dacey et al. (1998) made measurements on
samples from 140 m deep vertical profiles at a station in the Sargasso Sea that was visited biweekly
over a 2-year period. Despite the contrasting trophic regimes, periods of elevated DMS concentration
were noted in all three studies. A strong seasonality in DMS was apparent in the temperate Baltic and
North Seas. For the oligotrophic Sargasso Sea station, the data revealed a correlation between DMS
and water temperature. Seasonal maxima for DMS were remarkably and consistently high for this site
(>10 nM), considering the extreme oligotrophy of this system.
Bates and Quinn (1997) collated data from 11 cruises in the Equatorial Pacific undertaken from 1982
to 1996. They reported that mean DMS levels during El Nino periods were not significantly different
from those in normal years. It should be noted that the cruise data were all short-term (< a month), so
that a proper interannual comparison was not possible. Despite the major physical changes that
occurred during the well-documented 1992 El Nino, the chemical and biological variability was small
(Murray et al. 1994). Even though primary production decreased during the ENSO event, this
appeared to be due to a reduction in the numbers of larger diatoms, which are not major DMS
producers.
In contrast to the Bates and Quinn (1997) study, Legrand and Feniet-Saigne (1991) found a good
correlation between El Nino events and high MSA concentrations in south polar snow layers deposited
over the 1922-1984 time period presumably due to enhanced DMS concentrations at high southern
latitudes during El Nino years. Legrand and Feniet-Saigne (1991) suggest this could have been due to
higher sea surface wind speed (implying increased sea-to-air exchange), or variations in sea-ice cover,
which can affect ocean salinity and hence the osmotic balance in the algal cell for which DMSP is
thought to have a regulating role.
Analysis of an 8-year time series of atmospheric measurements at Cape Grim, Tasmania (40°41'S, 144°
41'E), illustrates the strong seasonality in DMS, and has confirmed the connection between
atmospheric DMS and aerosol sulfur species in this region (Ayers et al., 1991; Boers et al., 1994). A
multi-decadal times eries of MSA observations at Cape Grim is shown in Figure 1. Although there is
considerable interannual variability in the magnitude of the MSA peak, the strong seasonality and early
January timing of the MSA maximum is remarkably consistent.
In the absence of long-term oceanic time series, modeling can provide some insights into the potential
for an interdecadal feedback. Gabric et al (in press) forced a regional DMS production model in the
Subantarctic Southern Ocean with data on temperature, cloud, wind speed and mixed layer depth
under enhanced greenhouse conditions derived from a coupled general circulation model. The GCM
and DMS models were run in transient mode over the time period 1961-2080. Interestingly, the results
( Figure 2) showed considerable interdecadal variability in the annual integrated DMS flux, suggesting
the potential for a significant DMS response to changes in the physical forcings.
Acknowledgements
The MSA data was kindly provided by Dr Greg Ayers, CSIRO Atmospheric Research (Melbourne).
This work was partially supported by an ARC Large Grant.
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Figure 1
MSA concentrations measured at Cape Grim (Tasmania) 1978-2000.
MSA Time Series Cape Grim
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Figure 2.
Model simulation of the trend in annual DMS flux in Subantarctic Southern Ocean
Trend in Annual Flux (Baseline Parameters)
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DMS Flux ( mole/m )
2000
Trend line:
y = 0.5696x + 1429.5
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