Abstract

Abstract. Dimethylsulfoniopropionate (DMSP) is produced in surface seawater by phytoplankton. Phytoplankton culture experiments have shown that nanoeucaryotes (NANO) display much higher mean DMSP-to-Carbon or DMSP-to-Chlorophyll (Chl) ratios than Prochlorococcus (PRO), Synechococcus (SYN) or diatoms (DIAT). Moreover, the DMSP-lyase activity of algae which cleaves DMSP into dimethylsulfide (DMS) is even more group specific than DMSP itself. Ship-based observations have shown at limited spatial scales, that sea surface DMS-to-Chl ratios (DMS:Chl) are dependent on the composition of phytoplankton groups. Here we use satellite remote sensing of Chl (from SeaWiFS) and of Phytoplankton Group Dominance (PGD from PHYSAT) with ship-based sea surface DMS concentrations (8 cruises in total) to assess this dependence on an unprecedented spatial scale. PHYSAT provides PGD (either NANO, PRO, SYN, DIAT, Phaeocystis (PHAEO) or coccolithophores (COC)) in each satellite pixel (1/4° horizontal resolution). While there are identification errors in the PHYSAT method, it is important to note that these errors are lowest for NANO PGD which we typify by high DMSP:Chl. In summer, in the Indian sector of the Southern Ocean, we find that mean DMS:Chl associated with NANO + PHAEO and PRO + SYN + DIAT are 13.6±8.4 mmol g−1 (n=34) and 7.3±4.8 mmol g−1 (n=24), respectively. That is a statistically significant difference (P<0.001) that is consistent with NANO and PHAEO being relatively high DMSP producers. However, in the western North Atlantic between 40° N and 60° N, we find no significant difference between the same PGD. This is most likely because coccolithophores account for the non-dominant part of the summer phytoplankton assemblages. Meridional distributions at 22° W in the Atlantic, and 95° W and 110° W in the Pacific, both show a marked drop in DMS:Chl near the equator, down to few mmol g−1, yet the basins exhibit different PGD (NANO in the Atlantic, PRO and SYN in the Pacific). In tropical and subtropical Atlantic and Pacific waters away from the equatorial and coastal upwelling, mean DMS:Chl associated with high and low DMSP producers are statistically significantly different, but the difference is opposite of that expected from culture experiments. Hence, in a majority of cases PGD is not of primary importance in controlling DMS:Chl variations. We therefore conclude that water-leaving radiance spectra obtained simultaneously from ocean color sensor measurements of Chl concentrations and dominant phytoplankton groups can not be used to predict global fields of DMS.

Highlights

  • Charlson et al (1987) proposed a potential climate feedback involving DMS emissions, aerosols, and cloud albedo

  • Sea surface Carbon or DMSP-toChlorophyll (Chl) concentrations and climatological (1998–2006) monthly Phytoplankton Group Dominance (PGD) data are used to illustrate the regional context of the field studies (Sect. 3.1) in three broad areas: Equatorial Pacific and eastern North Pacific Ocean, North and South Atlantic Ocean, and the Indian and Pacific sectors of the Southern Ocean

  • The PHYSAT tool allows the characterization at the global scale of dominant phytoplankton groups

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Summary

Introduction

Charlson et al (1987) proposed a potential climate feedback involving DMS emissions, aerosols, and cloud albedo. Predictions of the direct and indirect aerosol forcing due to changes in DMS emissions by year 2100 lies between −0.125 and +0.25 W m−2 This range was calculated from five independent simulations based on empirical surface ocean DMS concentration parameterizations or mechanistic models (Carslaw et al, 2010). In the diagnostic DMS model of Vallina et al (2007), the critical parameters are irradiance and mixed layer depth whereas in the study of Bopp et al (2003) the controlling parameter is the community structure of marine phytoplankton These diagnostic models are so conceptually different that it is hard to believe that they will reproduce present day seawater DMS concentrations with the same degree of skill as suggested by Halloran et al (2010). Tools are needed to evaluate global emissions of DMS to the atmosphere and refine the current parameterizations

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