A team of scientists from the Center for Marine Environmental Sciences (MARUM) at the University of Bremen, the Alfred Wegener Institute (AWI), Helmholtz Center for Polar and Marine Research in Bremerhaven, and the University of Utrecht studied an important part of the global sulfur cycle, the subseafloor microbial conversion of sulfate. To estimate how much sulfate is turned over by microorganisms worldwide they developed a novel computer model. Their findings differ significantly from previous estimates and are now published in the magazine Science .
Sulfate is an inorganic sulfur compound occurring in all natural waters. A group of so-called sulfate reducing microorganisms use sulfate for the oxidation of organic matter under anoxic conditions and obtain energy by “breathing” it. The activity of sulfate reducers is often identified by the characteristic smell of rotten eggs, which comes from its by-product, hydrogen sulfide. Sulfate reducers generate most of the naturally occurring hydrogen sulfide worldwide. In the seafloor this microbial process is ubiquitous and constitutes an important link between the cycles of sulfur and carbon. The study constrains which fraction of organic carbon reaching the ocean floor is oxidized by sulfate reduction versus buried in sediments on geological time scales, and thus addresses central questions pursued by members of the Deep Carbon Observatory. Sulfate reduction is also considered an essential energy source for microbial life in the deep biosphere and as such an important research target for the Deep Life Community.
The amount of sulfate converted annually by microorganisms in the seafloor is difficult to estimate on a global scale because the turnover rates vary strongly according to the marine environment. Previous estimates are rather coarse and do not include the spatial differences. “The goal of our study was to integrate these spatial differences in our calculations to get realistic values for the global rates of microbial sulfate reduction,” explains Dr. Marshall Bowles, postdoctoral scientist in the group of DCO’s Deep Life co-chair Kai-Uwe Hinrichs. Together with his colleague Dr. José Mogollón, formerly at AWI, now working at the University of Utrecht, Dr. Bowles and a team of scientists developed an artificial neural network that predicts sulfate reduction rates according to the local chemical and physical conditions, thus capturing various regional heterogeneities across the globe. The model was based on a vast accumulation of data collected over more than four decades by the international drilling programs Deep Sea Drilling Project, Ocean Drilling Program, and International Ocean Discovery Program.