Sven Petersen

For decades, hydrothermal activity along the Red Sea Rift was only inferred from metalliferous sediments and hot brines. Active hydrothermal fluid discharge was never directly observed from this young ocean basin, but could be key to understanding the evolution of hydrothermal vent fields and associated life. Here we report the discovery of widespread diffuse venting at Hatiba Mons, the largest axial volcano in the Red Sea. The active vent fields are composed of iron-oxyhydroxide mounds, host thriving microbial communities and are larger and more abundant than those known from any other (ultra) slow-spreading mid-ocean ridge. Diffuse venting, controlled by intense faulting, and the lack of vent-specific macrofauna, are likely causes for the abundant microbial mats that dominate and built up the hydrothermal mounds. These microbe-rich hydrothermal vent fields, occurring in a warm ocean, may be analogous to Precambrian environments hosting early life and supporting the formation of large iron deposits.

Accessible seafloor minerals located near mid‐ocean ridges are noticed to mitigate the projected metal demands of the net‐zero energy transition, promoting growing interest in quantifying the global distributions of seafloor massive sulfides (SMS). Mineral potentials are commonly estimated using geophysical and geological data that lastly rely on additional confirmation studies using sparsely available, locally limited, seafloor imagery, grab samples, and coring data. This raises the challenge of linking in situ confirmation data to geophysical data acquired at disparate spatial scales to obtain quantitative mineral predictions. Although multivariate data sets for marine mineral research are incessantly acquired, robust, integrative data analysis requires cumbersome workflows and experienced interpreters. We introduce an automated two‐step machine learning approach that integrates the mound detection through image segmentation with geophysical data. SMS predictors are subsequently clustered into distinct classes to infer marine mineral potentials that help guide future exploration. The automated workflow employs a U‐Net convolutional neural network to identify mound structures in bathymetry data and distinguishes different mound classes through the classification of mound architectures and magnetic signatures. Finally, controlled source electromagnetic data are utilized together with in situ sampling data to reassess predictions of potential SMS volumes. Our study focuses on the Trans‐Atlantic Geotraverse area, which is among the most explored SMS areas worldwide and includes 15 known SMS sites. The automated workflow classifies 14 of the 15 known mounds as exploration targets of either high or medium priority. This reduces the exploration area to less than 7% of the original survey area from 49 to 3.1 km².

Methylmercury is a potent toxin threatening the global population mainly through the consumption of marine fish. Hydrothermal venting directly delivers natural mercury to the ocean, yet its global flux remains poorly constrained. To determine the extent to which anthropogenic inputs have increased oceanic mercury levels, it is crucial to estimate natural mercury levels. Here we combine observations of vent fluids, plume waters, seawater and rock samples to quantify the release of mercury from the Trans-Atlantic Geotraverse hydrothermal vent at the Mid-Atlantic Ridge. The majority (67–95%) of the mercury enriched in the vent fluids (4,966 ± 497 pmol l⁻¹) is rapidly diluted to reach background seawater levels (0.80 pmol l⁻¹). A small Hg fraction (2.6–10%) is scavenged to the Trans-Atlantic Geotraverse mound rocks. Scaling up our findings and previous work, we propose a mercury flux estimate of 1.5–64.7 t per year from mid-ocean ridges. This hydrothermal flux is small in comparison to anthropogenic inputs. This suggests that most of the mercury present in the ocean must be of anthropogenic origin and that the implementation of emissions reduction measures outlined in the Minamata Convention could effectively reduce mercury levels in the global ocean and subsequently in marine fish.

The presence of active hydrothermal vent fields near residential areas and their possible link to volcanic activity poses a potential hazard to the environment, society, and the economy. By capitalizing on Autonomous Underwater Vehicle sampling methodologies and applying the Generalized Moments Method model for geological and physical processes in these environments, we shed light on the underlying dynamics shaping the physicochemical characteristics of the vents. In this study, we focus on the Northern Caldera of Santorini and, more specifically, on the recorded CTD data (Conductivity, Temperature, Depth). The data sets were collected in 2017 in Santorini using an Autonomous Underwater Vehicle during the GEOMAR POS510 mission. Our research shows that the active vent field within the caldera probably follows a multifractal behavior and exhibits a weak memory effect. Depth Profiles and Time Series show similar behavior among conductivity and temperature. The variance and moments of both parameters underline the existence of two different mechanisms governing the behavior of the vent field. Finally, the structure function shows that changes in the time series are described by a Cauchy–Lorentz distribution.

Submarine massive sulfide deposits on slow-spreading ridges are larger and longer-lived than deposits at fast-spreading ridges^1,2, likely due to more pronounced tectonic faulting creating stable preferential fluid pathways^3,4. The TAG hydrothermal mound at 26°N on the Mid-Atlantic Ridge (MAR) is a typical example located on the hanging wall of a detachment fault^5-7. It has formed through distinct phases of high-temperature fluid discharge lasting 10s to 100s of years throughout at least the last 50,000 years⁸ and is one of the largest sulfide accumulations on the MAR. Yet, the mechanisms that control the episodic behavior, keep the fluid pathways intact, and sustain the observed high heat fluxes of up to 1800 MW⁹ remain poorly understood. Previous concepts involved long-distance channelized high-temperature fluid upflow along the detachment^5,10 but that circulation mode is thermodynamically unfavorable¹¹ and incompatible with TAG's high discharge fluxes. Here, based on the joint interpretation of hydrothermal flow observations and 3-D flow modeling, we show that the TAG system can be explained by episodic magmatic intrusions into the footwall of a highly permeable detachment surface. These intrusions drive episodes of hydrothermal activity with sub-vertical discharge and recharge along the detachment. This revised flow regime reconciles problematic aspects of previously inferred circulation patterns and can be used as guidance to one critical combination of parameters that can generate substantive mineral systems.

The Trans‐Atlantic Geotraverse (TAG) hydrothermal field on the Mid‐Atlantic Ridge is one of the best‐studied hydrothermal systems to date. However, high‐resolution bathymetric data obtained in 2016 by an autonomous underwater vehicle (AUV) reveal new information about the distribution of active and inactive hydrothermal deposits, and their relation to structural features. The discovery of previously undocumented inactive vent sites contributes to a better understanding of the accumulation rates and the resource potential of seafloor massive sulfide deposits at slow‐spreading ridges. The interpretation of ship‐based and high‐resolution AUV‐based data sets allowed for the determination of the main tectonic stress regimes that have a first‐order control on the location and distribution of past and present hydrothermal activity. The data reveal the importance of cross‐cutting lineament populations and temporal variations in the prevalent stress regime. A dozen sulfide mounds contribute to a substantial accumulation of hydrothermal material (~29 Mt). The accumulation rate of ~1,500 t/yr is comparable to those of other modern seafloor vent fields. However, our observations suggest that the TAG segment is different from many other slow‐spreading ridge segments in its tectonic complexity, which confines sulfide formation into a relatively small area and is responsible for the longevity of the hydrothermal system and substantial mineral accumulation. The inactive and weakly active mounds contain almost 10 times the amount of material as the active high‐temperature mound, providing an important indication of the global resource potential for inactive seafloor massive sulfide deposits.

Back‐arc basins open in response to subduction processes, which cause extension in the upper plate, usually along trench‐parallel spreading axes. However, global seismic databases reveal that the majority of seismic events in the Lau Basin occur along transcurrent (strike‐slip) rather than extensional faults. To better characterize active deformation in this region, we compared centroid moment tensors (CMTs), calculated for large (Mw > 5), shallow (<30 km) seismic events, to the orientations of seafloor lineaments mapped throughout the Lau Basin. Ship‐based multibeam and satellite altimetry were combined with vertical gravity gradient data to create the lineament map. By comparing the possible focal planes of the CMTs to the orientations of the lineaments, the most likely fault plane solutions were selected, thus classifying the faults and establishing the nature of the highly variable stress regimes in the basin. We resolved the strike, dip, and dip direction of 308 faults and classified 258 additional structures by fault type. The analysis highlights a stress regime that is dominated by a combination of left‐lateral and right‐lateral strike‐slip faults, large‐scale transcurrent motion along rigid crustal‐scale fault zones, and nonrigid diffuse deformation along preexisting seafloor structures, with extension mainly limited to the tips of propagating rifts and spreading centers. By resolving many of the uncertain motions on the mapped lineaments of the Lau Basin, the CMT analysis addresses a number of questions concerning basin‐scale stress regimes and microplate development, complementing GPS measurements, and providing a more complete picture of the complexities of back‐arc basin development.