Magnetic studies of the seafloor have produced the first empirical model of a hydrothermal upflow zone.

Van Dover, C. L. 2011. Mining seafloor massive sulphides and biodiversity: what is at risk? – ICES Journal of Marine Science, 68: 341–348. Scientific exploration of the deep sea in the late 1970s led to the discovery of seafloor massive sulphides at hydrothermal vents. More recently, sulphide deposits containing high grades of ore have been discovered in the southwest Pacific. In addition to metal-rich ores, hydrothermal vents host ecosystems based on microbial chemoautotrophic primary production, with endemic invertebrate species adapted in special ways to the vent environment. Although there has been considerable effort to study the biology and ecology of vent systems in the decades since these systems were first discovered, there has been limited attention paid to conservation issues. Three priority recommendations for conservation science at hydrothermal vent settings are identified here: (i) determine the natural conservation units for key species with differing life histories; (ii) identify a set of first principles for the design of preservation reference areas and conservation areas; (iii) develop and test methods for effective mitigation and restoration to enhance the recovery of biodiversity in sulphide systems that may be subject to open-cut mining.

The Nankai Trough is an active convergent region in southwest Japan and mega-thrust earthquakes have repeatedly occurred in some areas of its plate-boundary interface. Generation of mega-thrust earthquakes is inferred to be related to the existence of water. The resistivity structure is very sensitive to the existence of water. For that reason, it is important to obtain the resistivity image around the rupture area of mega-thrust earthquakes. We carried out land and marine magnetotelluric surveys in the Kii Peninsula and the offshore Kii Peninsula where the 1944 Tonankai earthquake occurred. We constructed a 2D resistivity model using an inversion technique. The modeled resistivity structure portrayed the Philippine Sea Plate as a resistive region. However, its resistivity becomes more conductive as the plate subducts, showing 10 Ω-m around the down-dip limit. These characteristics are considered to relate to the water. Therefore, we infer that water might control the generation of mega-thrust earthquakes.

Seafloor massive sulfide (SMS) deposits have attracted growing interest and become the focus of current seafloor mineral exploration. One key challenge is to delineate potential SMS accumulations and estimate their quantity and quality for prospective resource mining. Recently, geophysical electromagnetic methods which are routinely used for land-based mineral exploration are being adapted to detect and assess SMS occurrences by imaging their conductivity distributions. However, the rough seafloor topography and electrical anisotropy of the seafloor formations encountered in practical surveys pose challenges for reliable data interpretation, and recent studies have revealed that the rough bathymetry could cause measurable distortions. Here, we consider a fixed-offset marine controlled-source electromagnetic method (CSEM) for SMS exploration, and investigate the effects of electrical anisotropy of sedimentary formations through numerical simulations for marine CSEM surveys aiming at conductive targets in the shallow regions of the seafloor. Numerical results demonstrate that the presence of electrical anisotropy could impose significant influence on fixed-offset marine CSEM data and suggest that the distortions should be sufficiently accounted for reliable data interpretation, thus lending confidence to subsequent quantification of available SMS minerals.

Seafloor massive sulfide (SMS) deposits are of increasing economic interest in order to satisfy the relentless growth in worldwide metal demand. The Trans‐Atlantic Geotraverse (TAG) hydrothermal field at 26°N on the Mid‐Atlantic Ridge hosts several such deposits. This study presents new controlled source electromagnetic, bathymetric, and magnetic results from the TAG field. Potential SMS targets were selected based on their surface expressions in high‐resolution bathymetric data. High‐resolution reduced‐to‐the‐pole magnetic data show negative anomalies beneath and surrounding the SMS deposits, revealing large areas of hydrothermal alteration. Controlled source electromagnetic data, sensitive to the electrical conductivity of SMS mineralization, further reveal a maximum thickness of up to 80 m and conductivities of up to 5 S/m. SMS samples have conductivities of up to a few thousand Siemens per meter, suggesting that remotely inferred conductivities represent an average of metal sulfide ores combined with silicified and altered host basalt that likely dominates at greater depths.

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.

Introduction: Although, there is an increasing focus on inactive or extinct seafloor massive sulfide (SMS) deposits driven by the possibility of marine mining, only few studies have been devoted to them so far. The Trans-Atlantic Geotraverse (TAG) hydrothermal field is probably one of the best-studied hydrothermal systems even if the relict SMS deposits known since the mid-1980s have not been thoroughly explored.