Earth and Planetary Science Letters 119 (1993) 85-101. doi:10.1016/0012-821X(93)90008-WReceived by publisher: 1992-08-18Harvest Date: 2016-01-04 12:19:37DOI: 10.1016/0012-821X(93)90008-WPage Range: 85-10

Using the near-bottom ARGO imaging system, we visually and acoustically surveyed the narrow (< 200 m wide) axial zone of the fast-spreading East Pacific Rise (EPR) along 83 km of its length (9°09'-54'N), discovered the Venture Hydrothermal Fields, and systematically mapped the distribution of hundreds of hydrothermal features relative to other fine-scale volcanic and tectonic features of the ridge crest. The survey encompasses most of a 2nd order ridge segment and includes at least ten 4th order (5-15 km) segments defined by bends or small lateral offsets of the ridge crest or axis (Devals). 4th order segmentation of the ridge crest is clearly expressed in the high-resolution ARGO data by the fine-scale behavior of the ridge axis and by changes in the characteristics of the axial zone (axial lava age, extent of fissuring, axial morphology and structure, etc.) across segment boundaries. The distribution and along-strike variability of hydrothermal features corresponds closely to the morphotectonic/structural segmentation of the ridge. On the 2nd order scale, we find that high T hydrothermal activity correlates with: (1) shallowing of the axial magma chamber (AMC) reflector to depths < 1.7 km beneath the ridge axis; and, (2) with the presence of a well-developed axial summit caldera (ASC). Previous work refers to this feature as an axial summit graben (ASG); however, the extent of volcanic collapse along the ASG revealed by the ARGO survey adds to evidence that on fast-spreading ridges it is an elongate volcanic caldera rather than a tectonic graben, and supports the introduction of "axial summit caldera" as a more accurate descriptor. All but 1 of the 45 active high T vent features identified with ARGO are located within 20 m of the margins of the ASC. Despite the significant extent of our track coverage outside the ASC, no important signs of venting were seen beyond the axial zone. On the 4th order scale, the abundance and distribution of hydrothermal features changes across 4th order segment boundaries. We find that high T vents are most abundant where: (1) the ASC is very narrow (40-70 m), (2) the AMC reflector is most shallow (< 1.55 km beneath the axial zone), and (3) the axial lavas are youngest and least fissured. To explain the observed distribution of vent activity, a two-layer model of ridge crest hydrothermal flow is proposed in which 3-D circulation at lower T in the volcanic section is superimposed on top of axis-parallel high T circulation through the sheeted dike complex. In the model, circulation parallel to the ridge axis is segmented at the 4th order scale by variations in thermal structure and crustal permeability which are directly associated with the spacing of recent dike intrusions along strike and with cracking down into the sheeted dikes, especially along the margins of the ASC. Based on ratios between numbers of active high T vents and inactive sulfide deposits along particular 4th order segments, and on corresponding volcanic and tectonic characteristics of these segments, we suggest tha...

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We report new geochemical data for boninites and backarc basin‐type basalts recovered from the northern termination of the Tonga trench and Lau Basin. Boninitic pillow lavas, ranging from high‐Mg compositions to andesites and dacites, have been erupted within large submarine volcanic edifices (calderas and volcanoes) associated with active rifting of both the northern end of the Tofua volcanic arc and in a backarc position relative to the arc volcanoes on the northern Tonga Ridge. The mantle sources in the area are a complex mixture of (1) the “normal” Tongan mantle wedge source that has “Pacific”‐type isotopic signature with (2) the plume‐related components (EMI, EMII, and HIMU) and (3) an “Indian”‐type source upwelling beneath the backarc spreading. Some of these sources, such as the “normal” mantle wedge and variably depleted residual plume mantle, are fluxed by subduction components from the slab, which produces boninites, tholeiites, and mixtures thereof. Other mantle sources, such as “Indian”‐type backarc mantle and also some of the plume mantle, produce melts due to adiabatic decompression. These melts are variably mixed with each other and with the slab‐fluid fluxed subduction‐related melts to form the observed spectrum of magma compositions.

High resolution remotely sensed bathymetric data is rapidly increasing in volume, but analyzing this data requires a mastery of a complex toolchain of disparate software, including computing derived measurements of the environment. Bathymetric gradients play a fundamental role in energy transport through the seascape. Benthic Terrain Modeler (BTM) uses bathymetric data to enable simple characterization of benthic biotic communities and geologic types, and produces a collection of key geomorphological variables known to affect marine ecosystems and processes. BTM has received continual improvements since its 2008 release; here we describe the tools and morphometrics BTM can produce, the research context which this enables, and we conclude with an example application using data from a protected reef in St. Croix, US Virgin Islands.Geosciences 2018, 8, 94 2 of 24 and better understanding of the algorithms in use, the field will lend itself more readily to expanding understanding of our oceans.Today, modern seafloor mapping technologies such as light detection and ranging (LiDAR) and multibeam bathymetry have done much to lower the costs, and provide consistent bathymetric products which incorporate in-sensor error models, provide high point density, and accurate georeferencing making them suitable for scientific analysis [10,11]. Bathymetric data are often captured, processed to remove artifacts and errors, and integrated into a consistent geomorphological model. Creation and interpretation of such a model has been aided by geomorphometry analysis tools in packages such as Benthic Terrain Modeler (BTM) [12,13]. BTM is built on top of the popular ArcGIS platform, is open source, has an intuitive interface, and has received continual development. When BTM was first introduced in 2006, transforming collected data to research results required mastery of many different pieces of software.Recent methodological developments have reduced the complexity of doing such analysis, but this has coincided with the emergence of even more sophisticated tools and the ability to collect much higher resolution data. Here, we describe the tools provided with the current release of BTM (v3.0), and highlight how it can be used in powerful analytical workflows for seafloor classification, by combining it with the capabilities of ArcGIS, the Python scientific stack, and the R statistical programming language. As the sphere of scientific software continues to grow, it will be important to provide easy-to-use tools to aid the broader community in performing rigorous analysis of marine geomorphometry.