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Record W4404211799 · doi:10.1016/j.margeo.2024.107432

Tracking hydrothermal particles from the ridge axis to the sediment column along the Endeavour segment of the Juan de Fuca Ridge

2024· article· en· W4404211799 on OpenAlexafffund
Melissa Mills, Jay T. Cullen, Jody Spence, Patrick A. Rafter, Steve Mihály, L. A. Coogan

Bibliographic record

VenueMarine Geology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Tectonic Studies in Latin America
Canadian institutionsOcean Networks Canada SocietyUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyRidgeSedimentHydrothermal circulationGeomorphologyTracking (education)OceanographyPaleontologyGeochemistry

Abstract

fetched live from OpenAlex

Elemental fluxes associated with mid-ocean ridge hydrothermal systems are thought to be important in the ocean budgets of many elements but quantitative models of these fluxes, and how they vary in space and time due to different boundary conditions, are in their infancy. This is especially true for non-conservative elements that can be involved in multiple processes transforming them between the dissolved and particulate phases both in the water column and after sedimentation. To help develop a more robust database for parameterizing the processes operating, we undertook a coupled sediment trap and sediment core study of hydrothermal sediments on the west flank of the Endeavour segment of the Juan de Fuca Ridge. Sediment traps deployed in the Main Endeavour Field (MEF) and 3 and 9 km southwest of this field, along the mean flow direction of the hydrothermal plume, show that the rate of change of the concentration of sulfide-associated elements (Cu, Zn, Cd, Pb, Ag, As, Mo) in sediment settling from the plume differs between elements. We interpret this as indicating both different dissolution rates of phases containing these elements and different rates of scavenging of these elements from seawater. Scavenging is most readily tracked using elements for which the scavenged fraction is large relative to the hydrothermally derived fraction. For such elements, the relative efficiency of scavenging from seawater (REE > Cr > Ni > V > P > U) matches that previously reported from the TAG system on the Mid-Atlantic ridge despite different vent fluid and seawater chemistries that are expected to lead to both differing roles of Fe-sulfide and Fe-oxyhydroxides and different Fe oxidation rates. In the sediment trap samples collected 9 km off-axis, but not in those collected 3 km off-axis, the Mn and Ti concentrations correlate strongly despite these samples having much higher Mn concentrations than background sediment. Since Ti is sourced almost entirely from background terrigenous material such a correlation was not expected. The most reasonable explanation for this is that aggregation of hydrothermally derived particles with terrigenous material settling through the water column controls removal of hydrothermally derived particles from the water column. Changes in sediment composition with depth in the off-axis sediment core, along with differences between the composition of material from the sediment core and the off-axis sediment traps, are interpreted as indicating large post-deposition changes in sediment composition. For example, much or all of the Mn, P, As and Mo carried to the sediments with hydrothermally derived particles is released back into the water column during diagenesis. In contrast, V and REE concentrations in the sediment core are higher than those in the off-axis sediment trap samples, which may be due to continued scavenging in a benthic boundary layer post-deposition. Overall these data are interpreted as indicating that the net loss of many elements from the non-buoyant plume may not be a proxy for loss from the ocean, and a better understanding of post-depositional processes in hydrothermal settings may be important in understanding cycling of the aforementioned elements, and likely others, in seawater. • Hydrothermal particles dissolve at different rates within the water column. • Early diagenesis is important in controlling net fluxes of many elements. • Benthic scavenging is important in controlling REE and V fluxes. • Post-depositional processes are potentially invisible to plume surveys.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.219
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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