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Record W3159032587 · doi:10.5194/egusphere-egu21-16596

A field-scale laboratory to study particulate transport from river source to marine sink: Bute Inlet (Canada)

2021· article· en· W3159032587 on OpenAlexaffabout
Sophie Hage, Sanem Açıkalın, Lewis Bailey, Matthieu Cartigny, Michael Clare, Ye Chen, Valier Galy, Maarten Heijnen, Catharina Heerema, Stephen M. Hubbard, Jennifer M. Jackson, Gwyn Lintern, Dan H. Shugar, Stephen M. Simmons, Cooper Stacey, Peter J. Talling, Michael Tilston, Daniel Parsons, Ed Pope

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaTula FoundationUniversity of Calgary
FundersNatural Environment Research CouncilSight Research UK
KeywordsInletFjordSink (geography)OceanographySedimentSubmarine pipelineSediment transportGeologySubmarineEnvironmental scienceHydrology (agriculture)GeomorphologyGeography

Abstract

fetched live from OpenAlex

It is often assumed that particles produced on land (e.g., sediment, pollutants and organic matter) are transported through watersheds to a terminal sediment sink at the seashore. However, terrestrial particles can continue their journey offshore via submarine channels, accumulating in abyssal plains of the oceans. Offshore sediment transport processes are key controls on the burial of organic carbon and the distribution of benthic food, yet they are challenging to study due to the difficulty of capturing usually short duration events within large-scale systems at great ocean depths. Fjords are sufficiently small scale to enable their submarine channel systems to be studied from river source to terminal sink on seafloor fans. Bute Inlet is an up to 650 m deep fjord in British Columbia, Canada. The Homathko and Southgate rivers both feed Bute Inlet with freshwater and terrestrial sediment. A large landslide occurred on 28th November 2020, which caused a Glacial-Lake Outburst Flood (GLOF) which breached a moraine-dam and transported huge volumes of material through the Southgate valley and into Bute Inlet. The impact of this recent event on the submarine system in Bute is, for now, poorly constrained but ongoing work is exploring the impact of this major event on the Inlet. Bute Inlet is one of the most studied fjords worldwide, with a range of offshore campaigns that have been conducted during the last seventy years, providing an unprecedented background dataset and thus opportunity to explore what impact a large magnitude, low frequency terrestrial event had on the submarine system. This presentation will provide an overview of the past research conducted on the Bute submarine channel system, under more usual river discharge conditions and compare this background context to the recent GLOF event. Previous studies have revealed that the floor of the Inlet is characterized by a 40 km long submarine channel formed by submarine avalanches of sediment (turbidity currents) that can be up to 30 m thick and reach velocities of up to 6.5 m/s. Based on time-lapse bathymetric mapping over 10 years, the evolution of this channel is known to be controlled by the fast (100 to 450 m/yr) upstream migration of 5 to 30 m high steps (called knickpoints) in the channel floor. Sediment cores reveal that the channel floor and proximal lobe are dominated by sand and up to 3 % of total organic carbon in the form of young woody debris. Research in Bute Inlet has thus allowed submarine flow processes, seafloor morphology and deposits to be linked in unprecedented detail. Using those past results as a baseline, new data collected after the GLOF will be crucial for testing the impact of high-magnitude catastrophic events on a marine system and the ultimate sink for the terrestrial material. Understanding what impact the GLOF had on the usual seafloor processes has direct implications for the preservation of benthic communities living in the fjord and for the global carbon cycle.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2021
Admission routes2
Has abstractyes

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