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Record W4389625409 · doi:10.1080/15230430.2023.2284456

Methane emissions from subglacial meltwater of three alpine glaciers in Yukon, Canada

2023· article· en· W4389625409 on OpenAlexaboutno aff
Sarah Elise Sapper, Christian Juncher Jørgensen, Moritz Schroll, Frank Keppler, Jesper Riis Christiansen

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersHORIZON EUROPE European Research Council
KeywordsMeltwaterGlacierGeologyPhysical geographyGeomorphologyGeography

Abstract

fetched live from OpenAlex

Subglacial meltwater of land-terminating glaciers in Greenland and Iceland are sources of methane (CH4) to the atmosphere, but sparse empirical data exist about the spatial distribution of subglacial CH4 production and emission from glaciers in other regions of the world. This study presents the first measurements of CH4 emissions from the subglacial meltwater of three outlet glaciers of the St. Elias Mountains in Yukon, Canada. Dissolved CH4 concentrations were highly elevated at 45, 135, and 250 times compared to the atmospheric equilibrium concentration in the meltwater of Dusty, Kluane, and Donjek glaciers, respectively. Dissolved CO2 concentrations were depleted relative to the atmospheric equilibrium. This points to the meltwater being a source of CH4 and a sink of CO2. Stable carbon (13C) and hydrogen (2H) isotopic signatures of the subglacial CH4 were depleted compared to atmospheric CH4 at all sites, indicating both biotic and abiotic sources and possible alteration from bacterial CH4 oxidation in the meltwater. No relation was found between CH4 concentrations in the meltwater and the meltwater chemistry or the size of the glaciers in this study. These findings suggest that CH4 emissions from subglacial environments under alpine glaciers may be a more common phenomenon than previously thought.

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 score0.011
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.295
Teacher spread0.230 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

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