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Record W4392758353 · doi:10.5194/egusphere-egu24-12816

Atmospheric deposition of local mineral dust delivers nutrients to the ‘Dark Zone’ of the Greenland Ice Sheet

2024· preprint· en· W4392758353 on OpenAlexaff
Jenine McCutcheon, James B. McQuaid, Nuno Canha, Sarah Barr, Stefanie Lutz, Vladimir Roddatis, Sathish Mayanna, Andrew Tedstone, Martyn Tranter, Liane G. Benning

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGreenland ice sheetNutrientDeposition (geology)MineralMineral dustEnvironmental scienceChemistryGeologyOceanographySedimentIce sheetGeomorphologyAerosol

Abstract

fetched live from OpenAlex

The ‘Dark Zone’ refers to a region of low-albedo ice currently prominent along the western margin of the Greenland Ice Sheet (GrIS). The Dark Zone hosts pigmented glacier ice algae that bloom on the ice surface, thereby contributing to darkening and melting of surface ice. These pigmented glacier ice algae grow in association with other impurities found on the ice surface, namely mineral dust. Mineral dust provides inorganic nutrients to the ice surface habitat in the Dark Zone. As such, constraining the abundance, composition, source, and deposition rate of mineral dust is important for understanding the role of mineral dust in glacier ice algal bloom development and thus the further development of the Dark Zone in other areas of Greenland. Here we characterize the mineralogy, geochemistry, and deposition rates of airborne mineral dust delivered to a site in the SW-margin of the Dark Zone during two field campaigns. Mineral dust delivered by both dry deposition and snowfall was composed of very fine-grained (< 1 µm diameter) silicate mineral fragments, and based on the rare Earth element (REE) signature the dust was primarily from local Greenlandic sources. Potential emission sensitivity (PES) hindcast simulations produced using the Lagrangian FLEXible PARTicle (FLEXPART) dispersion model indicated that PES values were highest over Greenland, thereby corroborating the REE geochemical results by indicating that the sampled aerosols were more likely derived from locations above or near Greenland than more distal locations. The deposited mineral dust contained low concentrations of phosphorus, present in the mineral apatite (Ca5[PO4]3[Cl/F/OH]), confirming that atmospheric deposition of mineral dust provides a mechanism for delivering phosphorus to the Dark Zone of the GrIS, thereby fertilizing the glacial ice algal blooms growing on the ice surface. Our findings have crucial implications for the current and future development of glacier ice algal blooms in this region as well as their role in albedo reduction and surface melting across Greenland in a future warming climate.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.225
Teacher spread0.203 · 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
Published2024
Admission routes1
Has abstractyes

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