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Record W3177239194 · doi:10.5194/egusphere-egu21-9883

New Late Glacial and Holocene 36Cl and 10Be moraine chronologies from sub-Antarctic Kerguelen Archipelago

2021· preprint· en· W3177239194 on OpenAlexaff
Joanna Charton, Vincent Jomelli, Irene Schimmelpfennig, Déborah Verfaillie, Vincent Favier, Guillaume Delpech, Régis Braucher, Pierre‐Henri Blard, Vincent Rinterknecht, Léo Chassiot, Georges Aumaître, Didier Bourlès, Karim Keddadouche

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsASTERUniversité LavalCenter for Northern Studies
Fundersnot available
KeywordsMoraineGlacial periodGlacierGeologyArchipelagoHoloceneOceanographyTerminal morainePhysical geographyPaleontologyGeography

Abstract

fetched live from OpenAlex

The Kerguelen Archipelago (49°S, 69°E) is an excellent location for the study of multi-millennial glacier fluctuations, since it is the largest still glaciated emerged area (552 km2 in 2001) in the sub-Antarctic sector of the Indian Ocean, where many glacio-geomorphological formations such as moraines may be dated. To investigate the so-far little-known Late Glacial and the Holocene glacier fluctuations in Kerguelen, we apply cosmogenic nuclide dating of moraines in 3 glacial valleys: Val Travers valley, Ampere glacier valley and Arago glacier valley. We use in situ 36Cl dating of the basaltic moraine boulders at the first two sites, and 10Be dating of the quartz-bearing syenite boulders at the third site. The new 36Cl and 10Be exposure ages provide time constraints over the last 17,000 years. A glacial advance was highlighted during the Late Glacial at 14.4 ± 1.4 ka ago, probably linked to the Antarctic Cold Reversal event. These results are consistent with those previously obtained on the archipelago (Jomelli et al., 2017, 2018; Charton et al., 2020) and more generally those from other the sub-Antarctic regions (e.g. Sagredo et al., 2018). This suggests that all glaciers at this latitude were broadly sensitive to this specific climatic signal. No Early nor Mid Holocene advances were evidenced in Kerguelen glacier evolution during the Holocene due to missing moraines that may have formed in these specific periods. Radiocarbon-dated peat, published in the 1990s, provides evidence of less extensive glacier extents during the Early Holocene than during the Late Holocene (Frenot et al., 1997). Finally, glaciers seem to have re-advanced only during the Late Holocene, especially within the last millennium, at ⁓1 ka, ⁓620 years and ⁓390 years (Verfaillie et al., submitted). A comparison of this new dataset with the available 10Be ages from other sub-Antarctic regions allows for the identification of 3 different glacier evolution patterns during the Holocene. The glacial fluctuations experienced by Kerguelen glaciers seems particularly uncommon, and are likely due to its singular location in the Southern Indian Ocean. Finally, climatic factors that may explain the Kerguelen glacier evolution (temperature, precipitation) are discussed. To this end, we investigate the chronology of glacier advance/retreat periods with (i) the variation in atmospheric temperatures recorded in ice cores in Antarctica and (ii) the variation in precipitation (Southern Westerly Winds, Southern Annular Mode). Charton et al., 2020 : Ant. Sci. 1-13 Frenot et al., 1997 : C.R. Acad. Sci. Paris Life Sciences 320, 567-573 Jomelli et al., 2017 : Quat. Sci. Rev. 162, 128-144 Jomelli et al., 2018 : Quat. Sci. Rev. 183, 110-123 Sagredo et al., 2018 : Quat Sci. Rev. 188, 160-166 Verfaillie et al., submitted

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.239
Teacher spread0.217 · 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 routes1
Has abstractyes

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