New Late Glacial and Holocene 36Cl and 10Be moraine chronologies from sub-Antarctic Kerguelen Archipelago
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".