Precipitation as the main driver of Neoglacial fluctuations of Gualas glacier, Northern Patagonian Icefield
Bibliographic record
Abstract
Abstract. Glaciers are frequently used as indicators of climate change. However, the link between past glacier fluctuations and climate variability is still highly debated. Here, we investigate the mid- to late-Holocene fluctuations of Gualas Glacier, one of the northernmost outlet glaciers of the Northern Patagonian Icefield, using a multi-proxy sedimentological and geochemical analysis of a 15 m long fjord sediment core from Golfo Elefantes, Chile, and historical documents from early Spanish explorers. Our results show that the core can be sub-divided in three main lithological units that were deposited under very different hydrodynamic conditions. Between 5400 and 4180 cal yr BP and after 750 cal yr BP, sedimentation in Golfo Elefantes was characterized by the rapid deposition of fine silt, most likely transported by fluvio-glacial processes. By contrast, the sediment deposited between 4130 and 850 cal yr BP is composed of poorly sorted sand that is free of shells. This interval is particularly marked by high magnetic susceptibility values and Zr concentrations, and likely reflects a major advance of Gualas glacier towards Golfo Elefantes during the Neoglaciation. Several thin silt layers observed in the upper part of the core are interpreted as secondary fluctuations of Gualas glacier during the Little Ice Age, in agreement with historical and dendrochronological data. Our interpretation of the Golfo Elefantes glaciomarine sediment record in terms of fluctuations of Gualas glacier is in excellent agreement with the glacier chronology proposed for the Southern Patagonian Icefield, which is based on terrestrial (moraine) deposits. By comparing our results with independent proxy records of precipitation and sea surface temperature, we demonstrate that the fluctuations of Gualas glacier during the last 5400 yr were mainly driven by changes in precipitation in the Andes.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".