Four North American glaciers advanced past their modern positions thousands of years apart in the Holocene
Bibliographic record
Abstract
Abstract. The global retreat of alpine glaciers provides visible evidence of industrial-era warming, but how glacier position today compares to glacier length fluctuations over the Holocene is less clear. Glaciers in North America advanced over the Holocene, occupying their maximum Holocene position in the late 19th century before rapidly retreating to their sizes today. We assess when four North American glaciers, located between 38–60° N, were larger or smaller than their modern (2018–2020 CE) sizes during the Holocene. We measure 26 paired cosmogenic in situ 14C and 10Be concentrations in recently exposed proglacial bedrock and applied a Monte Carlo forward model to reconstruct plausible bedrock exposure-burial histories. We find that these glaciers advanced past their modern sizes thousands of years apart during the Holocene: a glacier in the Juneau Ice Field (BC, Canada) by ~2 ka, Kokanee Glacier (BC, Canada) at ~6 ka, and Mammoth Glacier (WY, USA) at ~1 ka; the fourth glacier, Conness Glacier (CA, USA), was larger than its modern size for the duration of the Holocene until present. The disparate Holocene exposure-burial histories are at odds with expectations of similar glacier histories given the presumed shared climate forcings of decreasing Northern Hemisphere summer insolation through the Holocene followed by global greenhouse gas forcing in the industrial era. We interpret the range in histories to be the result of unequal amounts of modern retreat relative to each glacier’s Holocene length history, rather than asynchronous Holocene advance histories. The intensity and rate of modern warming has exacerbated length differences between glaciers that occur due to hypsometry and response time. We hypothesize that highly varying magnitudes of glacier change in North America today is a departure from similar magnitudes of glacier change over the Holocene.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".