MétaCan
Menu
← Back to cohort
Record W3188464659 · doi:10.5194/cp-2021-95

Glaciers and ice caps through the Holocene: A pan–Arctic synthesis of lake–based reconstructions

2021· article· en· W3188464659 on OpenAlexaboutno aff
Laura J. Larocca, Yarrow Axford

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsArcticHoloceneGlacierContext (archaeology)GeologyClimatologyPhysical geographyArctic dipole anomalyOceanographyArctic ice packBorealGreenland ice sheetPeninsulaIce sheetGeographyAntarctic sea iceArchaeologyPaleontology

Abstract

fetched live from OpenAlex

Abstract. The recent retreat of nearly all glaciers and ice caps (GICs) located in Arctic regions is one of the most clear and visible signs of ongoing climate change. This paper synthesizes published records of Holocene GIC fluctuations from lake archives, placing their recent retreat into a longer–term context. Our compilation includes sixty–six lake–based GIC records (plus one non–lake–based record from the Russian Arctic) from seven Arctic regions: Alaska; the archipelagos of the eastern Canadian Arctic; GICs peripheral to the Greenland Ice Sheet; Iceland; the Scandinavian peninsula; Svalbard; and the Russian high Arctic. For each region, and for the full Arctic, we summarize evidence for when GICs were smaller than today or absent altogether, indicating warmer than present summers, and evidence for when GICs regrew in lake catchments, indicating summer cooling. Consistent with orbitally driven high boreal summer insolation in the early Holocene, the pan–Arctic compilation suggests that the majority (50 % or more) of studied GICs were smaller than present or absent by ~10 ka. The regional compilations suggest even earlier GIC loss, and thus warmth, in the Russian Arctic and in Svalbard. We find the highest percentage (>90 %) of Arctic GICs smaller than present or absent in the middle Holocene ~7–6 ka, probably reflecting more spatially ubiquitous and consistent summer warmth during this period than in the early Holocene. Following this interval of widespread warmth, our compilation shows that GICs across the Arctic began to regrow, and summers began to cool by ~6 ka. Together, the pan–Arctic records also suggest two periods of enhanced GIC growth in the mid–to–late Holocene, from ~4.5–3 ka and after ~2 ka. The regional records show substantial variability in the timing of GIC regrowth within and between regions, suggesting that the Arctic did not cool synchronously despite the smooth and hemispherically symmetric decline in Northern Hemisphere summer insolation. In agreement with other studies, this implies a combined response to glacier–specific characteristics such as topography, and to other climatic forcings and feedback mechanisms, perhaps driving periods of increased regional cooling. Today, the direction of orbital forcing continues to favor GIC expansion, however, the rapid retreat of nearly all Arctic GICs underscores the current dominance of anthropogenic forcing on GIC mass balance. Our review finds that in the first half of the Holocene, most of the Arctic’s small GICs became significantly reduced or melted away completely in response to summer temperatures that, on average, were only moderately warmer than today. In comparison, future projections of temperature change in the Arctic far exceed estimated early Holocene values in most locations, portending the eventual loss of most of the Arctic’s small GICs.

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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.021
GPT teacher head0.238
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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicGeology and Paleoclimatology Research→French-language works237,207→