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Record W2104603938 · doi:10.14430/arctic448

Re-evaluating the Relevance of Vegetation Trimlines in the Canadian Arctic as an Indicator of Little Ice Age Paleoenvironments

2010· article· en· W2104603938 on OpenAlexvenueaboutno aff
G. J. Wolken, John England, Arthur S. Dyke

Bibliographic record

VenueARCTIC · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsArcticPhysical geographySnowLichenSnowmeltPlateau (mathematics)Arctic vegetationVegetation (pathology)EcologyClimatologyPerennial plantPaleoclimatologyClimate changeGeographyGeologyTundraBiology

Abstract

fetched live from OpenAlex

The origin of trimlines associated with the so-called “lichen-free” areas in the Canadian Arctic has been attributed both to perennial snowfield expansion during the Little Ice Age (LIA) and to seasonally persistent snow cover in more recent times. Because of the disparate hypotheses (ecological versus paleoclimatic) regarding the formation of these trimlines, their use as a paleoclimatic indicator has been abandoned for more than two decades. We re-examine this debate and the validity of the opposing hypotheses in the light of new regional mapping of trimlines across the Queen Elizabeth Islands (QEI). The ecological hypothesis—insufficient duration of the growing season resulting from seasonally persistent snow cover—fails to account for the poikilohydric nature of lichens and their ability to endure short growing seasons. It cannot adequately explain the existence of sharp trimlines or account for the occurrence of those trimlines on sparsely vegetated carbonate terrain. Furthermore, trimlines outlining the former extent of thin plateau ice caps are accordant with trimlines associated with former perennial snowfields, indicating that these trimlines record snow and ice expansion during the LIA rather than the seasonal persistence of more recent snow cover. We suggest that these features represent an important LIA climate indicator and should therefore be used for paleoclimatic reconstruction.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.823
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.300
Teacher spread0.266 · 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 teacher head, 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

Citations25
Published2010
Admission routes2
Has abstractyes

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