MétaCan
Menu
Back to cohort
Record W2587363001

Preservation and Sediment Cycling Beneath "Ghost Glaciers": How Cold-Based Ice Dictates Arctic Landscape Evolution

2016· article· en· W2587363001 on OpenAlexaboutno aff
Lee B. Corbett

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsGlacierGeologyCyclingSedimentPhysical geographyEarth scienceGeomorphologyGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Constraining past episodes of climate change and glacial response is critical for understanding future impacts of climate change, especially in the high latitudes where warming is expected to be rapid and most of Earth's glaciers exist. Many studies of past glacier size utilize rare isotopes called cosmogenic nuclides to perform surface exposure dating. Since most areas of Earth's surface that were previously glaciated were covered by erosive ice, which stripped away pre-existing cosmogenic nuclides, surface exposure dating yields the timing of the most recent deglaciation. However, in some high latitude areas where glacial ice is cold-based and non-erosive (so-called 'ghost glaciers'), the assumptions of surface exposure dating are violated. Alternate approaches are required to constrain the complex histories of such landscapes. My doctoral dissertation focuses on both developing and employing alternative approaches to studying glacial history in the high latitudes, where glacial ice is non-erosive and dating rock surfaces with a single cosmogenic nuclide does not yield exposure ages. Here, I utilize optimized laboratory methods, paired analyses of two cosmogenic isotopes (10Be and 26Al), numerical models to assess possible exposure/burial histories, and Monte Carlo simulations to constrain uncertainties. To study the exposure and burial history of long-preserved landscapes in the Arctic, I investigate landscapes in two high-latitude locations: Thule, northwestern Greenland; and Cumberland Sound, southern Baffin Island, Canada. Bedrock surfaces, sampled on Baffin Island, exhibit evidence of long-lived subaerial weathering and have simple 10Be exposure ages up to 160,000 yr, despite being glaciated until ~10,000 yr. Simple exposure ages tend to increase with elevation, suggesting more effective erosion in the fjords and longer-term preservation of the uplands. Minimum limiting total histories calculated with 26Al/10Be range up to several million years, with periods of exposure representing ~20% of the total history, describing surfaces that have been alternately preserved beneath non-erosive glacial ice and weathered subaerially over many glacial/interglacial cycles. Boulders, sampled at both sites, have simple 10Be exposure ages up to 78,000 yr in Thule and 79,000 yr on Baffin Island, and yield multi-modal age distributions. Simple exposure ages of boulders tend to under-estimate bedrock ages in the cases of paired bedrock/boulder samples. Minimum limiting total histories calculated with 26Al/10Be range up to 700,000 yr in Thule and several million years on Baffin Island, with periods of exposure representing only a small portion of the total history. Forward numerical models suggest that boulders have been repeatedly reworked, likely experiencing partial or complete shielding during interglacial periods because of rotation and/or burial by till. The landscapes I assess here preserve histories of hundreds of thousands to millions of years, and represent a complex interplay of interglacial exposure, subglacial preservation beneath cold-based ice, periglacial processes, and subaerial weathering. Although such landscapes represent methodological challenges, they contain valuable information about long-term variations in glacial extent and climate.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.162
Teacher spread0.147 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueScholarWorks -A service of University of Vermont Libraries (University of Vermont)Same topicClimate change and permafrostFrench-language works237,207