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Record W2112137471 · doi:10.4319/lo.2007.52.5.2013

Spatial analysis of ice phenology trends across the Laurentian Great Lakes region during a recent warming period

2007· article· en· W2112137471 on OpenAlexaffabout
Olaf P. Jensen, Barbara J. Benson, John J. Magnuson, Virginia Card, Martyn N. Futter, Patricia A. Soranno, Kenton M. Stewart

Bibliographic record

VenueLimnology and Oceanography · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsTrent University
Fundersnot available
KeywordsSnowPhenologyEnvironmental scienceClimate changePhysical geographyClimatologyElevation (ballistics)Period (music)GeographyEcologyGeologyOceanographyMeteorologyBiology

Abstract

fetched live from OpenAlex

We examined spatial patterns of trends in ice phenology and duration for 65 waterbodies across the Great Lakes region (Minnesota, Wisconsin, Michigan, Ontario, and New York) during a recent period of rapid climate warming (1975‐2004). Average rates of change in freeze (3.3 d decade −1 ) and breakup (22.1 d decade −1 ) dates were 5.8 and 3.3 times more rapid, respectively, than historical rates (1846‐1995) for Northern Hemisphere waterbodies. Average ice duration decreased by 5.3 d decade −1 . Over the same time period, average fall through spring temperatures in this region increased by 0.7°C decade −1 , while the average number of days with snow decreased by 5.0 d decade21, and the average snow depth on those days decreased by 1.7 cm decade −1 . Breakup date and ice duration trends varied over the study area, with faster changes occurring in the southwest. Trends for each site were compared to static waterbody characteristics and meteorological variables and their trends. The trend toward later freeze date was stronger in large, low‐elevation waterbodies; however, freeze date trends had no geographic patterns or relationships to meteorological variables. Variability in the strength of trends toward earlier breakup was partially explained by spatial differences in the rate of change in the number of days with snow cover, mean snow depth, air temperature (warmer locations showed stronger trends), and rate of change in air temperature. Differences in ice duration trends were explained best by a combination of elevation and the local rate of change in either temperature or the number of days with snow cover.

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 score0.084
Threshold uncertainty score0.862

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 studies0.0000.001
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 head0.009
GPT teacher head0.225
Teacher spread0.215 · 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

Citations189
Published2007
Admission routes2
Has abstractyes

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