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Record W4221054007 · doi:10.1002/joc.7608

A 247‐year tree‐ring reconstruction of spring temperature and relation to spring flooding in eastern boreal Canada

2022· article· en· W4221054007 on OpenAlexaffabout
Alexandre Florent Nolin, Martin P. Girardin, Jacques Tardif, Xiao Jing Guo, France Conciatori, Yves Bergeron

Bibliographic record

VenueInternational Journal of Climatology · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of WinnipegUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsBorealSnowmeltSpring (device)Flooding (psychology)ClimatologyEnvironmental scienceDendrochronologySnowTaigaClimate changePaleoclimatologyPhysical geographyGeologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract Few records of spring paleoclimate are available for boreal Canada, as biological proxies recording the beginning of the warm season are uncommon. Given the spring warming observed during the last decades, and its impact on snowmelt and hydrological processes, searching for spring climate proxies is receiving increasing attention. Tree‐ring anatomical features and intra‐annual widths were used to reconstruct the regional March to May mean air temperature from 1770 to 2016 in eastern boreal Canada. Nested principal component regressions calibrated on 116 years of gridded temperature data were developed from one Fraxinus nigra and 10 Pinus banksiana sites. The reconstruction indicated three distinct phases in spring temperature variability since 1770. Ample phases of multi‐decadal warm and cold springs persisted until the end of the Little Ice Age (1850–1870 CE) and were gradually replaced since the 1940s by decadal to interannual variability associated with an increase in the frequency and magnitude of warm springs. Significant correlations with other paleotemperature records, gridded snow cover extent and runoff support that historical high flooding were associated with late, cold springs with heavy snow cover. Most of the high magnitude spring floods reconstructed for the nearby Harricana River also coincided with the lowest reconstructed spring temperature per decade. However, the last 40 years of observed and reconstructed mean spring temperature showed a reduction in the number of extreme cold springs contrasting with the last few decades of extreme flooding in the eastern Canadian boreal region. This result indicates that warmer late spring mean temperatures on average may contribute, among other factors, to advance the spring break‐up and to likely shift the contribution of snow to rain in spring flooding processes.

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 score0.265
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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