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Record W2043305779 · doi:10.1002/hyp.7674

A multi‐species dendroclimatic reconstruction of Chilko River streamflow, British Columbia, Canada

2010· article· en· W2043305779 on OpenAlexaffabout
Sarah J. Hart, Dan J. Smith, John J. Clague

Bibliographic record

VenueHydrological Processes · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsStreamflowPacific decadal oscillationTsugaProxy (statistics)DendrochronologyClimatologyWater yearDischargeHistorical recordDendroclimatologyDrainage basinHydrology (agriculture)SnowEnvironmental sciencePhysical geographyGeologyClimate changeOceanographyGeographyEl Niño Southern OscillationEcology

Abstract

fetched live from OpenAlex

Abstract Dendroclimatological data were used to reconstruct the discharge history of Chilko River, which drains a glacierized watershed in the Coast Mountains of British Columbia. We correlated ring‐width records from Engelmann spruce (ES) ( Picea engelmanni ) and mountain hemlock (MH) ( Tsuga mertensiana ) trees to historical hydroclimate data. Over the period of record, spruce and hemlock radial growth correlates significantly with temperature and snow depth, respectively. We found that a multi‐species approach provided a better model fit and reconstructive power. Using these relationships, we developed generalized linear models for mean June, July, and June‐July discharge. The proxy records provide insights into streamflow variability of a typical Coast Mountains river over the past 240 years and confirm the long‐term influence of the Pacific Decadal Oscillation (PDO) on hydroclimatic regimes in the region. A relationship also exists between the reconstructed June‐July discharge record and the North Pacific (NP) Index, suggesting that winter atmospheric patterns over the North Pacific influence the hydrology of coastal British Columbia. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0060.000

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 head0.013
GPT teacher head0.194
Teacher spread0.181 · 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.

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

Citations35
Published2010
Admission routes2
Has abstractyes

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