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Record W4293255251 · doi:10.1139/cjfr-2021-0210

Intra-annual ring width and climate response of red pine in Itasca State Park in north-central Minnesota

2022· article· en· W4293255251 on OpenAlexvenueno aff
Kurt F. Kipfmueller, Evan E. Montpellier, Matthew L. Trumper, Daniel Griffin

Bibliographic record

VenueCanadian Journal of Forest Research · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsDendrochronologyChronologyDendroclimatologyRed pinePrecipitationPinus <genus>ClimatologyEnvironmental scienceClimate changePhysical geographyGrowing seasonGeographyEcologyGeologyMeteorologyArchaeologyBiologyBotany

Abstract

fetched live from OpenAlex

Red pine (Pinus resinosa Ait.) of northern Minnesota are part of a growing network of tree-ring chronologies aimed at understanding climate dynamics in the Upper Great Lakes Region. Red pine has been widely used in tree-ring studies of fire and climate variability across its range. Earlier studies have relied primarily on total annual ring width. Here we develop annual and subannual (i.e., earlywood, latewood, and adjusted latewood) chronologies from Itasca State Park to refine our understanding of red pine climate response. Our chronologies extend to the early 18th century and display common growth and cross-dating characteristics indicative of a significant common controlling mechanism. We found that total ring width contains dampened attributes reflective of both the temperature-limited earlywood and moisture-dependent latewood chronologies. The strongest relationship between climate and radial growth is between the adjusted latewood chronology and 3-month summer precipitation, suggesting that overall summer wetness rather than any single summer month primarily limits growth. The ability to disaggregate and improve upon the mixed climate signal of red pine highlights the potential of using intra-annual chronologies to strengthen future climate reconstructions. We hope the methodologies demonstrated here serve as a potential guide for future red pine chronology development in the region.

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)0.005
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 score0.861
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.274
Teacher spread0.245 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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