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Record W2164001692 · doi:10.1139/x2012-031

Forest mortality in high-elevation whitebark pine (<i>Pinus albicaulis</i>) forests of eastern California, USA; influence of environmental context, bark beetles, climatic water deficit, and warming

2012· article· en· W2164001692 on OpenAlexvenueno aff
Constance I. Millar, Robert D. Westfall, Diane L. Delany, Matthew J. Bokach, Alan L. Flint, Lorraine E. Flint

Bibliographic record

VenueCanadian Journal of Forest Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationForskningsrådet om Hälsa, Arbetsliv och Välfärd
KeywordsBark beetleContext (archaeology)Basal areaMountain pine beetleClimate changeGeographyPrecipitationEcologyForestryEnvironmental scienceBark (sound)BiologyArchaeology

Abstract

fetched live from OpenAlex

Whitebark pine ( Pinus albicaulis Engelm.) in subalpine zones of eastern California experienced significant mortality from 2007 to 2010. Dying stands were dense (mean basal area 47.5 m 2 /ha), young (mean 176 years), and even-age; mean stand mortality was 70%. Stands were at low elevations (mean 2993 m), on northerly aspects, and experienced warmer, drier climates relative to the regional species distribution. White pine blister rust was not observed; mountain pine beetle infestations were extensive. Ring widths were negatively correlated with climatic water deficit and positively correlated with water-year precipitation. Although trees that survived had greater growth during the 20th century than trees that died, in the 19th century trees that eventually died grew better than trees that survived, suggesting selection for genetic adaptation to current climates as a result of differential tree mortality. Air surveys (2006–2010) in the Sierra Nevada, Mt. Shasta, and Warner Mountains showed similar trends to the intensive studies. Observed mortality from air surveys was highest in the Warner Mountains (38%) and lowest in the Sierra Nevada (5%); northern aspects at lower elevations within each mountain region had the highest probabilities of mortality and dying stands had higher climatic water deficit. Scenarios for the future of whitebark pine in California are discussed.

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)0.003
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 score0.437
Threshold uncertainty score0.912

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.258
Teacher spread0.238 · 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

Citations112
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicFire effects on ecosystemsFrench-language works237,207