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Record W2017357026 · doi:10.3955/046.083.0203

Synchronicity and Geographic Variation in Oregon White Oak Acorn Production in the Pacific Northwest

2009· article· en· W2017357026 on OpenAlexaboutno aff
David H. Peter, Constance A. Harrington

Bibliographic record

VenueNorthwest Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersPacific Northwest Research StationU.S. Forest ServiceInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsAcornGeographyForestryPrecipitationEcologyBiology

Abstract

fetched live from OpenAlex

We explored geographic patterns and synchrony of Oregon white oak (Quercus garryana) acorn production over 8 years from Vancouver Island, British Columbia to Medford, Oregon. We divided our data into geographic areas: Puget-Willamette Trough, Columbia Gorge-East Cascades (Eastside) xeric, Eastside mesic, Cascade Mountain foothills, Roseburg, and Medford to compare annual acorn production among areas. We observed high within-area synchrony, but synchrony across areas was only apparent in 2004 and 2006 (high production), and 2005 (low production). Correlogram analysis indicated significant acorn crop correlation throughout the Puget-Willamette Trough, but synchrony was higher over greater distances among stands than among trees. Relationships between acorn production and mean monthly temperature or precipitation were examined with correlation analyses for each month between floral initiation and acorn maturation over 8 years of observations. Acorn production in the Puget-Willamette Trough was negatively correlated with spring precipitation, possibly due to an effect on floral processes, and winter temperature, which might relate to bud chilling requirements. In Eastside uplands, June precipitation positively correlated with current acorn production, but negatively correlated with the following year's production suggesting a climatically mediated depression by one year's production on that in the following year. Eastside production negatively correlated with precipitation in March suggesting precipitation interferes with floral processes at that time. We developed predictive linear regression models for the two analysis areas with largest sample sizes. Oregon white oak masting is similar to that in other white oaks in terms of periodicity and the effects of spring weather, but is also influenced by other weather related factors following floral induction.

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)0.001
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 score0.080
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Citations15
Published2009
Admission routes1
Has abstractyes

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