MétaCan
Menu
Back to cohort
Record W2148294141 · doi:10.1139/b06-084

Genetic variation in fall cold hardiness in coastal Douglas-fir in western Oregon and Washington

2006· article· en· W2148294141 on OpenAlexvenueno aff
J. Bradley St. Clair

Bibliographic record

VenueCanadian Journal of Botany · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersU.S. Forest Service
KeywordsHardiness (plants)PhenologyPopulationBiologyDouglas firAnnual growth cycle of grapevinesFreezing toleranceEcologyBotanyHorticultureDemographyShoot

Abstract

fetched live from OpenAlex

Genetic variation in fall cold damage in coastal Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii ) was measured by exposing excised branches of seedlings from 666 source locations grown in a common garden to freezing temperatures in a programmable freezer. Considerable variation was found among populations in fall cold hardiness of stems, needles, and buds compared with bud burst, bud set, and biomass growth after 2 years. Variation in fall cold hardiness was strongly correlated (r = 0.67) with cold-season temperatures of the source environment. Large population differences corresponding with environmental gradients are evidence that natural selection has been important in determining genetic variation in fall cold hardiness, much more so than in traits of bud burst (a surrogate for spring cold hardiness), bud set, and growth. Seed movement guidelines and breeding zones may be more restrictive when considering genetic variation in fall cold hardiness compared with growth, phenology, or spring cold hardiness. A regional stratification system based on ecoregions with latitudinal and elevational divisions, and roughly corresponding with breeding zones used in Oregon and Washington, appeared to be adequate for minimizing population differences within regions for growth and phenology, but perhaps not fall cold hardiness. Although cold hardiness varied among populations, within-population and within-region variation is sufficiently large that responses to natural or artificial selection may be readily achieved.

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 score0.880
Threshold uncertainty score0.917

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 head0.004
GPT teacher head0.174
Teacher spread0.170 · 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

Citations43
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of BotanySame topicForest ecology and managementFrench-language works237,207