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Record W1696822910 · doi:10.1163/22941932-20150091

MAPPING EVENTS: CAMBIUM PHENOLOGY ACROSS THE LATITUDINAL DISTRIBUTION OF BLACK SPRUCE

2015· article· en· W1696822910 on OpenAlexaffabout
Marie‐Josée Girard, Sergio Rossi, Hubert Morin

Bibliographic record

VenueIAWA Journal - KU Leuven/IAWA Journal · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsPhenologyCambiumXylemBlack spruceAltitude (triangle)LatitudeTaigaBorealBiologyPhysical geographyEcologyBotanyGeographyMathematics

Abstract

fetched live from OpenAlex

This study used statistical models for describing the spatial patterns of variation in cambium phenology and xylem cell production across the entire latitudinal distribution of a species. The studied area extends over 600 km from the 48 th to the 53 rd parallel in the boreal forest of Quebec, Canada. Microcores were collected weekly from April to October 2012 from 50 Black spruce [ Picea mariana (Mill.) BSP] trees in five stands. The dates of occurrence of the phases of cambium phenology were identified on histological sections and correlated to the latitude and altitude of the sites by means of linear and non-linear functions. The results were used to estimate the timings of xylem growth and cell production across the sampled region. Phenology was mostly represented by linear functions. The increase in latitude and altitude produced a proportional variation in the beginning and ending of xylem differentiation, thus leading to a shorter length of the period of wood formation. The phase of cell enlargement and cell production changed according to a non-linear pattern represented by a negative exponential curve. Latitude was the factor with the greatest impact on xylem phenology, while altitude had a slight or no effect, especially for nonlinear relationships. Xylem formation is a complex process composed of several phenological phases that change across a species distribution area according to either linear or non-linear patterns. Knowledge and quantification of these patterns are important for modelling the dynamics of tree growth across wide geographical areas and for predicting productivity of forest ecosystems under climate change scenarios.

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)0.004
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 score0.040
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.285
Teacher spread0.239 · 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
Published2015
Admission routes2
Has abstractyes

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