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Record W2326243253 · doi:10.1093/treephys/27.8.1125

Using simple causal modeling to understand how water and temperature affect daily stem radial variation in trees

2007· article· en· W2326243253 on OpenAlexfundno aff
Annie Deslauriers, Tommaso Anfodillo, Sergio Rossi, Vinicio Carraro

Bibliographic record

VenueTree Physiology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersMinistero dell’Istruzione, dell’Università e della RicercaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPicea abiesEcotoneAbies albaChemistryAnimal scienceBotanyBiology

Abstract

fetched live from OpenAlex

Variation in tree stem diameter results from reversible shrinking and swelling and irreversible radial growth, all processes that are influenced by tree water status. To assess the causal effects of water and temperature on stem radial variation (DeltaR) and maximum daily shrinkage (MDS), the diurnal cycle was divided into three phases: contraction, expansion and stem radius increment. Diurnal cycles were measured during 1996-2004 in Picea abies (L.) Karst., Pinus cembra L. and Larix decidua Mill. in a timberline ecotone to understand the links between stem diameter variation (v; defined as MDS or DR), phase duration (h), and weather or sap flow descriptors (d). We demonstrated that a high proportion of MDS and DeltaR was explained by h because of the nonlinearity of the physiological responses to weather d. By causal modeling, we tested whether the relationship between d and v was due to h (lack of causal relationship between d and v) or to both d and h (double cause). The results of this modeling added new physiological insight into daily growth-climate relationships. Negative correlations were found between DeltaR and air temperature owing to the negative effect of temperature on h only, and did not correspond to a direct effect on tree growth mediated by an alteration in metabolic activities. Precipitation had two main effects: a direct effect on DeltaR and an indirect effect mediated through an effect on h. A reduction in sap flow at night led to an increase in DeltaR for P. abies and L. decidua, but not for P. cembra.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.267
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations98
Published2007
Admission routes1
Has abstractyes

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