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Record W4285230786 · doi:10.1007/978-3-030-92698-4_3

Anatomical, Developmental and Physiological Bases of Tree-Ring Formation in Relation to Environmental Factors

2022· book-chapter· en· W4285230786 on OpenAlexaff
Cyrille Rathgeber, Gonzalo Pérez‐de‐Lis, Laura Fernández‐de‐Uña, Patrick Fonti, Sergio Rossi, Kerstin Treydte, Arthur Geßler, Annie Deslauriers, Marina V. Fonti, Stéphane Ponton

Bibliographic record

VenueTree physiology/Tree physiology (Dordrecht) · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec à Chicoutimi
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la RechercheNational Science Foundation
KeywordsXylemCambiumBiologyBotanyVascular cambiumGrowing season

Abstract

fetched live from OpenAlex

Abstract Understanding the process of wood formation and its dynamics over the growing season is fundamental to interpret the isotopic signature of tree rings. Indeed, the isotopic signal recorded in wood does not only depend on the conditions influencing carbon, water, and nitrogen uptake in the leaves and roots, but also on how these elements are translocated to the stem and incorporated into the developing xylem. Depending on environmental conditions, tree developmental stage, and physiological status, wood formation dynamics can vary greatly and produce tree-ring structures carrying specific isotopic signatures. In this chapter, we present the physiological processes involved in wood formation, along with their relationships with anatomical, developmental, and environmental factors, to understand when and how photosynthetic assimilates are progressively incorporated into the forming xylem, creating the final isotopic signature of a tree ring. First, we review current knowledge on the structure and functions of wood. Then we describe the xylogenesis process (how and when the new xylem cells produced by the cambium develop through successive differentiation phases), and its relationships with physiological, developmental, and environmental factors. Finally, we explain the kinetics of xylemcell differentiation and show why the knowledge recently acquired in this field allows us to better understand the isotopic signals in tree rings.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.210
Teacher spread0.188 · 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.

Study designBench or experimental
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

Citations17
Published2022
Admission routes1
Has abstractyes

Explore more

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