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Record W2152192722 · doi:10.1139/b10-029

Drought-triggered false ring formation in a Mediterranean shrub

2010· article· en· W2152192722 on OpenAlexvenueno aff
Carolyn A. Copenheaver, Holger Gärtner, Isabelle Schäfer, Francesco Primo Vaccari, Paolo Cherubini

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsDeserts and xeric shrublandsShrubMediterranean climateDrought toleranceBiologyDrought stressDendrochronologyEcologyAgronomyHabitat

Abstract

fetched live from OpenAlex

Recently, the Mediterranean region has experienced unprecedented drought. Climate models continue to predict an increase in drought frequency and duration, which increases the importance of quantifying the response of already drought-tolerant Mediterranean plants to increased drought. We examined the wood anatomy and dendroecological features of a Mediterranean shrub, Arbutus unedo L., at a xeric and a mesic site on the Italian island of Elba to identify shrub growth response to drought. Cross-sectional microsections of A. unedo stems were stained, described, and crossdated. Annual ring widths of radial microsections were measured and compared with regional climatic variables. False rings (intra-annual bands of latewood typically formed in response to a specific stressor) were visible in the wood samples when viewing radial microsections under high magnification. False ring formation coincided with below-average rainfall in late summer at the xeric site, and below-average rainfall and high temperatures in spring and summer at the mesic site. If increased drought occurs in the Mediterranean region, it is likely that plants in this region will experience a drought-induced growth response similar to that seen in A. unedo, and slight differences in drought tolerance may become more important as plants compete for moisture under drier conditions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

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)0.0010.001

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 head0.244
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 teacher head, not a consensus.

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

Citations38
Published2010
Admission routes1
Has abstractyes

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