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Record W2911584040 · doi:10.1163/22941932-40190222

Influence of climatic factors on silver fir xylogenesis along the Italian Peninsula

2019· article· en· W2911584040 on OpenAlexaff
Serena Antonucci, Sergio Rossi, Fabio Lombardi, Marco Marchetti, Roberto Tognetti

Bibliographic record

VenueIAWA Journal - KU Leuven/IAWA Journal · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsPhenologyXylemGrowing seasonCambiumAbies albaPrecipitationBiologyPopulationEcologyBotanyPicea abiesGeography

Abstract

fetched live from OpenAlex

ABSTRACT Xylem phenology has been widely recognised as an ecological indicator of the impact of environmental changes on forest ecosystems, especially at the edge of a species distribution. We investigated xylem phenology of silver fir ( Abies alba Mill.) in three sites in Italy, between the 38 th and 46 th parallels. The phases of xylem phenology were assessed weekly on wood microcores collected from March to November 2015 to calculate timing and duration of xylem cell production. The effect of temperature and precipitation on xylem phenology were sequentially included in stepwise regressions and used to predict the duration of each phenological phase under three future climatic scenarios at different concentrations of greenhouse gases (RCP 2.6; 4. 5; 8. 5). A growing season of 163 days was detected in the southern site that was longer compared to the central (132 days) and northern (120 days) sites. A longer duration of xylogenesis was mostly related to a delayed completion of xylem differentiation in autumn rather than an earlier onset of cambium reactivation in spring. Overall, 67–76% of the duration of phenological phases was controlled by growing season precipitation, while 24 –33% was influenced by minimum temperature. Inclusion of both the above factors in the modelling exercise simulated a lengthening of the silver fir growing season during the 21 st century. A longer duration of xylogenesis was envisaged in the scenario RCP 8. 5, especially in the central site. Population and climate gradients need to be considered when addressing phenological shifts and growth dynamics of silver fir in Mediterranean mountains.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.239
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; both teacher heads agree on what is shown here.

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

Citations17
Published2019
Admission routes1
Has abstractyes

Explore more

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