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Record W1909578828 · doi:10.1139/x11-096

Growth responses to climate and drought in silver fir (<i>Abies alba</i>) along an altitudinal gradient in southern Kosovo

2011· article· en· W1909578828 on OpenAlexvenueno aff
Elvin Toromani, Mitat Sanxhaku, Edmond Pasho

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsAbies albaDendroclimatologyDendrochronologyPrecipitationEnvironmental sciencePhysical geographyAtmospheric sciencesClimatologyGeographyForestryEcologyBiologyGeologyMeteorology

Abstract

fetched live from OpenAlex

This paper deals with the response of silver fir ( Abies alba Mill.) growth to climate, mainly drought, presenting data from southern Kosovo, for which only little information is available. Two cores from 55 dominant trees were extracted at two sites representing the limits of the natural distribution of silver fir. We built 80- and 112-year-long chronologies for each site. Comparison of both ring width chronologies showed that they were diverse. Pointer year analysis indicated that high spring temperatures and ample rainfall (1082 mm) influenced positively silver fir growth (wide ring), while low spring temperatures and scarce precipitation had an inverse effect. Bootstrapped response functions confirmed that April and May temperatures of the current growth year influenced positively silver fir growth at the low-elevation site, while the July precipitation of the previous growth year had a negative influence. At the high-elevation site, warm previous December temperatures had a positive influence on silver fir growth. Drought indices indicated two periods (1953–1961 and 1994–2001) with moderate drought. Correlation analysis between silver fir radial growth and drought indices revealed that the impact of drought on radial growth was significant at the time scale of 1.5 months during the summer months.

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)0.003
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 score0.643
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.067
GPT teacher head0.291
Teacher spread0.224 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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