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Record W3082669243 · doi:10.1139/cjfr-2020-0211

Four-decadal series of dendrometric measurements reveals trends in <i>Pinus sylvestris</i> inter- and intra-annual growth response to climatic conditions

2020· article· en· W3082669243 on OpenAlexvenueno aff
Rūtilė Pukienė, Adomas Vitas, Justas Kažys, Egidijus Rimkus

Bibliographic record

VenueCanadian Journal of Forest Research · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsScots pinePinus <genus>Environmental sciencePrecipitationForestryAnnual growth %Growth rateAtmospheric sciencesPhysical geographyBiologyBotanyGeographyMathematicsMeteorologyGeology

Abstract

fetched live from OpenAlex

We analyzed a 42-year series (1976–2017) of Scots pine (Pinus sylvestris L.) tree-diameter data, obtained using band dendrometers, from our study site in Aukštaitija National Park, Lithuania. We evaluated the intra- and inter-annual growth dynamics of tree diameter and their response to meteorological forcing, as well as the long-term annual and monthly growth-rate changes in tree diameter in the study area. On average, the largest growth in tree diameter was found to have taken place in June (35% of the annual increase). After 24 June, the tree-diameter growth rate strongly decreased. Pine growth in May and August was mostly affected by the temperature during the previous month. Precipitation was the main driver that determined tree growth in June–August, with heavy precipitation events having the largest impact on short-term increases in tree diameter. We determined that the largest positive growth-rate changes in Scots pine tree diameter occurred as a result of higher air temperature in May and June between 1976 and 2017.

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)0.005
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 score0.196
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
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 head0.109
GPT teacher head0.319
Teacher spread0.210 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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