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Record W4246457021 · doi:10.1139/x00-039

Stand structure, invasion, and growth dynamics of bog pine (<i>Pinus uncinata</i> var. <i>rotundata</i>) in relation to peat cutting and drainage in the Jura Mountains, Switzerland

2000· article· en· W4246457021 on OpenAlexvenueno aff
François Freléchoux, Alexandre Buttler, Fritz Hans Schweingruber, Jean‐Michel Gobat

Bibliographic record

VenueCanadian Journal of Forest Research · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersFonds National de la Recherche Luxembourg
KeywordsBogPeatCuttingGeologyEcologyForestryPhysical geographyGeographyBiologyBotany

Abstract

fetched live from OpenAlex

A description of bog pine stands (Pinus uncinata Ramond var. rotundata (Link) Antoine) on uncut oligotrophic mires affected by drainage and nearby peat cuttings at three sites of the Jura Mountains (Switzerland) is given. In all sites, three situations were chosen: (i) central parts of the bogs, (ii) surfaces near cutting walls and bog margins, and (iii) intermediate situations. Population structures were characteristic for each situation. In the open and wet central parts of the bogs, trees were scattered, small, and uneven aged. In the intermediate situations, tree density was higher, and the stand was multilayered with taller and uneven-aged individuals. Near the edges of the bogs or close to the peat cutting walls, the trees were tall, even-aged, and younger with a high growth rate. The nonsynchronous colonization of the bog pine trees on the three sites indicates that local factors such as drainage and peat cuttings in the vicinity of the uncut surfaces were more influential than climate factors. Radial growth patterns, very similar between the sites and the various pinewood stands, and the numerous common pointer years reflect local and regional climate fluctuations. The pinewood development on uncut bogs in the Jura Mountains thus represents a recent dynamics, which is strongly linked to human activities.

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 score0.714
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Citations26
Published2000
Admission routes1
Has abstractyes

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