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Record W2115187220 · doi:10.1890/07-1740.1

The effect of fire frequency on local cembra pine populations

2009· article· en· W2115187220 on OpenAlexaff
Aurélie Genries, L. Mercier, Martin Lavoie, Serge Müller, Olivier Radakovitch, Christopher Carcaillet

Bibliographic record

VenueEcology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFire ecologyWoodlandFire regimeMacrofossilEcologyPopulationEnvironmental scienceJuniperVegetation (pathology)EcosystemPollenGeographyPhysical geographyBiology

Abstract

fetched live from OpenAlex

It has been predicted that global climate change will lead to increasing drought in the Alps during the 21st century, as well as an increased fire risk, fires being currently rare in these mountains. Herein we describe fire frequency reconstruction using high-resolution analyses of macroscopic sedimentary charcoal, pollen, and plant macrofossils. Sediments were sampled from a subalpine pond within the dry western French Alps. Results show that the early-Holocene expansion of Pinus cembra (7200 calibrated years BP) occurred in Acer/Alnus incana/Betula woodlands, which were affected by fires with moderate mean fire-free intervals (MFFI = 173 +/- 61 yr [mean +/- SE]). Superposed Epoch Analyses show that the abundance of P. cembra macroremains decreased significantly after burning, although they never disappeared entirely. Statistics suggest that fires spread through cembra pine communities; they were not stand-replacing fires but mainly surface fires, probably killing nonreproductive pines. An increase in fire frequency occurred 6740 years ago, when four fires appear to have occurred within 140 years. These fires may have been associated with a regional drought and could have affected the composition of the subalpine forest by depleting the local P. cembra population in the short-term. The predicted increase in drought in the future could, therefore, affect the cembra pine ecosystem in the Alps if fire frequency is reduced to intervals of less than 80 years.

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 score0.358
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)0.0000.001

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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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

Citations34
Published2009
Admission routes1
Has abstractyes

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