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Record W2131046914 · doi:10.1111/nph.12833

Cryptic no more: soil macrofossils uncover Pleistocene forest microrefugia within a periglacial desert

2014· article· en· W2131046914 on OpenAlexafffund
Guillaume de Lafontaine, Carlos A. Amasifuén Guerra, Alexis A. Ducousso, Rémy J. Petit

Bibliographic record

VenueNew Phytologist · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité Laval
FundersLabEx COTEErasmus+Fonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsMacrofossilGlacial periodBeechGeologyPleistocenePopulationStadialEcologyPhysical geographyPaleontologyGeographyBiologyHolocene

Abstract

fetched live from OpenAlex

Despite their critical importance for understanding the local effects of global climate change on biodiversity, glacial microrefugia are not well studied because they are difficult to detect by using classical palaeoecological or population genetics approaches. We used soil macrofossil charcoal analysis to uncover the presence of cryptic glacial refugia for European beech (Fagus sylvatica) and other tree species in the Landes de Gascogne (southwestern France). Using botanical identification and direct radiocarbon dating (140 (14) C-dates) of macrofossil charcoal extracted from mineral soils, we reconstructed the glacial and postglacial history of all extant beech stands in the region (n = 11). Soil charcoal macrofossils were found in all sites, allowing the identification of up to at least 14 distinct fire events per site. There was direct evidence of the presence of beech during the last glacial period at three sites. Beech was detected during Heinrich stadial-1, one of the coldest and driest intervals of the last glacial period in Western Europe. Together with previous results on the genetic structure of the species in the region, these findings suggest that beech persisted in situ in several microrefugia through full glacial and interglacial periods up to the present day.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.026
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.006

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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations61
Published2014
Admission routes2
Has abstractyes

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