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Record W2570486497 · doi:10.1139/cjfr-2016-0211

Spatiotemporal heterogeneity of larch budmoth outbreaks in the French Alps over the last 500 years

2017· article· en· W2570486497 on OpenAlexvenueno aff
Mélanie Saulnier, Alain Roques, F. Guibal, Philippe Rozenberg, Ginette Saracco, Christophe Corona, Jean-Louis Édouard

Bibliographic record

VenueCanadian Journal of Forest Research · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersEuropean Commission
KeywordsLarchDendrochronologyChronologyPhysical geographyGeographyTree lineDendroclimatologyEcologyClimatologyClimate changeGeologyBiology

Abstract

fetched live from OpenAlex

In the subalpine forest ecosystems of the French Alps, European larch trees (Larix decidua Mill.) are periodically affected by outbreaks of a defoliating insect, the larch budmoth (Zeiraphera griseana (Hübner, 1799); LBM). To assess the long-term dynamics of LBM populations, we propose a spatiotemporal analysis of a long outbreak chronology reconstruction for the entire French Alps covering the period 1414–2009. This chronology was obtained by analyzing tree ring width (TRW) chronologies collected from 44 larch populations. The evidence of a latitudinal gradient in LBM is an original result that we have related to the “travelling waves” and “epicenter” theory. Wavelet analyses revealed a strong explicit continuous signal for periodicities of 4, 8, and 16 years throughout the entire 1500–2003 time series, except for a loss of power from 1690 to 1790 and since the early 1980s. We hypothesize that these abrupt changes could reflect a physiological response of LBM to past climatic variations. The spatial and temporal variability of LBM outbreaks and the propagation phenomenon in the French Alps highlighted by this study raises questions regarding its future dynamics in response to the expected climate change.

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)0.004
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 score0.652
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 science0.0020.000
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 head0.071
GPT teacher head0.328
Teacher spread0.256 · 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
Published2017
Admission routes1
Has abstractyes

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