Spatiotemporal heterogeneity of larch budmoth outbreaks in the French Alps over the last 500 years
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".