Pine processionary moth outbreaks cause longer growth legacies than drought and are linked to the North Atlantic Oscillation
Bibliographic record
Abstract
Climatic warming is assumed to expand the geographic range of insect pests whose distribution is mainly constrained by low temperatures. This is the case of the pine processionary moth (Thaumetopoea pityocampa), which is one of the main conifer defoliators in the Mediterranean Basin. Warmer winters may lead to a northward/upward expansion of this insect, as short-term studies have shown. However, no long-term data, i.e. spanning at least one century, has been used to examine these projections. We test the hypotheses that climatic warming (i) has caused an upward shift of the pine processionary moth, and (ii) has increased the frequency of severe defoliations. We used dendrochronological methods to reconstruct defoliations over the period 1900-2006 in 14 sites spanning a wide altitudinal range (1070-1675 m) in Teruel, eastern Spain. We built local ring-width chronologies for four co-occurring pine species with different degree of susceptibility against the moth defoliations, from highly suitable or palatable species (Pinus nigra) to moderately (Pinus sylvestris, Pinus halepensis) or rarely defoliated species (Pinus pinaster). We validated the tree-ring reconstructions of outbreaks using a field record of stand defoliations spanning the period 1971-2006. Outbreaks in the most affected P. nigra stands corresponded to abrupt one- to two-year growth reductions (70-90% growth loss). Reconstructed outbreaks occurred on average every 9-14 years. The growth memory of outbreaks was weaker but lasted longer (1-6 years) than that due to droughts (1-3 years). Neither an upward expansion nor an increase in outbreak frequency was observed. Severe PPM defoliations did not increase as climate warmed, rather they were positively related to the winter North Atlantic Oscillation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".