Multiyear defoliations in southern New England increases oak mortality
Bibliographic record
Abstract
After decades of multiyear defoliation episodes in southern New England, Lymantria dispar dispar (previously gypsy moth) populations diminished with the appearance of the L. dispar fungus in 1989. Multiyear defoliations did not occur again until 2015–2018. To assess the impact of the return of multiyear defoliations, we examined 3095 oaks on 29 permanent study areas in Connecticut and Rhode Island that were established at least 11 years before the latest outbreaks. Pre-defoliation stand-level oak mortality averaged 2% (3-year basis). Post-defoliation mortality did not differ between managed and unmanaged stands but was much higher in severely defoliated stands (36%) than in stands with moderate (7%) or low to no defoliation (1%). Pre-defoliation mortality of individual trees differed among species, was lower for larger diameter trees and on unmanaged than managed stands. Post-defoliation mortality on plots with no to moderate defoliation was similar to pre-defoliation mortality levels. Following multiyear defoliations, white oak (Quercus alba L.) mortality was higher than for northern red oak (Quercus rubra L.) and black oak (Q. velutina Lam.). There was weak evidence that mortality was elevated on stands with higher basal area following severe defoliation. Natural resource managers should not assume that oaks that survived earlier multiyear defoliations episodes will survive future multiyear outbreaks, possibly because trees are older.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".