Current and Future Insect Threats to Oaks of the Midwest, Great Lakes, and Northeastern United States and Canada
Bibliographic record
Abstract
Increasing temperatures, prolonged drought, the increased severity and intensity of storms, and other effects of climate change are being felt globally, and long-lived forest tree species may struggle in their current ranges. Oaks (Quercus spp.) have evolved a range of adaptations to dry and hot conditions and are believed to be a “climate change winner” by increasing their suitable habitat. However, a mixture of life history traits and increasing susceptibility to herbivores and xylovores as well as secondary pathogen infections still put oaks at risk of decline. Oak species found in the Midwestern, Great Lakes, and Northeastern United States and Canada are important keystone species with high ecological and economical importance. They are also vulnerable to existing, new, and emerging threats that have the potential to cause mortality across entire stands quickly. Current examples of insect threats include the Lymantria dispar (spongy moth), Agrilus bilineatus (twolined chestnut borer), and Nitidulidae (sap beetles) as disease vectors. Examples of emerging insects of concern include Cynipidae (oak gall wasps) and Enaphalodes rufulus (red oak borer). This study describes these insects, explains their mechanisms of action and the effects on oaks, and explores mitigation strategies for each.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".