Mixedwood management positively affects forest health during insect infestations in eastern North America<sup>1</sup>
Bibliographic record
Abstract
Mixedwood stands are composed of hardwoods and softwoods, with neither comprising greater than 75%–80% of basal area or aboveground biomass. By conferring associational resistance and greater resilience to forests when stressed or disturbed, the more diverse composition of mixedwood stands contributes to forest health. We analyzed three examples where mixedwood stands are more resistant to insect infestations in eastern North America. In balsam fir (Abies balsamea L. Mill.) and spruce (Picea spp.) forests, susceptibility and vulnerability to spruce budworm infestations is reduced with increasing hardwood density. In mid-Atlantic oak-dominated forests, oak mortality following gypsy moth infestations was much greater in oak-dominated forests than in oak–pine mixedwoods, while pine mortality during southern pine beetle infestations was greater in pine-dominated forests than in oak–pine mixedwoods. Overall, mixedwood stands have greater resistance to infestations of defoliators and bark beetles and recover more rapidly from disturbances, reducing economic losses associated with tree mortality and mitigating short-term impacts to ecosystem functioning resulting from insect damage, especially carbon sequestration. Finally, we discuss challenges and opportunities for mixedwood management to minimize insect damage. Management strategies that incorporate mixedwood stands may provide better continuity in supply of forest products and ecosystem services in the face of projected increases in insect infestations associated with changing climate.
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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 | 0.000 | 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) | 0.001 | 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".