Canopy treatment influences growth of replacement tree species in <i>Fraxinus nigra</i> forests threatened by the emerald ash borer in Minnesota, USA
Bibliographic record
Abstract
Fraxinus nigra Marsh. (black ash), a dominant tree species of wetland forests in northern Minnesota, USA, is imperiled by the invasive insect emerald ash borer (EAB; Agrilus planipennis Fairmaire, 1888). Regeneration of associated tree species is generally low in F. nigra forests and could be impacted further by climate change. Proactive management may be critical to maintaining tree cover and ecosystem function following EAB invasion. We investigated the mean height and diameter relative growth rate (RGR) of seedlings of 10 potential replacement tree species, including two from the next southern climate zone projected to be adapted to the future northern Minnesota climate. Seedlings were planted in F. nigra wetlands under four canopy treatments: unharvested control, clearcut, girdling F. nigra to emulate EAB-induced mortality, and group selection. Mean height and diameter RGR was fastest overall in the clearcut treatment, followed by the girdling, group selection, and control treatments. Depending on species, treatment significantly influenced RGR. Several species projected to be adapted to the future northern Minnesota climate had moderate to rapid mean RGR, including one from the next southern climate zone. Our results suggest that seedling plantings and overstory treatment represent an effective strategy for establishing F. nigra replacement tree species as EAB approaches, while reducing future risk from climate change.
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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".