Overstory treatment and planting season affect survival of replacement tree species in emerald ash borer threatened <i>Fraxinus nigra</i> forests in Minnesota, USA
Bibliographic record
Abstract
Fraxinus nigra Marsh. (black ash) wetland forests in northern Minnesota, USA, are threatened by the invasive insect, emerald ash borer (Agrilus planipennis Fairmaire (EAB)). A potential management option is promoting regeneration of tree species that are not EAB hosts to maintain ecosystem functions. Using an operational-scale field experiment, we examined the survival of 12 alternative tree species in response to different canopy treatments. We planted the seedlings in 1.6 ha plots assigned to four replicated canopy treatments: untreated control, group selection (0.04 ha gaps, 20% of stand), black ash girdling to emulate EAB-induced mortality, and clearcut. Fall and spring plantings were used to compare the effects of spring ponding. Control (32.9%), group selection (34.5%), and girdling (33.3%) treatments had comparable overall seedling survival. Survival in the clear-cut treatments was significantly lower (22%). Species selection, overstory treatment, and season of planting together resulted in survival rates ranging from 0.08% to 94.1%. Conifer species had low overall rates of survival (10.7%), whereas some species with native ranges not presently overlapping with northern F. nigra forests, e.g., Quercus bicolor Willd. (75.5%), had high survival rates. If growth is light-limited, group selection may be effective in promoting recruitment and supporting a larger variety of species.
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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".