Forty years of spruce–fir stand development following herbicide application and precommercial thinning in central Maine, USA
Bibliographic record
Abstract
We examined the development of a 33-year experiment in spruce–fir stands that received nine herbicide treatments (applied aerially in 1977), with and without precommercial thinning (PCT) (applied in 1986). We tested two commonly held assumptions about the long-term effects of herbicide and PCT in mixedwood stands managed for softwoods: (i) herbicide release produces stands dominated by softwoods and (ii) PCT promotes both softwood dominance and merchantable volume. All herbicides were effective at releasing balsam fir ( Abies balsamea (L.) Mill.) and spruce ( Picea spp.) from overtopping shrubs and hardwoods that had naturally regenerated following clearcut harvesting in 1970. Glyphosate (Roundup), triclopyr amine (Garlon 3A), 2,4,5-T, and a mixture of 2,4,5-T and 2,4-D herbicide treatments were all effective at shifting long-term species composition to softwood dominance after 30 years, irrespective of the rates applied. Herbicide-treated stands that did not receive PCT were overstocked with softwoods for at least 24 years and produced less than half of the merchantable softwood volume by 40 years than herbicide-treated stands that received PCT. Intolerant hardwoods dominated untreated stands for all 33 years of the experiment. When unsprayed plots received PCT, however, they produced stands at 40 years that were compositionally and structurally indistinguishable from those that had received both herbicide and PCT treatments. Results from this experiment clearly demonstrated that early herbicide application, regardless of type and rate of herbicide, created softwood-dominated mixedwood stands over the long term and that PCT more than doubled merchantable softwood volume within 25 years of application.
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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) | 0.000 | 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".