Large spruce seedling responses to the interacting effects of vegetation zone, competing vegetation dominance and year of mechanical release
Bibliographic record
Abstract
It is necessary to evaluate how large seedling stock, used as an alternative to chemical herbicide for vegetation management, interacts with the timing of mechanical release (MR) and if use of such stock offers a broader window of intervention for release than conventional stock. Such a context is present in Quebec (Canada), where chemical herbicides were banned from use on public lands in 2001. We thus evaluated the impact of delaying MR on the performance of large spruce seedlings established in a gradient of vegetation zones and competition environments. Fourteen experiments were conducted in Picea glauca or P. mariana plantations in the temperate hardwood (TH), temperate mixedwood or boreal mixedwood vegetation zones. On each site, we established a completely randomized block design with 5–8 replicates, each divided into four plots: (1) control; (2) MR applied the year during which light availability to the planted seedlings averaged 60 per cent of full sunlight (EARLY); (3) MR at EARLY + 1 year (LATE1); and (4) MR at EARLY + 2 years (LATE2). Vegetation data collected in controls 8 years after MR was submitted to a correspondence analysis to group the sites according to their competing species dominance. Seedling responses to the timing of MR, 5–8 years after treatment, varied across competing vegetation dominance, vegetation zone or a combination of both. On sites where intolerant hardwoods were dominant, postponing MR 1 year after light availability had reached 60 per cent of full sunlight had a positive effect on seedling dimensions, especially in the TH zone. However, the LATE2 treatment resulted in significant stem volume losses on these sites. Whereas treatment effects were limited on ericaceous dominated sites, MR promoted seedling growth on sites dominated by shrub/herbaceous species, with no difference between EARLY, LATE1 and LATE2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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 teacher head, 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".