Seedling establishment and survival on decaying logs in boreal mixedwood stands following a mast year<sup>1</sup>This article is one of a selection of papers from the International Symposium on Dynamics and Ecological Services of Deadwood in Forest Ecosystems.
Bibliographic record
Abstract
In the boreal forest, establishment of tree regeneration is tightly linked to both mast years and the availability of adequate germination beds for seedlings. We took advantage of a mast year (2006) in the eastern boreal mixedwood to compare seedling establishment in 2007 and seedling survival 2 and 4 years later on sections of fallen logs and equivalent areas of adjacent forest floor. Several factors that could explain establishment of seedlings on logs were measured, including wood resistance, density, moisture content, and C/N ratio. Our results show that small-seeded species, such as white birch ( Betula papyrifera Marsh.) and white spruce ( Picea glauca (Moench) Voss), establish preferentially on logs whereas balsam fir ( Abies balsamea (L.) Mill.), a relatively large-seeded species, establishes more often on the forest floor. Using logistic regressions, we confirmed that the probability of seedling establishment on logs declines with wood resistance, while the survival probability is inversely proportional to stand deciduous basal area. Survival rate was similar for seedlings established on the forest floor and on logs. However, none of the white birch seedlings established on the forest floor in 2007 were alive by 2011. Even following an exceptional mast year, log occurrence in eastern mixedwood stands would not suffice to obtain adequate white spruce stocking levels.
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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 | 0.001 |
| 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".