Age and size effects on seed productivity of northern black spruce
Bibliographic record
Abstract
Slow-growing conifers of the northern boreal forest may require several decades to reach reproductive maturity, making them vulnerable to increases in disturbance frequency. Here, we examine the relationship between stand age and seed productivity of black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) in Yukon Territory and Alaska. Black spruce trees were aged and surveyed for cone production and seed viability across 30 even-aged stands ranging from 12 to 197 years old. Logistic regression indicated that individual trees had a ∼50% probability of producing cones by age 30 years, which increased to 90% by age 100 years. Cone and seed production increased steadily with age or basal area at both the tree and stand level, with no evidence of declining seed production in trees older than 150 years. Using published seed:seedling ratios, we estimated that postfire recruitment will be limited by seed availability in stands for up to 50 years (on high-quality seedbeds) to 150 years (low-quality seedbeds) after fire. By quantifying these age and seed productivity relationships, we can improve our ability to predict the sensitivity of conifer seed production to a range of disturbance frequencies and thus anticipate changes in boreal forest resilience to altered fire regime.
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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".