Leaf area dynamics of a boreal black spruce fire chronosequence
Bibliographic record
Abstract
Specific leaf area (SLA) and leaf area index (LAI) were estimated using site-specific allometric equations for a boreal black spruce (Picea mariana (Mill.) BSP) fire chronosequence in northern Manitoba, Canada. Stands ranged from 3 to 131 years in age and had soils that were categorized as well or poorly drained. The goals of the study were to: (i) measure SLA for the dominant tree and understory species of boreal black spruce-dominated stands, and examine the effect of various biophysical conditions on SLA; and (ii) examine leaf area dynamics of both understory and overstory for well- and poorly drained stands in the chronosequence. Overall, average SLA values for black spruce (n = 215), jack pine (Pinus banksiana Lamb., n = 72) and trembling aspen (Populus tremuloides Michx., n = 27) were 5.82 +/- 1.91, 5.76 +/- 1.91 and 17.42 +/- 2.21 m2 x kg-1, respectively. Foliage age, stand age, vertical position in the canopy and soil drainage had significant effects on SLA. Black spruce dominated overstory LAI in the older stands. Well-drained stands had significantly higher overstory LAI (P < 0.001), but lower understory LAI (P = 0.022), than poorly drained stands. Overstory LAI was negligible in the recent (3-12 years old) burn sites and highest in the 70-year-old burn site (6.8 and 3.0 in the well- and poorly drained stands, respectively), declining significantly (by 30-50%) from this peak in the oldest stands. Understory leaf area represented a significant portion (> 40%) of total leaf area in all stands except the oldest.
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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 | 0.001 | 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".