Leaf area dynamics of a boreal black spruce fire chronosequence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 it