Nitrogen dynamics of a boreal black spruce wildfire chronosequence
Bibliographic record
Abstract
This study examined the nitrogen (N) dynamics of a black spruce (Picea mariana (Mill.) BSP)-dominated chronosequence in Manitoba, Canada. The seven sites studied each contained separate well- and poorly drained stands, originated from stand-killing wildfires, and were between 3 and 151 years old. Our goals were to (i) measure total N concentration ([N]) of all biomass components and major soil horizons; (ii) compare N content and select vegetation N cycle processes among the stands; and (iii) examine relationships between ecosystem C and N cycling for these stands. Vegetation [N] varied significantly by tissue type, species, soil drainage, and stand age; woody debris [N] increased with decay state and decreased with debris size. Soil [N] declined with horizon depth but did not vary with stand age. Total (live + dead) biomass N content ranged from 18.4 to 99.7 g N m−2 in the well-drained stands and 37.8–154.6 g N m−2 in the poorly drained stands. Mean soil N content (380.6 g N m−2) was unaffected by stand age. Annual vegetation N requirement (5.9 and 8.4 g N m−2 yr−1 in the middle-aged well- and poorly drained stands, respectively) was dominated by trees and fine roots in the well-drained stands, and bryophytes in the poorly drained stands. Fraction N retranslocated was significantly higher in deciduous than evergreen tree species, and in older than younger stands. Nitrogen use efficiency (NUE) was significantly lower in bryophytes than in trees, and in deciduous than in evergreen trees. Tree NUE increased with stand age, but overall stand NUE was roughly constant (∼ ∼150 g g−1 N) across the entire chronosequence.
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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 | 0.001 | 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".