Differences in C, N, <i>δ</i><sup>13</sup>C, and <i>δ</i><sup>15</sup>N among plant functional types after a wildfire in a black spruce forest, interior Alaska
Bibliographic record
Abstract
We measured differences in %C, %N, δ13C, and δ15N of plant functional types (PFTs) between burned and unburned ground surfaces soon after a wildfire on a north-facing slope in interior Alaska. The C and N were measured for 16 species and Sphagnum litter. δ13C differed among the PFTs and was low for trees and shrubs, suggesting that woody stems slowed C dynamics or showed low water use efficiency. δ15N concentrations suggested that the herbaceous plants depended less on the mycorrhizal associations that became weak on the burned surfaces. The shrub leaves showed the lowest δ15N of PFTs and showed higher δ15N on the burned surface, showing that N transfer from the soils to the leaves in the shrubs was slowed by the wildfire. Mosses showed the highest C/N ratio. Sphagnum litter decomposed faster on the burned surface, and %N and δ15N in the litter increased from the second to third year on both burned and unburned surfaces, while %C changed little. In conclusion, the responses to the wildfire differed among the PFTs as characterized by their C and N dynamics.
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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 | 0.000 | 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) | 0.001 | 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".