Carbon distribution of a well‐ and poorly‐drained black spruce fire chronosequence
Bibliographic record
Abstract
Abstract The objective of this study was to quantify carbon (C) distribution for boreal black spruce ( Picea mariana (Mill.) BSP) stands comprising a fire chronosequence in northern Manitoba, Canada. The experimental design included seven well‐drained (dry) and seven poorly‐drained (wet) stands that burned between 1998 and 1850. Vegetation C pools (above‐ground + below‐ground) steadily increased from 1.3 to 83.3 t C ha −1 for the dry chronosequence, and from 0.6 to 37.4 t C ha −1 for the wet chronosequence. The detritus C pools (woody debris + forest floor) varied from 10.3 to 96.0 t C ha −1 and from 12.6 to 77.4 t C ha −1 for the dry and wet chronosequence, respectively. Overstorey biomass, mean annual biomass increment (MAI), woody debris mass, and litterfall were significantly greater (α = 0.05) for the dry stands than for the wet stands, but the bryophyte, understorey, and forest floor C pools were significantly less for the dry than for the wet stands. The root mass ratio decreased with stand age until 37 years after fire, was fairly constant thereafter, and was not significantly affected by soil drainage. The C pools of the overstorey and bryophyte tended to increase with stand age. Foliage biomass, litterfall, and MAI (for the dry stands) peaked at 71 years after fire and declined in the oldest stands. The results from this study illustrate that the effects of disturbance and edaphic conditions must be accounted for in boreal forest C inventories and C models. The appropriateness of using chronosequences to examine effects of wildfire on ecosystem C distribution is discussed.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".