Site carbon storage along productivity gradients of a late-seral southern boreal forest
Bibliographic record
Abstract
The quantity and distribution of carbon (C) storage in old-growth forests is a fundamental parameter needed to more accurately predict management effects on landscape C. C accounting on a regional or national level is generally based on zonal ecosystems, but total ecosystem C can vary widely with soil productive capacity within landscapes. To illustrate this, I compared old-growth forests of contrasting plant associations reflecting typical soil productivity gradients of the southern boreal forest in British Columbia, Canada. Total ecosystem C of zonal sites (medium–Huckleberry plant association) averaged 309 Mg C·ha–1, while less and more productive forest types ranged from 120 to 725 Mg C·ha–1, respectively. On average, 62% of ecosystem C was in live trees, 20% in mineral soils (0–50 cm), 9% in forest floors, and 9% in coarse woody debris and snags. Positive linear correlations between total ecosystem C and soil nitrogen availability or asymptotic stand height confirmed the strong influence of site productive capacity on C storage. The results demonstrate how ecological site classification or direct measures of stand productivity could refine estimates of the upper limits in potential C storage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".