Detrital carbon pools in temperate forests: magnitude and potential for landscape-scale assessment
Bibliographic record
Abstract
Reliably estimating carbon storage and cycling in detrital biomass is an obstacle to carbon accounting. We examined carbon pools and fluxes in three small temperate forest landscapes to assess the magnitude of carbon stored in detrital biomass and determine whether detrital carbon storage is related to stand structural properties (leaf area, aboveground biomass, primary production) that can be estimated by remote sensing. We characterized these relationships with and without forest age as an additional predictive variable. Results depended on forest type. Carbon in dead woody debris was substantial at all sites, accounting for ∼17% of aboveground carbon, whereas carbon in forest floor was substantial in the subalpine Rocky Mountains (36% of aboveground carbon) and less important in northern hardwoods of New England and mixed forests of the upper Midwest (∼7%). Relationships to aboveground characteristics accounted for between 38% and 59% of the variability in carbon stored in forest floor and between 21% and 71% of the variability in carbon stored in dead woody material, indicating substantial differences among sites. Relating dead woody debris or forest floor carbon to other aboveground characteristics and (or) stand age may, in some forest types, provide a partial solution to the challenge of assessing fine-scale variability.
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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 | 0.001 | 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".