Net ecosystem CO2 exchange for moss and lichen dominated forest floors of old-growth sub-boreal spruce forests
Bibliographic record
Abstract
This study used instantaneous chamber-based CO2 exchange measurements (2004) in conjunction with a seasonal record of microclimate (2003) to model growing season forest floor net ecosystem CO2 exchange (ffNEE) for terrestrial bryophyte and lichen communities in sub-boreal forests in central British Columbia, Canada. Multiple regression models using microclimate variables described between 35 and 53 % of the variation in ffNEE for moss or lichen dominated forest floor at an ambient CO2 concentration. Light and moss or lichen moisture and temperature were all important variables in describing ffNEE from moss and lichen dominated forest floor patches while substrate temperature was the most important variable explaining ffNEE from bare litter + soil and wood. Moss dominated forest floor had relatively invariant mean diel ffNEE across the 3-month growing season while lichen dominated wood had low summer ffNEE which increased in September. Over a 3-month growing season in 2003, moss dominated forest floor had a total ffNEE of!33.8 g C m!2 and lichen dominated wood had a total ffNEE of!42.9 g C m!2. When ffNEE values from the moss, lichen, bare wood, and bare litter + soil components of the forest floor community were summed over the 3-month period, the old-growth sub-boreal spruce forest floor had a net CO2 exchange of!31.6 g C m!2, representing a loss of this amount of carbon over the growing season. The moss dominated, but not lichen dominated, forest floor appeared limited by ambient forest floor CO2 levels (430 mmol CO2 mol!1) and exhibited increased photosynthesis at elevated CO2 (700 mmol CO2 mol
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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 | 0.000 | 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".