Forest floor versus ecosystem CO<sub>2</sub> exchange along boreal ecotone between upland forest and lowland mire
Bibliographic record
Abstract
We determined the landscape variation of forest floor (FF) CO2 uptake (photosynthesis, P), FF CO2 emission (respiration, R) in relation to net ecosystem CO2 exchange (NEE) and environmental factors along a forest-mire ecotone in Finland. The 450 m long ecotone extended from xeric, upland pine dominated habitats, through spruce and transitional spruce-pine-birch forest, to sedge peatlands downslope. The CO2 fluxes were measured at nine stations during 2005 using chamber and IR techniques. Instantaneous P and R measurements for each station were interpolated by fitting their response to continuous records of light (mean R2 = 0.66) and temperature (mean R2 = 0.77) recorded nearby to give annual estimates. Stand biomass increment was used to estimate the annual CO2 exchange contribution of the trees. Annual P values from -307 to -1632 gCO2m-2yr-1 were inversely correlated with FF light (r = -0.96), FF above-ground biomass (r=-0.92) and canopy openness (r=-0.95). Annual R values from 1263 to 2813 gCO2 m-2 yr-1 were correlated with tree stand foliar biomass (r = 0.77). Estimated NEE values varied from 546 to -1679 gCO2m-2/yr-1, with P contributing from -307 to -1632 gCO2m-2yr-1 (4–90%) to gross ecosystem photosynthetic production, and R from 1263 to 2813 gCO2m-2yr-1 (70–98%) to gross ecosystem respiration (GR).
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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) | 0.001 | 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".