Abundance and composition of plant biomass as potential controls for mire net ecosytem CO<sub>2</sub>exchange
Bibliographic record
Abstract
We compared the amount and composition of different aboveground biomass (BM) fractions of four mires with their net ecosystem CO 2 exchange (NEE) measured by eddy covariance. We found clear differences in response of green biomass (GBM) of plant functional types (PFTs) to water table (WT), which resulted in larger spatial variation in GBM within a mire than variation between mires. GBM varied between mires from 126 ± 7 to 336 ± 16 g·m –2 (mean ± SE), while within mire variation at largest was from 157 ± 17 to 488 ± 20 g·m –2 (mean ± SE). GBM of dominant PFTs appeared to be better in explaining the peak growing season NEE than the total BM or GBM of a mire. The differences in photosynthetic capacity between PTFs had a major role, and thus a smaller GBM with different species composition could result in higher NEE than larger GBM. Vascular plant GBM, especially that of sedges, appeared to have a high impact on NEE. Eleven PFTs, defined here, appeared to capture well the internal variation within mires, and the differences in GBM between communities were explained by the water table response of PFTs. Our results suggest the use of photosynthesizing BM, separated into PFTs, in modelling ecosystem carbon exchange instead of using just total BM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".