Variations in above- and below-ground vascular plant biomass and water table on a temperate ombrotrophic peatland
Bibliographic record
Abstract
In wetland ecosystems, little is known about the relationships between above- and below-ground plant biomass and water table, a primary driver of their distribution in these systems. These relationships can provide a means for estimating belowground stocks over large areas with variable biomass and predicting vascular plant responses to changing water tables resulting from climate change. We measured above- and below-ground vascular plant biomass across species and microtopography (i.e., hummocks and lawns) in a bog in eastern Ontario. We examined the relationships between above- and below-ground vascular plant biomass their variation with water table and species richness. We took 56 cores during a growing season, separating above- and below-ground biomass by species and plant part (small and coarse root, leaf, stem). Hummocks had greater above- and below-ground biomass, and significantly greater aboveground:belowground ratios than lawns. Lawns had a more even distribution of biomass across species than hummocks aboveground, indicating that only a few species (e.g., Vaccinium myrtilloides Michx. and Chamaedaphne calyculata Moench) are able to thrive in the driest bog conditions. Additionally, fewer species contributed to root biomass at depth, suggesting possible resource partitioning among species. Lower water tables lead to greater belowground biomass. Total above- to below-ground plant biomass relationships were strongest when separated by plant species.
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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 | 0.001 | 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) | 0.001 | 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".