The relationship among micro-topographical variation, water table depth and biogeochemistry in an ombrotrophic bog
Bibliographic record
Abstract
Peatlands store 30% of global terrestrial organic carbon. At the Mer Bleue research site in southern Canada (45.40° N, 75.50° W), it has been shown that changes in water storage affect carbon fluxes in and out of the peatland. Mer Bleue has a distinct hummock – hollow surface topography. The micro-topographical features affect the temporal and spatial variations in water table. Sampling the temporal and spatial variations on two separate plots with varying degrees of micro-topographic relief took place during the 2010 field season. Each plot has 100 manual observation wells in a 2 x 2 metre grid that have been sampled every 2-3 weeks and several transects of 4-7 automatic capacitance data loggers, continuously recording water levels every 15 minutes. The continuous water table measurements were situated to maximize the difference in elevation between adjacent hummocks and hollows. Our results indicate that the spatial pattern of the water table at any given time is a subdued reflection of the surface topography – i.e. greater depth under hummocks than hollows. The continuous water table measurements show that the variations in water table are synchronized, despite differences in surface micro-topography. When combined with the surface elevation the patterns in time and space can be used to provide a tempo-spatial ecologically meaningful measure of water storage, explain the feedbacks between moisture and peat accumulation, and suggest a basis for scaling point measurements to account for topographic variations.
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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 | 0.000 | 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".