Plant community type is an indicator of the seasonal moisture deficit in a disturbed raised bog
Bibliographic record
Abstract
Abstract Depth to water table is a simple, commonly used measure of hydrological function in raised bogs. The maximum depth of the water table or the average annual water table is often monitored over the long term to track the hydrological trajectory of the ecosystem. These measures, however, may not take into account the duration of the moisture deficit period. The annual water table moisture deficit (WTMD) at 67 sites in a single disturbed raised bog was calculated using the amount of time that the water table was at each depth below the surface during the moisture deficit season. The calculated value estimates a linearly developing deficit that dewaters the acrotelm during the moisture deficit season. At each site, plant species composition was assigned to one of eight plant community types. The approximate threshold above which bog plant communities will begin transitioning into drier types with taller shrubs and trees was a WTMD of 62 m‐days. An annual climatic moisture deficit (CMD) was calculated using daily air temperature, spatially interpolated precipitation and estimated potential evapotranspiration for each site. Mixed‐effects modelling of WTMD as a function CMD indicated a positive linear relation for most vegetation types, which was affected by the presence of drainage ditches, ditch blocking, fire and evapotranspiration by shrubs and trees. Tracking the WTMD and its relation to CMD may be useful for assessing ecosystem health and serve as a basis for estimating moisture deficit thresholds for bogs of conservation concern.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".