Bogs and their laggs in coastal British Columbia, Canada: Characteristics of topography, depth to water table, hydrochemistry, peat properties, and vegetation at the bog margin
Bibliographic record
Abstract
The transition zone at the margin of raised bogs (the lagg) is rarely studied, yet it can be important for maintaining a high water table in the peat mound. Where the lagg has been damaged or lost to agriculture, industry, or residential development, it may be necessary to restore a functional lagg inside the historic bog boundary to maintain the ecological health of the bog. Seventeen laggs from raised bogs in coastal British Columbia (BC) were studied to determine the natural range of lagg characteristics in this region. The laggs could be separated into two hydrotopographic forms: Marginal Depression (with mean early summer depth to water table of 12 cm and mean tree basal area of 2.8 m2/ha) and Flat Transition to forest (with mean early summer depth to water table of 34 cm and mean tree basal area of 26.3 m2/ha). These hydrotopographic forms were further classified into four vegetative lagg types: 1) Spiraea Thicket, 2) Carex Fen, 3) Peaty Forest, and 4) Direct Transition to forest (no lagg ecotone). The Carex Fen and Direct Transition lagg types were generally found in the Pacific Oceanic wetland region (cool, wet climate), while the Spiraea Thicket and Peaty Forest lagg types were more common in the Pacific Temperate wetland region (relatively warmer and drier climate). Regional differences in bog and lagg characteristics appear to be related to mean annual precipitation and mean annual temperature. The timing of seasonal fluctuations in depth to water table were similar for bogs and laggs, but the amplitude was generally greater in the lagg. Near-surface pore-water chemistry varied across the bog expanse – bog margin transition: pH, Ca2+ concentrations, and pH-corrected electrical conductivity generally increased from bog to lagg, although not consistently for individual study transects. Mg2+ and Na+ concentrations increased from bog to lagg for less than half of the studied transects. The most consistent indicators of the lagg, which may be of greatest use for delineation of lagg conservation zones include: topography, depth to water table, tree basal area, ash content of the peat, and dominant species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".