Experimental hydrological forcing to illustrate water flow processes of a subarctic ladder fen peatland
Bibliographic record
Abstract
Abstract Large peatland complexes dominate the landscape of the James Bay Lowland in subarctic Ontario, Canada. However, there is not a thorough understanding of the hydrological processes occurring in these important systems, particularly how ladder fens connect large domed bogs to the aquatic ecosystems that drain the peatland complex. Ladder fens consist of a pool‐rib topography where flow downgradient is controlled by the peat ribs. Within the ribs, low‐lying preferential flow paths typically enhance the transmission of water, whereas the elevated ridge microforms impede water flow to downgradient aquatic ecosystems. To assess the hydrological connectivity, we study the role of the water table, peat transmissivity, and microtopography of a small ladder fen for 3 summers (2013–2015) in the James Bay Lowland. The system was manipulated with a sustained hydrological forcing (water addition) to the upslope boundary of the fen during 2014 (38 m3/day) and 2015 (30 m3/day). There was an exponential increase in transmissivity towards the peat surface due to extremely high‐hydraulic conductivities within the upper few centimeters of the peat deposit. At the maximum water table, the saturated hydraulic conductivity of the 0.1 m layer of peat below the water table varied depending on peat microtopography (preferential flow paths = 42–598 m/day and ridges = 16–52 m/day), resulting in high‐hydrological connectivity periods. Furthermore, during 2015, there was an abnormally large amount of precipitation (300 mm vs. long‐term average ~ 100 mm) that resulted in complete surface water connectivity of the site. This caused rapid movement of water from the head of system to the outlet (~15 hr) and runoff ratios >1, compared to low‐water table periods (runoff ratio ~ 0.05). This study highlights the profound importance of the transmissivity–water table feedback mechanism in ladder fens, on controlling the water retention and drainage of large peatland complexes.
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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 | 0.001 |
| 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".