Seasonal ground ice impacts on spring ecohydrological conditions in a western boreal plains peatland
Bibliographic record
Abstract
Abstract Peatlands in the Western Boreal Plains act as important water sources in the landscape. Their persistence, despite potential evapotranspiration (PET) often exceeding annual precipitation, is attributed to various water storage mechanisms. One storage element that has been understudied is seasonal ground ice (SGI). This study characterized spring SGI conditions and explored its impacts on available energy, actual evapotranspiration, water table, and near surface soil moisture in a western boreal plains peatland. The majority of SGI melt took place over May 2017. Microtopography had limited impact on melt rates due to wet conditions. SGI melt released 139mm in ice water equivalent (IWE) within the top 30cm of the peat, and weak significant relationships with water table and surface moisture suggest that SGI could be important for maintaining vegetation transpiration during dry springs. Melting SGI decreased available energy causing small reductions in PET (<10mm over the melt period) and appeared to reduce actual evapotranspiration variability but not mean rates, likely due to slow melt rates. This suggests that melting SGI supplies water, allowing evapotranspiration to occur at near potential rates, but reduces the overall rate at which evapotranspiration could occur (PET). The role of SGI may help peatlands in headwater catchments act as a conveyor of water to downstream landscapes during the spring while acting as a supply of water for the peatland. Future work should investigate SGI influences on evapotranspiration under differing peatland types, wet and dry spring conditions, and if the spatial variability of SGI melt leads to spatial variability in evapotranspiration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".