Insights into mountain wetland resilience to climate change: An evaluation of the hydrological processes contributing to the hydrodynamics of alpine wetlands in the Canadian Rocky Mountains
Bibliographic record
Abstract
Hydrological conditions play an important role in provisioning the exceptionally valuable\necosystem services and functions of wetlands. In alpine areas, wetland functions and services are\nexpected to be very sensitive to climate-mediated changes in hydrology. However, few field\nstudies of alpine wetland hydrology currently exist, thus limiting understanding of how wetlands\nwill respond to warming and drying, and how their ecosystem services and functions will\nchange. This study examines key processes contributing to the hydrological stability of alpine\nwetlands in Banff National Park, AB, Canada. During the two-year study, snowmelt timing\ndiffered by over three weeks, allowing for the examination of water table patterns under\ncomparatively wet and dry conditions. Contrary to expectations, water table positions were\nrelatively stable in each study year, particularly in the peat-bearing soils. Hydrophysical and\nhydrochemical data together provide evidence that the observed stability is in part due to\ngroundwater contributions, which made up as much as 53% of the water budget in one peatland.\nSoil conditions also appear to play a role in stabilizing water table regimes. The results suggest\nthat alpine wetlands, and peatlands in particular, may be more resilient to changes in climate than\ncurrently thought. Mineral wetlands, comparatively, may have limited adaptive capacity.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".