Distinct Fluvial Patterns of a Headwater Stream Network Underlain by Discontinuous Permafrost
Bibliographic record
Abstract
Hydrology, permafrost, and vegetation will likely respond to warming of northern latitudes with concurrent shifts in channel form and network pattern. At present, data on channel structure and networks in most northern regions are sparse, thus restricting any comprehensive understanding of channel processes or predictions of change in response to warming. We conducted a survey in 2011 of stream hydraulic geometry and network pattern in an upland headwater catchment of the Yukon River basin that is underlain by discontinuous permafrost. We found atypical hydraulic geometry exponents for depth and velocity but not for width and slope. We also found the study catchment to have unusually low drainage density and bifurcation ratios. Our data support the hypothesis that snow and channel ice decrease geomorphic effectiveness during snowmelt, which ultimately constrains channel and network development. Additionally, qualitative data support the hypothesis that dense riparian vegetation promotes bank stabilization and leads to nearly vertical channel walls in small streams, thus leading to anomalous hydraulic geometry. Simple metrics such as the drainage density and hydraulic geometry relationships may prove to be useful metrics of boreal and subarctic warming and permafrost thaw, and this study may serve as an important baseline to evaluate future changes.
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 | 0.001 |
| 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) | 0.001 | 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".