Soil partitioning and surface store controls on spring runoff from a boreal forest peatland basin in north‐central Manitoba, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The mid‐ to high‐boreal forest in Canada occupies the discontinuous permafrost zone, and is often underlain by glaciolacustrine sediments mantled by a highly porous organic mat. The result is a poorly drained landscape dominated by wetlands. Frost‐table dynamics and surface storage conditions help to control runoff contributions from various landscape elements, hydrological linkages between these elements, and basin streamflow during spring snowmelt. Runoff components and pathways in a forested peatland basin were assessed during two spring snowmelts with contrasting input and basin conditions. Runoff from relatively intense melt (up to 16 mm day −1 ) on slopes with limited soil thawing combined with large pre‐melt storage in surface depressions to produce high flows composed primarily of meltwater (78% of the 0·29 m 3 s −1 peak discharge) routed over wetland surfaces and through permeable upper peat layers. Melt intensity was less in the subsequent year (maximum of 10 mm day −1 ) and active layer development was relatively greater (0·2 m deeper at the end of spring melt), resulting in less slope runoff. Coupling of reduced slope contributions with lower storage levels in basin wetlands led to relatively subdued streamflows dominated by older water (73% of the 0·09 m 3 s −1 peak discharge) routed through less‐permeable deeper peat layers and mineral soil. Interannual differences in runoff conditions provide important insight for the development of distributed hydrological models for boreal forest basins and into potential influences on biogeochemical cycling in this landscape under a warming climate. Copyright © 2001 John Wiley & Sons, Ltd.
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.
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) | 0.000 | 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 it