Effects of glacial retreat on proglacial streams and riparian zones in the Coast and North Cascade Mountains
Bibliographic record
Abstract
ABSTRACT Proglacial stream development was studied in coastal British Columbia and Washington, focusing on reaches exposed by post‐Little Ice Age (LIA) glacier retreat, to address three principal questions: (i) Does the legacy of LIA glaciation influence the evolution of channel morphology? (ii) How long does it take for riparian forest to establish following glacier retreat? (iii) Can newly exposed proglacial streams provide suitable fish habitat? Channel morphologies were identified by field surveys of 69 reaches in 10 catchments. Riparian forest development and potential fish habitat were characterized in those reaches and an additional 22 catchments using GIS analysis. The landscape template imposed by the Quaternary glaciation appears to override most of the modern effects of the LIA in controlling channel‐reach morphology. Binary logistic regression analysis identified elevation and time since deglaciation as primary controls on the presence of riparian forest. At higher elevations, establishment of morphologically functional riparian forest could take several centuries, prolonged by channel instability associated with post‐LIA sediment inputs. Of the recently deglaciated streams included in this analysis, the majority (86%) of the total length was of suitable gradient for fish and could be accessed either by downstream populations or from adjacent lakes. Predicted maximum weekly average stream temperature (MWAT) indicated that the post‐LIA study streams were thermally suitable for cold‐water fish. A future scenario of glacier loss would cause a 14% decline in accessible cold‐water thermal habitat in post‐LIA streams. Decreased summer flows due to glacier retreat could further limit usable habitat by reducing stream depths and wetted perimeters. Copyright © 2013 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.
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 | 0.001 |
| 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".