River–groundwater interactions in salmon spawning habitat: riverbed flow dynamics and non‐stationarity in an end member mixing model
Bibliographic record
Abstract
Abstract Salmonids commonly spawn in locations of upwelling vertical flow, but it is unclear whether this upwelling water is groundwater, river water which has spent some time flowing through the riverbed before re‐emerging downstream or some mixture of the two. Vertical specific discharge and riverbed water chemistry were monitored in spawning habitat of Sockeye ( Oncorhynchus nerka ) and Chinook Salmon ( Oncorhynchus tshawytscha ) in contiguous natural and modified sections of Okanagan River in southern British Columbia, Canada. A quasi‐stationary end member mixing model was developed to describe mixing between end members as well as hydrochemical modification along a subsurface flowpath. For this work, a hydrochemical category called ‘hyporheic water’ was defined as river water which spent some time flowing within the riverbed and developed a distinct chemistry. The resulting mixing triangle was used to categorise intragravel water chemistry as (1) river‐like, (2) mixed river and regional groundwater, (3) hyporheic water or (4) mixed hyporheic and regional groundwater. Sockeye Salmon spawned in locations with all combinations of vertical specific discharge and intragravel water chemistry, which was interpreted as a high degree of habitat use plasticity. Chinook Salmon redds were more common where regional groundwater mixed with river or hyporheic water in locations with upwelling or near‐neutral vertical specific discharge. Current efforts at restoring or enhancing salmonid spawning habitat can be improved by considering the subsurface flow dynamic needs of different target species. Copyright © 2016 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 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 | 0.001 |
| 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 teacher head, 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".