A method for long-term year-round water temperature monitoring in salmonid spawning habitats in remote dynamic streams
Bibliographic record
Abstract
Warming temperatures have added urgency to characterizing the thermalscapes and thermal tolerances of cold-adapted fishes to effectively manage and conserve such species. This is especially relevant at high latitude and high elevation streams, which are experiencing rapid environmental changes, yet are data-poor, remote, and difficult to access. Here, we describe a method to assess temporal and spatial variation in surface and hyporheic water temperatures that can be effectively deployed to remain year-round in remote dynamic streams. We then demonstrate the utility of this method by assessing Dolly Varden Salvelinus malma spawning sites in a remote river. Characterizing and quantifying the amount of viable thermal habitat for cold-adapted species improves predictions of how warming may affect high latitude and high elevation stream ecosystems. Together with species-specific thermal tolerances, this information can then be used to identify the thermal refugia that are essential for conservation of endemic species, and assess risks associated with range expansions of potentially colonizing species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".