Exposure Risk of Fish Downstream of a Hydropower Facility to Supersaturated Total Dissolved Gas
Bibliographic record
Abstract
Abstract Fish exposed to supersaturated total dissolved gas (TDG) levels can develop gas bubble trauma (GBT) which can lead to sublethal effects or mortality. Access to refugia in areas of high TDG that allows for hydrostatic (depth) compensation can mitigate exposure risk and GBT occurrence. The goals for this study were to examine resident fish habitat and depth use and assess exposure risk to elevated TDG levels related to hydropower operations in the Columbia‐Kootenay system in British Columbia. Modeling was used to predict TDG levels for three operational cases (low, medium, and high spill rates). Acoustic telemetry was used to track rainbow trout Oncorhynchus mykiss (RT) and mountain whitefish Prosopium williamsoni (MW) reach and depth residency. Telemetry results did not differ among operational scenarios and aligned with known biological/life history characteristics for fluvial or fluvial‐adfluvial species. Within‐species MW reach residency appeared to be reflective of seasonal habitat selection for spawning, foraging, and refuge movements. Within‐species RT reach residency appeared to follow habitat association patterns reflective of RT ecology. A risk assessment revealed that RT had a significantly higher TDG exposure risk relative to MW, but sufficient depth refugia habitat was available to mitigate exposure risk and GBT occurrence in both species. The results suggested that TDG exposure risk and actual risk depend on the interplay between species‐specific ecology and TDG patterns generated by hydropower facilities. The ecological and TDG patterns in this study suggested that system‐ and species‐specific studies will be required to generate detailed TDG exposure predictions for management decision‐making.
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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 | 0.000 | 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) | 0.001 | 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".