Drawdown, Habitat, and Kokanee Populations in a Western U.S. Reservoir
Bibliographic record
Abstract
Abstract Greater drought frequency and severity due to climate change will result in greater drawdown of water storage reservoirs. However, changes to oxythermal regimes due to drawdown are reservoir specific and interface with fish species-specific habitat requirements, producing varying effects on coldwater fish populations. We examined the effect of drawdown on the oxythermal habitat and relative abundance of kokanee Oncorhynchus nerka, a coldwater salmonid, in Island Park Reservoir on the Henrys Fork of the Snake River, Idaho. A measure of relative kokanee abundance was negatively, exponentially related to drawdown. Oxythermal patterns measured in the reservoir during 2021, a severe drought year, revealed that drawdown reduced kokanee habitat by increasing water temperatures and decreasing dissolved oxygen concentrations. Oxythermal refugia for kokanee appeared to relate to inflow from the spring-fed Henrys Fork and other groundwater inflows. However, we did not quantify groundwater flow or connections, and we did not study kokanee population demographics or mortality. Reducing these sources of uncertainty is a priority for future study. Still, our study highlights a potential mechanism connecting reservoir drawdown to fish populations and the unique yet predictable mechanisms by which reservoir drawdown interacts with reservoir morphometry to affect fish habitat availability.
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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 | 0.001 |
| 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 | 0.001 |
| 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".