Low summer river flows associated with low productivity of Chinook salmon in a watershed with shifting hydrology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Climate change and human activities are transforming river flows globally, with potentially large consequences for freshwater life. To help inform watershed and flow management, there is a need for empirical studies linking flows and fish productivity. We tested the effects of river conditions and other factors on 22 years of Chinook salmon productivity in a watershed in British Columbia, Canada. Freshwater conditions during adult salmon migration and spawning, as well as during juvenile rearing, explained a large amount of variation in productivity. August river flows while salmon fry reared had the strongest effect on productivity—our model predicted that cohorts that experience 50% below average flow in the August of rearing have 21% lower productivity. These contemporary relationships are set within long‐term changes in climate, land use, and hydrology. Over the last century, average August river discharge decreased by 26%, air temperatures warmed, and water withdrawals increased. Seventeen percent of the watershed was logged in the last 20 years. Our results suggest that, in order to remain stable, this Chinook salmon population being assessed for legal protection requires substantially higher August flow than previously recommended. Changing flow regimes—driven by watershed impacts and climate change—can threaten imperilled fish populations.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 it