Kootenay Lake kokanee (<i>Oncorhynchus nerka</i>) collapse into a predator pit
Bibliographic record
Abstract
Kootenay Lake is a large, oligotrophic waterbody in southern British Columbia renowned for recreational fisheries for piscivorous rainbow trout (Oncorhynchus mykiss) and bull trout (Salvelinus confluentus). Long-term datasets showed an increase in large-bodied (>2 kg) piscivore abundance followed by a collapse of the kokanee (Oncorhynchus nerka) prey population in 2013 and subsequent decline of large-bodied piscivores. An unprecedented post-collapse state formed in 2015–2018, characterized by low kokanee spawner abundance and biomass and high catch rates for small-bodied (<2 kg), slow-growing piscivores. Bioenergetics model estimates of average historical (1961–2008) piscivore consumption was 29.3% of the average historical (1993–2008) kokanee prey supply (biomass and production), but increased to 78.7% in 2011, immediately preceding kokanee collapse. From 2015–2018, kokanee did not recover due to persistently poor juvenile survival; estimated piscivore consumption relative to prey supply remained high (73.0%), suggesting that kokanee were trapped in a predator pit. Although the ultimate and interacting causes of the predator build up remain uncertain, overcoming current depensatory dynamics may be aided by kokanee stocking or increasing harvest on still-abundant, unsatiated piscivores.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".