Evidence for extirpation of native kokanee in a large impounded watershed following introduction of a conspecific
Bibliographic record
Abstract
Abstract Objective Williston Reservoir in north-central British Columbia was stocked with kokanee Oncorhynchus nerka from the Columbia River during the 1990s. A native population of kokanee already existed in the reservoir, but that population has not been found in sampling efforts since 2000. Most of the recent sampling, however, has targeted tributaries, and the stocked Columbia River-type kokanee are stream spawners, whereas Thutade Lake kokanee, from which the native Williston Reservoir kokanee originated, are shore spawners. Methods In August 2021, pelagic surveys were conducted in Williston Reservoir by gillnetting and trawling to capture kokanee for subsequent genotyping to assess whether the native Williston Reservoir kokanee have persisted. We used 14 microsatellite loci to genotype 165 samples from the pelagic surveys and compared them to 623 previously genotyped kokanee from four reference populations: native reservoir fish; fish from the source population (Thutade Lake) that naturally colonized the reservoir; fish from isolated lakes in the Williston Reservoir watershed; and Columbia River-type fish that now spawn in tributaries to the reservoir. Result Kokanee collected from the pelagic survey conducted in Williston Reservoir were entirely assigned to the Columbia River type by using the Bayesian clustering program STRUCTURE and a discriminant analysis of principal components. We found no evidence of any native Williston Reservoir genotypes. Conclusion Formation of Williston Reservoir favored pelagic species, such as kokanee, which have gradually increased in proportion over time—particularly since the introduction of kokanee from the Columbia River. Unfortunately, native Williston Reservoir kokanee appear to have been extirpated from the reservoir and were likely outcompeted by the introduced Columbia River-origin kokanee.
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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 | 0.001 | 0.001 |
| 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 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".