Long-term Changes in the Fish Assemblage in Sandybeach Lake, Northern Ontario, Following the Introduction of Rainbow Smelt (<i>Osmerus mordax</i>)
Bibliographic record
Abstract
Rainbow Smelt (Osmerus mordax, Mitchill, 1814) has been widely introduced into lakes across North America and are reported to have an adverse effect on native fishes. In this study, we investigated the long-term changes to the pelagic fish assemblage in a northwestern Ontario lake (Sandybeach Lake) after Rainbow Smelt were introduced in the 1980s. We repeated an earlier summer, pelagic gill-netting survey of Sandybeach Lake and a nearby reference lake (Little Vermillion Lake) that does not contain Rainbow Smelt. Fishes throughout the water column were sampled with overnight sets of 5.2-m-deep, multi-mesh horizontal gill-nets. Compared with 1990 pelagic sampling, native fishes were significantly less abundant, less diverse, and largely absent from the deeper parts of Sandybeach Lake in 2012. Cisco (Coregonus artedi, Lesueur, 1818), Emerald Shiner (Notropis atherinoides Rafinesque, 1818), and Lake Whitefish (Coregonus clupeaformis, Mitchill, 1814) were notably absent in 2012. In contrast, Rainbow Smelt remained abundant at all depths sampled. A small number of ciscoes — including Shortjaw Cisco (Coregonus zenithicus (Jordan and Evermann, 1909)) — and Lake Whitefish were captured from benthic gill-nets. Based on the lack of ciscoes in pelagic gill-nets, the very old ages (mean 30 years) of the few individuals captured in benthic gill-nets, and a severely skewed sex ratio, it is highly likely that ciscoes will be extirpated from Sandybeach Lake. Although the composition of the pelagic fish assemblage differed between years, Cisco was still abundant in Little Vermillion Lake with the presence of young individuals indicating ongoing recruitment.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".