Spatial ecology of two Lake Whitefish (Coregonus clupeaformis) spawning aggregations in eastern Lake Ontario
Bibliographic record
Abstract
Lake Whitefish (Coregonus clupeaformis) in the Laurentian Great Lakes have experienced major ecological changes and overexploitation by commercial fisheries throughout the past century. In Lake Ontario, the Lake Whitefish population was severely reduced and has shown minimal reproductive success since the 1990s. In Canadian waters, two major spawning aggregations persisted in the eastern basin, one in the Bay of Quinte and the other in Lake Ontario, and currently support a commercial fishery. At the present time, there is an urgent need for more research on this species in Lake Ontario to better understand the impacts of ecological changes and to ensure that the commercial fishery is sustainable. Using acoustic telemetry, this study analyzed the spatial distribution and movement patterns of Lake Whitefish in eastern Lake Ontario to determine whether the two spawning groups were spatially discrete. A total of 57 Lake Whitefish were tagged with acoustic transmitters between 2016 and 2018. Spatial analysis revealed clear differences in space use between the spawning aggregations. Lake Whitefish from the Bay of Quinte spawning group occupied the northwestern area of the eastern basin and did not leave the eastern basin, whereas Lake Whitefish from the Lake Ontario spawning group mainly occupied the southeastern area of the eastern basin and moved outside the eastern basin. Mixing of the spawning groups did not occur during the spawning season and was minimal at other times of the year in the northwestern area of the eastern basin, primarily in August and September. This provided insight into the relative harvest of the spawning groups by the commercial fishery in spring and summer when the groups are not spatially isolated at spawning grounds in the fall. Differences in seasonal distribution were also observed for both spawning groups and provided insights into what factors may have influenced habitat selection. In summary, the spatial discreetness observed between the spawning aggregations suggests differences may exist in commercial exploitation and factors related to habitat use such as diet and energy expenditure. Although there is still a need for further research in these areas, this study has provided valuable insights for the management and conservation of this species in Lake Ontario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".