Information to support the Ikaluit Lake (Robert Peel Inlet) Arctic Char (Salvelinus alpinus) Assessment
Bibliographic record
Abstract
Within Cumberland Sound there are multiple stocks of Arctic Char (Salvelinus alpinus). This evaluation was performed to provide an updated summary of information available to assess the status of the Ikaluit Lake (Robert Peel Inlet) Arctic Char stock and recommend a long-term plan for the fishery. This waterbody was harvested as a test fishery from 1977 until 1982, as an exploratory fishery from 1983 until 1989, and as a commercial fishery (Schedule V) from 1990 until 2000, at which time the Pangnirtung Hunters and Trappers Organization (PHTO) requested that the commercial fishery be closed for a five-year period due to declining catches of larger Arctic Char. The initial quota was set at 1,500 kg for the test fishery and then reduced to 1,400 kg for the commercial licence. The Ikaluit Lake fishery was reopened in 2006 as an exploratory fishery with a reduced quota of 1,000 kg, where it currently remains. In this assessment there are four types of data presented from Ikaluit Lake: test fishery data; fishery-dependent data; fishery-independent data; and plant data. In addition to the licenced harvest, Ikaluit Lake Arctic Char are also harvested for subsistence purposes by both the community of Pangnirtung and the community of Iqaluit, however the rate of subsistence harvesting is not well documented. The results from this assessment suggest that the Ikaluit Lake Arctic Char stock is stable under present harvest levels. Consistency among recent years in Catch-Per-Unit-Effort (CPUE) data, weight-length relationships, length-frequency distributions, age-frequency distributions, mean trend data, length-at-age data, and age-at-maturity data support this conclusion. However, there are some signs that the stock is changing in response to fishing pressure as seen in the catch curves and instantaneous mortality rates over the years. Abundance modelling calculated a potential population size ranging from 4,288 to 9,594 individuals in the Ikaluit Lake stock. After applying a 5% threshold of the modelled abundance for sustainable harvesting (the ‘Tallman Rule’), current harvest rates (not including subsistence fishing) are sustainable for the stock, however when subsistence fishing estimates are factored in, the stock becomes under significant harvest pressure. The recommendations for the long-term plan for Arctic Char in Ikaluit lake are to: more accurately account for subsistence harvesting in future assessments, continue close monitoring of the stock, ensure that future sampling is done in a consistent manner, and to collect and document the available traditional knowledge.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.059 | 0.014 |
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".