Data from: Risk of extinction of a unique skate population due to predation by a recovering marine mammal
Bibliographic record
Abstract
Benefitting from reduced harvesting and an end to culling, many marine mammals are now recovering from past overexploitation. These recoveries represent important conservation successes but present a serious conservation problem when the recovering mammals are predators of species of conservation concern. Here we examine the role of predation by recovering grey seals (Halichoerus grypus) in the near-extinction of a unique skate population in the southern Gulf of St. Lawrence (sGSL) in Atlantic Canada. Winter skate (Leucoraja ocellata) in the sGSL are distinct from winter skate elsewhere and may represent an endemic species. Their adult abundance has declined by 98% since 1980 and these skates are now detectable in only a small fraction of their former range. Population modelling indicates that the ongoing collapse of this population is due to increases in the natural mortality of adults. Based on model projections this population would be extinct by mid-century if its current rate of productivity were to persist. A second population model incorporated predation by grey seals. Model estimates of skate consumption by seals were consistent with historical and recent estimates of the contribution of skates to grey seal diets. The estimated consumption accounted for the increases in the natural mortality of adult skates. A Type III functional response for grey seals preying on winter skate emerged from the model results. This indicates that, when skate abundance is very low, grey seals are expected to switch to alternate prey, resulting in declines in the mortality of skates due to predation. Consequently, contrary to projections at current productivity, winter skate are expected to be trapped at very low abundance in a “predator pit” instead of declining to extinction. Nonetheless, extinction risk would remain very high at the very small population size in the predator pit. Our results emphasize the need for an ecosystem-based approach to the management of living resources in this ecosystem.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.012 |
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".