The role of harp seals, fisheries and food availability in driving the dynamics of northern cod
Bibliographic record
Abstract
The Atlantic cod Gadus morhua population off Newfoundland collapsed in the early 1990s due to over-exploitation, and despite marked reduction in fishing effort the stock remains depressed.Harp seal Pagophilus groenlandicus predation has been repeatedly proposed as an explanation for this lack of recovery, but other hypotheses include reduced prey availability and/or food quality (i.e.lack of capelin Mallotus villosus), as well as fisheries catches and environmental effects.Using a bioenergetics-allometric model, we gauged the relative contributions of these drivers on the lack of recovery and dynamics of the northern cod stock.Biomass dynamics were best explained by a combination of fisheries removals and capelin availability, whereas seal consumption was found not to be an important driver of the northern cod stock.Prey availability was linked to reduced somatic condition during the 1990s and 2000s.We discuss evidence that suggests that cod may be experiencing depensatory dynamics, but not related to a 'predator pit effect'.Our study suggests that trophic control is bottom-up, and that a depressed capelin stock could be a serious impediment for cod rebuilding.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".