Variable forage fish biomass and phenology influence marine predator diet, foraging behavior, and species interactions in coastal Newfoundland, Canada
Bibliographic record
Abstract
Abstract Forage fish species provide essential linkages for energy transfer within pelagic marine food webs. Capelin (Mallotus villosus), the focal forage fish in coastal Newfoundland, Canada, suffered a stock collapse in 1991 and has not recovered. Despite this collapse, capelin continue to provide locally abundant prey aggregations. Here, I synthesize the lessons learned from a long-term capelin-predator research program (2004–2022) on the northeast Newfoundland coast during the postcollapse period. I highlight the importance of simultaneously estimating forage fish biomass and predator responses in a multispecies and multiyear context. High interannual variation in capelin spawning timing and biomass was observed. Lower capelin biomass consistently resulted in predator species- and assemblage-level dietary shifts toward a higher diversity of lower trophic level, alternative prey. Energetic foraging costs of seabirds also increased under lower capelin biomass, but responses differed among species. Summer capelin consumption by dominant seabirds (9389 tonnes) and whales (778 tonnes) indicated predator energetic requirements and revealed higher natural mortality relative to fishery-based (1289 tonnes) mortality. Overall, this case study illustrated that, despite high observed behavioural plasticity, varying species-specific predator responses to changing capelin biomass integrated to increase potential competitive interactions under low capelin biomass, providing a basis for ecosystem-level change.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".