Evidence for adaptive strategies in larval capelin on the northeastern coast of Newfoundland, Canada
Bibliographic record
Abstract
Abstract Fish species with high mortality during early life may maximize fitness using adaptive strategies to time hatching to match favorable environmental conditions (match/mismatch) or extending spawning/hatching to disperse risk (bet-hedging). We examined support for these strategies in a collapsed forage fish, capelin (Mallotus villosus), in coastal Newfoundland (2018–2021). Capelin shift from spawning at warm, intertidal to cool, subtidal (15–40 m) habitats in warmer years, with unknown recruitment consequences. We hypothesized that match/mismatch (specifically, Coastal Water Mass Replacement Hypothesis) would be supported if densities of recently hatched larvae showed pulses that overlapped with high prey and low predator densities. Generalized additive models revealed that larval densities increased with zooplankton prey biomass, but were not influenced by predator biomass or temperature, contrasting with pre-collapse studies and providing equivocal support for match/mismatch. Protracted larval emergence and previously documented high variability in larval traits supported a bet-hedging strategy. Larval condition (i.e. length, yolk-sac diameter) did not differ between habitats but varied among years, where the highest proportion of larvae in poor condition was from the intertidal site in the warmest year (2018). Findings suggest that spawning habitat shifts may have limited impact on stock recovery relative to year-specific environmental conditions that influence larval condition.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".