The integration of locomotion and prey capture in divergent cottid fishes: functional disparity despite morphological similarity
Bibliographic record
Abstract
Many mobile animals rely on the integration of locomotion and feeding to capture prey. Fishes commonly swim up to a prey item and utilize a combination of ram and suction feeding for prey capture. Marine cottids represent a diverse and abundant lineage of fishes that exhibit variation in feeding mode that is related to their mouth morphology. However, little is known regarding the integration of the locomotor and feeding systems during prey capture. We quantified the feeding kinematics, feeding performance and integration of locomotion and feeding in two species of divergent cottids: Blepsias cirrhosus (silver-spotted sculpin) and Oligocottus maculosus (tidepool sculpin). Individuals were caught from sympatric habitats near the Bamfield Marine Sciences Centre on Vancouver Island and filmed with a high-speed video camera (500 Hz) while feeding on amphipod prey. Two principal component axes summarize differences in integration and feeding mode despite similarity in attack velocity and feeding morphology (peak gape, peak cranial elevation and peak jaw protrusion). A greater number of correlations between locomotor and feeding variables in B. cirrhosus, compared with O. maculosus, indicate greater integration. We conclude that traditional measures of attack kinematics do not capture functionally and ecologically relevant differences between species. The mechanisms underlying differences in locomotor strategy likely result from unexplored morphological or ecological differences between species. In cottids, integration is apparent in more basal, subtidal species such as B. cirrhosus, and the need for integration may be superceded by demands from the habitat in more derived, shallow-water species such as O. maculosus.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".