Association between porpoise presence and fish choruses: implications for feeding strategies and ecosystem‐based conservation of the East Asian finless porpoise
Bibliographic record
Abstract
The associations between feeding activities and environmental variables inform animal feeding tactics that maximize energetic gains by minimizing energy costs while maximizing feeding success. Relevant studies in aquatic animals, particularly marine mammals, are scarce due to difficulties in the observation of feeding behaviors in aquatic environments. This data scarcity concurrently hinders ecosystem-based fishery management in the context of small toothed-cetacean conservation. In the present study, a passive acoustic monitoring station was deployed in an East Asian finless porpoise habitat in Laizhou Bay to investigate potential relationships between East Asian finless porpoises and their prey. The data revealed that porpoises were acoustically present nearly every day during the survey period. Porpoise detection rates differed between spring and autumn in concert with activities of fish choruses. During spring, fish choruses were present throughout the afternoon, and this was the time when porpoise vocalizations were the most frequently detected. During autumn, when fish choruses were absent, porpoise detection rates decreased, and diurnal patterns were not detected. The close association between fish choruses and finless porpoise activities implies an "eavesdropping" feeding strategy to maximize energetic gains, similar to other toothed cetaceans that are known to engage similar feeding strategies. Underwater noise pollution, particularly those masking fish choruses, could interrupt finless porpoises' feeding success. Fisheries competing soniferous fishes with finless porpoise could impact finless porpoise viability through ecosystem disruption, in addition to fishing gear entanglement.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".