Fluctuations in Hawaii’s humpback whale Megaptera novaeangliae population inferred from male song chorusing off Maui
Bibliographic record
Abstract
Approximately half of the North Pacific humpback whale Megaptera novaeangliae stock visits the shallow waters of the main Hawaiian Islands seasonally. Within this breeding area, mature males produce an elaborate acoustic display known as song, which becomes the dominant source of ambient underwater sound between December and April. Following reports of unusually low whale numbers that began in 2015/16, we examined song chorusing recorded through long-term passive acoustic monitoring at 6 sites off Maui as a proxy for relative whale abundance between 2014 and 2019. Daily root-mean-square sound pressure levels (RMS SPLs) were calculated to compare variations in low-frequency acoustic energy (0-1.5 kHz). After 2014/15, the overall RMS SPLs decreased between 5.6 and 9.7 dB re 1 µPa 2 during the peak of whale season (February and March), reducing ambient acoustic energy from chorusing by over 50%. This change in song levels co-occurred with a broad-scale oceanic heat wave in the northeast Pacific termed the ‘Blob,’ a major El Niño event in the North Pacific, and a warming period in the Pacific Decadal Oscillation cycle. Although it remains unclear whether our observations reflect a decrease in population size, a change in migration patterns, a shift in distribution to other areas, a change in the behavior of males, or some combination of these, our results indicate that continued monitoring and further studies of humpback whales throughout the North Pacific are warranted to better understand the fluctuations occurring in this recently recovered population and other populations that continue to be endangered or threatened.
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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".