Fight or flight: antipredator strategies of baleen whales
Bibliographic record
Abstract
ABSTRACT The significance of killer whale Orcinus orca predation on baleen whales (Mysticeti) has been a topic of considerable discussion and debate in recent years. Discourse has been constrained by poor understanding of predator‐prey dynamics, including the relative vulnerability of different mysticete species and age classes to killer whales and how these prey animals avoid predation. Here we provide an overview and analysis of predatory interactions between killer whales and mysticetes, with an emphasis on patterns of antipredator responses. Responses of baleen whales to predatory advances and attacks by killer whales appear to fall into two distinct categories, which we term the fight and flight strategies. The fight strategy consists of active physical defence, including self‐defence by single individuals, defence of calves by their mothers and coordinated defence by groups of whales. It is documented for five mysticetes: southern right whale Eubalaena australis , North Atlantic right whale Eubalaena glacialis , bowhead whale Balaena mysticetus , humpback whale Megaptera novaeangliae and grey whale Eschrichtius robustus . The flight strategy consists of rapid (20–40 km/h) directional swimming away from killer whales and, if overtaken and attacked, individuals do little to defend themselves. This strategy is documented for six species in the genus Balaenoptera . Many aspects of the life history, behaviour and morphology of mysticetes are consistent with their antipredator strategy, and we propose that evolution of these traits has been shaped by selection for reduced predation. Fight species tend to have robust body shapes and are slow but relatively manoeuvrable swimmers. They often calve or migrate in coastal areas where proximity to shallow water provides refuge and an advantage in defence. Most fight species have either callosities (rough and hardened patches of skin) or encrustations of barnacles on their bodies, which may serve (either primarily or secondarily) as weapons or armour for defence. Flight species have streamlined body shapes for high‐speed swimming and they can sustain speeds necessary to outrun pursuing killer whales (>15–20 km/h). These species tend to favour pelagic habitats and calving grounds where prolonged escape sprints from killer whales are possible. The rarity of observed successful attacks by killer whales on baleen whales, especially adults, may be an indication of the effectiveness of these antipredator strategies. Baleen whales likely offer low profitability to killer whales, relative to some other marine mammal prey. High‐speed pursuit of flight species has a high energetic cost and a low probability of success while attacks on fight species can involve prolonged handling times and a risk of serious injury.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".