Anti‐Predator Benefits of Mixed‐Species Groups of Cowtail Stingrays (<i>Pastinachus sephen</i>) and Whiprays (<i>Himantura uarnak</i>) at Rest
Bibliographic record
Abstract
Abstract Heterospecific grouping can sometimes provide greater antipredator benefits to individuals than grouping with conspecifics. We explored the potential benefits of mixed‐species group resting in the cowtail stingray, Pastinachus sephen, and the reticulate whipray, Himantura uarnak, in Shark Bay, Western Australia. From focal follow data on individual resting choice, we first ascertained that cowtails preferred to rest with heterospecifics, as they chose to settle next to whiprays more often than to pass them (with the opposite trend observed for conspecifics). In addition, we determined from filmed boat transects that cowtails formed larger hetero‐ than monospecific groups despite the low density of whiprays. Possible benefits accrued by the cowtail were investigated in terms of predator protection. Whiprays responded earlier than cowtails to a mock predator (boat), and were most frequently the first to respond when in a mixed group. Thus, cowtails may benefit from grouping with heterospecifics by receiving earlier warning of a predator's approach. A decoy experiment using model whiprays demonstrated that cowtails were more willing to rest with models with relatively longer tails (controlled for body size). Ray tails, which are equipped with a mechanoreceptor capable of detecting predators, may constitute an important secondary means of predator detection aside from early warning. This contention is supported by the observation that stingrays mainly form resting groups when their visual ability is likely to be impaired by environmental conditions, and that tail length is negatively allometric with body size, suggesting its importance in vulnerable early life stages. If the efficacy of the mechanoreceptor increases with tail length, then cowtails may have further improved their likelihood of detecting predators by grouping with longer‐tailed heterospecifics.
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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 | 0.001 |
| 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".