Coordinated hunting behaviors of mixed-species groups of piscivores and associated species at Isla del Coco National Park (Eastern Tropical Pacific)
Bibliographic record
Abstract
ABSTRACT Studies of mixed-species groups of animals can reveal emergent complexities of collective behaviors. In this study we collected data on mixed-species hunting groups composed primarily of piscivorous fishes (species composition, abundance, behavioral interactions) and used both multivariate and network analyses to quantify pair-wise and guild level behavioral relationships. Our results indicate that such collective behaviors exhibit consistent patterns of associations (33 species with 282 pair-wise links within the observed network) with 10 dominant species accounting for 60% of pair-wise interactions. Species richness within groups varied (mean = 2.4, range 2-6 species) as did group size (mean = 8.1 individuals, range 2-80). Mixed-species groups, in general, were composed of species representing morphologically diverse forms that appeared to enhance access to shelter sites and implement diverse strategies for prey capture. It is noteworthy that the composition of groups did not reflect the relative abundances of their component species within the overall community of fishes, suggesting that group membership was an elective choice. The identification of these patterns, assuming they are persistent features of these communities, can be used as a foundation for studies to assess dynamics of mixed-species relationships, rates of predator success based on group membership, demographic consequences, and responses to variations in habitat attributes and associated prey resources. Such information could be used to interpret the nature of multispecies interactions within predator communities and potentially aid in conservation and management.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".