Living in mixed species groups promotes predator learning in degraded habitats
Bibliographic record
Abstract
Living in mix-species aggregations provides animals with substantive anti-predator, foraging and locomotory advantages while simultaneously exposing them to costs, including increased competition and pathogen exposure. Given each species possess unique morphology, competitive ability, parasite vulnerability and predator defences, we can surmise that each species in mixed groups will experience a unique set of trade-offs. In addition to this unique balance, each species must also contend with anthropogenic changes, a relatively new, and rapidly increasing phenomenon, that adds further complexity to any system. This complex balance of biotic and abiotic factors is on full display in the exceptionally diverse, yet anthropogenically degraded, Great Barrier Reef of Australia. One such example within this intricate ecosystem is the inability of some damselfish to utilize their own chemical alarm cues within degraded habitats, leaving them exposed to increased predation risk. These cues, which are released when the skin is damaged, warn nearby individuals of increased predation risk and act as a crucial associative learning tool. Normally, a single exposure of alarm cues paired with an unknown predator odour facilitates learning of that new odour as dangerous. Here, we show that Ambon damselfish, Pomacentrus amboinensis, a species with impaired alarm responses in degraded habitats, failed to learn a novel predator odour as risky when associated with chemical alarm cues. However, in the same degraded habitats, the same species learned to recognize a novel predator as risky when the predator odour was paired with alarm cues of the closely related, and co-occurring, whitetail damselfish, Pomacentrus chrysurus. The importance of this learning opportunity was underscored in a survival experiment which demonstrated that fish in degraded habitats trained with heterospecific alarm cues, had higher survival than those we tried to train with conspecific alarm cues. From these data, we conclude that redundancy in learning mechanisms among prey guild members may lead to increased stability in rapidly changing environments.
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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".