Species divergence under competition and shared predation
Bibliographic record
Abstract
Species competing for resources also commonly share predators. While competition often drives divergence between species, the effects of shared predation are less understood. Theoretically, competing prey species could either diverge or evolve in the same direction under shared predation depending on the strength and symmetry of their interactions. We took an empirical approach to this question, comparing antipredator and trophic phenotypes between sympatric and allopatric populations of threespine stickleback and prickly sculpin fish that all live in the presence of a trout predator. We found divergence in antipredator traits between the species: in sympatry, antipredator adaptations were relatively increased in stickleback but decreased in sculpin. Shifts in feeding morphology, diet and habitat use were also divergent but driven primarily by stickleback evolution. Our results suggest that asymmetric ecological character displacement indirectly made stickleback more and sculpin less vulnerable to shared predation, driving divergence of antipredator traits between sympatric species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.005 | 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 teacher head, 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".