HETEROSPECIFIC AGGRESSION AND ADAPTIVE DIVERGENCE IN BROOK STICKLEBACK (CULAEA INCONSTANS)
Bibliographic record
Abstract
Agonistic behavior between heterospecifics, in which individuals of one species attack another, may cause a subordinate species to shift resource or habitat use. Subsequent evolutionary responses to selection may mimic shifts expected under ecological character displacement, but with no role played by exploitative competition. Alternatively, aggressive behavior can evolve when fitness is improved by excluding members of a coexisting species from a defendable resource through interference. We tested whether heterospecific agonistic behavior has evolved in brook stickleback (Culaea inconstans) by comparing replicate allopatric populations to those sympatric with ninespine stickleback (Pungitius pungitius). We also tested for heritable variation in heterospecific aggressive behavior by rearing family groups in a common environment. Allopatric populations of brook stickleback were more aggressive than ninespine stickleback, suggesting that pre-existing aggression in brook stickleback contributed to niche shifts by ninespine stickleback. In addition, sympatric adult brook stickleback were more aggressive toward ninespine stickleback than brook stickleback from allopatric populations. Overt heterospecific aggressive behaviors were heritable, and aggression in juvenile brook stickleback increased with age in sympatric but not in allopatric populations reared in a common environment. Brook stickleback have evolved increased aggression when they coexist with ninespine stickleback. These stickleback communities have been structured by both evolved and pre-existing variation in heterospecific aggressive behavior in brook stickleback.
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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 | 0.001 | 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) | 0.001 | 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".