Frequent transitions from night-to-day activity after mass extinctions
Bibliographic record
Abstract
ABSTRACT Why certain species survive large-scale extinction events while others do not is poorly understood. While the fossil record can provide insights into morphological adaptations that increase survival probabilities, it provides limited information regarding behavioural traits. Here we integrate behavioural data with phylogenetic comparative models to study the evolution of day-night activity patterns (nocturnality and diurnality) in bony fishes, which have persisted through the last four mass extinction events. Our findings in fish, combined with data across all other clades of vertebrates, provide four lines of evidence that nocturnality conferred an evolutionary advantage during mass extinctions, and that frequent nocturnal-to-diurnal transitions facilitated post-extinction diversification: First, phylogenetic reconstruction indicates that the last common ancestors of all vertebrates and of clades of bony vertebrates were nocturnal. Second, in the lineage of bony fishes, which contains over half of all vertebrate species, twice as many transitions between nocturnal and diurnal activity patterns have occurred compared to tetrapods. Third, within a specific ecological niche, different species exhibit distinct temporal activity patterns, suggesting widespread temporal niche partitioning. Fourth, independent bursts in night-to-day transitions followed large-scale extinction events during the last two geological eras in all four major bony vertebrate groups. These observations suggest that ancestral nocturnality and frequent transitions to diurnality helped vertebrates survive and diversify in the face of extinction events, such as those expected during the current “6th mass extinction” event caused by anthropogenic climate change.
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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 | 0.000 |
| 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".