Maternal investment evolves with larger body size and higher diversification rate in sharks and rays
Bibliographic record
Abstract
Summary Across vertebrates, live-bearing has evolved at least 150 times from ancestral egg-laying into a diverse array of forms and degrees of prepartum maternal investment. 1,2 A key question is how this reproductive diversity arose and whether reproductive diversification underlies species diversification? 3–11 To test these questions, we evaluate the most basal jawed vertebrates, sharks, rays, chimaeras of Class Chondrichthyans, which have one of the greatest ranges of reproductive and ecological diversity among vertebrates. 2,12 We reconstructed the sequence of reproductive mode evolution across a time-calibrated molecular phylogeny of 610 chondrichthyans. 13 We find egg-laying is ancestral, and live-bearing evolved at least seven times. Matrotrophy (i.e. maternal contributions beyond the yolk) evolved at least 15 times, with evidence of one reversal. In sharks, transitions to live-bearing and matrotrophy are more prevalent in larger-bodied species in the tropics. Further, the evolution of live-bearing is associated with a near-doubling of the diversification rate, but, there is only a small increase in diversification associated with the appearance of matrotrophy and increased rates of speciation are associated with the colonization of novel habitats, contrary to what has been demonstrated in teleosts. 3,4 This highlights a potential key difference between chondrichthyans and other fishes, specifically a slower rate of reproductive isolation following speciation, suggesting different rate-limiting mechanisms for diversification between these clades. 14 The chondrichthyan diversification and radiation, particularly throughout the shallow tropical shelf seas and oceanic pelagic habitats, appears to be associated with the evolution of live-bearing and the proliferation of a wide range of maternal investment in developing offspring.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".