The evolutionary origins of diadromy inferred from a time-calibrated phylogeny for Clupeiformes (herring and allies)
Bibliographic record
Abstract
One of the most remarkable types of migration found in animals is diadromy, a life-history behaviour in which individuals move between oceans and freshwater habitats for feeding and reproduction. Diadromous fishes include iconic species such as salmon, eels and shad, and have long fascinated biologists because they undergo extraordinary physiological and behavioural modifications to survive in very different habitats. However, the evolutionary origins of diadromy remain poorly understood. Here, we examine the widely accepted productivity hypothesis, which states that differences in productivity between marine and freshwater biomes determine the origins of the different modes of diadromy. Specifically, the productivity hypothesis predicts that anadromous lineages should evolve in temperate areas from freshwater ancestors and catadromous lineages should evolve in tropical areas from marine ancestors. To test this, we generated a time-calibrated phylogeny for Clupeiformes (herrings, anchovies, sardines and allies), an ecologically and economically important group that includes high diversity of diadromous species. Our results do not support the productivity hypothesis. Instead we find that the different modes of diadromy do not have predictable ancestry based on latitude, and that predation, competition and geological history may be at least as important as productivity in determining the origins of diadromy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".