Don't bet against the natal homing abilities of marine fishes
Bibliographic record
Abstract
Whether marine fishes are capable of homing to their natal areas has long been something of an enigma. For some estuarine species or sharks (which have extended nondispersal juvenile stages or are born as relatively large, fully formed juveniles), the answer is clearly 'yes' (Thorrold et al. ; Feldheim et al. ), but for most marine fishes, the issue is much more mysterious. Many species have free-floating eggs, and most have pelagic, passively dispersing larvae. It is challenging to imagine how adult fish might navigate to a region of the ocean they experienced only as eggs or larvae, and easier to assume that such dispersal leads inexorably to high gene flow, and even panmixia. One way to resolve the conundrum would be to track fish from hatching to reproduction, but for marine fishes with tiny eggs and drifting larvae, this is notoriously difficult to do (Bradbury & Laurel ). In this issue of Molecular Ecology, Bonanomi et al. () use a creative approach to solve this challenge for Atlantic cod (Gadus morhua) populations that mingle in the vicinity of Greenland. They show that cod that disperse more than a 1000 km away from Iceland as eggs and larvae, then spend years growing on the far side of Greenland, while mixing with two local populations, return as adults to spawning areas near Iceland - and further, that this behaviour has remained stable over more than six decades. They manage this feat with a clever use of historical cod tracking data, modern genomic data and genetic analysis of decades-old DNA obtained from archived materials. Their results have important implications for our view of the biocomplexity of marine fish populations, and how we should manage them.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.016 | 0.027 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".