A genetic assessment of polyandry and breeding‐site fidelity in lemon sharks
Bibliographic record
Abstract
We here employ 11 microsatellite markers and recently developed litter reconstruction methods to infer mating system parameters (i.e. polyandry and breeding-site fidelity) at a lemon shark nursery site in Marquesas Key, Florida. Four hundred and eight juvenile or subadult sharks were genotyped over eight complete breeding seasons. Using this information, we were able to infer family structure, as well as fully or partially reconstruct genotypes of 46 mothers and 163 fathers. Multiple litter reconstruction methods were used, and novel simulations helped define apparent bias and precision of at least some mating system parameters. For Marquesas Key, we find that adult female lemon sharks display high levels of polyandry (81% of all litters sampled) and stronger fidelity to the nursery site than do males. Indeed, few male sharks sired offspring from more than one litter during the course of the study. These findings were quite similar to previous results from another lemon shark nursery site (Bimini, Bahamas), suggesting conserved mating system parameters despite significant variation in early life-history traits (i.e. body size and growth) among sites. The finding of at least some site fidelity in females also supports the need for careful conservation of each nursery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".