Sex‐biased dispersal in a salmonid fish: implications for growth rate and survival
Bibliographic record
Abstract
I tested the hypothesis that dispersal is sex‐biased in an unexploited population of brook trout (Salvelinus fontinalis Mitchill). Based on the assumptions that trout are promiscuous and that reproductive success is limited primarily by either number of mates (males) or fecundity (females), I predicted that males would disperse greater distances than females. I also tested the hypothesis that trout populations comprise stationary and mobile individuals, predicting that males have greater mobility than females. Based on a 5‐year, mark‐recapture study of almost 1000 fish, there was strong support for the hypothesis of male‐biased dispersal. On average, males dispersed 2·5 times as far as females; during the spawning period only, male dispersal exceeded that by females almost four‐fold. Both sexes were heterogeneous with respect to movement, with a lower incidence of mobility among females than males. Sex differences in dispersal may have been responsible for sex biases in seasonal growth. Importantly, growth rate was positively associated with survival, independent of the effects of body size. Sex‐biased dispersal may (1) reduce mate competition among male kin, (2) decrease the probability that males will reproduce with related females, and (3) have important implications for life history.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".