Non-linear genetic isolation by distance: implications for dispersal estimation in anadromous and marine fish populations
Bibliographic record
Abstract
Indirect genetic approaches such as those based on the association between genetic and geographic distance (isolation by distance, IBD) may provide one of the best means of estimating dispersal in marine systems. We evaluated the scale-dependency and the ecological covariates of the IBD relationship through a combined modeling and meta-analytical approach. Using Wright's fixation index F ST , simulations were used to generate IBD relationships, F ST /(1-F ST ) and geographic distance, for various combinations of average dispersal distance and number of generations. IBD linearity increased with time since colonization and dispersal distance, although the effect of dispersal distance predominated after initial colonization. Simulations suggest that declines in the IBD slope were associated with increases in the spatial scale of observation, suggesting that the IBD pattern is non-linear at very short and long average dispersal distances. We hypothesized that non-linear IBD would be common in marine populations, and apparent through a biologically significant non-zero intercept and decreasing slope with increasing geographic scale. Predictions of common non-linearity were examined through IBD relationships (i.e. slope, intercept, R 2 of the regression) and life history parameters from the published literature for 18 species of anadromous/philopatric fishes. As predicted, IBD parameters (intercept and slope) were consistently correlated with many life history traits (e.g. fecundity, egg size). However, the statistical removal of adult size eliminated most significant life history-IBD correlations. Increases in IBD slope were associated with decreasing gene flow (p = 0.014, R 2 = 0.33), and decreasing migration distance (p = 0.039, R 2 = 0.23). Non-linearity was further supported by consistent declines in the IBD slope with increased geographic scale in anadromous fish as well as several marine species, suggesting the ubiquity of this phenomenon. We conclude that isolation by distance patterns may reflect dispersal phenotype and are biologically significant. Nonetheless, non-linearity in IBD pattern is probably the norm in aquatic organisms, resulting from large ranges and limited dispersal. Accordingly, approximations of demographic parameters based on the IBD must be made cautiously, taking into account possible non-linearity, scale dependencies, and assumptions of genetic drift -dispersal equilibrium.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".