When central populations exhibit more genetic diversity than peripheral populations: A simulation study
Bibliographic record
Abstract
The central-peripheral population hypothesis (CPH) predicts that peripheral populations have reduced genetic variability. Therefore, it is often assumed that they deserve higher conservation priority over central populations. We examined this hypothesis using computer simulations with the objective of determining the range of species properties (parameters) under which a species is likely to exhibit the CPH pattern. The interaction between migration, genetic drift, and time of population establishment was examined; in particular, various parameters of migration, such as mode of dispersal, migration rate, and maximum migration distance, were investigated. The CPH pattern was observed only within a narrow parameter window of various species properties. Active dispersers with low migration rate and moderate maximum migration distance were more likely to have higher genetic diversity in the central populations than in the peripheral populations. Newly established populations were also more likely to exhibit the CPH pattern. Although migration rate appeared to be the most important determining factor, sensitivity analysis suggested that the interaction between parameters is probably more important than any single parameter. Our findings have important implications for conservation programs.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".