Contemporary gene flow and the spatio‐temporal genetic structure of subdivided newt populations (<i>Triturus cristatus</i>,<i>T. marmoratus</i>)
Bibliographic record
Abstract
Gene flow and drift shape the distribution of neutral genetic diversity in metapopulations, but their local rates are difficult to quantify. To identify gene flow between demes as distinct from individual migration, we present a modified Bayesian method to genetically test for descendants between an immigrant and a resident in a nonmigratory life stage. Applied to a metapopulation of pond-breeding European newts (Triturus cristatus, T. marmoratus) in western France, the evidence for gene flow was usually asymmetric and, for demes of known census size (N), translated into maximally seven reproducing immigrants. Temporal sampling also enabled the joint estimation of the effective demic population size (Ne) and the immigration rate m (including nonreproductive individuals). Ne ranged between 4.1 and 19.3 individuals, Ne/N ranged between 0.05 and 0.65 and always decreased with N; m was estimated as 0.19-0.63, and was possibly biased upwards. We discuss how genotypic data can reveal fine-scale demographic processes with important microevolutionary implications.
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".