Invasion success and genetic diversity of introduced populations of guppies<i>Poecilia reticulata</i>in Australia
Bibliographic record
Abstract
High genetic diversity is thought to characterize successful invasive species, as the potential to adapt to new environments is enhanced and inbreeding is reduced. In the last century, guppies, Poecilia reticulata, repeatedly invaded streams in Australia and elsewhere. Quantitative genetic studies of one Australian guppy population have demonstrated high additive genetic variation for autosomal and Y-linked morphological traits. The combination of colonization success, high heritability of morphological traits, and the possibility of multiple introductions to Australia raised the prediction that neutral genetic diversity is high in introduced populations of guppies. In this study we examine genetic diversity at nine microsatellite and one mitochondrial locus for seven Australian populations. We used mtDNA haplotypes from the natural range of guppies and from domesticated varieties to identify source populations. There were a minimum of two introductions, but there was no haplotype diversity within Australian populations, suggesting a founder effect. This was supported by microsatellite markers, as allelic diversity and heterozygosity were severely reduced compared to one wild source population, and evidence of recent bottlenecks was found. Between Australian populations little differentiation of microsatellite allele frequencies was detected, suggesting that population admixture has occurred historically, perhaps due to male-biased gene flow followed by bottlenecks. Thus success of invasion of Australia and high additive genetic variance in Australian guppies are not associated with high levels of diversity at molecular loci. This finding is consistent with the release of additive genetic variation by dominance and epistasis following inbreeding, and with disruptive and negative frequency-dependent selection on fitness traits.
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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".