Shared genetic diversity across the global invasive range of the monk parakeet suggests a common restricted geographic origin and the possibility of convergent selection
Bibliographic record
Abstract
While genetic diversity is hypothesized to be an important factor explaining invasion success, there is no consensus yet on how variation in source populations or demographic processes affects invasiveness. We used mitochondrial DNA haplotypic and microsatellite genotypic data to investigate levels of genetic variation and reconstruct the history of replicate invasions on three continents in a globally invasive bird, the monk parakeet (Myiopsitta monachus). We evaluated whether genetic diversity at invasive sites could be explained by (i) the native source populations from which they were derived and (ii) demographic bottlenecks during introduction. Genetic data indicated a localized source area for most sampled invasive populations, with limited evidence for admixing of native source populations. This pattern largely coincides with historical data on pet trade exports. However, the invasive populations are genetically more similar than predicted from the export data alone. The extent of bottleneck effects varied among invasive populations. The observed low genetic diversity, evidence of demographic contraction and restricted source area do not support the hypothesis that invasion is favoured by the mixing and recombining of genetic variation from multiple source populations. Instead, they suggest that reduced genetic variation through random processes may not inhibit successful establishment and invasion in this species. However, convergent selection across invasive sites could also explain the observed patterns of reduction and similarity in genetic variation and/or the restricted source area. In general, the alternative explanation of intraspecific variation in invasive potential among genotypes or geographic areas is neglected, but warrants more attention as it could inform comparative studies and management of biological invaders.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".