Invasive species and postglacial colonization: their effects on the genetic diversity of a Patagonian fish
Bibliographic record
Abstract
The present distribution of Patagonian species is the result of a complex history involving Quaternary refugial populations, Holocene range expansions and demographic changes occurring during the Anthropocene. Invasive salmonids were introduced in Patagonia during the last century, occupying most rivers and lakes, preying on and competing with native species, including the fish Galaxias platei. Here, we used G. platei as a case study to understand how long-term (i.e. population differentiation during the Holocene) and short-term historical processes (salmonid introductions) affect genetic diversity. Using a suite of microsatellite markers, we found that the number of alleles is negatively correlated with the presence of salmonids (short-term processes), with G. platei populations from lakes with salmonids exhibiting significantly lower genetic diversity than populations from lakes without salmonids. Simulations (100 years backwards) showed that this difference in genetic diversity can be explained by a 99% reduction in population size. Allelic richness and observed heterozygosities were also negatively correlated with the presence of salmonids, but also positively correlated with long-term processes linked to Quaternary glaciations. Our results show how different genetic parameters can help identify processes taking place at different scales and their importance in terms of conservation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".