Genetic and Ecological Approaches to Introduced Populations of Pumpkinseed Sunfish (Lepomis gibbosus) in Southwestern Europe
Bibliographic record
Abstract
Freshwater systems are among the most affected by the introduction of exotic species. The pumpkinseed sunfish Lepomis gibbosus, a centrarchid native to eastern North America, is listed among the top ten introduced freshwater fishes with the greatest ecological impact globally. Despite this, genetic and evolutionary studies of the species are still scarce. Here, we analyzed the genetic variability of introduced populations of L. gibbosus using three mitochondrial genes (COI, d-loop, and ND1). In addition, we used species distribution modeling to compare the niche of introduced versus native populations to assess the present and potential future distribution of the species under different climate change scenarios. Compared with the native populations, introduced ones present a lower level of genetic variability, indicating these populations originated from a small number of individuals from the native (Atlantic) population in the USA and Canada. The low variability was likely driven by a founder effect and subsequent bottleneck, as often occurs in invasive species. Our modeling results suggest not only that L. gibbosus modified its niche during the invasion process in Europe but also the possible global expansion of the species under future climatic conditions, which could facilitate its establishment in almost all continents.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".