The genetic structure of raccoon introduced in Central Europe reflects multiple invasion pathways
Bibliographic record
Abstract
Invasions of non-native species are of great concern as they have a devastating impact on native biodiversity and can also affect the economy of a region. Multiple introductions in several locations of a new range greatly promote the success of non-native species. The raccoon ( Procyon lotor ) is an omnivore whose native distribution extends from southern Canada to Panama. It has been successfully introduced in many European countries. We examined the microsatellite and mitochondrial diversity of raccoon populations in Central Europe (Germany, Poland, and Czech Republic) in order to determine their introduction sources and pathways as well as the factors affecting genetic structure in this invasive species. We found low diversity of the mtDNA control region and moderate diversity of microsatellite markers. Raccoon showed three hierarchic levels of genetic structure which separate at different levels sampled from Czech Republic, Germany and raccoon inhabiting two different habitats in Poland. In Poland the raccoon population was established through migration from Germany to Czech Republic. Analysis of the intensity of migration between two different habitat types indicated source-sink dynamics in the Polish populations of raccoons. Our results confirm the high intensity of the raccoon invasion in Central Europe and point to specific measures needed as part of an effective management strategy.
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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 | 0.001 |
| 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".