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Record W2051103695 · doi:10.1007/s10530-013-0595-8

The genetic structure of raccoon introduced in Central Europe reflects multiple invasion pathways

2013· article· en· W2051103695 on OpenAlexaboutno aff
Aleksandra Biedrzycka, Andrzej Zalewski, Magdalena Bartoszewicz, Henryk Okarma, Ewa Jędrzejewska

Bibliographic record

VenueBiological Invasions · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenetic diversityInvasive speciesRaccoon DogsEcologyIntroduced speciesCzechBiodiversityRange (aeronautics)HabitatPopulationPanamaZoologyDemography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.236
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2013
Admission routes1
Has abstractyes

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