Looking for a home in foreign waters: population genetic structure of the introduced Arapaima in Bolivia
Bibliographic record
Abstract
Establishment of invasive aquatic species is increasing globally due to factors related to globalization and accelerated trade between regions. Such invasions and subsequent establishment generally cause ecosystem disturbance with occasional local and/or regional socioeconomic impacts. The paiche (tentatively identified as Arapaima gigas), one of the largest fish in the Amazon, was introduced into Bolivia via Peru in the 1960s and has generated significant changes in Amazonian fisheries. In recent years, it has been proposed that the genus Arapaima is composed of different species distributed along the Amazon Basin. The present study evaluated the genetic variability of the paiche in the Bolivian Amazon Basin (sub-basins of the Orthon, Madre de Dios and Beni rivers) using nuclear (nDNA- microsatellites) and mitochondrial (mtDNA NADH and CO1) genetic markers to determine species identity and population structure. Microsatellite DNA analysis suggested that the three populations corresponding to geographic sub-basins are genetically distinct. The genetic distance between populations was not significantly related to the geographic distance between collection sites. We suggest that the founder population in Bolivia was composed of a limited number of individuals that subsequently dispersed in search of environmental conditions similar as those habitats from which they were extracted. Planning for the sustainable use of the species by fisheries should consider the existence of different populations in the Bolivian sub- basins. Recruitment seems to depend on exchanges between nearby surrounding aquatic habitats rather than between sub-basins.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".