The Casiquiare river acts as a corridor between the Amazonas and Orinoco river basins: biogeographic analysis of the genus <i>Cichla</i>
Bibliographic record
Abstract
The Casiquiare River is a unique biogeographic corridor between the Orinoco and Amazonas basins. We investigated the importance of this connection for Neotropical fishes using peacock cichlids (Cichla spp.) as a model system. We tested whether the Casiquiare provides a conduit for gene flow between contemporary populations, and investigated the origin of biogeographic distributions that span the Casiquiare. Using sequences from the mitochondrial control region of three focal species (C. temensis, C. monoculus, and C. orinocensis) whose distributions include the Amazonas, Orinoco, and Casiquiare, we constructed maximum likelihood phylograms of haplotypes and analyzed the populations under an isolation-with-migration coalescent model. Our analyses suggest that populations of all three species have experienced some degree of gene flow via the Casiquiare. We also generated a mitochondrial genealogy of all Cichla species using >2000 bp and performed a dispersal-vicariance analysis (DIVA) to reconstruct the historical biogeography of the genus. This analysis, when combined with the intraspecific results, supports two instances of dispersal from the Amazonas to the Orinoco. Thus, our results support the idea that the Casiquiare connection is important across temporal scales, facilitating both gene flow and the dispersal and range expansion of species.
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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 | 0.000 | 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".