DNA barcodes highlight genetic diversity patterns in rodents from lowland desert and Andean areas in Argentina
Bibliographic record
Abstract
Rodents are an important component of South America fauna. Their high diversity has motivated researchers to continually review their taxonomy, genetic diversity, species limits, and phylogenetic relationships. Here, we applied DNA-barcodes for assessing the taxonomic and genetic diversity in the two major lineages of South American rodents: caviomorphs and sigmodontines. We analysed 335 COI barcodes in 34 morphologically determined species from 39 localities along central Andes and arid lands of Argentina. Neighbour-joining and maximum likelihood reconstruction provided clear separation between species. The Barcode Index number and Bayesian Poisson tree processes were used to confirm concordance between sequence clusters and species designations by taxonomy. We found deep divergence within the Phyllotis xanthopygus species complex, with distances up to 13.0% between geographically separated lineages. Minor divergences (3.30% and 2.52%) were found within Abrothrix hirta, and Tympanoctomys barrerae, respectively, with differentiation in their genetic lineages. Also, we documented geographically separated clusters for Akodon spegazzinii and A. oenos with up to 2.3% divergence, but clustering methods failed to distinguish them as different species. Sequence results show a clear barcode gap with a mean intraspecific divergence (0.56%) versus a minimum nearest-neighbour distance averaging (10.1%). Distances between congeneric species varied from 4.1 to 14%, with the exception of two related forms within Euneomys and the sister species Akodon spegazzinii and A. oenos. This study constitutes a substantial contribution to the global barcode reference library. It provides insights into the complex phylogeographic patterns and speciation scenarios in rodents, while highlighting areas that require in-depth taxonomic and integrative research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".