Decoding Anotylus (Thomson 1859) Beetle Diversity: DNA and External Morphology Match in Área de Conservaciόn Guanacaste, Costa Rica
Bibliographic record
Abstract
Taxonomy underpins biological research because names are needed for comparative analysis, conservation status, and public communication. Despite this, many species remain undescribed and are therefore vulnerable and unprotected, particularly in the tropics. Neotropical Staphylinidae beetles (Coleoptera) are among the insect groups most likely to contain significant unknown and/or cryptic diversity. Here we used an integrative taxonomic framework to conduct a preliminary review of one particularly diverse genus of Staphylinidae (Anotylus) in Área de Conservaciόn Guanacaste, northwestern Costa Rica. We began by DNA barcoding novel collections and using Barcode Index Numbers (BINs) as an estimate of taxonomic diversity; we found 18 provisional new species. We augmented this genetic analysis with a morphometric analysis of adult morphological characters and found that we could differentiate most provisional species by external morphology as well as by elevation of collection. All the most abundant species could be differentiated from each other by differences in body size. One BIN included slight (~1%) genetic variation that corresponded with some morphological differentiation suggesting the existence of two species within a DNA BIN. Our results support the efficacy of DNA barcoding collections of tropical insects as an effective biodiversity estimator, one that can be used as a primer for integrative taxonomic studies using BINs as species hypotheses.
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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 | 0.002 | 0.002 |
| 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) | 0.000 | 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".