DNA Barcoding Distinguishes Pest Species of the Black Fly Genus <I>Cnephia</I> (Diptera: Simuliidae)
Bibliographic record
Abstract
Accurate species identification is essential for cost-effective pest control strategies. We tested the utility of COI barcodes for identifying members of the black fly genus Cnephia Enderlein (Diptera: Simuliidae). Our efforts focus on four Nearctic Cnephia species-Cnephia dacotensis (Dyar & Shannon), Cnephia eremities Shewell, Cnephia ornithophilia (Davies, Peterson & Wood), and Cnephia pecuarum (Riley)--the latter two being current or potential targets of biological control programs. We also analyzed one Palearctic species, Cnephia pallipes (Fries). Although Cnephia adults can be identified anatomically to species, control programs target the larval stage, which is difficult or impossible to distinguish morphologically. By using neighbor-joining, maximum parsimony, and Bayesian methods, we found that COI barcodes successfully identified three Nearctic Cnephia species, but not C. pecuarum. The Palearctic C. pallipes was also successfully identified. Despite nonmonophyly of C. pecuarum, we show that data from COI barcoding, in combination with geographical and ecological information, can be used to distinguish all four Nearctic species. Finally, we discussed 1) possible reasons for paraphyly in C. pecuarum, 2) topological concordance to previously reported chromosomal dendrograms, and 3) evolution of diverse feeding strategies within the genus Cnephia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".