DNA barcoding uncovers cryptic diversity in minute herbivorous mites (Acari, Eriophyoidea)
Bibliographic record
Abstract
Eriophyoid mites (Acari: Eriophyoidea) are among the smallest of terrestrial arthropods and the most species-rich group of herbivorous mites with a high host specificity. However, knowledge of their species diversity has been impeded by the difficulty of their morphological differentiation. This study assembles a DNA barcode reference library that includes 1850 mitochondrial COI sequences which provides coverage for 45% of the 930 species of eriophyoid mites known from China, and for 37 North American species. Sequence analysis showed a clear barcode gap in nearly all species, reflecting the fact that intraspecific divergences averaged 0.97% versus a mean of 18.51% for interspecific divergences (minimum nearest-neighbour distances) in taxa belonging to three families. Based on these results, we used DNA barcoding to explore the species diversity of eriophyoid mites as well as their host interactions. The 1850 sequences were assigned to 531 barcode index numbers (BINs). Analyses examining the correspondence between these BINs and species identifications based on morphology revealed that members of 45 species were assigned to two or more BINs, resulting in 1.16 times more BINs than morphospecies. Richness projections suggest that over 2345 BINs occurred at the sampled locations. Host plant analysis showed that 89% of these mites (BINs) attack only one or two congeneric host species, but the others have several hosts. Furthermore, host-mite network analyses demonstrate that eriophyoid mites are high host-specific, and modularity is high in plant-mite networks. By creating a highly effective identification system for eriophyoid mites in the Barcode of Life Data Systems database (BOLD), DNA barcoding will advance our understanding of the diversity of eriophyoid mites and their host interactions.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".