Combining DNA barcoding and morphological analysis to identify specialist floral parasites (Lepidoptera: Coleophoridae: Momphinae:<i>Mompha</i>)
Bibliographic record
Abstract
Close interactions between insects and plants have played a major role in the evolution of both these diverse groups of organisms. Studying these interactions, however, can be difficult because many insects, especially parasites, impinge most strongly on plants during larval stages when they are morphologically difficult to identify, and many belong to diverse groups for which most species remain undescribed. We used DNA barcoding to identify nondescript lepidopteran larvae that regularly parasitize flower buds of the coastal dune endemic Camissoniopsis cheiranthifolia (Onagraceae). We obtained cytochrome oxidase 1 mitochondrial DNA sequences from 201 parasite specimens from across the host geographical range. The Barcode of Life Database Identification System combined with Bayesian analysis grouped all 15 parasite haplotypes in a distinct, monophyletic clade within the genus Mompha (Lepidoptera: Coleophoridae: Momphinae), a group known to be host specialists on plants of the Onagraceae. Species identity and phylogenetic affinities within Mompha could not be confirmed because few barcode sequences exist from this diverse and poorly known group of moths. However, morphological analysis, including detailed dissection of genitalia for a subsample of 23 reared adults and comparison with known species of Mompha, also indicated that the larvae parasitizing C. cheiranthifolia constitute a distinct and undescribed species within this genus. Knowing that floral parasitism of C. cheiranthifolia involves a single, putatively host-specific microlepidopteran greatly facilitates formulating and testing hypotheses concerning how floral parasitism has promoted the evolution of striking floral diversity within this species. More generally, DNA barcoding combined with morphological analysis can greatly hasten identification of problematic specimens and enhance our understanding of the diversity, ecology and evolution of plant-insect interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".