Integrating morphology and mitochondrial DNA for species delimitation within the spruce budworm ( <i>Choristoneura fumiferana</i> ) cryptic species complex (Lepidoptera: Tortricidae)
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Bibliographic record
Abstract
Species in cryptic complexes tend to be very difficult, if not impossible, to identify using morphological characters. One such complex is the spruce budworm ( Choristoneura fumiferana Clemens, 1865) species group, an economically important group of Nearctic forest pests. Morphological, ecological, behavioural and genetic characters have been studied to try to understand the taxonomy of this group better, but diagnostic character states differ in frequency rather than being complete replacements between each species. We used mitochondrial DNA (mtDNA), together with a new morphology‐based character system that focuses on forewing colour components, to determine if one or a combination of character sources can be used for species diagnoses within the spruce budworm complex. We characterized 47 forewing morphometric measurements and sequenced a 470 bp region of cytochrome c oxidase I mtDNA for 111 ingroup individuals comprising five taxa within the complex. Larval host association and coloration or adult pheromone attraction were used as the prior method for grouping individuals. Our results showed that linear discriminant analysis of morphometric wing characters gave unique clusters for all species on the first and second canonical axes, except for a partial overlap between C. fumiferana and C. biennis , which are not sympatric in nature. In contrast, mtDNA distinguished C. fumiferana , C. pinus pinus Freeman, 1953 and a group of western species, but the three western species ( C. occidentalis , C. biennis and C. lambertiana Busck, 1915) shared mtDNA haplotypes. On the basis of the linear discriminant analysis of the combined character set, this study supports the application of both morphology and mtDNA within a framework of integrative taxonomy as the most accurate method for species identification. Furthermore, it demonstrates the utility of quantitative colour analysis, which may be particularly helpful for groups in which colour characters are difficult to divide into discrete units due to intergrading hues.
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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 | 0.002 |
| 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 | 0.000 | 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 it