Systematics and diversity of Ichneumonidae, with an emphasis on the taxonomically neglected genus Ophion Fabricius
Bibliographic record
Abstract
Ichneumonidae are the most species-rich family of parasitic Hymenoptera and are important for regulating populations of other arthropods. However, with an estimated 75% of species undescribed, we lack fundamental information about their taxonomy, ecology, and distributions. Using two different groups of Ichneumonidae, I address each of these issues in this thesis. In Chapters 2 – 4, I focus on the taxonomically-neglected genus Ophion. I provide the first phylogenetic hypothesis of Ophion based on molecular data (COI, ITS2 and 28S) and divide the genus into ten provisional species-groups (Chapter 2). I also describe the secondary structure of ITS2 for the first time in Ichneumonidae, and discuss its potential to inform phylogenetic inference in Ophion (Chapters 2, 3). I investigate the diversity of Ophion at the species level by comparing quantitative species delimitation methods with each other and with morphologically-defined species (Chapter 3). The total number of delimited species is dependent on the method and parameters used; however all methods agree that there is a wealth of undescribed diversity in Nearctic Ophion. Finally, I revise the Nearctic species within the newly defined Ophion scutellaris species-group (Chapter 4). An integrative analysis of DNA, geometric wing morphometrics, classical morphometrics and morphology indicates that this species-group contains a minimum of seven species in Canada, although the full diversity of the group has likely not been sampled. Ophion clave sp. n., O. aureus sp. n., O. brevipunctatus sp. n., O. dombroskii sp. n., O. keala sp. n., and O. importunus sp. n. are described. Once species have names, it is possible to address other fundamental questions about their distribution and ecology. I conducted a survey of Ichneumonidae in a boreal deciduous forest, with an emphasis on Pimplinae, Poemeniinae, and Rhyssinae. Responses to forest harvesting were weak, but there is evidence that the community composition at the species level is correlated with shrub composition. Even within this relatively well-known group, there is much unexplored diversity. Any nomenclatural changes or new taxa proposed in this thesis should not be considered valid until published in primary journals as defined by the ICZN (International Commission on Zoological Nomenclature 1999).
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".