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Record W6977826527 · doi:10.7939/r3-21n7-rs41

Delimitation and identification of crescent butterflies (Nymphalidae: Phyciodes) in Alberta using molecular and morphological techniques

2022· dissertation· en· W6977826527 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxonomic rankDNA barcodingIntraspecific competitionTaxonTaxonomy (biology)Identification (biology)Coalescent theorySpecies complex

Abstract

fetched live from OpenAlex

Species delimitation can be challenging, especially in taxonomic groups that exhibit little morphological divergence. Many techniques and concepts have been developed for detecting species boundaries, and molecular methods are becoming increasingly common. Next generation sequencing techniques make it feasible to obtain hundreds to thousands of genome-wide markers, even for non-model organisms. This can provide powerful insights into species boundaries and the integrity of those boundaries in the presence of gene flow. However, classical taxonomic information, such as morphology, is often excluded from molecular studies, creating a disconnect between delimitation and identification. Integrative and iterative approaches to taxonomy that include morphological data maintain a link between delimitation and identification while providing a more complete understanding of the organisms being studied. The Phyciodes tharos species group of nymphalid butterflies is currently thought to comprise four species. However, interspecific overlap and intraspecific variability of the wing patterns have resulted in a complicated taxonomic history with uncertainty regarding the level of divergence between species. Discordance of mitochondrial COI with traditional taxonomic identifications has added to this uncertainty but has been attributed to incomplete lineage sorting and contemporary introgression. In this thesis, I used an iterative approach to examine the species limits of this group using genome-wide single nucleotide polymorphisms (SNPs) and the barcoding region of the mitochondrial COI gene. I then quantitatively examined the utility of eighteen morphological characters for identification based on the genomic species lineages. I focused on Alberta, the only region where all four species occur, and no other species of the genus are present. Genomic SNPs resolved all four species boundaries with strong support for P. tharos (Drury, 1773), P. cocyta (Cramer, 1777), and P. pulchella (Boisduval, 1852). Phyciodes batesii (Reakirt, 1865) did not form a monophyletic clade but did form a distinct cluster in all genomic analyses. Evidence of occasional hybridization and low levels of introgression indicate that these lineages maintain their genomic integrity when in contact. The COI haplotypes were discordant with genomic SNPs but provided evidence of unidirectional mitochondrial gene flow likely due to brood timing and opportunistic mating between species. Morphological characters exhibited extensive intraspecific variation and broad interspecific overlap. None of the character states were strictly diagnostic, but the proportions of character states exhibited for each species are provided as an identification resource.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.467

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.192
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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