Morphological diversity of two phylogeographic lineages of Arctic grayling (<i>Thymallus arcticus</i>) in Alberta
Bibliographic record
Abstract
Biodiversity is declining globally, necessitating conservation strategies that protect genetic and phenotypic diversity within species. In North America, Arctic grayling ( Thymallus arcticus (Pallas, 1776)) exhibit substantial mitochondrial DNA divergence corresponding to two phylogeographic lineages termed Nahanni and Beringia. However, phenotypic variation has not been widely explored and there has been no direct comparison between the two lineages. This study examined morphological variation between these lineages in Alberta and whether observed variability was associated with sex. Morphology of T. arcticus was investigated using two approaches after assigning fish to a lineage based on their mitochondrial DNA haplotype. Geometric morphometric techniques were used to assess body shape differences between the two lineages and sex considering 16 two-dimensional landmarks. Twelve meristic characters were also enumerated and compared. Subtle yet significant differences in body shape and three meristic traits (lateral line scales, branched pelvic rays, and pyloric caeca) were identified, with body shape analysis resulting in 95% accuracy in lineage assignment. Body shape was also influenced by sex, corroborating evidence of sexual dimorphism in T. arcticus. These results support potential classification of the lineages as evolutionary significant units worthy of independent protection.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".