Host Co‐Occurrence and Population Size Explain Genetic Differentiation and Diversity in Seal Lice
Bibliographic record
Abstract
We studied the drivers of population-genetic structuring and genetic diversity in specialist parasites based on whole-genome resequencing data from 82 Echinophthirius horridus seal louse individuals sampled from 12 ecologically and behaviourally different phocine seal species, subspecies and populations across the Holarctic. We found that the main genetic disjunctions in E. horridus lice occur across seal host species and subspecies, with a further level of population subdivision emerging among host individuals within some populations. Endemic and relict landlocked seal (sub)species host the genetically most distinct louse populations, while lice associated with sympatric marine seals show signatures of occasional gene flow across hosts. Within the latter, the most extreme case is seen in the near-panmictic lice associated with northern European grey and harbour seals, which aggregate in shared rookeries and colonies. Although the louse and seal phylogenies were overall statistically significantly congruent, evidence for similar host shifts in the past is reflected in several conflicts in the phylogenetic trees of the lice and their hosts. Population-level mean heterozygosity and theta in seal lice varied considerably, and both measures of genetic variation were statistically significantly related to host population size. Taken together, our results support a non-adaptive model of parasite diversification, in which geographic and behavioural isolation among hosts drives parasite genetic differentiation, and genetic erosion in bottlenecked hosts cascades up to their specialist parasites. Our results provide new insights into processes that generate parasite diversity and trigger parallel losses of genetic diversity in endangered host-parasite systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".