Population structure and mating patterns of Killer Whales (Orcinus orca) as revealed by DNA analysis
Bibliographic record
Abstract
This thesis reports a genetic investigation of population segregation, social organization, and mating patterns in killer whales (Orcinus orca) of the northeastern Pacific Ocean. Previous studies identified two sympatric, non-associating populations, fish-eating residents and mammal-eating transients, and described many aspects of their demography, ecology, and social behaviour. Less is known about a third offshore population. Here, I focused on two aspects of killer whale social organization that are unusual among wellstudied mammals: maintenance of complete segregation between residents and transients in sympatry, and lack of dispersal in individual residents of either sex. I began by developing and testing lightweight pressure-propelled biopsy darts. They were an efficient way of acquiring skin samples from free-ranging whales and caused only minor behavioural responses in sampled animals. Using these darts and sampling stranded carcasses, colleagues and I collected biopsies from 269 individually-identified killer whales in British Columbia and Alaska. I used DNA from the biopsies to sequence the mitochondrial D-loop of 111 matrilines, and genotyped all individuals at 11 polymorphic microsatellite loci. I found that residents and transients are strongly differentiated genetically and that there is little or no gene flow between them. Both are divided into three genetically-differentiated regional subpopulations. Each resident subpopulation is more closely related to other resident subpopulations than to any transient subpopulation and vice versa, implying that the differences between residents and transients stem from a single divergence. The offshore population is not closely related to either of the other populations. The propensity of killer whales to live in fixed groups of a few hundred individuals apparently allows sympatric or parapatric populations to diverge genetically and could eventually result in speciation. I examined mating patterns in residents by conducting paternity tests and analysing fixation indices based on microsatellite genotypes. I found that residents rarely mate within their pods. Further, in the most thoroughly-sampled resident subpopulation, most matings were between rather than within acoustic clans (groups of pods with similar acoustic repertoires). Because pods within clans proved to be closely related, inter-clan mating appears to be an inbreeding avoidance mechanism. Most matings were between individuals from the same subpopulation. This pattern of population segregation coupled with inbreeding avoidance closely resembles marriage patterns in many human societies.
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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 | 0.000 |
| 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".