MICROSATELLITE DNA AND MITOCHONDRIAL DNA VARIATION IN REMNANT AND TRANSLOCATED SEA OTTER (ENHYDRA LUTRIS) POPULATIONS
Bibliographic record
Abstract
All existing sea otter (Enhydra lutris) populations have suffered at least 1, and in some cases 2, population bottlenecks. The 1st occurred during the 18th and 19th centuries as a result of commercial hunting that eliminated sea otters from much their native range and reduced surviving populations to small remnants. The 2nd bottleneck occurred when small numbers of otters were reintroduced, via translocation, to areas where the species had been eliminated. We examined genetic variation at 7 microsatellite loci and the mitochondrial DNA (mtDNA) control region in 3 remnant populations, Amchitka Island (Aleutian Islands, Alaska), central coastal California, and Prince William Sound (Alaska), and in 2 reintroduced populations, southeast Alaska and Washington, that were founded with transplants from Amchitka, and in the case of southeast Alaska, individuals from Prince William Sound as well. We found no evidence of reduced genetic diversity in translocated populations. Average expected microsatellite heterozygosities (HE) were similar in all populations (range, 0.40–0.47), and mtDNA haplotype diversities were higher in reintroduced populations (0.51 for both Washington and southeast Alaska) than in remnant populations (X̄ = 0.35; range, 0.18–0.45). The levels of genetic diversity we observed within sea otter populations were relatively low when compared with other mammals and are thought to be the result of fur trade exploitation.
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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 | 0.001 | 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) | 0.000 | 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".