Causes of Mortality in a Harbor Seal (Phoca vitulina) Population at Equilibrium
Bibliographic record
Abstract
The harbor seal (Phoca vitulina richardii) population in the Salish Sea has been at equilibrium since the mid-1990s. This stable population of marine mammals resides relatively close to shore near a large human population and offers a novel opportunity to evaluate whether disease acts in a density-dependent manner to limit population growth. We conducted a retrospective analysis of harbor seal stranding and necropsy findings in the San Juan Islands sub-population to assess age-related stranding trends and causes of mortality. Between January 1, 2002 and December 31, 2018, we detected 882 harbor seals that stranded and died in San Juan County and conducted necropsies on 244 of these animals to determine primary and contributing causes of death. Age-related seasonal patterns of stranded animals were evident, with pups found in the summer, weaned pups primarily recovered during fall, and adults and sub-adults recovered in summer and fall. Pups were the most vulnerable to mortality (64% of strandings). Pups predominantly died of nutritional causes (emaciation) (70%), whereas sub-adults and adults presented primarily with clinical signs and gross lesions of infectious disease (42%) and with non-anthropogenic trauma (27%). Primary causes of weaned pup mortality were distributed equally among nutritional, infectious, non-anthropogenic trauma, and anthropogenic trauma categories. Nutritional causes of mortality in pups were likely related to limitations in mid- and late-gestational maternal nutrition, post-partum mismothering, or maternal separation possibly related to human disturbance. Infectious causes were contributing factors in 33% of pups dying of nutritional causes (primarily emaciation–malnutrition syndrome), suggesting an interaction between poor nutritional condition and enhanced susceptibility to infectious diseases. Additional primary causes of harbor seal mortality were related to congenital disorders, predation, human interaction, and infections, including zoonotic and multidrug-resistant pathogens. Bottom-up nutritional limitations for pups, in part possibly related to human disturbance, as well as top-down predatory influences (likely under-represented through strandings) and infectious disease, are important regulators of population growth in this stable, recovered marine mammal population.
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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 | 0.001 |
| 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".