Fecal genotyping reveals demographic variation in river otters inhabiting a contaminated environment
Bibliographic record
Abstract
Abstract The deposition and accumulation of persistent contaminants into coastal systems can have lingering negative consequences for wildlife populations and their habitats. Using multi‐locus genotyping of non‐invasively collected feces, we assessed the effects of such pollution on reproduction, survival, genetic variability, and abundance of river otters ( Lontra canadensis ) along a gradient of urban–industrial development on southern Vancouver Island, British Columbia, Canada. Genetic analyses indicated a pattern consistent with small‐scale structuring, with individuals partitioned into 2 local subpopulations—those identified in the contaminated harbors of southern Vancouver Island and points west (Colwood/Harbors), and those inhabiting uncontaminated habitat east of the harbors (Oak Bay). Genetic and demographic analyses for the 2 clusters provide strong support for the conclusion that, despite contamination concerns, Colwood/Harbors river otters exhibited acceptable levels of survival and successfully reproduced (i.e., high levels of relatedness, high self‐recruitment, and high emigration). However, our data indicate that the Colwood/Harbors area constitutes lower quality habitat supporting lower densities of otters, especially during winter, and excess individuals produced in that region emigrate to other areas. Immigration into Colwood/Harbors, however, seems limited, possibly because of behavioral aversion of non‐habituated otters to anthropogenic disturbance associated with the harbors and limited optimal otter habitat. Our findings suggest that the effects of chronic contaminant exposure at the population level may be inadvertently mitigated through the behavioral decisions of individuals to avoid poor quality habitats. We conclude that populations of river otters can persist in and around locally contaminated sites if relatively less disturbed and contaminated habitats remain in the vicinity of the affected areas. © 2012 The Wildlife Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".