Effects of oiling on exercise physiology and diving behavior of river otters: a captive study
Bibliographic record
Abstract
Following the Exxon Valdez oil spill (EVOS), river otters (Lontra canadensis) on oiled shores had lower body mass, selected different habitat characters, and had larger home ranges and less diverse diets than did otters living in non-oiled areas. We explored the possibility that these changes were due to the effect of crude oil contamination on physiological and behavioral processes in otters. Fifteen otters were exposed to two levels of oil contamination under captive controlled conditions at the Alaska Sealife Center in Seward, Alaska, U.S.A. We collected blood samples for hematological examinations and measured oxygen consumption in otters exercising on a motorized treadmill. We also observed diving and foraging behavior of otters offered live fish. Otters exposed to oil became anemic relative to controls. While oxygen consumption of resting river otters was not related to changes in hemoglobin concentration, exercising river otters with decreased hemoglobin levels displayed significantly increased oxygen consumption (P = 0.042). Oiled otters also performed fewer dives when chasing fish (P = 0.04), representing a potential decrease of 64% in the capture rate of prey. Our data strongly support the hypothesis that changes in prey types and home-range utilization by oiled river otters following EVOS were influenced by hematological changes, associated increases in energetic costs, and reduced diving ability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".