The role of demographic and environmental variables on the presence of snow tracks by river otters <i>Lontra canadensis</i>
Bibliographic record
Abstract
Unknown causes of heterogeneity in the presence or detection of wildlife tracks and other signs could bias interpretations of population indices derived from surveys. These surveys can be the basis of management decisions for populations of wildlife. However, we know very little about potential biases affecting the presence of tracks in the landscape. We used an Information Theoretic Model Comparison approach to investigate the role of environmental, demographic and behavioural influences on the presence of river otter Lontra canadensis snow tracks in central British Columbia, Canada, from January to March 2008. We repeatedly located five radio‐collared otters and recorded the presence of tracks within an estimated 100‐m radius of the otter's location. We used combinations of five variables to develop logistic regression models that predicted the presence or absence of snow tracks when the location of otters was known. The presence of snow tracks was best described by a model containing covariates for gender and movement distance per day. The probability of detecting snow tracks was higher for male compared to female otters and was positively related to the daily movement distance of the individual animal. Track‐sign heterogeneity among individuals could bias surveys that assess and monitor river otter populations, and should be incorporated into the design and interpretation of track surveys.
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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 | 0.000 | 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 | 0.002 |
| 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 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".