Analysis and Evaluation of Coyote (Canis Latrans) Activity on University of British Columbia Campus
Bibliographic record
Abstract
The campus of the University of British Columbia is topographically situated in an area which may increase the risk for human-coyote conflict (Lukasik & Alexander, 2011; Poessel et al., 2013), and coyotes have been known to be increasingly active on campus, especially in recent years (Sangar, 2020). While human-coyote conflict is generally quite rare (Lukasik & Alexander, 2011; Poessel et al., 2013; Poessel et al., 2017), risk perception is greatly affected by media-reported incidents of conflict (Nardi et al., 2020) which has been occuring nearby in areas such as Vancouver’s Stanley Park (Brend, 2021). This study observed the activity of coyotes on UBC campus and compared this to patterns of human activity to investigate human-coyote conflict risk in the area and evaluate management strategies that could be effective in managing conflict potential in the area. Motion activated camera traps were placed around campus and used to record activity of coyotes and humans over an 8 week period. Coyote activity was found to be inversely related to human activity, both temporally and spatially. Coyote activity was most prevalent in nighttime hours and in locations that were closer to the border of campus and the surrounding forest, compared to more central locations on campus. Evidence was also observed that coyotes at UBC may be using one of the roads in the area as a travel corridor along the border of campus. This study discusses how the coyote behavior observed illustrates a tendency to human avoidance, rather than bold, human-seeking behavior that is a strong precursor of human-coyote conflict (Gehrt et al., 2009; Timm et al., 2004). Conclusions are then drawn regarding implications this carries for current and future human-coyote conflict management in the area. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".