Human disturbance affects latrine‐use patterns of raccoon dogs
Bibliographic record
Abstract
ABSTRACT Although urbanization is a leading threat to wildlife conservation, some species have adapted to a synanthropic lifestyle. We used a population of raccoon dogs (Nyctereutes procyonoides) in the Akasaka Imperial Grounds in central Tokyo, Japan to investigate how latrine‐using carnivores can maintain their socio‐spatial organization with human disturbance. Between 2012 and 2014, we selected 4–11 latrines per year (from a max. of 18 latrines recorded in the area) using 1 camera per latrine. We focused on latrines that included varying levels of human disturbance. We analyzed the temporal patterns of 3,257 latrine visits, of which 878 included defecation events. Overall, latrine use (i.e., visits with and without defecation events) increased as winter approached, coinciding with dispersal, and showed a seasonal shift from diurnal to nocturnal use patterns as days got shorter. Generalized linear mixed model results confirmed that temporal visiting and defecation patterns were affected by human disturbance and shifted from diurnal to nocturnal, although overall frequency of visits and defecation events did not decrease at disturbed latrines and raccoon dogs continued to use disturbed latrine sites. Raccoon dogs likely perceive human disturbance as predation risk and avoided this by shifting their temporal, but not spatial, activity pattern to minimize disturbance. Minimizing the amount of disturbance around raccoon‐dog latrines at sensitive sites and times of day would allow them to co‐exist with people with the minimal compromise to their latrine‐centered socio‐spatial organization. © 2018 The Wildlife Society.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".