Assessing the effects of cattle on Andean bear habitat use in a protected area in northern Peru
Bibliographic record
Abstract
The Andean bear (Tremarctos ornatus) is the largest carnivore in the tropical Andes and is an essential apex predator. Andean bears are vulnerable to extinction, and human-caused disturbances are driving population declines. Although the presence of free-ranging cattle is a major disturbance within protected areas, the effect of cattle on Andean bears is poorly understood. We used camera traps and remotely sensed data to assess the spatial and temporal relationships between cattle and bears in a protected area in northern Peru from 2015 to 2016. We hypothesized that cattle grazing represented a disturbance for Andean bears and predicted that bears would avoid cattle in space and/or time. We further predicted that the effects of cattle would be stronger during the wet season when their abundance and activity was higher. We tested the spatial prediction using generalized linear models, where we expected a negative relationship between the occurrence of cattle and bears. We included other factors potentially influencing bear occurrence in our models, including other measures of anthropogenic disturbance (occurrence of humans and dogs, and proximity to towns and farms) and of natural habitat variation in the refuge (elevation, slope, and forest cover). To test for temporal avoidance, we estimated the degree of overlap between daily activity patterns of bears and cattle. As predicted, we found a negative spatial association between bears and cattle and bears and humans and dogs. Bears were also less likely to occur closer to towns and farms adjacent to the refuge. Overall, bear responses to anthropogenic disturbance were stronger than to natural habitat variation. Surprisingly, the spatial avoidance of cattle by bears was stronger during the dry season. We did not find evidence of temporal avoidance, as there was high overlap between the daily activity patterns of bears and cattle, and between bears and humans and dogs, suggesting the potential for interaction where they do spatially co-occur. Given the threatened status of Andean bears, and the critical role of protected areas in their conservation, we recommend effective management of cattle and associated disturbances to protect and recover populations of this ecologically and culturally important carnivore.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".