Dynamic riskscapes for prey: Disentangling the impact of human and cougar presence on deer behavior using GPS smartphone locations

Dataset Summary
This dataset includes high-resolution animal movement and environmental data used to evaluate prey behavioral responses to spatial and temporal risk from predators and humans. Data were collected between 2015 and 2022 across two ecologically distinct study areas in the American Southwest (Book Cliffs, Colorado/Utah and Pine Valley, Utah). The dataset supports risk-sensitive habitat selection and movement analyses by integrating information on animal space use, human activity, and landscape features.
Structure and Contents
Wildlife GPS Data: Location data were collected from GPS-collared female mule deer (Odocoileus hemionus). Deer GPS fixes were recorded at 2-hour intervals. Each GPS location is associated with a phenological season (e.g., late gestation, rearing, hunting) and a diel period (day, night, crepuscular). To protect sensitive wildlife location information, all raw spatial coordinates have been removed or generalized. Derived environmental and behavioral metri..., , # Dynamic riskscapes for prey: Disentangling the impact of human and cougar presence on deer behavior using GPS smartphone locations

Dataset DOI: [10.5061/dryad.51c59zwkg](10.5061/dryad.51c59zwkg)

## Description of the data and file structure

This dataset includes high-resolution animal movement and environmental data used to evaluate prey behavioral responses to spatial and temporal risk from predators and humans. Data were collected between 2015 and 2022 across two ecologically distinct study areas in the American Southwest (Book Cliffs, Colorado/Utah and Pine Valley, Utah). The dataset supports risk-sensitive habitat selection and movement analyses by integrating information on animal space use, landscape features, and modeled risk surfaces.

**Important note:** Only the wildlife GPS data and associated environmental covariates are included in this Dryad data package. The raw human mobility data (e.g., smartphone detections) and aggregated products used in the original study are n..., The data provider has anonymized the data. Human data has been scaled such that personal information is no longer identifiable.