DOI: 10.5061/dryad.qv9s4mwt0
title: Data from: Predator activity and scent cues influence white-tailed deer behavior in a multi-predator landscape

description: When navigating landscapes, prey make decisions that balance their need to
 acquire high-quality resources with the risk of predation. When risk is
 heterogenous across the landscape, prey can alter their habitat use to
 avoid high-risk patches, or they can employ behavioral modifications, such
 as shifting their temporal activity, that allow them to continue to use
 high-risk patches while offsetting risk. Our objective was to discern how
 white-tailed deer in a predator-rich environment (the Greater Yellowstone
 Ecosystem [GYE]) and an environment containing only mesopredators (Ohio,
 USA) respond to predator urine cues and predator activity. We used camera
 traps to quantify the spatiotemporal activity of deer before, during, and
 after applying predator-scent cues (control/water, wolf urine, mountain
 lion urine, and coyote urine). In the GYE, deer decreased diurnal activity
 in response to all predator-scent cues, and increased nocturnal activity
 in response to wolf, mountain lion, and control scents. Deer also
 spatially avoided the physical presence of grizzly bears and temporally
 aligned their activity patterns with bears as bear detections increased
 over time. In Ohio, deer did not alter their spatial or temporal activity
 in response to predator-scent cues, and we found that deer activity was
 positively associated with coyote activity, thereby suggesting that deer
 may be naïve to the predator-scent cues in this region. Our study shows
 that scent cues alone do not alter the spatial activity of deer, but in
 regions where deer are not naïve to the risk of predation, they may
 exhibit changes in their temporal activity.
description: # Predator activity and scent cues influence white-tailed deer behavior in
 a multi-predator landscape ## Description of the data and file structure
 We used camera traps to measure how white-tailed deer (*Odocoileus
 virginianus*) in Wyoming, USA, and Ohio, USA, altered their spatial and
 temporal activity in response to predator-scent cues (urine) and predator
 activity on the landscape. Camera traps enabled us to quantify deer
 spatial activity as detection rates at a given location, and time strips
 associated with each detection allowed us to quantify deer temporal
 activity. In both Wyoming and Ohio, we deployed 20 camera traps during 3
 phases that lasted approximately 30 days each: pre-urine phase, urine
 phase, and post-urine phase. During the urine phase, cameras were treated
 with either water (a control), coyote (*Canis latrans*) urine, wolf
 (*Canis lupus*) urine, or mountain lion (*Puma concolor*) urine. We used
 negative binomial regressions to determine how deer detection rates varied
 in response to scent treatment types and predator detection rates, and we
 used kernel density estimation to compare temporal activity curves of deer
 between urine treatment types and phases. ### Files and variables **File:
 Cody.data.images.csv** **Description:** Camera data from Wyoming during
 the pre-treatment and treatment phases of data collection, identified by
 each individual image. ##### Variables * project_id: Unique identifier
 assigned to the project by Wildlife Insights software used to tag all
 images. * deploment_id: Unique identifier containing the sampling period
 (Pre-treatment or treatment) an image is from, and the identity of the
 camera trap that captured the image. * image_id: Unique identifier
 assigned to each image by Wildlife Insights software. * filename: Name of
 original image file captured by each camera trap. * location: Location of
 file uploaded to wildlife insights. Because this information is tied to a
 specific user account, it is not applicable to for use beyond that
 specified account. All values are therefore "NA". * is_blank:
 Binary statement of whether an image is blank (1) or not blank (0). *
 identified_by: Information on the individual who entered data from each
 image. * wi_taxon_id: Unique identifier assigned to a species by Wildlife
 Insights. * class: The taxonomic class classification of the animal in the
 specified image. * order: The taxonomic order classification of the animal
 in the specified image. * family: The taxonomic family classification of
 the animal in the specified image. * genus: The taxonomic genus
 classification of the animal in the specified image. * species: The
 taxonomic species classification of the animal in the specified image. *
 common_name: The common name in English of the animal in the specified
 image. * uncertainty: Definition on whether or not there is uncertainty
 regarding the identity of the animal in the specified image. * timestamp:
 Date and time which the specified image was captured (mm/dd/yyyy
 hh:mm:ss). * number_of_objects: Number of animals that are of the
 specified species, age, and sex within an image. * age: Age (adult,
 juvenile, unknown) of specified animal(s) within specified image. * sex:
 Sex (male, female, unknown) of specified animal(s) within specified image.
 * individual_id: Identification of whether or not images are part of the
 same sequence. Sequences consisted of all images that were captured within
 60 s of the most recent image and were filtered for using Wildlife
 Insights. Sequences were separated by deployment_id. * behavior: Column
 generated by Wildlife Insights that could be used to identify specific
 animal behaviors. Left blank for our study. * highlighted: Column
 generated by Wildlife Insights that could be used to identify if an image
 is highlighted for further review. All levels are false. * markings:
 Column generated by Wildlife Insights that could be used to identify
 specific animal markings. Left blank for our study. * cv_confidence:
 Column generated by Wildlife Insights that could be used to label
 confidence in species identification. Left blank for our study. * license:
 Licensing type for the data stored by Wildlife Insights. **File:
 Cody.data.sequences.post.csv** **Description:** Camera data from Wyoming
 during the post-treatment phase of data collection, identified as
 sequences in which all images were captured within 60 s of the most recent
 image. ##### Variables * project_id: Unique identifier assigned to the
 project by Wildlife Insights software used to tag all images. *
 deploment_id: Unique identifier containing the project names and the
 identity of the camera trap that captured the image. * sequence_id: Unique
 identifier assigned to each sequence of images by Wildlife Insights
 software. * is_blank: Binary statement of whether an image is blank (1) or
 not blank (0) * identified_by: Information on the individual who entered
 data from each image. * wi_taxon_id: Unique identifier assigned to a
 species by Wildlife Insights. * class: The taxonomic class classification
 of the animal in the specified image. * order: The taxonomic order
 classification of the animal in the specified image. * family: The
 taxonomic family classification of the animal in the specified image. *
 genus: The taxonomic genus classification of the animal in the specified
 image. * species: The taxonomic species classification of the animal in
 the specified image. * common_name: The common name in English of the
 animal in the specified image. * uncertainty: Definition on whether or not
 there is uncertainty regarding the identity of the animal in the specified
 image. * start_time: Time and date at which image sequence starts
 (mm/dd/yyyy hh:mm:ss). * end_time: Time and date at which image sequence
 ends (mm/dd/yyyy hh:mm:ss). * group_size: Number of animals that are of
 the specified species, age, and sex within a sequence. * age: Age (adult,
 juvenile, unknown) of specified animal(s) within specified image. * sex:
 Sex (male, female, unknown) of specified animal(s) within specified image.
 * animal_recognizable: Column generated by Wildlife Insights that could be
 used to identify if specific animals were recognized. Left blank for our
 study. * individual_id: Column generated by Wildlife Insights that could
 be used to identify specific animals by ID number. Left blank for our
 study. * individual_animal_notes: Column generated by Wildlife Insights
 that could be used to record notes for specific animals. Left blank for
 our study. * behavior: Column generated by Wildlife Insights that could be
 used to identify specific animal behaviors. Left blank for our study. *
 highlighted: Column generated by Wildlife Insights that could be used to
 identify if an image is highlighted for further review. All levels are
 false. * markings: Column generated by Wildlife Insights that could be
 used to identify specific animal markings. Left blank for our study. *
 cv_confidence: Column generated by Wildlife Insights that could be used to
 label confidence in species identification. Left blank for our study. *
 license: Licensing type for the data stored by Wildlife Insights. **File:
 CMP.data.sequences.csv** **Description:** Camera data from Ohio during all
 phases of data collection, identified as sequences in which all images
 were captured within 60 s of the most recent image. ##### Variables *
 project_id: Unique identifier assigned to the project by Wildlife Insights
 software used to tag all images. * deploment_id: Unique identifier
 containing the sampling period (pre-treatment, treatment, post-treatment)
 and the identity of the camera trap that captured the image. *
 sequence_id: Unique identifier assigned to each sequence of images by
 Wildlife Insights software. * is_blank: Binary statement of whether an
 image is blank (1) or not blank (0) * identified_by: Information on the
 individual who entered data from each image. * wi_taxon_id: Unique
 identifier assigned to a species by Wildlife Insights. * class: The
 taxonomic class classification of the animal in the specified image. *
 order: The taxonomic order classification of the animal in the specified
 image. * family: The taxonomic family classification of the animal in the
 specified image. * genus: The taxonomic genus classification of the animal
 in the specified image. * species: The taxonomic species classification of
 the animal in the specified image. * common_name: The common name in
 English of the animal in the specified image. * uncertainty: Definition on
 whether or not there is uncertainty regarding the identity of the animal
 in the specified image. * start_time: Time and date at which image
 sequence starts (mm/dd/yyyy hh:mm:ss). * end_time: Time and date at which
 image sequence ends (mm/dd/yyyy hh:mm:ss). * group_size: Number of animals
 that are of the specified species, age, and sex within a sequence. * age:
 Age (adult, juvenile, unknown) of specified animal(s) within specified
 image. * sex: Sex (male, female, unknown) of specified animal(s) within
 specified image. * animal_recognizable: Column generated by Wildlife
 Insights that could be used to identify if specific animals were
 recognized. Left blank for our study. * individual_id: Column generated by
 Wildlife Insights that could be used to identify specific animals by ID
 number. Left blank for our study. * individual_animal_notes: Column
 generated by Wildlife Insights that could be used to record notes for
 specific animals. Left blank for our study. * behavior: Column generated
 by Wildlife Insights that could be used to identify specific animal
 behaviors. Left blank for our study. * highlighted: Column generated by
 Wildlife Insights that could be used to identify if an image is
 highlighted for further review. All levels are false. * markings: Column
 generated by Wildlife Insights that could be used to identify specific
 animal markings. Left blank for our study. * cv_confidence: Column
 generated by Wildlife Insights that could be used to label confidence in
 species identification. Left blank for our study. * license: Licensing
 type for the data stored by Wildlife Insights. **File:
 Cody.station.details.csv** **Description:** Data providing details about
 each camera station in Wyoming. ##### Variables * Station: Camera trap
 identifier. * Site: Location where camera trap was deployed. All levels
 are P.Creek (GYE site). * pre.days.active: Number of days that the camera
 trap was active during pre-treatment phase. * treatment.days.active:
 Number of days that the camera trap was active during treatment phase. *
 post.days.active: Number of days that the camera trap was active during
 post-treatment phase. * treatment: Type of scent treatment applied at the
 camera station during the treatment phase (water, coyote urine, wolf
 urine, mountain lion urine). * lat: GPS latitude in WGS84 projection. *
 lon: GPS longitude in WGS84 projection. **File: cmp.station.details.csv**
 **Description:** Data providing details about each camera station in Ohio.
 ##### Variables * Station: Camera trap identifier. * Site: Location where
 camera trap was deployed. Levels are: Bedford, Brecksville, Hinckley, and
 Litchfield * pre.days.active: Number of days that the camera trap was
 active during pre-treatment phase. * treatment.days.active: Number of days
 that the camera trap was active during treatment phase. *
 post.days.active: Number of days that the camera trap was active during
 post-treatment phase. * treatment: Type of scent treatment applied at the
 camera station during the treatment phase (water, coyote urine, wolf
 urine, mountain lion urine). * lat: GPS latitude in WGS84 projection. *
 lon: GPS longitude in WGS84 projection. **File: WTD_predator_cues.rmd**
 **Description:** R code used to perform all data cleaning and statistical
 analyses. #### Authors & Contact \- Authors: Matthew A. Wuensch, Tony
 W. Mong, Brandon M. Scurlock, Nathan W. Byer, Jonathon D. Cepek, David
 Ward. \- For questions, contact: Matthew A.
 Wuensch[[matthew.a.wuensch@gmail.com](mailto:matthew.a.wuensch@gmail.com)]
 or [[mwuensch@kent.edu](mailto:mwuensch@kent.edu)]