Data and code from: Understanding sex-specific behavioral states of Bobcats in response to highway proximity in south Texas
Data files
Jul 31, 2026 version files 2.42 MB
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DataCleanUP_bobcat_revised.R
32.98 KB
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README.md
2.80 KB
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summary_bobcatID.csv
2.39 MB
Abstract
Roads are a major source of landscape fragmentation that can influence movement patterns, survival, and behavioral states of carnivore species. Understanding their behavior and response to roads is crucial for developing effective mitigation strategies such as wildlife crossing structures, exclusion fencing, and habitat connectivity planning. We examined the behavioral response of bobcats (Lynx rufus) from private ranchlands adjacent to US Highway 77 in South Texas. We used GPS collar data to track the movement of 10 bobcats (six males and four females) to quantify fine‐scale movement behavior and space use. We used Hidden Markov Models (HMMs) to predict three behavioral states of each individual movement pattern: State 1 (resting), State 2 (moderately active), and State 3 (traveling). Our model indicated that the interaction of distance to the highway and sex influenced bobcat behavioral state transitions. Male and female bobcats differed in nocturnal movement behavior, with females exhibiting slightly longer mean step length (distance between two consecutive relocations) than males, while turning angles (angle between previous and current displacement) were similar between both sexes during the resting state. Both sexes spent most of their time in the moderately active state (State 2) across all distance to highway classes. This behavior is consistent with foraging, territorial patrolling, and searching for mates during night hours. Although both sexes were moderately active, females reduced movement closer to the highway, whereas males showed more extensive travel. Home ranges of some bobcats overlapped and frequently abutted US Highway 77, suggesting the highway may function as a behavioral and spatial boundary. These findings highlight how expanding highways may reduce functional connectivity for bobcats and other felids and may inform mitigation strategies to reduce wildlife‐vehicle collisions, with potential applications for the conservation of sympatric felids like ocelots (Leopardus pardalis)
Dataset DOI: 10.5061/dryad.41ns1rnw5
Description of the data and file structure
Dataset DOI: https://doi.org/10.5061/dryad.41ns1rnw5
We have submitted our raw data (summary_bobcatID.csv), and R script (DataCleanUP_bobcat_revised.R), which consists of GPS-tracked movement data for bobcats monitored at study sites "Share3(SH3)" and "W1" during the year 2025. The data were collected as part of our study to apply a Hidden Markov Model to analyze three behavioral states (Resting, moderately active, Traveling) using step length and turning angles for each individual bobcat.
File: summary_bobcatID.csv
Variables:
- ID: Individual bobcats identifier
- step: Step length between consecutive GPS points (in meters)
- angle: Turning angle between consecutive movement steps (in radians)
- OID: Observation ID; sequential index for each movement observation
- Location: Study location or site code
- Sex: Sex of individual(F = Female , M = Male)
- Year: Year of observation
- Obs_No: Sequential observation number
- DateTime: Timestamp for each GPS fix (format: YYYY-MM-DD HH:MM:SS)
- FixRate: GPS fix schedule
- HDOP: Horizontal Dilution of Precision (GPS quality indicator)
- NumSats: Number of satellites used for GPS fix
- dt: Time difference between consecutive GPS points (in minutes)
- Night: Indicates whether the fix was taken at night or day
- Gap: Time gap in minutes between fixes; used for irregular intervals
- new_burst: Logical column ("True/False"); if "True" then a new burst begins
- burst_num: Sequential burst number for each individual
- burst: Unique identifier for each burst (Combines OID, ID, burst #)
- step_length: Step length of previous movement, for context (in meters)
- bearing: Bearing of previous movement step (in radians)
- turning_angle: Turning angle calculated relative to previous step (in radians)
- Distance: Distance between two consecutive points (in meters)
Missing data:
NA values represents missing measurements and represent where calculations are not possible, such as in the first step in a burst or after large time gaps.
File format:
csv file; UTF-8 encoding; comma-separated; header in first row.
Code/software
R is required to run DataCleanUP_bobcat_revised; the script was created using R version 4.4.2
Annotations are provided throughout the script through 1) library loading, 2) dataset loading 3) analyses, and 4) figure creation.
Access information
Other publicly accessible locations of the data:
- N/A
Data was derived from the following sources:
- GPS collar
