Data from: Faster and farther: wolf movement on linear features and implications for hunting behaviour ...

• Main Authors: Dickie, Melanie, Serrouya, Robert, McNay, R. Scott, Boutin, Stan
• Format: Dataset
• Language: English
• Published: Dryad 2017
• Subjects: kill rates; oil and gas; Rangifer tarandus; linear features; search rate; Canis lupus; caribou
• Online Access: https://dx.doi.org/10.5061/dryad.s7r47; https://datadryad.org/stash/dataset/doi:10.5061/dryad.s7r47

Predation by grey wolves Canis lupus has been identified as an important cause of boreal woodland caribou Rangifer tarandus caribou mortality, and it has been hypothesized that wolf use of human-created linear features such as seismic lines, pipelines and roads increases movement, resulting in higher kill rates. We tested if wolves select linear features and whether movement rates increased while travelling on linear features in north-eastern Alberta and north-western Saskatchewan using 5-min GPS (Global Positioning System) locations from twenty-two wolves in six packs. Wolves selected all but two linear feature classes, with the magnitude of selection depending on feature class and season. Wolves travelled two to three times faster on linear features compared to the natural forest. Increased average daily travelling speed while on linear features and increased proportion of steps spent travelling on linear features increased net daily movement rates, suggesting that wolf use of linear features can increase ... : Zip file of RSF Data and Step DataData collected using GPS collars. RSF data includes 10 random/GPS location. Step data are lines connecting sequential 5 minute locations. RSF data: Data collected using GPS collars. Fields include a unique ID field (SEQID), animal identifier field (DEVICE_ID), season, year, if the GPS location is on (1) or off (0) a linear feature (LF), what type of feature (LF_TYPE), landcover(HABITAT), if its a use (1) or random (0) location (USE) and the conditional point ID (PNTID). Additionally elevation (ELEV) and linear feature density (LINE_DENSE) are included fields, but were not used in these analyses. Step Data: a unique identifier (Unique_ID), animal identifier (DEVICE_ID), datatime field (DT_GMT), year, season, if the location is on (1) or off (0) a linear feature (LF), location linear feature class (PT_LF_TYPE), location landcover (PT_HABITAT), Northing (X) and Easting (Y) of the location, length between successive locations (Shape_Leng), speed (STEPLENGTH), if the path is on ...