Anthropogenic linear features facilitate access and travel efficiency for predators, and can influence predator distribution and encounter rates with prey. We used GPS collar data from eight wolf packs and characteristics of seismic lines to investigate whether (1) ease-of-travel or (2) access to areas presumed to be preferred by prey best explained seasonal selection patterns of wolves near seismic lines, and whether the density of anthropogenic features led to functional responses in habitat selection. At a broad scale, wolves showed evidence of habitat-driven functional responses by exhibiting greater selection for areas near low-vegetation height seismic lines in areas with low densities of anthropogenic features. We highlight the importance of considering landscape heterogeneity and habitat characteristics, and the functional response in habitat selection when investigating seasonal behaviour-based selection patterns. Our results support behaviour in line with search for primary prey during summer and fall, and ease-of-travel during spring, while patterns of selection during winter aligned best with ease-of-travel for the less-industrialized foothills landscape, and with search for primary prey in the more-industrialized boreal landscape. These results highlight that time-sensitive restoration actions on anthropogenic features can affect the probability of overlap between predators and threatened prey within different landscapes.

see Methods in SREP-18-16624D

This file explains all of the variables in each of the datasets that accompany:                         
"Pigeon, EK, D. MacNearney, M. Hebblewhite, M. Musiani, L. Neufeld, J. Cranston, G. Stenhouse, F. Schmiegelow, and L. Finnegan"                        
The density of anthropogenic features explains seasonal and behaviour-based functional responses in selection of linear features by a social predator
                        
                    
Dataset files:
wDen_LSMALP_m.csv, wRend_LSMALP_m.csv, wNom_LSMALP_m.csv, wDen_LSMALP_r.csv, wRend_LSMALP_r.csv, wNom_LSMALP_r.csv, 
wDen_RPCNAR_m.csv, wRend_RPCNAR_m.csv, wNom_RPCNAR_m.csv, wDen_RPCNAR_r.csv, wRend_RPCNAR_r.csv, wNom_RPCNAR_r.csv                

File name description:
RPCNAR        less-industrialized foothills landscape 
LSMALP        more-industrialized boreal        
m        travelling
r        resting-feeding 

Variables:   
Use        used (1) or available (0) steps        
pfix        probability of obtaining a fix - models from Frair et al. (2004) and Hebblewhite et al. (2007)        
fAnimalID_YR    animal ID                    
VEGHT_MEAN    "mean height of vegetation along 100 m section of seismic line, m"    
SEIS_NEARM    "distance to the nearest seismic line (m)"        
WAM        "mean wet areas mapping (depth to water, m) underneath seismic line sections represented as an exponential decay function with a threshold of 3 m"        
A1k        "density of anthropogenic features within 1km radius, km/km2"        
A70        "density of anthropogenic features within 70m radius, km/km2"                    
DST_HWY40    "distance to highway 40, km"
DST_W1M        "distance to 1M streams, m"
DST_W20k    "distance to 20k streams, m"
ELEV        "elevation, derived from 25-m digital elevation model, m"    
TPI        "topographic position index from Jenness (2006)"
CC        "% canopy cover from MODIS & Landsat imagery, 30m resolution from Frnaklin et al. (2002) and McDermid et al (2009)", 
CTIPoint    "compound topographic index, terrain wetness from Gessler (2000)"
E.Seral        "binary variable for early seral stage (1), other (0) landcover classification from MODIS & Landsat imagery, 30m resolution from Franklin et al. (2002) and McDermid et al (2009)"
Slope        "slope, derived from 25-m digital elevation model, degree"
fLee        "binary variable for fLee = from NW to E aspect (1) or not (0)"
fFlat        "binary variable for fFlat = 0° (1), other (0) 
fMixed        "binary variable for mixed forest (1), other (0) landcover classification from MODIS & Landsat imagery, 30m resolution from Franklin et al. (2002) and McDermid et al (2009)"
                        
                        
References                        
"Frair JL, Nielsen SE, Merrill EH, Lele SR, Boyce MS, Munro RHM, et al. Removing GPS collar bias in habitat selection studies. J Appl Ecol. 2004;41: 201–212. doi:10.1111/j.0021-8901.2004.00902.x"                        
"Hebblewhite M, Percy M, Merrill EH. Are All Global Positioning System Collars Created Equal? Correcting Habitat-Induced Bias Using Three Brands in the Central Canadian Rockies. J Wildl Manage. 2007;71: 2026–2033. doi:10.2193/2006-238"                        
"Jenness J. Topographic position index (tpi_jen.avx) extension for ArcView 3.x v. 1.3a http://www.jennessent.com/arcview/tpi.htm (2006).
"Gessler P.E., Chadwick, O.A., Chamran, F., Althouse, L. & Holmes, K. Modeling soil–landscape and ecosystem properties using terrain attributes. Soil Science Society of America Journal. 64, 2046 (2000).
"Franklin S.E., Peddle, D.R., & Dechka, J.A. Evidential reasoning with Landsat TM, DEM and GIS data for landcover classification in support of grizzly bear habitat mapping. International Journal of Remote Sensing. 23, 4633-4652 (2002).
"McDermid G.J., Hall, R.J., Sanchez-azofeifa, G.A., Franklin, S.E., Stenhouse, G.B., Kobliuk, T. & Ledrew, E.F. Remote sensing and forest inventory for wildlife habitat assessment, Forest Ecology and Management. 257, 2262-2269 (2009).