Safety first: seasonal and diel habitat selection patterns by red deer in a contrasted landscape

Abstract

Spatially heterogeneous landscapes provide solutions to the forage‐safety trade‐off when animals can access risky but energetically rewarding patches, or safer but resource‐poor patches. It can be advantageous for an animal to secure access to habitat heterogeneity at a broader scale in order to be able to dynamically adjust finer scale habitat use through time. We tested the hypothesis of a forage‐safety trade‐off optimization tactic in a hunted red deer (Cervus elaphus) population following a large accidental forest fire. We used telemetry data and fitted resource selection functions at the second‐ and third‐order scales. We then integrated the order‐specific probabilities into single, all‐in‐one multi‐level layers that synthetically captured the habitat selection patterns across scales by informing landscape‐scale annual habitat selectivity with finer within‐home‐range seasonal and diel processes. At the landscape scale, red deer anchored their home‐range at the interface of the disturbed and undisturbed patches, thereby securing habitat heterogeneity. This consequently enabled them to modulate within‐home‐range habitat selection depending on the season and the time of the day. In both seasons, red deer consistently used the burnt area for cover more during the day, and foraged in the unburnt forest and open fields at night. Interestingly there were no major seasonal differences in this diel habitat selection patterns. Increased mortality risk during the hunting season did not substantially change their spatial behaviour. We conclude that year‐round avoidance of non‐lethal human disturbance is the main driver of red deer habitat use in this system.

Winter severity and anthropogenic factors affect spatial behaviour of red deer in the Carpathians

“…Both in Beskid Niski and Beskid Sądecki, red deer avoided agricultural areas, likely because these open areas did not provide enough shelter from humans and adverse weather conditions. However, strong avoidance of agricultural habitats found in our study might be artificially enhanced by deficiency of locations obtained during nighttime, as deer tend to use safer habitats during daylight (Fattebert et al 2019). Stronger selection of mixed and coniferous forest stands in winter observed in Beskid Niski was most probably a result of foraging on young firs and black berry bushes, which are preferred by red deer in winter (Jamrozy 1980;Krojerová-Prokešová et al 2010).…”

Evidence for increasing human‐wildlife conflict despite a financial compensation scheme on the edge of a Ugandan National Park

“…Doing so enabled us only to predict a risk proportional to a true probability of risk that a use‐unused design (DeCesare et al, 2012; Yackulic et al, 2013), or an occupancy‐modeling framework would generate (Goswami, Medhi, Nichols, & Oli, 2015). This is however typical of resource selection function studies reporting habitat selection probabilities (e.g., from tracking data), as GPS collars only record use locations (DeCesare et al, 2012; Fattebert et al, 2015; Fattebert et al, 2018; Fattebert et al, 2019).…”

“…To define the domain of availability to sample environmental conditions, we built a convex polygon encompassing all the depredation points (Fattebert, Robinson, Balme, Slotow, & Hunter, 2015; Miller, 2015). We generated random pseudo‐absences at a 1:5 ratio to used locations (Fattebert, Morelle, Jurkiewicz, Ukalska, & Borkowski, 2019). We extracted landscape variables at each used, and available point using the package raster (Hijmans et al, 2013) in the R environment (Pinheiro, Bates, DebRoy, & Sarkar, 2018; R Core Team, 2018).…”

Population estimates of large carnivores and their conflict with humans in East Africa and India

“…To define the domain of availability to sample environmental conditions, we built a convex polygon encompassing all the depredation points Miller 2015). We generated random pseudo-absences at a 1:5 ratio to used locations (Fattebert et al 2019). We extracted landscape variables at each used, and available point using the package raster (Hijmans 2013) in the R environment (R Development Core Team 2015).…”

“…This is typical of resource selection function studies reporting habitat selection probabilities (e.g. from tracking data), as GPS collars only record use locations (DeCesare et al 2012, Fattebert et al 2018, Fattebert et al 2019). While it is unlikely that we missed conflict events in the area as reporting depredations was motivated by the perspective of being compensated, we do acknowledge that our spatiallyexplicit dataset is a subset of c. a third the 1102 conflict events we recorded in total.…”