Carnivore space use shifts in response to seasonal resource availability

Abstract

Estimating spatial and temporal resource use and partitioning among carnivore species varies based on life history and is critical to understanding ecological relationships of sympatric carnivores and their prey. Temporal variation in food availability can have a substantial influence on distribution, foraging behavior, prey selection, and population dynamics of carnivores. We investigated shifts in space use of black bears (Ursus americanus), bobcats (Lynx rufus), coyotes (Canis latrans), and gray wolves (C. lupus) in response to seasonal availability of white‐tailed deer (Odocoileus virginianus) fawns in Michigan, USA, May–August 2009–2011. We used generalized linear mixed models to identify whether probabilistic fawn space use resulted in shifts in carnivore space use from deer pre‐parturition (PPP, 1 May–24 May) to fawn limited mobility (LMP, 25 May–30 June) and social mobility (SMP, 1 July–31 August) periods. We developed a rule‐based algorithm to identify “clusters” of carnivore GPS locations and investigated carnivore clusters to identify fawn predation sites. Carnivores shifted space use among periods, but responses varied among species regarding fawn space use. Black bears selected against areas with greater fawn use during LMP and selected areas with greater fawn use during SMP. We suggest black bear space use was unrelated to fawn space use and reflected availability of vegetative forage. Bobcats selected areas with greater fawn use during LMP and SMP. Coyotes were indifferent to areas where fawns occurred during LMP but selected against areas with greater fawn use during SMP, likely foraging on alternative prey. Coyotes were spatially constrained by wolves, selecting against areas with greater wolf use during LMP and SMP. Wolves selected against areas with greater fawn use during LMP and SMP and selected areas near habitat edges and areas containing livestock carcasses. Carnivore responses to fawn white‐tailed deer distribution and vulnerability were congruent with life history strategies, resulting in space use shifts in response to temporarily abundant resources. Carnivores did not overall rely predominantly on fawns, likely shifting their space use to maximize intake of other seasonal resources. These events provide additional insight into life history strategies among co‐occurring species and dynamics of multi‐species predator–prey systems.

Variable intraspecific space use supports optimality in an apex predator

“…Brown bears prey on ungulate neonates to varying extents depending on species, availability, and location 64 , 65 . We did not find a relationship between the presence of female elk during calving (spring) and bear range size on Afognak, which may reflect population-level opportunistic foraging of elk calves, as observed with black bears ( Ursus americanus ) and neonatal ungulates 52 , 66 , 67 . However, during the elk hunting period (fall), a decrease in the probability of elk occurrence resulted in an increase in bear range size on Afognak Island.…”

Fine‐scale movements and behaviors of coyotes (Canis latrans) during their reproductive period

“…Animal movements are reflective of their responses to biotic and abiotic conditions within their ranges (Svoboda et al., 2019). We observed that on average, coyotes moved ~6 km per day within their home ranges, comparable to more contemporary studies detailing coyote movements using GPS telemetry (Grubbs & Krausman, 2009).…”

Responses of American black bears to spring resources

“…After emerging from hibernation, black bears consume substantial amounts of vegetation, but are unable to fully digest plant matter due to their simple digestive systems, making it difficult to meet their energetic needs on plant matter alone (Pritchard and Robbins 1990, Costello et al 2016, Herrero 2018. Later in spring, some black bears will take advantage of the availability of neonate ungulates, which are easier to digest than plant matter, but low in fat, which also makes regaining energy difficult (Pritchard and Robbins 1990, Barber-Meyer et al 2008, Bastille-Rousseau et al 2011, Schwartz et al 2014, Rayl et al 2018, Svoboda et al 2019.…”