Objective 1: determining whether predator movements indicated
active search for parturient ungulates
We determined whether predators were actively searching for parturient
female ungulates by assessing whether their actual movements (hereafter
“steps,” or the Euclidean distance between subsequent GPS relocations)
led to encounters with parturient females more often than hypothetical
steps that they could have taken but did not. To do so, we fit
step-selection functions (Fortin et al. 2005) for each carnivore
species to estimate the relative probability of selecting a location on
the landscape, given its previous location and a suite of covariates at
the ending locations of both real and hypothetical (hereafter,
“random”) steps. We excluded data from individuals whose home ranges
did not overlap deer and elk relocations in Starkey Experimental Forest
and Range. The covariate of primary interest was whether the endpoint of
each observed or random step was within a 200-meter proximity of a
parturient female ungulate. By comparing whether the observed steps were
more often within close proximity of a parturient ungulate than were
random steps, we could assess whether predators detected neonates more
often than expected by incidental encounter, which is evidence of active
search behavior. We restricted the analysis to include location data of
each female ungulate in the 30 days after a parturition event was
predicted to occur and fit separate models for deer and elk for each of
the four carnivore species (8 models total). We compared each real step
(coded 1) with 20 random steps (coded 0; Latombe et al . 2014) and
fit models using conditional logistic regression. The random locations
were generated by taking random draws from the fitted distributions of
step lengths and turning angles (Gamma and von Mises distributions,
respectively; Avgar et al. 2016) constructed from GPS data for
each predator species and projecting the random locations for each GPS
position onto the landscape given the previous location. To control for
the possibility that observed steps landed in close proximity to an
ungulate simply because of the predator’s preference for certain
landscape or vegetative features, we included additional covariates
known to influence carnivore movements (Ruprecht et al. 2021b):
canopy cover (derived from LEMMA’s generalized nearest neighbor model;
Ohmann et al. 2011), potential vegetation type (a factor variable
with classes for open forest, closed forest, grassland, and other),
ruggedness (using the vector ruggedness measure, a composite index of
terrain encompassing both slope and aspect; Sappington, Longshore &
Thompson 2007), the distance to nearest open road (natural log
transformed), and distance to nearest perennial water source (natural
log transformed). All continuous variables were centered to have a mean
of 0 and scaled to have a standard deviation of 1. The step-selection
function took the form\(w(x)\ \sim\ exp(\beta_{1}\times\text{parturient\ deer\ or\ elk\ presence}+\ \beta_{2}\times\text{canopy\ cover}+\ \beta_{3}\times p\text{otential\ vegetation\ type}\ +\ \beta_{4}\times\text{ruggedness}\ +\ \beta_{5}\times ln(\text{distance\ to\ road})\ +\ \beta_{6}\times ln(\text{distance\ to\ perennial\ water\ source})\ +\ \beta_{7}\times ln(\text{step\ length})\ +\ \beta_{8}\times cosine(\text{turning\ angle}))\).
Because the response to neonates can differ by sex of bears (Raylet al. 2015), we fit additional models for male and female bears
separately. We did not fit additional sex-specific models for cougars,
coyotes, or bobcats, however, because we had no evidence a priorithat predation of neonates would differ between the sexes for those
species.