Basic and Applied Ecology 51 (2021) 1 10

www.elsevier.com/locate/baae

Can’t bear the competition: Energetic losses fromkleptoparasitism by a dominant scavenger may alter foraging
behaviors of an apex predator
Maximilian L. Allena,*, L. Mark Elbrochb, Heiko U. WittmercaIllinois Natural History Survey, University of Illinois, 1816 S. Oak Street, Champaign, IL 61820, USA
Panthera, 8 West 40th Street, 18th Floor, New York, NY 10018, USAc
School of Biological Sciences, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealandb

Received 18 March 2020; accepted 24 January 2021
Available online 27 January 2021

Abstract
The interspeciﬁc interactions of apex predators are integral to the function of ecological communities, but most studies havefocused on understanding their top down effects. Kleptoparasitism (the stealing of procured food) by dominant scavengers canhave negative effects on populations and behaviors of apex predators. We captured 7 pumas (Puma concolor) and ﬁtted themwith GPS collars to investigate potential kill sites (n = 352), some of which we monitored with camera traps (n = 58). We analyzed whether observed kleptoparasitism by American black bears (Ursus americanus) affected puma energetics and foraging
behavior. We found that black bears were the most frequent scavenger of puma kills (72.4%), and we documented bears scavenging puma kills during every month. The top model for bear detection of puma kills included prey size, temperature, and canopy cover, with bears more likely to scavenge from adult black-tailed deer (Odocoileus hemionus columbianus) carcasses inwarmer temperatures and under dense canopy cover. When black bear scavenging occurred, pumas spent 22% less time at theirkill and incurred energetic losses. In response, pumas shortened their inter-kill intervals by 1.3 days thus increasing their killrates. Our results demonstrate how a dominant scavenger directly mediates the foraging behavior of an apex predator. These
results suggest that community interactions do not necessarily start at the top in top-down systems, and the effects of predatorson prey populations can only be understood within their respective ecological communities.
© 2021 Gesellschaft für Ökologie. Published by Elsevier GmbH. All rights reserved.

Keywords: kleptoparasitism; Predation; Puma concolor; scavenging; Ursus americanusInterspeciﬁc interactions (i.e., predation, competition, parasitism/disease) are integral to the structure and function of
ecological communities and ecosystems. Apex predators, inparticular, are known for their important top-down effects
on ecosystems (Estes & Palmisano 1974; McLaren & Peterson 1994; Ripple et al., 2014). Apex predators can both
directly and indirectly affect their prey populations (Estes &*Corresponding author.
E-mail address: maxallen@illinois.edu (M.L. Allen).

Palmisano 1974; Ripple et al., 2001) and, due to resulting
changes in both the abundance and distribution of theiroften-larger bodied prey, initiate trophic cascades more frequently than smaller predators (DeLong et al., 2015). Apex
predators, however, also have to mitigate negative effects ofdirect and indirect interactions with other species in theirecological communities. For example, juveniles of apex
predators are sometimes killed by other predators(Ruth et al., 2011), and predators affected by parasitism/

https://doi.org/10.1016/j.baae.2021.01.011
1439-1791/© 2021 Gesellschaft für Ökologie. Published by Elsevier GmbH. All rights reserved.

2

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

disease have been shown to change their hunting behavior(Cross et al., 2016). When multiple large-bodied predators
overlap, competition for prey can also result in subordinate
species having to shift their diet (i.e., resource partitioning;
Hayward et al., 2006).
Scavenging and kleptoparasitism (the stealing of alreadyprocured food; Krofel et al., 2012) are increasingly recognized
as important interspeciﬁc interactions, but their direct and indirect effects on other species within ecological communities canbe difﬁcult to quantify. Effects of dominant scavengers thatsteal and displace subordinate predators from their ungulate
kills include: reductions in energetic intake (Carbone et al.,
1997; Krofel et al., 2012), reduced subordinate predator abundances (Gorman 1998, Krofel & Jerina 2016), and changes inhunting and other behaviors exhibited by the subordinate species (Carbone et al., 1997; Krofel et al., 2012). Ultimately, theeffects of scavengers on predators are likely species-speciﬁc.
For example, social predators can often consume large portionsof their prey before scavengers are able to exploit it, although
there is intraspeciﬁc competition within the group (Gorman
1998). In contrast, solitary predators often consume large preyover multiple days and are thus more prone to losing food toscavengers (Allen, Elbroch, Wilmers & Wittmer, 2015;
Krofel et al., 2012). Fear of the apex predator appears to limit
losses to some species (Allen, Elbroch et al., 2015), but does
not appear to be an effective strategy against dominant scavengers which can overpower solitary carnivores(Allen, Elbroch et al., 2015; Krofel & Jerina 2016;
Krofel et al., 2012).
Bears are dominant scavengers known to outcompete
many other species for carrion (Allen, Elbroch et al., 2015;
Krofel et al., 2012). Bears are able to detect animal carcasses
quickly, with experimental work showing that American
black bears (Ursus americanus; hereafter black bears)
detected carcasses on average 2 days (48.5 hours) after being
placed on the landscape (Allen, Elbroch et al., 2015). Importantly, their large body size allows bears to usurp carcasses
from apex predators (Allen, Elbroch et al., 2015; Krofel &Jerina 2016; Krofel et al., 2012). For example, brown bears(Ursus arctos) in Europe have been found to usurp 32% ofEurasian lynx (Lynx lynx) kills and lynx feeding time atthese kills was reduced by 47%, leading to increases in lynx
kill rates and overall energetic losses of 41% (Krofel et al.,2012). The relationship between pumas (Puma concolor)and black bears in North America is likely similar. Puma
kill rates increase during seasons when black bears are active(Clark et al., 2014; Elbroch et al., 2015) and this is assumed
to be because of direct competition with black bears. For
example, pumas immediately abandoned 72% of their ungulate kills once they were detected by black bears(Allen, Elbroch et al., 2015), indicating the subordinate status of pumas. Nevertheless, determining the impacts of bearscavenging on puma kill rates is complicated by the fact thatpumas generally select smaller prey (e.g., neonate ungulates)
and increase their kill rates in the warmer months whenbears are most active, regardless of the presence of bears.

Therefore, the impacts of bears on puma foraging behaviors
may be marginal in comparison to the inﬂuence of prey size
(Clark et al., 2014).
Our goal was to increase our understanding of how kleptoparasitism by black bears affects puma energetics and foraging behavior. To meet this goal, we examined thefollowing objectives and hypotheses: 1) We compared thecorrelative strength of monthly bear scavenging andmonthly mean prey weight with monthly inter-kill intervals,
as a ﬁrst step in determining which variable more inﬂuences
puma kill rates. 2) We tested factors which might determine
whether black bears detected and scavenged from a puma
kill. Among a-priori models that we tested, our primary
hypothesis was that black bears would more likely detectand feed from larger kills (i.e., adult black-tailed deer; Odocoileus hemionus columbianus) during warmer temperatures(when bears are active), but that additional landscape variables would not explain kleptoparasitism from bears (e.g.,
Elbroch et al., 2015). 3) We determined the direct effects ofblack bear kleptoparasitism on puma feeding time (numberof hours in two-hour increments that a puma was associatedwith its kill), kg of meat consumed, and percent of the edible
meat consumed (amount consumed/available to consume ata kill). We expected bears feeding on puma kills to reduce
all three variables because they are a dominant scavenger(e.g., Allen, Elbroch et al., 2015, Krofel et al., 2012). 4) We
determined how kleptoparasitism by black bears affected thesubsequent inter-kill interval (days from making one kill tomaking next kill). We hypothesized that inter-kill intervalsof pumas would decrease after losing a carcass to a bear, sothat they could recoup energetic losses to bears. 5) We determined if pumas killed more small prey (fawns and otherprey) during the months that they suffered the highest ratesof black bear kleptoparasitism of adult deer (e.g.,
Krofel et al., 2012). We hypothesized that pumas would
vary the amount of adult deer that they ate each month due
to kleptoparasitism by bears (see above), and hypothesizedthat pumas would shift to consuming more small prey inmonths with higher kleptoparasitism (positive correlation),and as they consumed less adult deer (negative correlation).

Materials and methods
Study area
Our study extended across approximately 1,000 km2 centered on the Mendocino National Forest in northern California (Fig. 1). Terrain varied from valley bottoms as low as
396 m to steep and rugged slopes at elevations of up to2,466 m. Mean daily temperatures ranged from -1°C to 24°
C and mean annual precipitation was 132 cm. Habitats wereprimarily forested, but varied with elevation and vegetation
communities. For a full description of the study area see
Allen et al., and Wittmer (2015b). Black-tailed deer were
the only resident ungulate and primary prey of pumas in theM.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

3

Fig. 1. The study area in Mendocino National Forest in northern California, with the location of puma kill sites documented during the study.

study area (Allen, Elbroch et al., 2015). Pumas occurred at
low densities (0.68/100 km2; Allen, Elbroch et al., 2015),
while high black bear abundance explained much of theobserved spatial variability in mortality risk of fawns during
summer (Forrester & Wittmer 2019).

Field methods
We captured pumas using hounds and box traps from
June 2010 to November 2012 as detailed inAllen et al. (2015b) and ﬁt each puma with a satellite GPS
collar (Lotek 7000SAW, New Market, Ontario). All capture
and ﬁeld methods were approved by an independent Institutional Animal Care and Use Committee at the University ofCalifornia, Davis (Protocols 15341 and 16886), and by the
Wildlife Investigations Laboratory of the California Department of Fish and Wildlife, and conformed to all laws in theUSA. We programmed collars to collect a GPS location
every 2-hrs and downloaded GPS locations via satellite
every 3 days. We identiﬁed potential kills as clusters ofactivity with 5 GPS locations (minimum of 8 hours
between ﬁrst and last locations) within 150 m of each otherthat contained at least one crepuscular or nocturnal location(Allen, Elbroch et al., 2015).
We visited clusters within x̅ = 6.78 § 8.18 SD (range
0 60) days after the puma departed the kill. At potential kills
we investigated the site for predation events and determined

the prey species killed by pumas by identifying remains(bones, hair/feathers) found at each GPS cluster. This resulted
in documentation of 352 kills, of which 64 were non-ungulate
prey (Table 1). We also documented visual signs ofTable 1. Counts of non-ungulate prey killed by pumas in the
study.
Prey typen

American robin, Turdus migratorius
American black bear, Ursus americanusBlack-tailed rabbit, Lepus californicus
Brush rabbit, Sylvilagus bachmani
California ground squirrel, Otospermophilus beecheyi
California quail, Callipepla californica
California towhee, Melozone crissalis
Coyote, Canis latransDouglas squirrel, Tamiasciurus douglasii
Dusky-footed woodrat, Neotoma fuscipes
Fisher, Pekania pennantiGolden-mantled ground squirrel, Callospermophilus lateralis
Gray fox, Urocyon cinereoargenteus
Mountain quail, Oreortyx pictus
Mourning dove, Zenaida macroura
Northern raccoon, Procyon lotor
Red-breasted sapsucker, Sphyrapicus ruber
Western gray squirrel, Sciurus griseus
Wild turkey, Meleagris gallopavo

1
2
6
2
26
1
1
1
3
1
1
1
2
2
1
5
1
6
1

4

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

scavengers at each kill site, including black bears (indicatedby multiple scats in the immediate area of the kill). In addition, we deployed infrared video camera traps at 58 active
puma kills on average 39.8 (52.9 SE) hours after the puma
made the kill, to document feeding activity of pumas andpotentially black bears. We set the camera traps to record continuous activity at each kill, with 60 s of video recorded ateach trigger and a 1 s refractory period. We used this data to
determine detection time and amount of scavenging at thissubset of kills. We documented the elevation, slope, aspect,and canopy cover at each kill site. Finally, we determined thetemperature and precipitation for each kill site using datafrom a local weather station for the day the kill was made.

Estimation of mass and consumption
To determine the mass of prey, we used the monthly sexspeciﬁc weights of fawns, and the annual sex-speciﬁc weights
of adults based on Parker, Gillingham, Hanley, and Robbins(1993). We estimated the age of fawns (<1-year-old) tomonth assuming a birth date of June 16th
(Allen, Elbroch et al., 2015), and of adults using tooth irruption patterns (Heffelﬁnger, 2010) and cementum annuli analysis (Low & Cowan 1963) via Matson’s Laboratory (Milltown,
MT). For other mammals we used the mean mass based on
Jameson and Peeters (2004). For birds we used the mean
mass based on Sibley (2005).
We considered the time of kill to be the time associatedwith the ﬁrst GPS point of a cluster and time of abandonment to be the time of the last GPS point of a cluster. We
deﬁned feeding time as the duration a puma was at a kill sitefrom kill to abandonment (Krofel et al., 2012), and deﬁned
inter-kill interval as the duration from the time a kill was
made to the time the subsequent kill was made
(Knopff et al., 2010). We determined feeding time and interkill interval in 2-hr increments based on the GPS data, but
excluded the inter-kill interval for the kills where we did not
visit the next sequential potential kill (n = 5).
Field experiments by Wilmers et al., and Getz (2003)
found that 68% of ungulates was edible, and we calculated
the edible portion of puma kills as
estimated mass  0:68:
We based our active consumption rates on those of
Elbroch et al., and Wittmer (2014) (6.8 kg for the initial
24 hours of the kill, and 4.1 kg for subsequent 24-hour periods of the kill; based on experimental work by Ackerman, 1982, Danvir & Lindzey 1981), and estimated the total
kg consumed at each kill in two-hour intervals based on thefeeding time of the puma. For one female (F43) with known
yearling kittens (n = 2), we summed the kitten consumption
rates with those of their mother (e.g., Elbroch et al., 2014).
We also calculated the percent of each kill consumed as
kg consumed=kg available:

Statistical analyses
We used program R version 3.3.1 (R Core Team 2016)
for all of our statistical analyses, and in each analysis, weconsidered p 0.05 to be statistically signiﬁcant. We determined the distribution for our data before deciding on thespeciﬁc model to run in each analysis, and used the lme4
package (Bates et al., 2015) for generalized linear mixed
effect models (GLMMs) and the nlme package(Pinheiro et al., 2013) for linear mixed effect models(LMMs).
First, we used LMMs to determine if the overall amountof meat consumed by pumas, the amount of adult deer consumed by pumas, or the amount of small prey (fawns andother prey) varied by month. We used each of the variablesof interest (kg of meat consumed, kg of adult deer consumed, kg of small prey consumed) as our dependent variable, the identity of pumas as a random effect, and the given
month as a ﬁxed independent effect with the lowest or highest mean as the comparison. Second, we used non-parametric Spearman rank correlation coefﬁcients to determine if
the monthly mean of small prey consumed signiﬁcantly correlated with the amount of adult deer consumed and the percent of adult deer scavenged by bears.
Following Clark et al. (2014), we began by conducting
pair-wise Pearson’s correlation analyses between monthly
inter-kill intervals and 1) monthly mean prey size (kg), 2)
the monthly proportion of all kills at which we documented
bears, and 3) the monthly proportion of adult deer kills at
which we documented bears. In terms of puma diet, deer
comprised
98.6%
of
local
prey
biomass(Allen, Elbroch et al., 2015), and evidence of bears at kills
was almost certainly more easily detected than that of otherscavengers. These analyses were meant to help us determine
whether mean prey size or bear scavenging more strongly
impacted inter-kill rates across months. We reported R2 values and P values based on an alpha of 0.05.
To determine which factors allow black bears to detectand scavenge from a puma kill we used a series of a-priori
binomial GLMMs with a logit link based on a set of common variables (Table 2). We used a binary dependent variable (whether bears scavenged from the kill, yes-no), theidentity of the puma as a random effect, and all other variables as independent effects. In the models we considered
three types of puma kills: adult deer, fawns, and other prey
(birds, carnivores, lagomorphs, and squirrels). We comparedmodels in an AIC framework using the AIC weight (w), andconsidered models with the highest cumulative w to be our
top models (Burnham & Anderson 2002).
To determine the direct effects of black bear kleptoparasitism on puma feeding time, meat consumed, and percent ofedible carcass consumed we used LMMs to compare thesevariables at kills that were detected/not detected by bears.
We used each of the variables of interest (puma feeding
time, meat consumed, and percent of edible carcass

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

Table 2. A-priori variables and underlying reasons for black bears
detecting kills made by pumas.
Variables

ReasonType of kill

Bears will be able to detect large carcasses
more easily and also be motivated to ﬁnd larger
carcasses due to the larger potential energetic
rewards for their efforts
Bears will be able to detect carcasses more easily with warmer temperatures and in seasons
when they are active
Weather will be the key aspects affecting
whether bears can detect carcasses, being able
to detect carcasses better with higher temperatures and less precipitation
Bears will detect carcasses on ﬂatter slopes
Bears will be able to detect and exploit carcasses in areas with less dense canopy coverTemperature

Precipitation

Slope
Canopy coverconsumed) as our dependent variables, the identity of pumas
as a random effect, and an interaction between the presenceof bears and kill type (with adult deer as our contrast) as ourﬁxed independent effects.
To determine how kleptoparasitism by black bears affected
the subsequent inter-kill interval we used LMMs to compare
these variables for kills that were detected/not detected bybears. We used inter-kill interval as our dependent variable,
the identity of pumas as a random effect, and an interaction
between the presence of bears and kill type (with adult deeras our contrast) as our ﬁxed independent effects.

5amount of meat in April (48.9 kg §19.3 SE), signiﬁcantly
less than in six other months (p 0.03) with the most meat
consumed in January (88.1 kg §15.0 SE). In Octoberthrough January 80 kg were consumed by pumas, but<70 kg were consumed in April, July, August and September.
Pumas also varied signiﬁcantly in the amount of meat
consumed from adult deer and small prey (fawns and otherprey) each month. Pumas consumed the least meat fromadult deer in August (40.3 kg §18.6 SE), signiﬁcantly lessthan in six other months (p 0.03) with the most in January(84.7 kg §16.9 SE) (Fig. 2). Pumas consumed the largest
amount of small prey in October (19.8 kg §4.5 SE), signiﬁcantly more than in 6 other months (p 0.03), and the least
amount in April (0 kg) (Fig. 2).
The amount of small prey consumed in a given month had
a signiﬁcant negative correlation with the amount of deer consumed (r = -0.59, p = 0.04), meaning that pumas consumed
more small prey in months when they consumed fewer adultdeer. The amount of small prey consumed in a given month
had a signiﬁcant positive correlation with the percent of deerscavenged by bears (r = 0.63, p = 0.03), meaning that inmonths when bears were scavenging from more of the adultdeer killed by pumas, pumas ate more small prey.
Monthly inter-kill rates correlated highly with the monthly
proportion of adult deer kills at which we documented bears(r = 0.80, p = 0.002), and monthly mean prey size (r = 0.79,
p = 0.002), and, to a lesser degree, the monthly proportion of
all kills at which we documented bears (r = 0.67, p = 0.02).
This suggests that variable inter-kill rates were better
explained by the inclusion of bear scavenging, rather thanseasonal variation in mean prey size alone.

Results
Patterns in energetics by monthBlack bear detection of and feeding at puma kills

Pumas varied signiﬁcantly in the overall amount of meat
they consumed each month. Pumas consumed the least

We documented black bear activity at puma kills during
every month of the year. Our top model for bear detection ofFig. 2. The monthly values of the kg consumed by pumas of adult deer and small prey, as well as the percent of adult deer kleptoparasitizedby black bears.

6

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

Table 3. Results of our Generalized Linear Mixed Model analyses
for black bear detection and scavenging of kills made by pumas.
We rank the competing models by their AIC weight (w).
Variables

AIC

ΔAIC wAIC

Kill Type + Temperature + Canopy Cover
Kill Type + Temperature
Kill Type
Canopy Cover
Temperature + Canopy Cover + Slope
Canopy Cover + Slope
Temperature
null
Slope
Temperature x Precipitation

365.5
369.7
385.9
471.0
471.3
472.2
472.8
473.5
474.3
476.3

0.0
4.2
20.4
105.5
105.8
106.7
107.3
108.0
108.8
110.8

0.89
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

puma kills was type of kill + temperature + canopy cover(w = 0.89; Table 3), while the second best model was type ofkill + temperature (w = 0.11). Based on odds ratios in the
top model, adult deer (0.22), kills associated with warmer
temperatures (-10.85), and kills with denser canopy cover(-1.31) were more likely to be found than fawns (0.16) orother prey species (0.01). The odds ratios in the second bestmodel were essentially the same except for a substantial
increase in the odds ratio of adult deer to 2.45. Speciﬁcally,
black bears scavenged from 66.5% of adult deer kills(including a maximum of 94% in June, and >75% from
May through September; Fig. 2), but only 32.9% of fawns
and 3.4% of other prey.
Black bears were the most frequent scavenger detected at
the 58 puma kills we monitored with camera traps, and displaced pumas from the carcass at 29 of these kills (50%).
Bears were detected at nearly twice as many kills (n = 42,
72.4%) as the next most frequent scavenger (gray fox, Urocyon cinereoargenteus; n = 22, 37.9%). Bears detected carcasses more quickly than other scavengers, being the ﬁrst or
second scavenger at 73.8% (nﬁrst = 21, nsecond = 10) of kills
monitored with cameras. At these kills, black bears had amean total feeding time of 145.9 (95% CI 98.5 193.2)
minutes.

Black bear effects on consumption
In the absence of black bears, pumas on average spent
3.17 (§0.28 SE) days feeding at adult deer kills. The presence of bears signiﬁcantly affected puma feeding time(p = 0.0001), resulting in an average decrease of 0.71 days(§0.18 SE) during which the puma fed on the carcass. As
compared to how long pumas fed on adult deer, pumas fed
on fawns 1.91 days (§0.23 SE) shorter (p <0.0001). In thepresence of bears, however, pumas increased their average
feeding time on fawns by 0.77 days (§0.36 SE) (p = 0.03).
Pumas also fed on average 2.07 fewer days (§0.23 SE) atother prey kills (p <0.0001) than they did at adult deer kills.

Bears had no effect on puma feeding time at non-ungulate
kill sites.
Pumas consumed 17.2 kg (§1.4 SE) of meat at adult deerkills in the absence of black bears. The presence of bears signiﬁcantly affected the amount of meat consumed by pumas
at their kills (p = 0.02), and on average, pumas sufferedlosses of 2.03 kg (§0.88 SE). In comparison to the amountof meat pumas ate at adult deer kills, pumas consumed
11.23 kg (§1.11 SE) less meat at fawn kills (p <0.0001)
and 15.57 kg (§1.10 SE) less meat at other prey kills (p<0.0001). The presence of bears did not have an effect on
how much meat pumas consumed at fawn kills or other preykills.
In the absence of black bears, pumas consumed 56%(§0.5% SE) of adult deer kills, whereas in the presence ofbears, pumas consumed 6.6% (§3.1 SE) less of the carcass(p = 0.04). As compared with the percentage of the carcass
pumas consumed at adult deer kills, pumas consumed
25.5% (§4.0 SE) more of each fawn kill (p <0.0001) and
45.1% (§3.9 SE) more of other prey kills (p <0.0001).
Bears did not impact the percentage of the carcass pumas
consumed at fawn kills or other prey kills.

Effect of black bears on subsequent puma
predation behavior
In the absence of black bears, the inter-kill interval forpumas was 6.84 (§0.61 SE) days. The presence of bears signiﬁcantly affected the subsequent inter-kill interval forpumas (p = 0.02), and on average decreased the interval by
1.34 days (§0.55 SE). In the absence of bears, pumas interkill interval also decreased 3.17 days (§0.69 SE) following
smaller fawn kills (p <0.0001) and 2.78 days (§0.68 SE)
following other prey kills (p <0.0001). We did not detect asigniﬁcant effect of bear presence on intervals following
fawn kills and other prey kills.

Discussion
Pumas in our study area have the highest ungulate kill rates
reported for the species across their range (reviewed in
Cristescu et al., 2020). We attempted to provide a mechanistic
understanding of how kleptoparasitism by a dominant scavenger (black bear) in our system may have mediated their foraging behavior. Our results show that 1) monthly inter-kill rates
correlated most strongly with the monthly proportion of deerkills detected by bears, closely followed by monthly mean
prey size; 2) black bears were more likely to scavenge fromadult black-tailed deer than either fawns or other prey species;3) when black bears scavenged from adult deer kills, pumas
spent less time feeding at the kill and thus incurred energetic
losses; 4) the behavioral response of pumas was to kill prey
more frequently (shorten their inter-kill interval); and 5)

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

7

Fig. 3. A conceptual ﬁgure, showing that in months with little black bear kleptoparasitism pumas primarily prey on deer, but in months withhigh black bear kleptoparasitism pumas diversify the prey they kill and consume.

pumas increased the proportion of their diet that was small
prey during months when kleptoparasitism by black bears
was most frequent. The direct energetic losses caused byblack bears were substantial (>10 kg in many months withhigh bear activity); we documented bears actively feeding for~2.5 hours at each kill, during which bears can consume large
amounts of meat (see Appendix A). The kleptoparasitism bybears thus appears to have mediated changes in puma foraging behavior (Fig. 3). The effect of these changes on prey(i.e., deer) populations remains unclear. While the partitioningof different life stages of the same prey (i.e., bears preying primarily on neonates (Forrester & Wittmer 2019) and pumas on
adult deer (Allen, Elbroch et al., 2015) should theoreticallyfacilitate coexistence among competing predators (De Rooset al., 2008), the combined effects of low fawn survival
mostly due to bear predation, and low summer adult survival,
mostly due to puma predation, caused a decline in the local
deer population. Therefore, increased kill rates of pumas due
to kleptoparasitism by bears may have contributed toobserved declines in the local deer population(Marescot et al., 2015).
The potential ﬁtness consequences for apex predators
experiencing bear kleptoparasitism are not understood, andwe currently do not know the thresholds for energetic losses
due to kleptoparasitism that would lower ﬁtness for pumas(Elbroch et al., 2017). The spring peak in bear scavenging
corresponds with the kitten-rearing season for Eurasianlynx, and therefore kleptoparasitism by bears could lead todirect decreases in kitten survival (Krofel et al., 2012). In
contrast, pumas exhibit summer birth pulses in ecosystems
with cold, snowy winters, but do not exhibit a deﬁned birthing season in more moderate climates. Further, pumas carefor kittens for longer time periods than Eurasian lynx. These
distinctions may buffer pumas from any impact of kleptoparasitism on kitten survival when they are youngest, but
increase the impacts of bear kleptoparasitism on the longterm survival of their kittens as they age. Pumas do notappear to have behaviors that can limit detection by blackbears, as caching of kills has been found to be ineffective todeter bear scavenging (Elbroch et al., 2015).
Pumas also killed more small prey in the months in which
they experienced the highest kleptoparasitism by bears. This
relationship does not necessarily infer causation, but it may
indicate a behavioral strategy in which pumas can consume
small prey fast enough to avoid detection and kleptoparasitism by bears. Alternatively, puma prey switching to smaller
prey in warmer months may also reﬂect changes in preyavailability and vulnerability, as has been documented inpumas (e.g., Wilckens et al., 2015) and other carnivores(e.g., gray wolf, Canis lupus; Metz et al., 2012). There arecomparatively few studies of the seasonal prey selection ofpumas in the absence of bears. One, however, conducted in
Chilean Patagonia did reﬂect puma prey switching to newborn ungulates in the summer months (Elbroch & Wittmer
2013), suggesting that in our study area, puma switching tofawns was at least in part explained by their availability andvulnerability (Knopff et al., 2010). The presence of blackbears had no effect on the consumption of fawns and otherprey species, likely because pumas are able to consume
them entirely over shorter periods of time (Knopff et al.,2010). Somewhat counterintuitively, there was an increasein the time pumas spent at fawn kills that were found bybears, but this is likely because bears found larger fawns
during the latter parts of the year.

8

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

Pumas in our study system did exhibit habitat selection
when hunting deer but not when hunting other prey
(Cristescu et al., 2019), suggesting other prey may be opportunistically killed rather than selected for. Scavenging of
ungulate kills by dominant brown bears may have led Eurasian lynx to evolve for killing smaller prey in addition to
ungulates (Krofel et al., 2012), but pumas are generally
thought to be ungulate specialists, at least in North America(see review in Ruth & Murphy 2010). However, small prey
are more difﬁcult to detect than ungulate prey
(Allen, Elbroch et al., 2015; Bacon et al., 2011) and mostalgorithms to determine kill sites from GPS data only focus
on prey >8 kg in mass (Knopff et al., 2010). Studies fromSouth America also indicate a greater proportion of nonungulate prey in puma diets (Ruth & Murphy 2010), but areoften based on scat analyses that underestimate ungulate
prey and overestimate smaller prey when compared to studies based on GPS cluster investigation (Bacon et al., 2011).
The difﬁculty in detecting small prey from GPS cluster
investigations likely led to us underestimating their importance to puma diet. Our analyses suggest that small prey are
not consumed as much as adult deer (the only ungulate in
the system), but may be an important energy source to compensate for losses to black bears.
Black bears were more likely to ﬁnd kills of adult deer
during warmer temperatures. Most black bears hibernate atsome point during the winter, which may create a competition refuge for pumas (Elbroch et al., 2015). Despite hibernation, we documented bears scavenging from puma kills
during every month of the year, but scavenging was mostfrequent at adult deer kills during June (94%). This peak inearly summer is the same as found for brown bears at Eurasian lynx kills (Krofel et al., 2012). This may suggest thatscavenging is most important during the period when bears
emerge from hibernation but before the peak of fawn availability and mast crops mature. This also suggests thatpumas, lynx and other apex predators may facilitate bear
populations. Such seasonal facilitation via kleptoparasitism
has been suggested for smaller carnivores feeding at apex
predator kills (e.g., red fox, Vulpes vulpes; Helldin & Danielsson 2007), but not for dominant, apex predators.
Because pumas are apex predators that have important
effects on their ecosystems, it is important to consider how
their populations may be affected by increasing bear populations and the indirect effects on ecosystems. We have shownhow black bears directly affect pumas and their predation
behavior, but more importantly, these effects likely ripple
through the ecosystem and may become more pronouncedwith increasing bear densities. Kleptoparasitism by bears
directly causes increases in puma inter-kill intervals andmay thus indirectly cause higher mortality for the deer population, in addition to directly being a large source of fawn
mortality (Forrester & Wittmer 2019). Alternatively, bearscavenging at puma kills may satiate bears and reduce bear
predation on ungulate neonates, and therefore bear kleptoparasitism may ultimately be of compensatory impact on

ungulate dynamics. In areas where puma predation is themain cause of adult deer mortality (e.g., Marescot et al.,2015), increasing puma kill rates in response to kleptoparasitism may have negative consequences for ungulate populations and community structure (e.g., Ripple et al., 2001).
These direct and indirect effects that black bears have on
ecosystems are particularly important because black bears
are one of the few large carnivores that are currently expanding their range (Ripple et al., 2014). The effects of blackbears on pumas are likely linked to bear density (e.g., Krofel& Jerina 2016), and the increasing restrictions on bear hunting regulations (e.g., outlawing the use of trained hounds) inmany jurisdictions may lead to decreases in harvest andgreater population increases for black bears. Thus, resource
managers need to consider possible effects of changes inmanagement of one species as they can directly affect the
populations and conservation of others (Krofel & Jerina 2016).

Declaration of Competing Interest
The authors declare that they have no known competing
ﬁnancial interests or personal relationships that could haveappeared to inﬂuence the work reported in this paper.

Acknowledgments
The California Department of Fish and Wildlife, the University of California at Davis, and the California Deer Association generously provided funding for the project. M.
Allen was supported by a Victoria University of Wellington
tuition scholarship. We thank B. Millsap, C. Wiley and D.
Tichenor for their expertise and help in capturing pumas;
and D. Casady, J. Golla, B. Evans, and many others for their
help on the project. Constructive feedback from two anonymous reviewers improved previous drafts of our manuscript.

Supplementary materials
Supplementary material associated with this article can befound in the online version at doi:10.1016/j.baae.2021.01.011.

References
Ackerman, B. B. (1982). MS Thesis. Logan, Utah, USA: Utah State
University.
Allen, M. L., Elbroch, L. M., Wilmers, C. C., &Wittmer, H. U. (2015). The comparative effects of large carnivores on the acquisition of carrion by scavengers. American Naturalist, 185, 822–833.
Allen, M. L., Elbroch, L. M., Casady, D. S., &Wittmer, H. U. (2015). The feeding and spatial ecology ofM.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

mountain lions (Puma concolor) in Mendocino National Forest,
California. California Fish and Game Journal, 101, 51–65.
Bacon, M. M., Becic, G. M., Epp, M. T., & Boyce, M. S. (2011). Do
GPS clusters really work? Carnivore diet from scat analysis andGPS telemetry methods. Wildlife Society Bulletin, 35, 409–415.
Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting
linear mixed-effects models using lme4. Journal of Statistical
Software, 67, 1–48.
Burnham, K. P., & Anderson, D. R. (2002). Model selection andmultimodel inference: A practical information-theoretic
approach (2nd ed.). New York, New York: Springer.
Carbone, C., Du Toit, J. T., & Gordon, I. J. (1997). Feeding success in African wild dogs: Does kleptoparasitism by spottedhyenas inﬂuence hunting group size? Journal of Animal Ecology, 66, 318–326.
Clark, D. A., Davidson, G. A., Johnson, B. K., &Anthony, R. G. (2014). Cougar kill rates and prey selection in a
multiple-prey system in northeast Oregon. Journal of Wildlife
Management, 78, 1161–1176.
Cristescu, B., Bose, S., Elbroch, L. M., Allen, M. L., &Wittmer, H. U. (2019). Habitat selection when killing primaryversus alternative prey species supports prey specialisation in
an apex predator. Journal of Zoology, 309, 259–268.
Cristescu, B., Elbroch, L. M., Dellinger, J. A., Binder, W.,
Wilmers, C. C., & Wittmer, H. U. (2020). Biogeographical andecological factors associated with kill rates of an apex predator.
bioRxiv. doi:10.1101/2020.10.04.325779.
Cross, P. C., Almberg, E. S., Haase, C. G., Hudson, P. J.,
Maloney, S. K., Metz, M. C., Munn, A. J., Nugent, P.,
Putzeys, O., Stahler, D. R., & Stewart, A. C. (2016). Energetic
costs of mange in wolves estimated from infrared thermography. Ecology, 97, 1938–1948.
Danvir, R. E., & Lindzey, F. G. (1981). Feeding behavior of a captive cougar on mule deer. Encyclia, 58, 50–56.
DeLong, J. P., Gilbert, B., Shurin, J. B., Savage, V. M.,
Barton, B. T., Clements, C. F., Dell, A. I., Greig, H. S.,
Harley, C. D., Kratina, P., McCann, K. S., Tunney, T. D.,
Vasseur, D. A., & O'Connor, M. I. (2015). The body size
dependence of trophic cascades. The American Naturalist, 185,
354–366.
De Roos, A. M., Schellekens, T., Van Kooten, T., &Perrson, L. (2008). Stage-speciﬁc predator species help eachother to persist while competing for a single prey. Proceedingsof the National Academy of Science, 105 13939 13935.
Elbroch, L. M., Allen, M. L., Lowery, B. H., &Wittmer, H. U. (2014). The difference between killing and eating: Understanding puma energetic models. Ecosphere, 5, 53.
Elbroch, L. M., Lendrum, P., Allen, M. L., &Wittmer, H. U. (2015). Nowhere to hide: Pumas, black bears,
and competition refuges. Behavioral Ecology, 26, 247–254.
Elbroch, L. M., Peziol, M., O’Malley, C., & Quigley, H. (2017). Vertebrate diversity beneﬁting from carrion subsidies provided by subordinate carnivores. Biological Conservation, 215, 123–131.
Estes, J. A., & Palmisano, J. F. (1974). Sea otters: Their role instructuring nearshore communities. Science, 185, 1058–1060.
Forrester, T. D., & Wittmer, H. U. (2019). Predator identity andforage availability affect predation risk of juvenile black-tailed
deer. Wildlife Biology.
Hayward, M. W., Henschel, P., O’Brien, J., Hofmeyr, M.,
Balme, G., & Kerley, G. I. H. (2006). Prey preferences of theleopard (Panthera pardus). Journal of Zoology, 298–313.

9

Heffelﬁnger, J. (2010). Arizona Game and Fish Department Special Report #19. Phoenix, Arizona, USA.
Helldin, J. O., & Danielsson, A. V. (2007). Changes in red fox
Vulpes vulpes diet due to colonisation by lynx Lynx lynx. Wildlife Biology, 13, 475–480.
Jameson, E. W., & Peeters, H. J. (2004). Mammals of California.
Berkeley, California: University of California Press.
Knopff, K. H., Knopff, A. A., Kortello, A., & Boyce, M. S. (2010).
Cougar kill-rate and prey composition in a multi-prey system.
Journal of Wildlife Management, 74, 1435–1447.
Krofel, M., Kos, I., & Jerina, K. (2012). The noble cats and the big
bad scavengers: Effects of dominant scavengers on solitary predators. Behavioral Ecology and Sociobiology, 66, 1297–1304.
Krofel, M., & Jerina, K. (2016). Mind the cat: Conservation management of a protected dominant scavenger indirectly affects anendangered apex predator. Biological Conservation, 197, 40–46.
Low, W. A., & Cowan, I. M. (1963). Age determination of deer byannular structure of dental cementum. Journal of Wildlife Management, 27, 466–471.
Marescot, L., Forrester, T. D., Casady, D. S., &Wittmer, H. U. (2015). Using multistate capture-mark-recapture
models to quantify effects of predation on age-speciﬁc survival
and population growth in black-tailed deer. Population Ecology, 57, 185–197.
McLaren, B. E., & Peterson, R. O. (1994). Wolves, moose, and treerings on Isle Royale. Science, 266, 1555–1558.
Metz, M. C., Smith, D. W., Smith, J. A., Vucetich, J. A.,
Stahler, D. R., & Peterson, R. O. (2012). Seasonal patterns ofpredation for gray wolves in the multi-prey system of Yellowstone National Park. Journal of Animal Ecology, 81, 553–563.
Parker, K. L., Gillingham, P., Hanley, T. A., &Robbins, C. T. (1993). Seasonal patterns in body mass, bodycomposition, and water transfer rates of free-ranging and captive black-tailed deer (Odocoileus hemionus sitkensis) in
Alaska. Canadian Journal of Zoology, 71, 1397–1404.
Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2013). nmle: Linear
and nonlinear mixed effect models. R package version 3.1-108.
R Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for StatisticalComputing.
Ripple, W. J., Larsen, E. J., Renkin, R. A., & Smith, D. W. (2001).
Trophic cascades among wolves, elk and aspen on Yellowstone
National Park’s northern range. Biological Conservation, 102,
227–234.
Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C.,
Ritchie, E. G., Hebblewhite, M., Berger, J., Elmhagen, B.,
Letnic, M., Nelson, M. P., & Schmitz, O. J. (2014). Status andecological effects of the world’s largest carnivores. Science,
343, 1241484.
Ruth, T. K., & Murphy, K. (2010). Cougar prey relationships.
In M. Hornocker, & S. Negri (Eds.), Cougar: Ecology and conservation (pp. 163 172). Chicago: University of Chicago
Press.
Ruth, T. K., Haroldson, M. A., Murphy, K. M., Buotte, P. C.,
Hornocker, M. G., & Quigley, H. B. (2011). Cougar survival
and source-sink structure on Greater Yellowstone's Northern
Range. The Journal of Wildlife Management, 75, 1381–1398.
Sibley, D. A. (2005). The Sibley ﬁeld guide to birds of western
north America. New York, New York: Alfred A. Knopf Publishing.

10

M.L. Allen et al. / Basic and Applied Ecology 51 (2021) 1 10

Wilckens, D. T., Smith, J. B., Tucker, S. A., Thompson, D. J., &Jenks, J. A. (2015). Mountain lion (Puma concolor) feeding
behavior in the Little Missouri Badlands of North Dakota. Journal of Mammalogy, 97, 373–385.

Wilmers, C. C., Crabtree, R. L., Smith, D. W., Murphy, K. M., &Getz, W. M. (2003). Trophic facilitation by introduced top
predators: Grey wolf subsidies to scavengers in Yellowstone
National Park. Journal of Animal Ecology, 72, 909–916.

Available online at www.sciencedirect.com

ScienceDirect