Effects of predator control on behaviour of an apex
predator and indirect consequences for mesopredator
Leila A. Brook
*, Christopher N. Johnson
and Euan G. Ritchie
School of Marine and Tropical Biology, James Cook University, Townsville, QLD, 4811, Australia;
Zoology, University of Tasmania, Hobart, TAS, 7001, Australia; and
School of Life and Environmental Sciences,
Deakin University, Burwood, VIC, 3125, Australia
1. Apex predators can beneﬁt ecosystems through top–down control of mesopredators and
herbivores. However, apex predators are often subject to lethal control aimed at minimizing
attacks on livestock. Lethal control can affect both the abundance and behaviour of apex pre-
dators. These changes could in turn inﬂuence the abundance and behaviour of mesopreda-
2. We used remote camera surveys at nine pairs of large Australian rangeland properties,
comparing properties that controlled dingoes Canis lupus dingo with properties that did not,
to test the effects of predator control on dingo activity and to evaluate the responses of a
mesopredator, the feral cat Felis catus.
3. Indices of dingo abundance were generally reduced on properties that practiced dingo con-
trol, in comparison with paired properties that did not, although the effect size of control
was variable. Dingoes in uncontrolled populations were crepuscular, similar to major prey. In
populations subject to control, dingoes became less active around dusk, and activity was con-
centrated in the period shortly before dawn.
4. Shifts in feral cat abundance indices between properties with and without dingo control
were inversely related to corresponding shifts in indices of dingo abundance. There was also a
negative relationship between predator visitation rates at individual camera stations, suggest-
ing cats avoided areas where dingoes were locally common. Reduced activity by dingoes at
dusk was associated with higher activity of cats at dusk.
5. Our results suggest that effective dingo control not only leads to higher abundance of feral
cats, but allows them to optimize hunting behaviour when dingoes are less active. This double
effect could amplify the impacts of dingo control on prey species selected by cats. In areas
managed for conservation, stable dingo populations may thus contribute to management
objectives by restricting feral cat access to prey populations.
6. Synthesis and applications. Predator control not only reduces indices of apex predator
abundance but can also modify their behaviour. Hence, indicators other than abundance,
such as behavioural patterns, should be considered when estimating a predator’s capacity to
effectively interact with lower trophic guilds. Changes to apex predator behaviour may relax
limitations on the behaviour of mesopredators, providing enhanced access to resources and
Key-words: carnivore, interference competition, intraguild interactions, invasive species,
landscape of fear, pest management, risk effects
*Correspondence author. E-mail: email@example.com
©2012 The Authors. Journal of Applied Ecology ©2012 British Ecological Society
Journal of Applied Ecology 2012, 49, 1278–1286 doi: 10.1111/j.1365-2664.2012.02207.x
When predators occur in sympatry, smaller mesopredators
may face a reduction in ﬁtness due to competition from
larger apex predators (Creel & Creel 1996). This can take
the form of exploitation competition among species that
consume the same prey species or interference competition
via harassment, killing and (sometimes) consumption of
smaller mesopredators by apex predators (Polis, Myers &
Holt 1989; Polis & Holt 1992). These two forms of com-
petition can directly affect mesopredators by reducing
their abundance and causing modiﬁcations of behaviour
that allow them to avoid encounters with their larger ene-
mies (Durant 2000; Hunter & Caro 2008; Salo et al. 2008;
Ritchie & Johnson 2009; Elmhagen et al. 2010).
Mesopredator avoidance of apex predators can occur in
both space and time, but most research has focussed on
spatial shifts (Kronfeld-Schor et al. 2001). Although some
studies have recorded temporal partitioning between sym-
patric, similar-sized felids (Di Bitetti et al. 2010; Romero-
˜oz et al. 2010), few have directly explored temporal
shifts involving apex- and mesopredators (but see Hayward
& Slotow 2009). Patterns of temporal activity are driven
primarily by circadian stimuli such as light, but animals
may shift activity in response to other factors such as pre-
dation risk (Rasmussen & Macdonald 2011) or competi-
tion (Kronfeld-Schor et al. 2001). These shifts may incur
costs such as reduced foraging opportunities (Rasmussen
& Macdonald 2011). Larger predators are not immune:
their activity patterns can be inﬂuenced by the risk of
encounter with humans (Theuerkauf 2009), particularly
when facing persecution (Ordiz et al. 2012). Rasmussen &
Macdonald (2011) found that African wild dogs Lycaon
pictus shifted hunting activity to moonlit periods, which
would probably reduce the success rate of hunting, to
avoid encounters with humans.
Persecution by humans contributes to the decline of apex
predator populations (Treves & Karanth 2003) and conse-
quent ecological disruptions via trophic cascades (Estes
et al. 2011). Removal of apex predators can ‘release’ meso-
predators from top–down pressure (Soule
´et al. 1988;
Ritchie & Johnson 2009), lifting previous constraints on
abundance and behaviour and allowing their populations to
expand. As a consequence, abundance and diversity of prey
may decline (Crooks & Soule
´1999; Berger, Gese & Berger
2008). Maintaining apex predators may indirectly protect
vulnerable prey and sustain biodiversity (Sergio et al. 2006).
Since its arrival in Australia 3500–5000 years ago
(Savolainen et al. 2004), the dingo Canis lupus dingo (L.)
has been the largest mammalian predator on the continent.
Widespread control programmes, using poison baiting,
trapping and shooting, aim to reduce the dingo’s impacts
on livestock (Fleming et al. 2001). There is evidence that
dingoes can suppress abundance of the invasive red fox
Vulpes vulpes and thereby have positive effects on species
preyed upon by foxes (Johnson, Isaac & Fisher 2007; John-
son & VanDerWal 2009; Letnic et al. 2009; Wallach et al.
2010). Dingoes may also suppress a smaller mesopredator,
the feral cat Felis catus (L.), but there is less evidence for
this (Letnic, Ritchie & Dickman 2012; but see Moseby et al.
2012). Feral cats arrived with European settlers in the
1800s (Abbott 2002) and now occur across the entire conti-
nent (Denny 2008). They have contributed to the decline
and extinction of native mammals, reptiles and birds
(Johnson 2006), thwarted reintroduction programmes for
threatened species (Gibson et al. 1994; Priddel & Wheeler
2004) and may be partly responsible for current mammal
declines across Northern Australia (Woinarski et al. 2011).
Unfortunately, feral cats are difﬁcult to control or monitor.
Control efforts aimed at dingoes, and foxes usually involve
distribution of baits laced with the poison sodium ﬂuoroac-
etate (known as 1080), but these are ineffective against cats
because cats are disinclined to take baits.
Both dingoes and feral cats are mostly active during cre-
puscular and nocturnal periods in warm climates (Jones &
Coman 1982; Thomson 1992). They have physiological
adaptations for crepuscular and nocturnal activity, such as
optimal vision in low-light conditions and highly developed
olfactory (dingo) and auditory (cat) capabilities (Kavanau
& Ramos 1975; Kitchener, Van Valkenburgh & Yamaguchi
2010). In addition, predators may adjust their activity
schedules to match periods when their prey are most active
or vulnerable (Ferguson, Galpin & de Wet 1988). We would
expect crepuscular periods, particularly dusk and early
evening, to provide optimal foraging conditions for both
predators, because they coincide with activity of preferred
prey: nocturnal reptiles such as geckoes are most active in
the hours following dusk (Bustard 1967), while diurnal rep-
tiles are retreating, and mammals such as kangaroos and
small marsupials (Coulson 1996), rodents (Breed & Ford
2007) and rabbits (Williams et al. 1995) tend to be crepus-
cular or nocturnal. However, we might expect feral cats to
underutilize these time periods if they trade-off foraging
beneﬁts against the higher risk of encountering dingoes.
In this study, we explored the effects of predator control
on interactions between dingoes and feral cats. We worked
on nine pairs of large properties across Australia, where
each pair consisted of a site that controlled dingoes (mainly
by 1080 baiting, but also by opportunistic shooting) and a
similar site in the same environment that did not. We exam-
ine (i) how predator control affected indices of abundance
and activity schedules of dingoes, (ii) whether predator con-
trol resulted in shifts in spatio-temporal activity by feral
cats and (iii) whether predator control and/or dingo
removal led to increased abundance of feral cats.
Materials and methods
STUDY AREA AND DATA COLLECTION
We surveyed dingoes and feral cats on eighteen properties spread
across North and Central Australia, spanning tropical to arid
climates, in habitats varying from open forest and woodlands to
native grasslands (Fig. 1). The properties were arranged in pairs,
©2012 The Authors. Journal of Applied Ecology ©2012 British Ecological Society, Journal of Applied Ecology,49, 1278–1286
Interactions between an apex and mesopredator 1279
each consisting of one property on which dingoes were controlled
and a matched property with no dingo control. Properties varied
in size from 7850 to 705 496 ha and ranged from being adjacent
to up to 153 km apart. Paired properties were selected to mini-
mize differences in habitat, climate and management. Most prop-
erties were working cattle stations, with three exceptions: the
Townsville Field Training Area (TFTA), owned by the Depart-
ment of Defence, and Mt Zero-Taravale, owned by the Austra-
lian Wildlife Conservancy (AWC) and managed for conservation,
both in the Einasleigh Uplands, and Piccaninny Plains on the
Cape York Peninsula (CYP), jointly owned by the AWC and
WildlifeLink. The TFTA was paired with Mt Zero-Taravale. Nei-
ther property controls dingoes, but we selectively surveyed sec-
tions of the TFTA along the property boundary with cattle
stations that do control dingoes to measure the effect of that
baiting and obtain a contrast with Mt Zero-Taravale. Piccaninny
Plains, which has a herd contained behind wire and is grazed at
low levels by feral cattle and horses outside these paddocks, was
paired with a cattle station with patchy grazing pressure and
broad areas of ungrazed woodland.
We surveyed dingoes and feral cats (and other wildlife) using
infrared remote movement-triggered cameras. We used either I-60
Game Spy (Moultrie; EBSCO Industries, Birmingham, AL, USA)
or DLC Covert II (DLC Trading Co., Lewisburg, KY, USA)
cameras. Cameras were distributed in pairs along transects, with
a spacing of 2–5 km to avoid correlation between pairs (Sargeant,
Johnson & Berg 1998). We used minor, unsealed vehicle tracks as
transects, and each camera pair consisted of one camera placed
1–5 m from the track and the other 50–200 m away, to allow for
ﬁne-scale differences in predator activity due to the presence of
the track. Cameras were baited with different combinations of
attractants such as chicken, the synthetic fermented egg spray
(Animal Control Technologies, Somerton, VIC,
Australia), Felid Attracting Phonics (Westcare Industries, Bassen-
dean, WA, Australia), bird seed or wild cat urine (Outfoxed Pest
Control, Ivanhoe, VIC, Australia). In some paired areas, we sur-
veyed for prey prior to predator surveys, using small mammal
bait (rolled oats, vanilla and peanut butter) and positioning cam-
eras 100 m off the road midway between camera pairs. We used
20–40 cameras on each property depending on property size and
available tracks and operated the cameras for 5–8 days. Surveys
were generally run consecutively or concurrently on the proper-
ties within each pair, except on two occasions where surveys were
up to 2 months apart but still within the same season. Camera
type, number and spacing, survey duration and lure combinations
were consistent within paired study areas. In the three most
northern areas (areas 7, 8 and 9; Fig. 1), surveys were repeated in
the early and late dry season, with a maximum of three surveys
on CYP over 3 years. For this analysis, repeat surveys in the
same area were pooled. Other pairs of properties were surveyed
once, between March and November. Cameras were programmed
to record 5-s videos at night and 20- or 5-s videos during the
day. Time and date were recorded with each video.
To distinguish repeat ‘captures’ of the same individual on the
same camera at night, we plotted histograms of times elapsed
between consecutive nightly records for each predator species.
These showed a distinct peak for elapsed times of <10 min, which
we assumed were repeats. To avoid these, we considered records
as being independent only when separated by 30 min or more,
unless individuals were distinguishable. We then calculated an
abundance index (AI) for each species at each property (individu-
als individuals per trap night) (Rovero & Marshall 2009), which
accounted for the number of cameras, survey length and camera
failure in each survey. Abundance indices derived from camera
trap rates have successfully detected reductions in feral cat abun-
dance (Bengsen, Butler & Masters 2011). Cumulative indices (such
as our AI) are better than proportional indices at detecting
changes in density, and the relationship between AI and true
abundance is likely to be linear (MacFarland & Van Deelen 2011).
Contrasts in abundance indices
To contrast differences in dingo and feral cat AI within paired
areas, we calculated ratios of the AI on properties without preda-
tor control over properties with control. The ratios were then
converted to natural logs so that their values were centred on
1: Murchison (MUR) 6: Longreach (LGR)
2: Finke (FIN) 7: Gulf Plain (GP)
3: Burt Plain (BP) 8: Einasleigh Uplands (EU)
4: Mitchell (MIT) 9: Cape York Peninsula
0 500 1000 2000 km
5: Channel Country (CC)
Tropic of Capricorn
Fig. 1. Paired survey areas across Austra-
lia. Each pair consists of one site that
controls dingoes and one without dingo
©2012 The Authors. Journal of Applied Ecology ©2012 British Ecological Society, Journal of Applied Ecology,49, 1278–1286
1280 L. A. Brook, C. N. Johnson & E. G. Ritchie
zero and symmetrical about zero. To allow use of zero measures
of the raw AI scores in the ratio calculation, we added 0003 to
each index record, a value smaller than the minimum nonzero
recorded index (0004).
Station-level activity rates
We examined the potential for local separation by comparing dingo
and feral cat trap rates at camera stations, using quantile regression
implemented in the QUANTREG package version 4.76 (Koenker
2011) in Rversion 2.14.1 (R Development Core Team 2011). We
calculated regressions for the 50th, 75th, 95th and 99th quantiles.
Least squares regression was unsuitable for several reasons: the
data distributions were triangular and not normally distributed,
and we were interested in a limiting effect of dingoes on feral cat
activity rather than the average correlation (Cade, Terrell &
Schroeder 1999). Standard errors were estimated using bootstrap-
ping. Camera stations with no predators recorded were excluded.
We surveyed over a wide longitudinal range and at different times
of year, introducing variation to the relationship between clock
time, day and night length and the timing of sunrise and sunset.
We therefore rescaled clock time for each survey to a standard
unit range (from 0 to 1) with equal spacing between sunset (at 05)
and sunrise (at 0 and 1). Temporal distributions were analysed in
the program ORIANA 4 (Kovach Computing Services, Wales, UK),
using the nonparametric Mardia–Watson–Wheeler test to detect
differences in the mean angle or angular variance of circular data
(Batschelet 1981). This test assumes no repeat data, so identical
records were altered by 1-s in the raw data. Each independent
(>30 min interval) capture of a species was considered one time
record, regardless of the number of individuals detected.
We analysed the temporal patterns of mammal prey recorded
incidentally in the camera surveys. Species were categorized
depending on the prey preferences of the two predators. The
large macropod category included wallabies (>7 kg) and kanga-
roos hunted only by dingoes. The small mammal category
(665 kg) included species such as rodents, possums and small
wallabies, which are known to be preyed upon by cats and also
potentially by dingoes.
We recorded 398 independent dingo records (334 time
records) and 211 independent cat records (210 time
records) over 5308 trap nights.
EFFECT OF CONTROL ON INDICES OF DINGO
Dingo abundance index (AI) varied widely between differ-
ent properties, ranging from zero at MIT to a maximum
of 027 at Piccaninny Plains on CYP (Fig. 2). Abundance
indices were generally lower on properties where dingoes
were controlled than on matched properties without con-
trol: the natural log of the ratio of dingo AIs in unbaited
vs. baited areas was larger than zero (one-sided one-
sample t-test: t=194, d.f. =8, P=0044), demonstrating
a signiﬁcant reduction attributable to control. However,
the effectiveness of control was variable (Fig. 2), and in
one case, dingo AI was actually higher on the property
with dingo control.
RELATIONSHIPS BETWEEN INDICES OF DINGO AND
FERAL CAT ABUNDANCE
We detected a shift in abundance indices of feral cats
inverse to dingoes within paired sites (R
1625, P=0005, Fig. 3). As the ratio of dingo AI in the
unbaited to baited sites increased, cats were more likely to
show the inverse trend, that is, to occur at a higher rate
on the baited site than on the unbaited site. The x-inter-
cept at 075, indicating a dingo AI ratio of 212, suggests
that once dingo indices were reduced by more than half,
feral cat indices tended to be higher on the baited prop-
erty. Feral cat abundance indices did not increase consis-
tently with dingo control when tested across all areas; the
natural log of the ratio of AIs in unbaited vs. baited areas
was not <0 (one-sided one-sample t-test: t=003, d.f. =8,
Trap rates at individual camera stations also suggested
a limiting effect of dingoes on feral cats. We found a
threshold relationship between the trap rates of dingoes
and feral cats (Fig. 4). Where dingoes were rare or not
CYP MUR BP FIN CC EU GP LGR MIT
Abundance index (individuals trap night–1)
Fig. 2. Abundance indices of dingoes and
feral cats derived from camera records in
each paired survey area. Black and light
grey bars represent dingoes in sites without
and with predator control, and dark grey
and white bars represent feral cats in sites
without and with predator control, respec-
©2012 The Authors. Journal of Applied Ecology ©2012 British Ecological Society, Journal of Applied Ecology,49, 1278–1286
Interactions between an apex and mesopredator 1281
recorded, feral cat trap rates ranged from 0125 to 1 cats
per night. As dingo trap rates increased, feral cat records
declined. No feral cats were recorded at stations where
dingoes were recorded at least once per night. All quantile
regression slopes were signiﬁcant.
Activity patterns of dingoes were signiﬁcantly different
on properties with and without dingo control (Mardia–
Watson–Wheeler test: W=2295, P<0001; Fig. 5a,b).
Crepuscular activity in the early evening was reduced in
areas with predator control, and the activity pattern
shifted towards a single peak before sunrise.
FERAL CAT BEHAVIOUR
Feral cat activity patterns differed on properties with
and without predator control (W=587, P=0053), and
were signiﬁcantly different from dingoes in areas both
with (W=2378, P<0001; Fig. 5a) and without preda-
tor control (W=2550, P<0001; Fig. 5b). In areas
where dingoes were baited, feral cat activity peaked in
the early evening, when nocturnal dingo activity was
There was a negative relationship in the proportion of
activity concentrated around dusk (that is, during the
hour before and 3 h after sunset) between the two species
across survey areas: feral cats were more likely to be
active at dusk when dingoes were less active at dusk
=694, P=0023; Fig. 6).
The shift in predator activity patterns under dingo
control was most evident in areas where baiting was
more effective in reducing dingo AI. In BP, EU, GP,
LGR and MIT, where the difference in dingo AI with
control was weaker, the contrasting activity patterns bet-
ween dingoes and feral cats disappeared in baited areas
(W=117, P=056, n=16 dingoes, 36 cats), while in
CYP, MUR, FIN and CC, sites with a larger contrast in
dingo AI, the inverse relationship in crepuscular activity
remained strong (W=2378, P<0001, n=69 dingoes,
PREY ACTIVITY PATTERNS
Activity patterns of dingoes were not signiﬁcantly different
from those of their large macropod prey (number of prey
records n=82) in unbaited areas (W=503, P=0081;
Fig. 7a), but the reduction in dusk activity in areas with
predator control shifted dingo activity away from the
crepuscular peaks of large mammals (n=157) (W=1307,
P=0001). In contrast, feral cat activity patterns were
closer to the nocturnal activity of small mammals (n=56)
in areas with dingo control (W=328, P=019; Fig. 7b)
than without (W=537, P=0068, small mammal n=
Our study conﬁrms that predator control can inﬂuence
not only abundance but also the behaviour of large preda-
tors. The effects of predator control on dingoes and their
behaviour may provide opportunities in the spatial and
temporal landscape for increased feral cat activity, by
reducing the encounter rate between predators and lower-
ing risk for feral cats (Laundre
´ndez & Altendorf
–2 –1 0 1 2
–2 –1 0 1 2
Ratio of dingo AI without vs. with dingo control
Ratio of cat AI without vs. with dingo control
Fig. 3. Contrast in predator abundance indices (AI) in paired
survey areas differing in dingo control (n=9). Positive values
represent higher abundance indices in the site without dingo con-
trol, and negative values represent higher abundance indices in
site with control. Hence, the bottom right quadrant represents
survey areas with more dingoes in the site without control and
more cats in the site with control.
Tau τSlope Standard error P
0·5 –0·13 0·02 < 0·001
0·75 –0·11 0·02 < 0·001
0·95 –0·19 0·02 < 0·001
0·99 –0·37 0·10 < 0·001
0·0 0·5 1·0 1·5 2·0
0·0 0·2 0·4 0·6 0·8 1·0
Feral cats night−1
Fig. 4. Predator trap rates at individual camera stations
(n=279 stations with at least one predator recorded). Regres-
sion lines, slope coefﬁcients and signiﬁcance values for quantiles
are shown (50th quantile: dashed; 75th: grey; 95th: dot-dashed;
1282 L. A. Brook, C. N. Johnson & E. G. Ritchie
PREDATOR CONTROL AND PREDATOR NUMBERS
Sites with dingo control had signiﬁcantly lower indices of
dingo abundance than sites without control, but not in all
cases. The exceptions may be due to (i) ineffective con-
trol, (ii) control effects ﬂowing into neighbouring proper-
ties or (iii) low detection rates. The effectiveness of dingo
control is dependent on numerous factors. Dingo density
may actually increase following baiting (Wallach et al.
2009), as young dingoes can colonize vacant territories at
high density if control is not coordinated over sufﬁciently
large areas (Allen & Gonzalez 1998). Poison baits may
not be as accessible to dingoes in complex habitats and
landscapes, and abundant prey can also reduce bait
uptake (Allen & Sparkes 2001). Dingo density on unbait-
ed sites may be reduced if dingoes visit adjacent baited
properties and are killed. Dingoes probably traversed
property boundaries despite our large survey areas, as
dingo home ranges can be extensive (up to 22, 622 ha in
south-east Australia), and they can also make long-
distance forays up to 60 km (Claridge et al. 2009). That
detectability was imperfect was evident in one area
(MIT), where dingo tracks were observed on roads, but
no dingoes were recorded on camera (A. McNab, pers.
Shifts in indices of dingo abundance due to control
were associated with inverse shifts in feral cat abun-
dance, suggesting a negative relationship between abun-
dances of the two species. Although this shift was
signiﬁcant when comparing paired sites, we did not ﬁnd
an overall increase in feral cat indices in direct response
to predator control. However, we would not expect feral
cats to respond to predator control per se, but to conse-
quent changes in the dingo population, which were vari-
able. In some areas, both feral cat and dingo abundance
indices were higher on unbaited properties, suggesting
competition may have been minimized by prey densities
that could sustain both predators or by habitat features.
Habitat complexity can mediate interference competition
between predators (Janssen et al. 2007) by reducing the
encounter rate. Additionally, feral cats can climb trees to
avoid dingoes. Hence, in areas with considerable tree
cover, such as CYP, feral cats may be able to occur at
relatively high densities due to the protection provided
by complex habitats (Lima & Dill 1990; Ritchie & Johnson
AVOIDANCE IN TIME
Temporal activity of dingoes in unbaited areas was similar
to previous observations, with bimodal crepuscular peaks,
frequent activity during the night and sporadic activity
during the day (Harden 1985; Thomson 1992; Robley
et al. 2010). However, in areas where dingoes were con-
trolled, activity at dusk was reduced and shifted to a peak
before sunrise. This could allow dingoes to avoid poten-
Proportion of activity records
Dingo control No dingo control
Fig. 5. Proportion of activity records (a) with and (b) without dingo control. Time has been scaled to a circular distribution with equal
distance between sunset and sunrise. In 5a and b, black bars represent dingoes with (n=85) and without (n=249) control, and light
grey bars represent cats with (n=81) and without (n=129) control.
0·0 0·2 0·4 0·6 0·8 1·0
Fig. 6. Proportion of activity records in the dusk/early evening
(1 h pre-sunset to 3 h post-sunset) (n=13 sites with at least one
dingo and one cat record). Data are square-root-transformed.
Interactions between an apex and mesopredator 1283
tially lethal encounters with people, given that although
poison baiting is the primary method of lethal control,
landholders also opportunistically shoot dingoes. Canids
may trade-off crepuscular or diurnal hunting activity to
minimize the risk of encountering people (Theuerkauf
2009), particularly when faced with persecution (Kitchen,
Gese & Schauster 2000).
Feral cat activity was inversely related to differences in
dingo activity due to control of dingoes. This relationship
was evident in areas where dingo control was more effec-
tive, and was not apparent in areas where dingo control
had less effect, providing further support for the inference
that feral cats were responding to reduced dingo presence.
Feral cats may inherently have a bimodal circadian
rhythm (Randall et al. 1987), but they can exhibit cre-
puscular and nocturnal patterns (Jones & Coman 1982;
Burrows et al. 2003) or irregular cathemeral activity (Mol-
sher et al. 2005; Moseby, Stott & Crisp 2009), to adapt to
different needs such as predator avoidance (Langham
Temporal partitioning is probably due to interference
rather than exploitation competition, as it allows compet-
itors to reduce aggressive encounters (Carothers & Jaksic
1984). Harrington et al. (2009) found the invasive Ameri-
can mink Neovison vison exhibited a diel shift from noc-
turnal to diurnal activity, without reducing abundance,
following recolonization by native competitors in the
UK. Apart from a few such examples, competitors are
unlikely to drastically shift activity from their circadian
rhythms, which are entrained to environmental cues
(Kronfeld-Schor & Dayan 2003; but see Gutman &
Dayan 2005). Competitors that evolve under similar eco-
logical conditions may develop similar activity schedules,
a further limitation to diel-scale partitioning (Kronfeld-
Schor & Dayan 2003). Almost all small mammals in
Australia, a substantial prey resource for feral cats, are
crepuscular or nocturnal (Van Dyck & Strahan 2008);
hence, the activity shifts we observed in feral cats, which
still provide some prey overlap, may be a more likely
response to interference competition than a complete diel
AVOIDANCE IN SPACE
Species exposed to predation (or interference competition)
also avoid high-risk areas in space, forgoing potential for-
aging gains from using those areas (Brown, Laundre
Gurung 1999; Laundre
´ndez & Altendorf 2001;
Wirsing et al. 2008). For feral cats, hotspots of dingo activ-
ity may carry a greater risk of potentially lethal encounters.
Our results suggest that space use by dingoes restricts feral
cats at a patch level, although factors such as habitat and
prey availability will also inﬂuence their abundance. Pat-
terns of mesopredators avoiding dingoes have been
observed in other studies. In arid Australia, dingoes are
common around water points, and feral cats are rare, in
areas without predator control. However, where dingoes
are poisoned, feral cats use areas near water more often
(Brawata & Neeman 2011). Studies analysing ﬁeld data
(Johnson & VanDerWal 2009) and historical bounty data
(Letnic et al. 2011) both found signiﬁcant effects of dingo
activity indices on the upper range of fox indices, suggest-
ing dingoes can limit fox activity.
HOW COULD BEHAVIOURAL SHIFTS AFFECT PREY
Predators are expected to optimize their activity by
matching it to that of their prey. The reduced activity of
dingoes around dusk decoupled their activity patterns
from those of macropod prey. An indirect consequence of
this behavioural shift may be reduced hunting pressure
from dingoes and the demographic release of herbivores
such as kangaroos or rabbits. Herbivores trade-off opti-
mal foraging conditions with the perceived threat associ-
ated with obtaining those resources (Lima & Dill 1990).
Herbivores can more effectively exploit preferred foraging
areas if predator presence is reduced, potentially leading
to population growth and impacts on vegetation.
Reduced dingo activity at dusk may also provide a
window for feral cats to hunt with less interference.
Mesopredators released from top–down control can exert
more predation pressure on prey than apex predators
Proportion of activity records
Fig. 7. Proportion of (a) dingo (dark grey) and large macropod (light grey) activity records in areas without predator control and (b)
feral cat (white) and small mammal (black) activity records in areas with predator control.
1284 L. A. Brook, C. N. Johnson & E. G. Ritchie
(Prugh et al. 2009). They tend to be more effective hunt-
ers, allowing them to coexist with apex predators (Polis &
Holt 1992). Many Australian animals are active at dusk,
and some may be particularly vulnerable to predation by
feral cats at this time: reptiles become slower as tempera-
ture declines (Bennett 1983), and mammals must forage
or hunt to satisfy energy demands and are likely to show
a surge of activity early in the night. In Northern Austra-
lia where native mammals are in rapid decline (Woinarski
et al. 2011), increased hunting success by feral cats in the
absence of dingoes could accelerate the extinction trajec-
tories of these vulnerable species.
Our study shows that mesopredators can coexist with
apex predators by concentrating their use of space and
time to avoid encounters. Control measures not only
reduce the abundance of apex predators, but can lead to
behavioural changes that may relax top–down pressure on
mesopredators, potentially allowing them to shift to more
prey-rich areas or time periods, facilitating an increase in
mesopredator abundance and predation pressure on prey.
If predator control is used to reduce apex predator abun-
dance, but maintain a population to retain ecological
functions such as suppression of herbivores and mesopre-
´et al. 2003), it is important to consider the
effects of control on behaviour as well as abundance
(Ritchie et al. 2012). Hence, in areas managed primarily
for conservation, predator control should be reconsidered
in the light of potential risks to wildlife. The presence of
dingoes may restrict feral cats to suboptimal niches and
thus provide refuge from cat predation for prey.
We thank owners and managers for allowing us to survey their properties.
We particularly thank the Australian Wildlife Conservancy and Wildlife-
Link for surveys at Piccaninny Plains and Mt Zero-Taravale and the
Department of Defence for permission to survey the Townsville Field
Training Area. Laura Mitchell and Angus McNab coordinated much of
the ﬁeldwork, and we were assisted by many valuable volunteers. Jeremy
VanDerWal and Dale Nimmo provided advice with quantile regression.
This study was funded by an Australian Research Council Discovery grant
(DP0877398) and was permitted by the James Cook University Animal
Ethics Committee and Department of Environment and Resource Man-
agement (Scientiﬁc Purposes Permit: WITK06493009).
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Received 20 April 2012; accepted 23 August 2012
Handling Editor: Chris Dickman
1286 L. A. Brook, C. N. Johnson & E. G. Ritchie