ArticlePDF Available

Wait before running for your life: Defensive tactics of spiny mice (Acomys cahirinus) in evading barn owl (Tyto alba) attack

Authors:

Abstract and Figures

Raptor–prey encounters were studied to evaluate the strategies and success rate of both predator attack and prey defense. We compared the success of barn owls in catching stationary simulated prey (food item) with that of moving prey (food item that was pulled in various directions). We also tracked real encounters between barn owls and spiny mice in a captive environment. It was found that owls had higher success in attacking stationary prey and that they seemed to attack the prey as soon as it became motionless. When attacked, only a few spiny mice remained immobile (freeze response) whereas most fled and usually avoided capture by the owls. It was also found that spiny mice displayed a preference to escape in those directions in which owls had demonstrated a lower success in catching the simulated prey. Escape initiation dichotomized to a short or long (but rarely intermediate) distance between the spiny mouse and the owl with more successful avoidance at short-distance (last-moment) escapes. The best predictor of escape success was the velocity of the spiny mouse, and the second best predictor was its flight initiation distance (FID). We present an update for Ydenberg and Dill’s model for optimal FID in close encounters, suggesting that fleeing at the last moment is advantageous. However, a last-moment attempt to escape is also more risky with a split second differing between life and death, and is therefore appropriate mainly for agile prey under close-distance attack.
Content may be subject to copyright.
ORIGINAL PAPER
Wait before running for your life: defensive tactics
of spiny mice (Acomys cahirinus) in evading barn owl
(Tyto alba) attack
Amiyaal Ilany &David Eilam
Received: 27 February 2007 /Revised: 22 October 2007 / Accepted: 24 October 2007 / Published online: 19 December 2007
#Springer-Verlag 2007
Abstract Raptorprey encounters were studied to evaluate
the strategies and success rate of both predator attack and
prey defense. We compared the success of barn owls in
catching stationary simulated prey (food item) with that of
moving prey (food item that was pulled in various
directions). We also tracked real encounters between barn
owls and spiny mice in a captive environment. It was found
that owls had higher success in attacking stationary prey
and that they seemed to attack the prey as soon as it became
motionless. When attacked, only a few spiny mice
remained immobile (freeze response) whereas most fled
and usually avoided capture by the owls. It was also found
that spiny mice displayed a preference to escape in those
directions in which owls had demonstrated a lower success
in catching the simulated prey. Escape initiation dichoto-
mized to a short or long (but rarely intermediate) distance
between the spiny mouse and the owl with more successful
avoidance at short-distance (last-moment) escapes. The best
predictor of escape success was the velocity of the spiny
mouse, and the second best predictor was its flight initiation
distance (FID). We present an update for Ydenberg and
Dills model for optimal FID in close encounters, suggest-
ing that fleeing at the last moment is advantageous.
However, a last-moment attempt to escape is also more
risky with a split second differing between life and death,
and is therefore appropriate mainly for agile prey under
close-distance attack.
Keywords Flight initiation distance (FID) .Anti-predator
behavior .Predatorprey interactions .Predation risk
Introduction
On an evolutionary time scale, predatorprey encounters
are an adaptive arms-race (Lima and Dill 1990) with each
opponent attempting to optimize its skills, whether for
catching the prey or for evading the predator. On a real-
time scale, predatorprey encounter is a dynamic conflict
in which a split-second decision can make a life or death
difference. Aerial raptors utilize various hunting strategies
(Cresswell 1996), ranging from continuous active pursuit
to perch and pounce ambush. Nocturnal owls perch
motionless, merging into the background with the camou-
flage colors of their feathers, waiting to pounce; while in
active hunt on the wing, they fly silently by virtue of the
unique structure of their wings and feathers, which
suppress the sound of airflow over the wings (Graham
1934;ThorpeandGriffin1962). These offensive strate-
gies are considered to be extremely efficient; for example,
the tawny owl (Strix aluco) is a primary predator, taking
810 woodland mice per night (King 1985). Indeed, owl
predation poses a significant threat for small mammals,
especially rodents that constitute a major food source for
many owl species (Mikkola 1983;MartinandBusby
1990;Selaas1993;Tome1994; Jedrzejewski et al. 1993;
Jedrzejewski et al. 1996). Despite the numerous studies on
owl predation, there is ambiguity regarding their rate of
success and their offensive strategies. For example, it was
suggested that once owls have initiated the final attack
sequence, their success rate rarely falls below 90% (Curio
1976). This raises the question of what is the final attack
sequence. Furthermore, what were the preceding phases
Behav Ecol Sociobiol (2008) 62:923933
DOI 10.1007/s00265-007-0516-x
DO00516; No of Pages
Communicated by E. Korpimäkki
A. Ilany :D. Eilam (*)
Department of Zoology, Tel-Aviv University,
Ramat-Aviv 69978, Israel
e-mail: eilam@post.tau.ac.il
in the attack sequence, was the attack on moving or
stationary prey, etc.?
Prey species are capable of recognizing potential preda-
tors and of producing a defensive strategy that is appropriate
to the hunting strategy of that particular predator. Modulated
by the strong selective pressure of predation, defensive
behaviors converge to three categories that cross the entire
animal kingdom: freezing, fleeing, and fighting (defensive
attack). In freezing, the prey remains immobile to evade the
attention of the predator (Desy et al. 1990; Hendrie and
Weiss 1994; Hendrie et al. 1998; Ronkainen and Ylonen
1994). In fleeing, the prey escapes to remove itself from the
vicinity of the predator (Bolles 1970; Driver and Humphries
1988; King 1985). In fighting (or defensive attack), the prey
heads toward the predator to dissuade it and prevent
predation. Defensive fighting occurs only when the prey
has no possibility of freezing or fleeing and must face the
predator. Freezing and fleeing have been described in a
variety of prey species, from hermit crab (Scarratt and Godin
1992)todeer(Smith1991). For example, the white-tailed
deer (Odocoileus virginianus) typically flees flagging its tail
(Smith 1991)whereasthejerboa(Jaculus jaculus, a small
bipedal rodent) squats motionless, hiding its white ventral fur
and exposing its yellowish dorsal fur to match the desert
sand (Hendrie et al. 1998). Freezing or fleeing can be also
observed in the same individual animal under different
circumstances. For example, wood mice (Apodemous mys-
tacinus) either freeze or leap when exposed to stoats
(Mustela ermina)(Erlingeetal.1974) but scamper away
when exposed to other predators (Bolles 1970;King1985).
The response also varies with age because young white-
tailed deer tend to freeze when exposed to a predatory risk,
whereas adults typically flee (Smith 1991). Finally, freezing
and fleeing may occur in succession in the same individual.
For example, robins (Erithacus rubecula) reacted to an
approaching predator model by taking off toward the
opposite side of the cage where they hovered against the
wall for a short while before flying down to the floor and
remaining motionless (Lind et al. 1999). These examples
demonstrate that freezing and fleeing are general forms of
defensive behavior across species and individuals. In discus-
sing the question of when to freeze or flee (Eilam 2005), it
was suggested that freezing is efficient only if employed
before the prey is spotted by the predator, otherwise the prey
becomes a stationary target, which is easy to catch. Thus, a
clumsy prey that does not have access to a shelter would do
better to alternate between freezing and fleeing rather than
just freezing. In fleeing, the prey can move either directly
away and maximize its distance from the predator, move
toward the predator to confine it to a single clash point, or
dodge sideways to evade the attack (Eilam 2005). For
example, about 50% of sedge warblers (Acrocephalus
schoenobaenus) responded to an attackingcardboard
model of a merlin by darting sideways at an angle of almost
90° from the model (Kullberg et al. 2000). Prey can also run
in a straight path that is efficient against slow or distant
predators, or in a zigzag path that is efficient when a raptor is
close or fast (Furuichi 2002). Each one of these tactics
challenges the attacking raptor and its maneuvering abilities.
The distance between predator and prey at the moment the
prey initiates flight (flight initiation distanceFID) has
attracted attention in many studies. Ydenberg and Dill
(1986) presented a model based on economic considerations
in which FID for the prey should be at the point where the
cost of staying becomes higher than the cost of fleeing. For
example, prey should flee when the risk from an approaching
predator is higher than the revenue from a food patch. This
hypothetical model has been supported by numerous studies.
For example, woodchucks (Marmota monax) fled late
(shorter FID) when attacked closer to their burrows, reflecting
the lower risk (Bonenfant and Kramer 1996). Similarly, FID
of Bonaire whiptail lizards (Cnemidophorus murinus)was
longer when predators approached faster, heading directly
towards them; FID was shorter when food was nearby,
reflecting a higher cost of fleeing (Cooper et al. 2003). Male
broad-headed skinks (Eumeces laticeps) ran away later
(shorter FID) while guarding their females compared with
males without females (Cooper 1999). Other studies have
linked FID with different parameters, not necessarily related
to an approaching predator: 64 out of 68 species of Australian
birds fled earlier when the initial distance to the predator was
longer (Blumstein 2003). Other Australian birds have
species-typical FID (Blumstein et al. 2003). Finally, marsu-
pials in islands with no predators had shorter FIDs than their
conspecifics in the continent (Blumstein 2002).
In the present study of raptorprey encounters, we compared
the success of barn owls in catching stationary simulated prey
with that of catching simulated prey that moved in various
directions, and we tracked real encounters between barn owls
and spiny mice in a captive environment. Specifically, we
tested: (1) if owls have a preference to attack stationary or
moving prey, and which gives them a higher success rate; (2)
what are the characteristics of owl attack in terms of timing,
velocity, and maneuverability; (3) what is the most effective
FID in spiny mice, and how is it correlated with successful
escape; and (4) which parameters of the encounters between
barn owls and spiny mice best predict a successful escape.
Materials and methods
Study animals
Barn owl (Tyto alba) An efficient raptor that feeds mainly
on rodents. It uses sounds generated by prey movement to
locate its prey, aided by its sharp night-vision (Payne 1971;
924 Behav Ecol Sociobiol (2008) 62:923933
Ilany and Eilam, personal observation). Barn owls then
swoop down on the prey from a perch or on the wing,
catching it with their spiked talons, and killing it immedi-
ately. Eight barn owls that hatched at the research zoo of
Tel-Aviv University were hand-reared to adulthood (618
months old) and used in the present study. Each barn owl
was kept individually in a 80 × 60 × 60 cm cage. These cages
were placed in a large aviary (6 × 6 × 4 m) where each owl
was released separately once a week for 24 h. Like the
other zoo predators, owls were fed with freshly killed (and
from time to time also live) chicks and mice (one mouse per
night per owl) obtained from surplus stock from the animal
quarters and from chicken incubators. Thus, these captive
barn owls were accustomed to preying on live rodents. The
owls were habituated to the presence of humans by being
held in hand for 15 min daily.
Common spiny mouse (Acomys cahirinus) Weighs 3844 g
and is 11 cm long, plus a 10-cm tail. It is an agile rodent,
common on rocky mountains where it shelters in crevices
(Shkolnik 1971; Shargal et al. 2000). The high fecundity of
spiny mice (early maturation, short weaning period,
frequent all-year-round breeding in captivity) and the
extensive use of this species in other research projects had
resulted in a surplus of these rodents at the Tel-Aviv
University research zoo, which we used in the present
study. Several weeks before testing, spiny mice were
housed in groups of 510 in metal cages measuring 40 ×
70×25 cm located outdoors in the zoo yard under natural
(uncontrolled) temperature and light conditions. Overturned
ceramic pots and wooden boxes were placed in each cage to
provide shelter. Seeds and diced fresh vegetables were
provided ad lib.
Apparatus
Observations took place in a 6×4.5 × 3-m aviary. A wooden
box (0.3×0.4× 0.5 m) was hung on one of the walls. The
box had two openings: one to the other side of the aviary
wall, through which an owl could be placed in the box with
no need for the experimenter to enter the aviary area; and
another opening into the aviary. The door to the aviary
could be opened silently from the outside by means of a
rope. A wooden pole was installed inside the wooden box,
10 cm above the floor where the owl could perch. From this
point, the owl could see most of the aviary area, except for
the zone just below the wooden box. For experiment 1 (see
below), a pulley block was mounted outside the aviary, to
which a 1.5-kg weight was connected. The weight was tied
to a transparent fishing line hung from a hook above the
aviary center. From this hook, the string could be tied to a
prey item; and by letting the weight fall to the ground, it
would pull the prey in the desired direction. An infrared-
sensitive video camera (Ikegami ICD47E) that allows vivid
shots in complete darkness was installed in the ceiling of
the aviary, visually encompassing the whole area of the
aviary floor. An IR light (Tracksys, IR LED Illuminator,
UK) that emits light in a range invisible to owls and spiny
mice followed the direction of the camera. The camera was
connected to another video camera (Sony DCR-HC85E)
used for recording on DV cassettes.
Procedures
Experiment 1: timing, velocity, and maneuverability in owl
attack
Before testing, the eight owls were trained for several
weeks to receive their food in the center of the aviary, and
only then underwent the present study. Each of the owls
was placed in the wooden box for 2 min of habituation
before the experimenter pulled the string that opened the
box to uncover the food item. As soon as the owl took-off
from the perch to swoop down on the food item, which was
either left stationary or pulled away via the transparent line
(by letting the weight fall to the ground) in a direction that
followed a random sequence of numbers between 0 and 4
as generated by Microsoft Excel with each number in the
sequence assigned to one pulling direction (four pulling
directions and one for stationary food item). Behavior was
videotaped, commencing at exposure of the food item and
continuing until a successful catch was made. All owls
were tested 23 days/week with all testing sessions taking
place in the afternoon, using the owls in a random order in
each session. There was only one trial per day for each owl.
If an owl failed to swoop within 15 min, it was tested again
only on the next test day. Accordingly, we obtained 59
trials, 16 for stationary food item, 19 where the food item
was dragged toward the owl, 13 where the food item was
dragged sideways, and 11 where it was dragged forward
(directly away from the owl).
Experiment 2: do the owls attack stationary or moving prey;
which gives them a higher success rate; what is the most
effective FID in spiny mice, and how is it correlated
with successful escape; and which parameters best predict
asuccessfulescape
Tests (one per owl per night) took place between 6.00 P.M.
and 9 P.M., at a light level of 0.1 lux, coming from street
lights near the research zoosimilar to light level on full
moon nights. At the beginning of each test period, an
experimenter switched on the equipment, placed an owl in
the box while it was closed to the aviary, and released a
spiny mouse into the enclosure. After 2 min of acclimation,
Behav Ecol Sociobiol (2008) 62:923933 925
the box door was opened, allowing the owl to see into the
aviary area, and to launch an attack. The experimenter
waited either until attack was launched or until 15 min had
passed if the owl did not launch an attack, and then stopped
the experiment and returned the animals to their cages. In
total, we ran 54 trials.
Data acquisition
Tapes were digitized by connecting the Sony camera to a
computer using a firewire cable. Microsoft Windows Movie
Maker 2.0 created a .wmv file for each trial, saved in a 576×
720 resolution, 25 frames per second. This software was also
used for editing the films, cutting unneeded parts. We then
processed the video clips using Adobe After Effects 6.0,using
the Vector Paint function to mark the owl and the spiny
mouse in each frame. The owl was marked by a 10-pixel
diameter circle and the spiny mouse by a 5-pixel diameter
circle. These markings created a contrast against the white
background, needed by the tracking software. Markings were
added to each video clip in the part containing the attack. The
.avi files created by this software were converted to .mpg
files needed by the tracking software using Mainconcept
MPEG Encoder.Noldus Ethovision 3.1 was used to get the
location of the owl and spiny mouse in every frame of the
movie. This software produced the coordinates of the
animals, calculated the movement velocities and distances,
and created a graphic presentation of the routes of each
animal (Fig. 1). To measure the angles of escape relative to
owl direction, we used the ImageJ software.
Behavioral analysis
A moment-by-moment analysis was carried out, starting
with the initiation of the attack by the owl and ending either
with the successful capture of the spiny mouse, with the
owl landing on the aviary floor without catching the prey,
or with the return of the owl to its perch without landing. In
this analysis, twelve parameters were scored:
1. Location of spiny mouse at attack initiation:The
coordinates of the spiny mouses location at the
moment when the owl initiated its attack, leaving its
perch.
2. Attack timing: Whether the owl attacked the spiny
mouse when it was mobile or stationary.
Fig. 1 Data acquisition in Ethovision 3.1 from a video clip with the
owl and the spiny mouse marked with a large and a small black circle,
respectively. The bottom left panel provides the Xand Ycoordinates of
the animals for every frame. The top left panel provides the details of
the measured clip section, and the right bottom panel controls the
video display
926 Behav Ecol Sociobiol (2008) 62:923933
3. Response of the rodent to capture attempt: For each
capture attempt, the response of the rodent was scored
as moveor no move.
4. Owl speed: The barn owl average speed for the whole
attack, from leaving the perch until landing.
5. Attack duration: The duration of the barn owl attack,
from leaving the perch until landing.
6. Location of owl landing: The coordinates of the barn
owls location at the moment of landing on the aviary
floor, whether it caught the spiny mouse or not.
7. Distance between owl landing location and initial
spiny mouse position: The distance between the landing
position of the owl and the position of the spiny mouse
when the attack began. Because the owl was initially
aiming at the initial spiny mouse position but had to
make adjustments to its path if the spiny mouse ran
away, this parameter measures the magnitude of this
adjustment.
8. Distance between owl landing location and spiny
mouse location: The distance between the landing
position of the owl and the position of the spiny mouse
when the owl landed. If the owl failed to catch the
spiny mouse, this distance depicts the magnitude of the
failure.
9. Catch: This parameter describes whether the barn owl
caught the spiny mouse or failed in its attack.
10. FID: The distance between the owl and the spiny
mouse at the moment the spiny mouse began to flee.
11. Direction of flee: The angle between the owls
trajectory to the spiny mouse and the direction in
which the spiny mouse ran, as measured when the
flight began. If the spiny mouse changed its direction
substantially during the flight (>20°), this angle was
measured again.
12. Speed of flee: The average speed of the spiny mouse
during its flight, from its beginning to its end when
the spiny mouse stopped moving.
Statistics
Differences between different groups of spiny mice (i.e., those
that escaped early and those that escaped late) were tested
using t-test, unless noted otherwise. Transition of spiny mice
between mobility and immobility when attacked was tested
using McNemars test. Differences between expected vs
measured results were examined using χ
2
tests. Differences
between individual barn owl speeds were tested using one-
way ANOVA. A logistic regression was used to examine
which variables may best predict the success of an owl
attack. The compared variables were the speed of the fleeing
spiny mouse, owl speed, FID, escape direction, distance
between initial spiny mouse position and location of owl
landing, locomoting or stationary spiny mouse, and identity
of the individual owl.
Results
Experiment 1: owl success according to movement
direction of a simulated prey
Success rate in owl attack The owls had full success in
catching stationary food items (simulated prey) that were
not pulled away (16 successful catches in 16 trails; 2 per
owl). The owlssuccess in catching food items (simulated
prey) that were pulled by a string varied with the direction
of pulling. In 19 trials with a simulated prey dragged
toward the owls, there were 7 catches (37% success); in 13
trials with sideways drag direction, there were 3 catches
(23% success); and in 11 trials with drag direction forward
(directly away from the owl), there were 6 successful
catches (55% success). Owl speed did not differ between
success and failure (M=4.71, SD = 0.66 and M= 4.57, SD =
1.13 ms/s, respectively; t
41
=0.51; p=0.3); nor did the speed
of the pulled food (M=1.53, SD=0.43 and M= 1.69, SD =
0.35 m/s; t
41
=1.3; p=0.11). This latter speed matched that
of live rodents escaping from an owl, as detailed below in
Experiment 2. In all, owl success was highest when
simulated prey was dragged straight ahead of it and lowest
when it was dragged sideways.
Adjustments in flight path When attacking the simulated
prey, the owls displayed three patterns of response: (1)
giving up and turning on wing to return to the roost (23%
of trials; all counted as failures); (2) landing on the spot
where the food item had been located before pulling (7% of
trials; all counted as failures); and (3) adjusting their flight
path in an attempt to catch the moving simulated prey (70%
of trials; 53% of which were successful). When the food
item was pulled forward away from the owl, the owl
typically continued to fly forward in chase (Fig. 2a). When
the food item was pulled toward the owl, the adjustments
required in the flight path were relatively minor, generally
taking the form of a shortcut in swooping down toward the
approaching simulated prey (Fig. 2b). In sideways pulling,
the owl made a diagonal correction (Fig. 2c and d). The
following results are shown only for sideways and forward
trials where major adjustments were required because the
flight paths had to be longer (no shortcut possible). Path
adjustment significantly differed (t
22
=4.8; p<0.0001)
between successful attacks (n=9; forward and sideways
trials) where correction was of M=1.82, SD=0.41 m and
failed attacks (n=15) where correction was of M=0.90,
SD=0.48 m. Thus, a larger adjustment in flight path
Behav Ecol Sociobiol (2008) 62:923933 927
characterized successful attacks, whereas failed attacks
involved a smaller adjustment.
Experiment 2: encounters between barn owl and spiny
mouse
Attack on moving vs stationary spiny mouse
When deciding to launch an attack, the owls could choose
whether to attack a stationary or a moving spiny mouse. In
35 out of 54 observed attacks (64.8%), the spiny mouse
was stationary at the moment of the owls take-off for
attack, while the remaining 19 attacks (35.2%) were on a
moving spiny mouse. This preference to attack stationary
prey was significant (χ2
1¼4:74; p=0.029). Notably, 12 out
of the 35 attacks on stationary spiny mice occurred
immediately (<1 s) after the prey had ceased to locomote.
Of the 19 attacks on locomoting spiny mice, 7 (37%) were
heading away from the owl, 7 (37%) were locomoting
sideways in relation to the owl, and 5 (26%) were
locomoting toward the owl; all directions were measured
at the moment the owl launched its attack (see the
Materials and methodssection).
Duration and flight speed in attacking spiny mice
Duration between an owls take-off for attack and its
landing either on the prey or on the cage floor (when
missing the prey) was M=1.13, SD = 0.60 s. Flight speed
during attacks was M=4.49, SD = 1.03 m/s. There was no
significant difference between attack speeds of the eight
owls (one-way ANOVA; F
7,45
=1.2; p=0.31).
Adjustments in attacking path
The distance between the owls landing point and the position
of the spiny mouse at the moment of owl take-off describes
the actual adjustment in attack path. This distance was 0.57±
0.61 m for successful attacks and 0.7 0.95 m for failed
attacks. The distance between the owls landing point and the
position of the spiny mouse at the moment of landing
assesses the magnitude of failure: in successful attacks it was
zero, while in failed attacks it was 0.58±0.47 m.
Rate of success in owl attack on fleeing vs stationary spiny
mice
Of the 35 attacks that the owls launched on stationary spiny
mice, 19 spiny mice responded by fleeing, whereas the
other 16 remained stationary. In addition to the 35 attacks
on stationary spiny mice, the owls also launched 19 attacks
on moving spiny mice. Of these, one responded by
freezing. Thus, after the initiation of the attack, 17 spiny
mice were stationary whereas 37 were moving. Altogether,
spiny mice fled from an attacking owl and did not freeze
(McNemar test; χ
2
=24.1; p<0.001). As shown in Table 1,
owls had 100% success in catching stationary spiny mice,
but their success rate substantially declined to 22% in
attacks on fleeing spiny mice. Altogether, their rate of
success was 46% of their attacks on fleeing and stationary
spiny mice. The rodentsdecision whether to flee or not
together with the owlsabsolute success in catching non-
fleeing spiny mice indicates that the owlstotal rate of
success was primarily affected by the defensive response of
Table 1 Number of attacks and rate of success in attacking fleeing
and motionless spiny mice for each of the tested owls (rows 18) and
for all owls (bottom row)
Owl Total attacks
(% of success)
Attacks on
motionless prey
(100% success)
Attacks on
fleeing prey
(% of success)
1 3 (0) 0 3 (0)
2 4 (25) 1 3 (0)
3 7 (29) 2 5 (0)
4 10 (40) 3 7 (14)
5 8 (50) 3 5 20)
6 7 (57) 2 5 (40)
7 9 (67) 4 5 (40)
8 6 (67) 2 4 (50)
All owls 54 (46) 17 (100) 37 (22)
1
1
1
1
2
2
2
2
a
c
b
d
Fig. 2 Exemplary flight paths of owls in missed attacks in the
simulated prey experiment. In all four panels, the direction of owl
flight is from right to left (). Point 1 indicates the location of the
food item when the owl launched its attack; point 2 indicates the
location of the food item at owls touch-down. When food item was
pulled forward (a) the owl continued flying toward the prey, but
missed and landed before reaching it. In backward pulling (b), the owl
landed while the prey was behind it. In pulling to the left (c) and right
of the owl (d), the owl took a curved path toward the prey
928 Behav Ecol Sociobiol (2008) 62:923933
the spiny mice. Indeed, owl attack speed in successful
attacks (4.72±1.13 m/s) was not significantly higher than in
failed attacks (4.30± 0.90 m/s; t
44
=1.46; p=0.15).
Owl attack: timing of escape response in spiny mice
Figure 3a depicts the distribution of FID, which is the
distance between the attacking owl and the spiny mouse at
the moment that the spiny mouse begins to flee. As shown,
initiating escape occurred mainly at short or long FID, and
only 4 out of 37 attempted escapes occurred at the mid-
range FID. Twelve spiny mice fled when the owl was still
relatively distant; in fact, they seemed to flee as soon as the
owl launched its attack. In contrast, 21 spiny mice waited
for the owl and fled at the last moment when the owl was in
their immediate vicinity (less than 2 m). FID was not an
arbitrary outcome of the distance between the owl and
spiny mouse at the beginning of the attack. This is shown in
Fig. 3b in which the FID is shown in relation to the initial
distance between owl and spiny mouse. As shown, FIDs
dichotomized into two types: longer than 3 m and shorter
than 3 m. Correlating each group with the initial distance
between the owl and spiny mouse revealed that FIDs longer
than 3 m were in significant correlation with the initial
distance (r
2
=0.864; p=0.0001; n=10). In contrast, FIDs
shorter than 3 m were independent of the initial distance, as
illustrated by the horizontal correlation line (r
2
<0.001; p=
0.96; n=20). The latter result indicates that fleeing in the
last moment, when the owl was nearby, was not merely the
result of being attacked from a short initial distance. In
other words, the spiny mouse was waiting for the owl to get
closer and fled only at the last moment. In contrast, spiny
mice that were attacked from a relatively long initial
distance did not wait but fled immediately after launch of
attack.
Escape direction in relation to the approaching owl
Spinymiceweremorelikelytofleetoasideways
direction. Although four fled toward the attacking owl
at a range of ±45° to the approaching owl and another
four fled at a range of ±45° away from the approaching
owl, 20 fled sideways at an angle of 45° to 135° in
relation to the direction of the approaching owl. This
preference to flee sideways was significant (χ2
2¼7:07;
p=0.03). Another group of eight fleeing spiny mice were
not included in this count because they altered direction
during fleeing.
What are the parameters that may predict a successful owl
attack?
Logistic regression was used to examine which variables
may best predict the success of an owl attack revealing that
spiny mouse speed was the best predictor of owl success
(95% fit): the lower the mouses speed, the higher the owls
success (odds=0.978; 95%CI between 0.967 and 0.99; p<
0.001). Specifically, these results imply that with each spiny
mouse speed increase of 1 cm/s, the probability of being
caught declines to 0.978 of probability at the former speed.
The second best predictor was FID (odds=1.006; 95%CI
between 1.001 and 1.012; p=0.018): the lower the FID, the
lower the owls success. The other parameters were not
significant in predicting owl success.
0
5
10
15
20
0-2 2-4 4-6
Distance from the owl (m.)
Incidence
Predator-prey distance at the onset of attack (m.)
FID: Predator-prey distance
at the onset of fleeing (m.)
r2 = 0.864
r2 < 0.001
0
1
2
3
4
5
6
0246
a
b
Fig. 3 a Frequency distribution of FID (distance between the owl and
spiny mice at the onset of escape). bFID as a function of the initial
distance (distance between the owl and spiny mouse at the onset of
attack). Closed symbols represent successful escape; open symbols
represent successful attack. As shown, FID was usually short or long,
but not intermediate (a). In accordance, FID was plotted separately for
more than 3 m (squares) and for less than 3 m (diamonds). Trend-lines
for each of these data groups reveal that FIDs longer than 3 m were
correlated with the initial distance, whereas trend-line of FIDs shorter
than 3 m was horizontal, indicating independence between FID and
the initial distance
Behav Ecol Sociobiol (2008) 62:923933 929
Discussion
Surprise attack: the owlsstrategy
The results of the logistic regression indicate that once an
owl had launched its attack by swooping on the prey, it was
primarily the behavior of the spiny mouse that dictated the
success of the owl. In that sense, the owls offensive strategy
was based on surprising the prey before it could escape.
Accordingly, owl velocity and the adjustments it made in
flight path did not differ between failed and successful
attacks. However, the owl (as a predator) was the initiator of
the attack, and by timing the attack could surprise the prey,
preventing the exploitation of any defensive means. Indeed,
surprise attack is the most frequent type of attack in many
predators (Kenward 1978;Cresswell1993;Cresswell1996).
Nevertheless, in taking the decision to attack, owls have to
consider two cardinal parameters: attack on a stationary or a
moving prey, and the timing of the attack.
Attack on moving vs stationary prey
Barn owls in the present experiment showed an apparent
preference for attacking stationary prey. Moreover, tests
with simulated prey revealed 100% owl success in catching
stationary food items compared with catching food items
that were being dragged away (simulated moving prey).
Thus, it seems that a prey can dramatically decrease
predation risk by continuously locomoting when encoun-
tering a barn owl. Freezing, on the other hand, eliminates
the auditory and visual cues that owls use in pinpointing
prey (Mikkola 1983), and if a prey freezes before being
spotted, the owl may not be able to locate it (Kaufman
1974). However, upon noticing an owl, a prey might not
know whether it has already been spotted; and by freezing,
it may turn into a stationary, easy to catch target (Edut and
Eilam 2004; Eilam 2005). Accordingly, it may be advan-
tageous for a prey to alternate between freezing and fleeing,
combining disappearance through freezing with not being a
stationary target if freezing fails (Edut and Eilam 2004).
The present results elucidate the dynamic nature of the
encounter, revealing that barn owls optimize their offensive
behavior by attacking locomoting mice the moment these
mice cease their locomotion. The owls thereby benefit from
the easier tracking of a moving prey combined with the
easy catch of a stationary prey. However, the prey may cope
with this owl strategy by fleeing at the last moment, as
detailed below.
FID, instant escape, and last-moment escape
The timing of attempted escape was previously studied in
the context of FID, which is the distance between predator
and prey at which the prey starts to flee (Ydenberg and Dill
1986; Dill and Houtman 1989; Bonenfant and Kramer
1996; Kramer and Bonenfant 1997). FID was found to be
both species- and context-specific, ranging between two
extremes: (1) fleeing as soon as a predator is noticed and (2)
fleeing in the last moment (Ydenberg and Dill 1986; Dill and
Houtman 1989;Dill1990; Bonenfant and Kramer 1996;
Kramer and Bonenfant 1997; Cooper 1999; Blumstein et al.
2003; Cooper et al. 2003), which established the notion that
one cannot assume that a prey flees immediately upon
noticing a predator, but that it may notice the predator but
delay fleeing for some reason (economic gain). The present
results demonstrate that such a delayed attempt to escape
may also have a significant defensive value, limiting the
approaching owls ability to maneuver and adjust to the
route of the escaping prey. Moreover, the present results,
which were extracted from real encounters between barn
owls and spiny mice, revealed a dichotomy of escape
strategies: (1) immediate flighta distant-dependent FID in
which flight occurred when the predator was relatively
distant (more than 3 m in the present study), in correlation
with the initial distance between them; and (2) last-moment
flighta distance-independent FID in which flight occurred
when the predator was very close to the prey (less than 3 m
in the present study), independently of the initial distance
between them. Of these two strategies, in immediate flight,
the prey flees as soon as detecting the predator, presuming
that early flight will suffice for reaching a shelter or remove
of the prey from its immediate vicinity. In a last-moment
escape attempt, the prey flees only when the predator is
very close, as if waiting for the very final stage of the attack
(typically a distance of less than 1 m in the present study),
and then executes an agile escape. At that stage, the
predator is at maximum swooping velocity with limited
maneuverability, generally requiring it to land and then
launch a second attack. The delay to the second attack
enables the prey either to reach shelter or to move further
away from the predator.
Spiny mice are nimble (Eilam 1997; Oron et al. 1998),
living and foraging in crevices and spaces between and
under boulders, spending only little of their time in the
open (Kronfeld-Schor and Dayan 1999). Thus, an escaping
spiny mouse may quickly reach a shelter under rocks or
boulders, out of the reach of owls, and this makes both
immediate flight and last-moment flight efficient. Indeed, a
previous study found that when attacked by a barn owl, the
spiny mice fled; whereas a clumsier rodent species, the
social vole (Microtus socialis), favored alternating between
freezing and fleeing (Edut and Eilam 2004). A similar
dependence of defensive response on motor ability and
habitat structure was described in two deer species (Lingle
and Pellis 2002). White-tailed deer (Odocoileus virginianus)
that inhabit forests and are fast runners tend to flee when
930 Behav Ecol Sociobiol (2008) 62:923933
encountering coyotes (Canis latrans), whereas mule deer
(Odocoileus hemionus) that live in relatively open spaces
and are moderate runners tend to freeze or hold their ground
and fight the predator (Lingle and Pellis 2002). Their agility,
speed, and the availability of nearby shelters thus make the
two escape strategies of spiny mice the more appropriate
response to owl attack.
The present results elaborate on Ydenberg and Dills
model, which presumes that early flight is always safer than
a later one (Ydenberg and Dill 1986). Indeed, this is the
case in any attempt to escape when a relatively long
distance exists between predator and prey. Moreover, this is
the range where the prey may still trade between predation
risk and other benefits, such as foraging. The possibility of
the prey to continue to forage or perform any behavior
beneficial to it other than flight is virtually nil at closer
distances, and this shorter range probably includes the
entire distance available in the present study (6 m). At the
longer distances, FID and the initial distance between
the predator and prey upon launch of attack are still
relevant. In this situation, the prey will do better by fleeing
as soon as it detects the predator. However, in attacks from a
close distance, the prey may do better by attempting a last-
moment escape. This model of FID is illustrated in Fig. 4.
Notably, most studies dealing with FID could not test its
effect on attack success; mostly because in those studies,
the simulated predator was a human approaching the prey
(Kramer and Bonenfant 1997). Comparing the two different
tactics of immediate flight and last-moment flight in the
present study revealed that spiny mice that fled later
(shorter FID) were more successful in evading barn owls
(85% vs 50% success in escaping). Thus, a shorter FID may
be advantageous in evading predators, in contrast with the
intuitive prediction that fleeing earlier is better. This finding
supports our suggestion that an agile prey may be better off
delaying its attempt to escape until the last moment.
Nevertheless, considering the velocity of the attacking
owl, a last-moment escape is risky with a split second
differing between life and death. Therefore, this defense is
probably only appropriate for an agile prey responding to a
nearby predator, especially when the prey does not have
access to a refuge.
Is there a preferred direction of escape?
The present study replicated a previous study (Shifferman
and Eilam 2004) on barn owls attacking a simulated prey
a food item that was tied to a transparent string and pulled
away once the owl had launched its attack. As found in the
earlier study, in this study too, owls had a higher rate of
success in catching a simulated prey that was dragged
directly ahead of the direction of the attacking owl; lesser
success when the prey item was dragged toward the owl;
and least success when it was dragged sideways. In addition
to replicating the previous study (Shifferman and Eilam
2004), the present study also challenged the results
obtained with simulated prey by means of real encounters
between barn owls and spiny mice. Specifically, we tested
whether escaping spiny mice favor fleeing sideways in
relation to the approaching owl, a direction from which the
owls had had lowest success in catching the simulated prey.
Indeed, the present results unequivocally demonstrate that
spiny mice favor to flee sideways. Moreover, dodging
sideways is a common defense in numerous prey species.
For example, this is a common defense in song birds (Lima
1993). Blue tits (Parus caeruleus) jump to the side when
attacked by a swooping raptor (Lind et al. 2002; Lind et al.
2003). Ostriches (Struthio camelus) and rheas (Rhea
americana) move sideways (Farina et al. 2005), as also
do Thompsons gazelles (Gazella thompsoni; Farina et al.
2005). In escape maneuvering, eluding the predator
successfully depends on the velocity and the turning radius
of the prey (Howland 1974).
In the present study, we reconfirmed that prey speed was
the main predictor of successful escape (the results from
logistic regression). While we did not measure the turning
radius of escaping spiny mice, this was a minor factor
considering that a spiny mouse is an 11-cm long rodent
whereas the owl is about 30 cm long with a wing span of
more than 70 cm. Thus, by moving quickly sideways, an
escaping spiny mouse can impose on the owl an impossible
maneuver. Indeed, in many of the failed attacks, the owls
touched down and immediately took off again and turned
toward the escaping mouse (Shifferman and Eilam 2004).
Howland (1974) suggested that sideways escape would be
highly efficient if made at the last moment when the
FID (flight initiation distance)
Chances for successful escape
1 – FID independent of the initial distance to predator (last moment escape)
2 – FID dependent of the initial distance to predator and alternative benefits (inst ant escape)
12
Fig. 4 A model for successful escape as a function of FID which
combines the last-moment escape (1) and instant escape (2). The
vertical lines distinguish between the escapes. In instant escape, the
chance of successful escape is lower when FID is shorter. In contrast,
in last-moment escape, the chance for a successful escape is higher
when FID is shorter, until a reversal point at which the predator is very
close and the chance of escape drops to zero
Behav Ecol Sociobiol (2008) 62:923933 931
predator might not be able to adjust its path. This is exactly
what was found in spiny mice in their preference for a last-
moment escape attempt and in their preference to sideways
escape. In the logistic regression, however, escape direction
could not significantly predict the success of the owl, unlike
the velocity of the spiny mouse and the FID, which were
found to be reliable predictors.
Conclusions
Spiny mice under owl attack favor fleeing and by this, as
revealed in the present study, usually manage to evade the
owl. Escape initiation dichotomize to a short or long (but
rarely intermediate) distance between the spiny mouse and
the owl with higher success for the mouse attempting short-
distance (last-moment) escape. The best predictor of escape
success is the velocity of the spiny mouse and the second
best predictor is FID. While for the agile spiny mice, a high
velocity and a last-moment escape are the best strategies for
a successful escape, other strategies may better fit clumsier
prey species.
Acknowledgments We are grateful to Maoz Perlman and Yelena
Golan for their help in the experimentation and analyses, to the
zookeepers of the I. Meier Segals Garden for Zoological Research for
their help in rearing the owls and rodents, and to Naomi Paz for
editing the manuscript. This study was carried out under the
regulations and approval of the Institutional Committee for Animal
Experimentation (permit #L-05-059). The design carefully followed
the Guidelines for the Treatment of Animals in Behavioural Research
and Teaching (Animal Behaviour 2001) with special emphasis on the
Guidelines for Staged Encounters as outlined by Huntingford (1984).
References
Anonymous (2001) Guidelines for the treatment of animals in
behavioural research and teaching. Anim Behav 61:271275
Blumstein DT (2002) Moving to suburbia: ontogenetic and evolutionary
consequences of life on predator-free islands. J Biogeogr 29:685
692
Blumstein DT (2003) Flight-initiation distance in birds is dependent
on intruder starting distance. J Wildl Manage 67:852857
Blumstein DT, Anthony LL, Harcourt R, Ross G (2003) Testing a key
assumption of wildlife buffer zones: is flight initiation distance a
species-specific trait? Biol Conserv 110:97100
Bolles RC (1970) Species-specific defense reaction and avoidance
learning. Psychol Rev 77:3248
Bonenfant M, Kramer DL (1996) The influence of distance to burrow
on flight initiation distance in the woodchuck, Marmota monax.
Behav Ecol 7:299303
Cooper WE Jr (1999) Tradeoffs between courtship, fighting, and
antipredatory behavior by a lizard, Eumeces laticeps. Behav Ecol
Sociobiol 47:5459
Cooper WE Jr, Perez-Mellado V, Baird T, Baird TA, Caldwell JP, Vitt
LJ (2003) Effects of risk, cost, and their interaction on optimal
escape by nonrefuging Bonaire whiptail lizards, Cnemidophorus
murinus. Behav Ecol 14:288293
Cresswell W (1993) Escape responses by redshanks, Tringa tetanus,
on attack by avian predators. Anim Behav 46:609611
Cresswell W (1996) Surprise as a winter hunting strategy in
sparrowhawks Accipiter nisus, peregrines Falco peregrinus, and
merlins F. columbarius. Ibis 138:684692
Curio E (1976) The ethology of predation. Springer, Berlin
Desy EA, Batzli GO, Liu J (1990) Effects of food and predation on
behavior of prairie volesa field experiment. Oikos 58:159
168
Dill LM (1990) Distance-to-cover and the escape decisions of an
African cichlid fish, Melanochromis chipokae. Environ Biol
Fishes 27:147152
Dill LM, Houtman R (1989) The influence of distance of refuge on
flight initiation distance in the gray squirrel (Sciurus carolinen-
sis). Can J Zool 67:233235
Driver PM, Humphries DA (1988) Protean behavior: the biology of
unpredictability. Oxford University Press, London
Edut E, Eilam D (2004) Protean behavior under barn-owl attack: voles
alternate between freezing and fleeing and spiny mice flee in
alternating patterns. Behav Brain Res 155:207216
Eilam D (1997) Postnatal development of body architecture and gait
in several rodent species. J Exp Biol 200:13391350
Eilam D (2005) Die hard: a blend of freezing and fleeing as a dynamic
defenseimplications for the control of defensive behavior.
Neurosci Biobehav Rev 29:11811191
Erlinge S, Bergsten B, Kristiansson H (1974) The stoat and its prey-
hunting behaviour and fugitive reactions. Fauna Flora 69:203
211
Farina RA, Blanco RE, Christiansen P (2005) Swerving as the escape
strategy of Macrauchenia patachonica Owen (Mammalia;
Litopterna). Ameghiniana 42:751760
Furuichi N (2002) Dynamics between a predator and a prey switching
two kinds of escape motions. J Theor Biol 217:159166
Graham RR (1934) The silent flight of owls. J R Aeronaut Soc
38:837843
Hendrie CA, Weiss SM (1994) The development of an animal model
of panic with predictive and face validity. In: Cooper SJ, Hendrie
CA (eds) Ethology and pharmacology. Wiley, Chichester,
England, pp 111132
Hendrie CA, Weiss SM, Eilam D (1998) Behavioural response of wild
rodents to the calls of an owl: a comparative study. J Zool
245:439446
Howland HC (1974) Optimal strategies for predator avoidance: The
relative importance of speed and manoeuvrability. J Theor Biol
47:333350
Huntingford FA (1984) Some ethical issues raised by studies of
predation and aggression. Anim Behav 32:210215
Jedrzejewski W, Jedrzejewska B, Szymura A, Zub K (1996) Tawny
owl (Strix aluco) predation in a pristine deciduous forest
(Bialowieza National Park, Poland). J Anim Ecol 65:105120
Jedrzejewski W, Rychlik L, Jedrzejewska B (1993) Responses of bank
voles to odours of seven species of predators: experimental data
and their relevance to natural predatorvole relationship. Oikos
68:251257
Kaufman DW (1974) Differential predation on active and inactive
prey by barn owls. Auk 91:172173
Kenward RE (1978) Hawks and doves: factors affecting success and
selection in goshawk attacks on woodpigeons. J Anim Ecol
47:449460
King CM (1985) Interactions between woodland rodents and their
predators. Symp Zool Soc Lond 55:219247
Kramer DL, Bonenfant M (1997) Direction of predator approach and
the decision to flee to a refuge. Anim Behav 54:289295
Kronfeld-Schor N, Dayan T (1999) The dietary basis for temporal
partitioning: food habits of coexisting Acomys species. Oecologia
121:123128
932 Behav Ecol Sociobiol (2008) 62:923933
Kullberg C, Jackobsson S, Fransso T (2000) High migratory fuel
impair predator evasion in sedge warblers. Auk 117:1034
1038
Lima SL (1993) Ecological and evolutionary perspectives on escape
from predator attacks: a survey of North American birds. Wilson
Bull 105:1215
Lima SL, Dill LM (1990) Behavioral decisions made under the risk of
predationa review and prospectus. Can J Zool 68:619640
Lind J, Fransson T, Jakobsson S, Kullberg C (1999) Reduced take-off
ability in robins (Erithacus rubecula) due to migratory fuel load.
Behav Ecol Sociobiol 46:6570
Lind J, Hollen L, Smedberg E, Svensson U, Vallin A, Jakobsson S
(2003) Detection distance influences escape behaviour in two
parids, Parus major and P. caeruleus. J Avian Biol 34:233236
Lind J, Kaby U, Jakobsson S (2002) Split-second escape decisions in
blue tits (Parus caeruleus). Naturwissenschaften 89:420423
Lingle S, Pellis SM (2002) Fight or flight? Antipredator behavior and
the escalation of coyote encounters with deer. Oecologia
131:154164
Martin G, Busby J (1990) Birds by night. Poyser, London
Mikkola H (1983) Owls of Europe. Poyser, England
Oron U, Maltz L, Shefer G, Eilam D (1998) Histology and enzymatic
activity in the postnatal development of limb muscles in rodents.
Physiol Behav 63:651657
Payne RS (1971) Acoustic location of prey by barn owls (Tyto alba). J
Exp Biol 54:535573
Ronkainen H, Ylonen H (1994) Behavior of cyclic bank voles under
risk of mustelid predationdo females avoid copulations?
Oecologia 97:377381
Scarratt AM, Godin JGJ (1992) Foraging and antipredator decisions in
the hermit crab Pagurus acadianus (Benedict). J Exp Mar Biol
Ecol 156:225238
Selaas V (1993) A comparison of the diet of sympatric owls in Aust-
Agder country, Southern Norway. Fauna Norv 26:713
Shargal E, Kronfeld-Schor N, Dayan T (2000) Population biology and
spatial relationships of coexisting spiny mice (Acomys) in Israel.
J Mammal 81:10461052
Shifferman E, Eilam D (2004) Movement and direction of movement
of a simulated prey affect the success rate in barn owl Tyto alba
attack. J Avian Biol 35:111116
Shkolnik A (1971) Diurnal activity in a small desert rodent. Int J
Biometeorol 15:115120
Smith WP (1991) Ontogeny and adaptiveness of tail flagging behavior
in white-tailed deer. Am Nat 138:190200
Thorpe WH, Griffin DR (1962) The lack of ultrasonic component in
the flight noise of owls compared with other birds. Ibis 104:256
257
Tome D (1994) Diet composition of the long-eared owl in center
Slovenia: seasonal variations in prey use. J Raptor Res 28:253
258
Ydenberg RC, Dill LM (1986) The economics of fleeing from
predators. Adv Study Behav 16:229249
Behav Ecol Sociobiol (2008) 62:923933 933
... Barn owls, for example, are well known for their acute night vision and their high auditory sensitivity, enabling high spatial resolution in sound localization of their prey even in complete darkness [ 64,65]. Their prey, however, have evolved to avoid owl predation using various strategies such as minimizing exposure in risky times and habitats [66] and adopting escape strategies during an active owl attack [67,68]. Controlled experiments in a closed arena revealed that owls tend to postpone their attack until their prey becomes motionless [68], and there is a high variation in capture duration (from first attack to a successful capture) ranging from 0.5 sec to 43 min [67]. ...
... Their prey, however, have evolved to avoid owl predation using various strategies such as minimizing exposure in risky times and habitats [66] and adopting escape strategies during an active owl attack [67,68]. Controlled experiments in a closed arena revealed that owls tend to postpone their attack until their prey becomes motionless [68], and there is a high variation in capture duration (from first attack to a successful capture) ranging from 0.5 sec to 43 min [67]. Thus, as it is hard to catch highly apprehensive moving prey, adopting irreproducible (and thus unpredictable) movement tactics may prove beneficial for a predator, rather than committing to a single tactic or behavior. ...
Article
Full-text available
Quantifying and comparing patterns of dynamical ecological systems requires averaging over measurable quantities. For example, to infer variation in movement and behavior, metrics such as step length and velocity are averaged over large ensembles. Yet, in nonergodic systems, such averaging is inconsistent; thus, identifying ergodicity breaking is essential in ecology. Using rich, high-resolution, movement data sets (greater than 7×107 localizations) from 70 individuals and continuous-time random walk modeling, we find subdiffusive behavior and ergodicity breaking in the localized movement of three species of avian predators. Small-scale, within-patch movement was found to be qualitatively different, not inferrable and separated from large-scale interpatch movement. Local search is characterized by long, power-law-distributed waiting times with a diverging mean, giving rise to ergodicity breaking in the form of considerable variability uniquely observed at this scale. This implies that wild animal movement is scale specific, with no typical waiting time at the local scale.
... Barn owls, for example, are well known for their acute night vision and their high auditory sensitivity enabling high spatial resolution in sound localization of their prey even in complete darkness (60,61). Their prey, however, have evolved to avoid owl predation using various strategies such as minimizing exposure in risky times and habitats (62) and adopting escape strategies during an active owl attack (63,64). Controlled experiments in a closed arena revealed that owls had higher success in catching stationary rather than moving prey, and they tended to postpone their attack until their prey became motionless (64). ...
... Their prey, however, have evolved to avoid owl predation using various strategies such as minimizing exposure in risky times and habitats (62) and adopting escape strategies during an active owl attack (63,64). Controlled experiments in a closed arena revealed that owls had higher success in catching stationary rather than moving prey, and they tended to postpone their attack until their prey became motionless (64). Another experiment in the same settings revealed high variation in capture duration (from first attack to a successful capture) of spiny mice (Acomys cahirinus) and Günther's voles (Microtus guentheri), ranging from 0.5 sec to 43 min (63). ...
Preprint
Movement tracks of wild animals frequently fit models of anomalous rather than simple diffusion, mostly reported as ergodic superdiffusive motion combining area-restricted search within a local patch and larger-scale commuting between patches, as highlighted by the L\'evy walk paradigm. Since L\'evy walks are scale invariant, superdiffusive motion is also expected within patches, yet investigation of such local movements has been precluded by the lack of accurate high-resolution data at this scale. Here, using rich high-resolution movement datasets ($>\! 7 \times 10^7$ localizations) from 70 individuals and continuous-time random walk modeling, we found subdiffusive behavior and ergodicity breaking in the localized movement of three species of avian predators. Small-scale, within-patch movement was qualitatively different, not inferrable and separated from large-scale inter-patch movement via a clear phase transition. Local search is characterized by long power-law-distributed waiting times with diverging mean, giving rise to ergodicity breaking in the form of considerable variability uniquely observed at this scale. This implies that wild animal movement is scale specific rather than scale free, with no typical waiting time at the local scale. Placing these findings in the context of the static-ambush to mobile-cruise foraging continuum, we verify predictions based on the hunting behavior of the study species and the constraints imposed by their prey.
... Remaining stationary can also allow the prey to inspect the threat as it approaches (Dugatkin & Godin, 1992) and choose from a wider range of escape directions, making their trajectory less predictable (Wilson et al., 2018). This escape behaviour is especially effective if coupled with fleeing at the last moment from a less agile predator, as the predator is less able to change its heading in attack (Ilany & Eilam, 2008;Bulbert, Page, & Bernal, 2015). Such an ability to outmanoeurve may be successful at evading pursuit predators that are larger and less agile than bandicoots (Wilson et al., 2020). ...
Article
Full-text available
Escaping from predators is fundamental for the survival of any prey species. Australian fauna within the ‘critical weight range’ (CWR; 35 g–5.5 kg) are vulnerable to introduced eutherian predators. The absence of co‐evolution between native marsupials and these novel predators may suggest that their antipredator behaviour towards the hunting strategies of these predators is inappropriate or ineffective. We quantified the escape behaviour of eight CWR marsupial taxa (three quadrupedal bandicoots and five bipedal macropods) to determine if differences in how they escape from predators indicate their ability to respond appropriately and effectively to introduced predators. Animals were filmed escaping through a runway and 20 measures relating to their gait, speed and path characteristics were recorded. These were reduced to four dimensions using multidimensional scaling (MDS): MDS1 linear speed versus agility, MDS2 acceleration style, MDS3 reactivity and MDS4 gait characteristics. We found a strong link between the phylogenetic relatedness of species and their use of linear speed or agility when fleeing (phylogenetic heritability, h2 = 0.96). Bipedal macropod species used straight‐line, fast escapes, which may be suited to escape pursuit predators. The quadrupedal bandicoots had an overall slower escape but were more likely to use sudden changes of direction, which can be successful if pursued by a larger, less mobile predator or where there is sufficient vegetation cover to obstruct pursuit. Repeated exposure increased linear speed (MDS1) and hastened the timing of acceleration (MDS2). The phylogenetic signal for escape speed/straightness suggests specific escape tactics may be constrained by morphology, although animals increased the intensity of their response after repeated exposure, suggesting training could enhance effective antipredator responses. We tested the escape behaviour in five bipedal macropod and three quadrupedal bandicoot species to document how they respond to a pursuit. Macropods used straight‐line, fast escapes, whilst the bandicoots were slower but more likely to use sudden changes of direction. The phylogenetic signal for escape speed/straightness suggests escape tactics may be constrained by morphology, although animals increased the intensity of their response after repeated exposure, suggesting training could enhance effective antipredator responses.
... We speculate that, similar to our study, the presence of a predator cue generated the "uncooperative" behavior of these females and that treatment effects may have been uncovered had these behaviors been scored explicitly. Data from pure predator-prey studies highlight how capable prey are in customizing evasive maneuvers in subtle ways such as freeze/flee timing (Eilam 2005;Ilany and Eilam 2008;Nishiumi and Mori 2020), flight distance (Martín et al. 2005;Nishiumi and Mori 2015), escape trajectory (Shifferman and Eilam 2004;reviewed in Domenici et al. 2011), and mirroring the risk magnitude (Helfman 1989;Acharya and McNeil 1998). We consider the same behavioral flexibility expressed when dealing with predators, while foraging may also apply to the process of mate choice. ...
Article
Full-text available
Female mate choice is remarkably complex and has wide-ranging implications for the strength and direction of male trait evolution. Yet mating decisions can be fickle and inconsistent. Here, we explored predation risk as a source of variation in the effort a female is willing to invest in acquiring a preferred mate type (“choosiness”). We did so by comparing phonotaxis behaviors of female eastern gray treefrogs (Hyla versicolor) across trials with and without simulated predators. We tested the behavioral adjustment hypothesis (mate choice is unchanged under predation threat, but mate searching behaviors are modified to reduce conspicuousness) against the mate choice flexibility hypothesis (mate choice becomes indiscriminate under predation threat). Additionally, effectiveness of evasive behaviors may depend on predator attack strategy, so we incorporated two simulated predator cues (bird model vs predatory ranid call). We found support for the behavioral adjustment hypothesis: choosiness was maintained in the presence of predators, but females reduced conspicuousness of mate searching locomotion. Females approached the conspecific male stimuli slower and more cautiously in both predator treatments. In the ranid frog call treatment (stationary cue), females adjusted movements away from predator location. Females also attempted escape more frequently when predator cues were present. We suggest that focusing exclusively on the final mate decision may overlook nuances in mating decisions and hamper our understanding of the remarkable complexity of mate choice. Significance statement The presence of predators is an inherent threat to survival. This leads to the general expectation that higher predation risk results in more indiscriminate mate choice decisions and, hence, a weakening of sexual selection. Yet, discriminating mate choice may be maintained if prudent prey change their approach behavior when detecting the presence of a predator. We conducted playback trials with female treefrogs to test whether their willingness to invest in obtaining a more attractive mate (quantified by “choosiness”) differed depending on the presence and type of predation risk. We found that females adjusted their approach behavior in a way that should make them less conspicuous to predators, but that they did not compromise their mate choice decisions. Our results show that strong sexual selection by females’ choice can be maintained in high predation environments.
... Fleeing toward a predator may offer other benefits. Preys that flee toward approaching aerial predators are much more likely to survive than those that fled away from a predator (Shifferman and Eilam 2004;Ilanay and Eilam, 2008). By fleeing toward a predator, the relative speeds of the predator and prey are increased, decreasing the window of opportunity for a successful capture (Howland 1974). ...
Article
Full-text available
Escape theory has been exceptionally successful in conceptualizing and accurately predicting effects of numerous factors that affect predation risk and explaining variation in flight initiation distance (FID; predator–prey distance when escape begins). Less explored is the relative orientation of an approaching predator, prey, and its eventual refuge. The relationship between an approaching threat and its refuge can be expressed as an angle we call the “interpath angle” or “Φ,” which describes the angle between the paths of predator and prey to the prey’s refuge and thus expresses the degree to which prey must run toward an approaching predator. In general, we might expect that prey would escape at greater distances if they must flee toward a predator to reach its burrow. The “race for life” model makes formal predictions about how Φ should affect FID. We evaluated the model by studying escape decisions in yellow-bellied marmots Marmota flaviventer, a species which flees to burrows. We found support for some of the model’s predictions, yet the relationship between Φ and FID was less clear. Marmots may not assess Φ in a continuous fashion; but we found that binning angle into 4 45° bins explained a similar amount of variation as models that analyzed angle continuously. Future studies of Φ, especially those that focus on how different species perceive relative orientation, will likely enhance our understanding of its importance in flight decisions.
... Alternatively, they might choose to flee (flight; Edut and Eilam 2003), relying on speed to access a refuge (e.g. spiny mice (Acomys cahirinus), Ilany and Eilam 2008). Finally, if they are unable to avoid or evade a predator, they might be forced to defend themselves (fight; Edut and Eilam 2003). ...
Article
Habitat complexity reflects resource availability and predation pressure-both factors that influence behaviour. We investigated whether exploratory behaviour and activity varied in fawn-footed mosaic-tailed rats (Melomys cervinipes) from two habitats that were categorised differently based on vegetation. We conducted vegetation surveys to determine structural complexity and vegetation cover, confirming that an abandoned hoop-pine (Araucaria cunninghami) plantation forest was structurally less complex, with lower vegetation cover than a variable secondary rainforest. We then tested mosaic-tailed rats from both sites in four behavioural tests designed to assess exploratory and activity behaviours (open field, novel object, light-dark box, acoustic startle), predicting that rats from the less structurally complex habitat would be less exploratory, and show lower activity. Our results provide some evidence for a context-specific trade-off between exploratory behaviour and predation risk in rats from the abandoned hoop pine plantation, as rats were less active, and showed a freezing strategy in the light-dark box. We also found context-specific sex differences in behaviour in response to a novel object and sound. Our results suggest that small-scale variation in habitat structure and complexity, as well as sex differences, is associated with variation in behaviour, most likely through effects on resource availability and/or predation risk.
... For instance, the prey's escape strategy was not dependent on either the size of the pursuing predator or the complexity of the habitat. In reality, many animals adjust their escape strategies based on the identity and/or performance capabilities of the pursuing predator (Bulbert et al., 2015;Eilam, 2005;Fichtel, 2007;Furuichi, 2002;Ilany & Eilam, 2008;Walther, 1969). Similarly, animals will often adopt different anti-predator behaviours and escape responses based on distance to cover, familiarity with the terrain, the predator's proximity and approach speed, how conspicuous the prey feels and in response to social behaviours (Clarke et al., 1993;Cooper, 1997Cooper, , 1998Cooper, , 2009Dill, 1990;Kramer & Bonenfant, 1997;Martin & López, 1995;Quadros et al., 2019). ...
Article
Animals are responsive to predation risk, often seeking safer habitats at the cost of foraging rewards. Although previous research has examined how habitat features affect detection by predators, little is known about how the interaction of habitat features, sensory cues, and physical performance capabilities affect prey escape performance once detected. To investigate how specific habitat features affect predation risk, we developed an individual-based model of terrestrial predator-prey pursuits in habitats with programmable features. We ran simulations varying the relative performance capabilities of predator and prey as well as the availability and abundance of refuges and obstacles in the habitat. Prey were more likely to avoid detection in complex habitats containing a higher abundance of obstacles; however, if detected, prey escape probability was dependent on both the abundance of refuges and obstacles and the predator's relative performance capabilities. Our model accurately predicted the relative escape success for impala escaping from cheetah in open savanna versus acacia thicket habitat, though escape success was consistently underestimated. Our model provides a mechanistic explanation for the differential effects of habitat on survival for different predator-prey pairs. Its flexible nature means that our model can be refined to simulate specific systems and could have applications toward management programs for species threatened by habitat loss and predation.
Preprint
Full-text available
Spiny mice ( Acomys cahirinus ) are an emerging animal model in studies measuring tissue regeneration, but decades of research on social dominance in other animals indicates the relationships animals form in their home-cage may affect phenotypic plasticity in tissue regeneration and glucocorticoids. Studies in baboons and mice, for example, indicate that subordinate ranked animals heal wounds slower than their dominant group-mates, and have increased levels of basal glucocorticoids. Recent studies in tissue regeneration with salamanders and zebrafish indicate that increased glucocorticoids can delay tissue regeneration, but whether this effect extends to Acomys is unknown, especially regarding their social dominance relationships. Here we report that most adult Acomys had a social dominance status, but many groups had unclear social stability, with more frequent huddling than fighting during their active cycle. We also found no sex differences in social dominance behavior, and that Acomys more frequently fled than froze when chased or approached. After a 4mm ear-pinna biopsy, we found that social stability significantly accounted for variability in time to close the ear-hole but adding age to the statistical model removed the effect of social stability. When investigating glucocorticoid blood levels, there were no significant effects of social dominance status or social stability. A transcriptional enhancer for StAR, Nr5a1 had a significant effect for the interaction of social dominance status and social stability. This effect, however, was not reflected in StAR and unclear groups mostly had unclear social statuses, so this effect should be considered with caution. This is the first study to investigate home-cage social dominance behaviors in Acomys since the 1970s or measure any associations with their ability to regenerate tissue. This provides a platform for further work on their social dominance and glucocorticoids and highlights the need to consider the role of aging in their ability to regenerate tissue.
Article
Full-text available
Body size is a key factor that influences antipredator behavior. For animals that rely on jumping to escape from predators, there is a theoretical trade-off between jump distance and acceleration as body size changes at both the inter- and intraspecific levels. Assuming geometric similarity, acceleration will decrease with increasing body size due to a smaller increase in muscle cross-sectional area than body mass. Smaller animals will likely have a similar jump distance as larger animals due to their shorter limbs and faster accelerations. Therefore, in order to maintain acceleration in a jump across different body sizes, hind limbs must be disproportionately bigger for larger animals. We explored this prediction using four species of kangaroo rats (Dipodomys spp.), a genus of bipedal rodent with similar morphology across a range of body sizes (40-150 g). Kangaroo rat jump performance was measured by simulating snake strikes to free-ranging individuals. Additionally, morphological measurements of hind limb muscles and segment lengths were obtained from thawed frozen specimens. Overall, jump acceleration was constant across body sizes and jump distance increased with increasing size. Additionally, kangaroo rat hind limb muscle mass and cross-sectional area scaled with positive allometry. Ankle extensor tendon cross-sectional area also scaled with positive allometry. Hind limb segment length scaled isometrically, with the exception of the metatarsals, which scaled with negative allometry. Overall, these findings support the hypothesis that kangaroo rat hind limbs are built to maintain jump acceleration rather than jump distance. Selective pressure from single-strike predators, such as snakes and owls, likely drives this relationship.
Article
Full-text available
The hermit crab Pagurus acadianus (Benedict) possesses two major defences against mobile aquatic predators, viz., fleeing and refuging in its gastropod shell. When approached by a potential predator, a crab must choose to either continue its current activity (e.g., feeding), flee or hide in its shell. If a foraging crab flees when threatened, it must secondarily decide whether to carry its food item and, if so, how far to carry it whilst escaping. Alternatively, if the crab takes refuge in its shell, it must then decide how long to remain hidden and when to resume locomotory activity following emergence from the shell. Because these behavioural alternatives have associated costs (e.g., energy expenditure, predation risk, lost foraging opportunity), the crabs' decision as to which behaviour to adopt should be sensitive to the respective cost of each. We tested specific predictions of this general economic hypothesis of behavioural decision making by varying the weight of food items presented to crabs (= lost feeding opportunity cost, energetic cost of carry) and the amount of time the crabs were "handled" by a predator following "capture" (= predation risk). Most crabs tested fled from an approaching lobster predator model. Contrary to expectation, flight initiation distance was unaffected by the mass of the food item available to the foraging crabs. As predicted, however, the distances fleeing crabs carried individual food items varied inversely with the food's weight. Time spent hiding in the shell and latency to resume locomotion following a predator "attack" were relatively unaffected by the size of the food item available. As expected, the crabs' decision to emerge from their shell following a threat appeared sensitive to their perceived risk of predation, as evidence by an observed positive relationship between refuging time (in shell) and the duration of preceding handling of the crab by the predator. These findings are interpreted within the cost-benefit framework of behavioural decision making.
Article
The Lujanian megamammals (late Pleistocene of South America) show many palaeoautecological peculiarities. The present paper studies one of them, the locomotor habits of Macrauchenia patachonica Owen, through those morphological features related with its possible antipredation strategy. To avoid predation (especially by the sabre-tooth Smilodon Lund), this large litoptern seems to have been particularly adapted to swerving behaviour. This is suggested by the fact that its limb bones have indicators of higher transverse than anteroposterior strength (significantly so in the case of the femur), a feature which is also observed in modern swervers, and not so clearly in other fast running herbivores that do not use swerving so much.
Article
Food availability and predation were manipulated to determine if these environmental factors influence the behaviour (aggression and movements) of prairie voles (Microtus ochrogaster) under field conditions. We tested two specific hypotheses: (1) that greater availability of high quality food reduces aggression and movement of voles, and (2) that exposure to predators reduces movement of voles. Mean densities increased and mean home range size decreased for populations with supplemental food. Voles raised with supplemental food did display less aggression toward one another, but we detected no effect of food on home-range size when comparing treatments for a given density. Thus food appeared to act indirectly on home-range size via the effect of food on population density. Voles with supplemental food did move less between trapping sessions, which may indicate less shifting of home ranges with greater availability of food. Exposure to predation did not affect aggression among voles, but it appeared to reduce home-range size, even after correcting for the effect of density. This reduced movement was probably a direct behavioural response of voles to the presence of predators. We conclude that factors extrinsic to the vole populations can influence behaviour directly or indirectly. Such interactions should be considered carefully when explaining the population dynamics of voles.
Article
(1) A trained male goshawk was used to arrange attacks on single pigeons and flocks, at brassica feeding sites and elsewhere. Captured pigeons were compared with shot samples from the same sites, using dry weight of the pectoralis minor muscle as an index of condition. Attacks on pigeon flocks at brassica sites were more successful than when the birds were feeding on grasslands and stubbles, possibly because of variation in pigeon condition. (2) Attacks were more successful in the hour before sunset than in the four previous hours. Pre-roost crop filling may have made the pigeons more vulnerable in the last hour, and the hawk might have been trying harder to obtain food as dusk approached. (3) Attacks on single pigeons, and on birds in small flocks, were more successful than those on flocks of more than ten pigeons. This occurred partly because single birds were in poor condition and partly because the hawk achieved less surprise as flock size increased. The hawk may also have been (a) less likely to encounter weak pigeons, (b) more confused, and (c) `less confident' in attacks on large flocks than on small ones. (4) Unless the hawk surprised pigeons feeding in flocks it was usually outflown. Pigeons captured from flocks which did not fly until the hawk reached them were in relatively good condition, but selection for poor condition became more marked if the birds took off when the hawk was further away and it had to chase them. (5) The predation was selective, partly because single pigeons tended to be both worse in quality and more vulnerable to attack than birds in flocks, and partly because pigeons captured from flocks were below average in condition when the hawk did not achieve complete surprise. There was selection for diseased and defective pigeons, but not for those of one particular age or sex. Goshawk predation could also select for behaviour which delays crop filling until as late in the day as possible, and for flocking.