The Aerodynamic Signature of Running Spiders
Je´roˆ me Casas1*, Thomas Steinmann1, Olivier Dangles2,3
1 University of Tours, Institut de Recherches sur la Biologie de l’Insecte, UMR CNRS 6035, 37200 Tours, France, 2 IRD, UR 072, LEGS, UPR 9034, CNRS, 91198 Gif-sur-Yvette,
France, 3 Universite´ Paris-Sud 11, 91405 Orsay, France
Abstract
Many predators display two foraging modes, an ambush strategy and a cruising mode. These foraging strategies have been
classically studied in energetic, biomechanical and ecological terms, without considering the role of signals produced by
predators and perceived by prey. Wolf spiders are a typical example; they hunt in leaf litter either using an ambush strategy
or by moving at high speed, taking over unwary prey. Air flow upstream of running spiders is a source of information for
escaping prey, such as crickets and cockroaches. However, air displacement by running arthropods has not been previously
examined. Here we show, using digital particle image velocimetry, that running spiders are highly conspicuous
aerodynamically, due to substantial air displacement detectable up to several centimetres in front of them. This study
explains the bimodal distribution of spider’s foraging modes in terms of sensory ecology and is consistent with the escape
distances and speeds of cricket prey. These findings may be relevant to the large and diverse array of arthropod prey-
predator interactions in leaf litter.
Citation: Casas J, Steinmann T, Dangles O (2008) The Aerodynamic Signature of Running Spiders. PLoS ONE 3(5): e2116. doi:10.1371/journal.pone.0002116
Editor: Andrew Iwaniuk, Smithsonian Institution, United States of America
Received January 7, 2008; Accepted March 31, 2008; Published May 7, 2008
Copyright:  2008 Casas et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work is part of the research conducted within the Cricket Inspired perCeption and Autonomous Decision Automata (CICADA) project (IST-2001-
34718) and within the Customized Intelligent Life Inspired Arrays (CILIA) project (FP6-IST-016039). These projects are both funded by the European Community
under the ‘‘Information Society Technologies-IST’’ Program, Future and emergent Technologies (FET).
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: casas@univ-tours.fr
Introduction
Many predatory species can switch between foraging modes,
usually alternating between an ambush and a cruising mode in
water,
soil
or
vegetation.
Much
care
has
been
taken
in
evolutionary ecology to evaluate the relative advantages of
foraging strategies in terms of energetics, biomechanics, success
rate and impact on the ecosystem [1–7]. However, the relationship
between the sensory processes involved in signal production by a
predator attacking with one of both strategies and the corre-
sponding signal perception by its escaping prey is unknown for
most systems. The outcome of this relationship is likely to play an
important role in defining the most appropriate predatory foraging
mode. For instance, wolf spiders pursue their cricket prey on the
bare soil and in leaf litter using two attack strategies [8–10].
Spiders attack prey using either an extremely slow-motion
approach, corresponding almost to the ambush strategy, or by
running over at relatively high speed (up to 40 cm/s, cruising
strategy) [10]. Spiders attack at intermediate speeds much less
frequently; biotests using a piston mimicking the attack of a spider
showed that a cricket’s chances of survival were highest for attacks
at intermediate speed (20 cm/s) [10]. Although crickets and many
other detritivorous and herbivorous arthropods are sometimes
caught unaware by a spider’s fast strike, they often escape with fast
movements. Information contained in air signals upstream from
running spiders can be used by prey in these fast escape reactions.
Indeed, crickets, cockroaches and other orthropteroid insects are
equipped with air-flow sensors (filiform hairs) at the rear end of
their abdomen [11]. They possess many short hairs, serving as
acceleration sensors, and fewer long hairs (velocity sensors) on
their cerci [12]. These mechanosensors are among the most
sensitive sensors in the animal kingdom, with action potentials
triggered by less than one tenth the energy of a photon [13];
indeed, the orthropteroid escape system, and in particular fluid flow
sensing using filiform hairs, has maintained textbook-example status
over many years [14–17]. Thus, we hypothesised that spiders use the
two different hunting strategies to cope with optimal air-flow
detection by crickets. One strategy (ambush) substantially reduces
the distance at which the prey can perceive the attack, while the
other strategy (cruising) reduces the escape probability by over-
whelming the prey sensory capabilities. The high speed ensures that
the encounter occurs faster than the escape response.
The aims of this study were therefore: (1) to quantify the air flow
in front of a running spider using digital particle imaging
velocimetry (DPIV), and (2) to assess these complex flow patterns
in the context of attack and escape strategies by predators and
prey. Very little is known about air movements upstream from a
running arthropod, limiting potential evaluation of the ecological
and evolutionary importance of air-flow sensing for many
predator-prey interactions. Near-field fluid movement cues are
used by many invertebrate species to obtain information about
potential predators, prey or mates, in both terrestrial and aquatic
ecosystems. In particular, several recent studies have led to greater
understanding of the physics of near-field fluid motion in animal
locomotion and sensing in open enclosures. Such technological
and conceptual advances have opened up the arena for similar
studies on running animals [18–23].
Results
We recorded the air flow produced by wolf spiders (Pardosa
[lugubris] sp., most likely P. lugubris (Walkenaer)) running in a small
wind tunnel (Figure 1). As spiders dislike the intense laser light
sheet, we obtained 14 runs from six different individuals with the
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horizontal set-up, but only two runs with the vertical set-up. These
were not used in the following quantitative analysis, but gave
useful information on several other qualitative aspects of the flow,
described below. The mean velocity of the spiders recorded in the
horizontal set-up was 9.44 cm/s (SD = 65.51; N = 14). This lies
within the range of attack speeds observed under unconstrained
hunting behaviour [10]. One spider ran at a high speed of 40 cm/
s. This was an outlier in the velocity distribution, and so was not
used to calculate the mean. Running spiders displaced air in front
of and above their body trunk (Figures 2 & 3). Pockets of high
velocity produced by moving legs could be distinguished and
substantially extended the region of flow influenced by the spider
(Figure 2). Front legs still produce a forward air movement when
moving downwards, as they do not move back and forth (Figure 3B
and cartoon on Figure 2). The air field within the first centimetre
upstream from a spider varies considerably from run to run
because it is not possible to synchronise the PIV clock with the leg
kinematics. Thus, depending on the exact moment of flow field
mapping, a leg may or may not have a large effect on the flow in
its near vicinity (see cartoon, Figure 2). This also explains the
absence of relationship observed between the air velocity at 6 mm
away from the spider and the spider’s body velocity, and our
subsequent decision to pool individual runs for a statistical
analysis. The air flow upstream from a running spider declines
smoothly with distance (Figure 4); a constrained regression, using
the function given in (Eq. 2) and the independently measured
mean spider’s velocity as a fixed parameter, lead to a good fit over
the whole range of distances (R2 = 0.80).
Discussion
The air field upstream from a running spider is disturbed over a
large distance of several body lengths. The need for prey to
perceive attacking predators from as large a distance as possible,
using the minimal amount of energy, means that this information
is of biological importance. Indeed, previous experimental studies
on the air flow produced by attacking toads shooting out their
toungs [24] and independent theoretical studies [25] suggested
that cockroaches may recognise the wind signature of a predator
by the low frequency components in the far field. The most sensitive
hairs of crickets are the longest ones (.1000 microns), working near
the thermal noise level [13]. Electrophysiological studies estimate
their minimal threshold at Vthresh= 30 mm/s. Thus, using the
expected flow velocity upstream from a running spider from the
fitted model, this threshold should be attained at around 3 cm in
front of a spider. This distance, obtained using the observed mean
speed, will vary as a function of the speed of the spider. Crickets seem
to make full use of this information, with their largest escape
distances being 2.4 cm in front of a spider and 2.1 cm in front of a
piston device mimicking the kinematics of the attack [10]. This is
most impressive, given the time taken for processing information in
the abdominal terminal ganglion, the insect brain, and from leg
movements [26]. Thus, the cricket’s entire escape system, including
sensory and locomotive control, is indeed optimised to pick up the
slightest air movements by the best sensors.
The implications of our results for the foraging modes of spiders
are twofold. First, spiders markedly increase their likelihood of
successful attacks by launching fast strikes, at the same time
decreasing the potential escape time (time between danger
perception by a cricket and encounter by a spider) in a non-
linear fashion (Figure 5). While low speed movements imply high
potential escape times, the distance at which prey can perceive
predatory signals is so short that prey are nearly within reach of
spiders (ambush strategy). Second, their highest speeds may
correspond to the lowest potential prey escape time [26]. Such
attack speeds are between 25–35 cm/s, corresponding well with
Figure 1. Digital particle image velocity (DPIV) measurements of a running spider. In the horizontal position, the laser light sheet is
focussed 3 mm above the floor, at mid-height of the spider, just below the bottom eye row level. The yellow portion represents the camera’s field of
view. Spiders were gently triggered to run using a stick inserted through a small hole at the entrance of the wind tunnel.
doi:10.1371/journal.pone.0002116.g001
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the higher speeds distribution observed during spider-cricket
interactions. Higher hunting speeds are seldom observed, as they
do not increase the capture rate but are energetically expensive.
Thus, our quantification of air flow upstream from a running
predator extends the interpretation of the two foraging modes in
terms of sensory processes, beyond the classical description in
energetic and biomechanical terms. Future studies dedicated to
body
and
leg
kinematics
should
be
prioritised,
since
our
understanding of this subject is substantially poorer than that of
wing and leg kinematics in insects, and their influence on the
upstream flow. The role of acceleration, body posture and height
over the substrate [27,28] as well as the nature of the substrate,
aspects which we have neglected here, are also expected to have a
major impact on the flow field upstream from the spider.
Many other invertebrate predators, including several other
arachnid groups, carabid, cincidelid and staphylinid beetles, hunt
prey using the same two strategies as those used by spiders. At the
same time, many prey living in litter harbour well-developed cerci
bearing filiform hairs triggered by slight air movements. These
include primitive and modern insects such as bristletails, firebrats,
springtails, cockroaches and crickets; indeed, most prey-spider
interactions observed today are the same as they were some
400 million years ago [29,30]. For example, cockroaches have been
extremely successful and thrive in tropical leaf litter despite strong
predator pressure. Our findings demonstrate a significant role of the
physical information contained in slight air currents in interspecific
interactions among terrestrial arthropods and suggest a tight sensory
coevolution between both opponents. Lurking predators may mostly
hide and wait for their prey, but the final strike produces conspicuous
signals that prey exploit for their survival.
Materials and Methods
DPIV
Our measurement set-up was composed of a sealed glass box
(106262 cm), seeded with 0.2 mm oil particles. Oil particles (Di-
Ethyl-Hexyl-Sebacat, 0.5 L, TPAS, Dresden, Germany) were
generated using an aerosol generator (ATM 230, ACIL, Chatou,
France). The laser (NewWave Research Solo PIV 2, Nd:YAG, dual
pulsed; Dantec Dynamics A/S, Skovlunde, Denmark) illuminated
the flow produced by the spider’s displacement through glass. The
laser sheet (width = 17 mm, thickness at focus point = 50 mm) was
operated at low power (3 mJ at 532 nm) to minimise glare. A target
area (17630 mm) was then imaged onto the CCD array of a digital
camera (Photron FastCam X1280 PCI 4K) using a Macro Lens
(Nikon, AF Nikkor, 60 mm, f : 2.8). The CCD captured separate
image frames (128061024 px). Once a sequence of two light pulses
was recorded, the images were divided into small subsections which
were cross-correlated with each other using flow map software (Flow
Manager 4.4. Dantec Dynamics A/S, Skovlunde, Denmark). The
Figure 2. Horizontal flow field and close-up view of the flow around a running spider. The sequence in (A) highlights the pockets of high
air-flow velocity created by leg strokes superimposed on the air movements created by the body trunk movement. Neither the tips of the spider’s
legs, nor their associated flow patterns, are visible as they are located below the light sheet. The time delay between two images is 500 ms; the spider
was running at a speed of 5.7 cm/s. The cartoon, adapted from [9], highlights the relative position of legs to body trunk. An overlay of two images
(first image in white, second image in grey) of the moving spider, separated by 500 ms, is shown in (B). The zone of flow velocities above the
measurable range is in black. The running speed was 10.5 cm/s.
doi:10.1371/journal.pone.0002116.g002
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correlation was achieved using an interrogation area of 32632
pixels, allowing us to obtain valid measurements down to a particle
displacement of 0.1 pixels. Using the equation,
sV~ sDx
Dtime
~ spixdr
Dtime
ð1Þ
with sDx the minimal displacement measurable (m), Dtime = 33 ms,
the time separating two image record and dr = 27 mm the spatial
resolution, one obtains the lowest detectable speed of 0.082 mm/s,
and of 5.4 mm/s for a time interval of 500 ms. Conversely, with the
maximal measurable particle displacement of 32 pixels, the maximal
detectable speed is 2.62 cm/s for a time interval of 33 ms, and
17.3 cm/s for a time interval of 500 ms.
Estimation of spider’s velocity and profile extraction
Pardosa (Koch) is the most speciose genus among Holarctic wolf
spider genera. Several species groups have been recognized, based
on characteristics of the copulatory organs [31]. Based upon
identification of mature males from our collecting sites, Pardosa
lugubris (Walkenaer) was the most common species. However, this
species was recently shown to incorporate distinct cryptic species
whose immature individuals are, to date, impossible to differen-
tiate (Kronestedt 2007). In our experiments, we used only
immature spiders because they naturally spend much of their
time hunting for prey and not seeking for partners. The mean
body size was 3.6 mm (S.D. = 0.2 mm, N = 6). The body size was
obtained by measuring the largest width of the prothorax, to which
we added the lengths of coxa and the trochanter, as these three
body parts act aerodynamically as a single unit. In the studied
spiders, this unit was wider than the abdomen. During a single
time interval of 33 ms, a spider travelled a distance of 5 mm when
moving at a speed of 15 cm/s. There are therefore no data
available on flow velocity for the 5 mm space next to the body
surface. The distance from the body for which no information was
available was greater for greater speeds.
In the horizontal set-up, we took care that the laser light sheet is
focused 3 mm above the floor, at mid-height of the spider, just
below the bottom eye row level. However, we cannot ascertain
that the laser light sheet, which is diverging with an angle of 24u
Figure 3. Vertical flow field and close-up view of the flow around a running spider. The sequence in (A) highlights the high air-flow
velocity above the spider’s body. The time delay between two images is 500 ms; the spider was running at a speed of 3.7 cm/s. An overlay of two
images (first image in white, second image in grey) of a moving spider, separated by 500 ms, is shown in (B). The horizontal component of the air flow
in the near vicinity of the legs is always directed forward, as front legs do not move back and forth (see cartoon in Figure 2). The running speed was
21 cm/s.
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from the focal point, did not affect the spider, or during the low
phase of the body oscillations. Whatever the amount of light
spiders did get, it was much below the intensity of the bulk of the
laser sheet, as we would otherwise see the eyes within the light
sheet. We observed a tendency to avoid the laser light sheet rapidly
in the vertical set-up.
We recorded 14 runs made by six Pardosa [lugubris] sp. spiders
with the horizontal set-up. Measurements were only made when
the spider velocity was assumed constant for several centimetres
and
spiders
were
running
straight.
The
constant
velocity
assumption is derived from the measurements in [10] reporting
an acceleration phase restricted to one centimetre, followed by a
constant velocity. We therefore positioned the field of view of the
camera at least 2–3 centimetres away from the entrance of the
tunnel. The spider’s velocity was determined by measuring the
average velocity of the spider’s body on a run. A run was restricted
5
10
15
20
25
0
1
2
3
4
5
6
7
Distance from body (mm)
Velocity (mm/s)
Figure 4. Flow velocity upstream of running spiders. The observed speeds (mean and standard deviation; dots and error bars, respectively),
and the fit of the statistical function (Eq. 2) are represented.
doi:10.1371/journal.pone.0002116.g004
Figure 5. Spider’s attack speed and cricket escape time. The potential escape time for a cricket (red line) is expressed as a function of the
spider’s attack speed. At slow attack speeds, the distance at which crickets can perceive spiders is limiting (ambush strategy), whereas at high
hunting speeds, the escape time becomes limiting (cruising strategy). The potential escape time is defined as the time interval between predator
perception by a cricket and hit by a spider running at a given speed. It is based on the distance, for a given speed, at which the threshold of 30 mm/s
for danger perception is attained [13]. The minimal recorded escape time for crickets is around 0.2 ms (horizontal bar, [26]). The distribution of
observed attack speeds and the five successful attacks (stars) were obtained from observations of real attacks, at constant speeds, during cricket-
spider interactions [10].
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to the pairs of images (varying from one to five pairs) for which the
images were of quality high enough for a faithful quantification of
air flow. We extracted velocity profiles from the vector fields for
each measurement. Profiles were evaluated along the upstream
axis. In order to describe the flow velocity as faithfully as possible,
we fitted the data with a flexible statistical function:
V~Vbody
1
6
A
A
2 zx z 1
12
B2
A
2 zx

2 z 1
24
C3
C
2 zx

3
 
!
ð2Þ
With x being the distance to the spider’s body (m), A = 0.0007,
B = 20.0011 and C = 0.0179 and Vbody, the spider’s body velocity
(0.0944 m/s).
Acknowledgments
We thank the consortium members of CICADA and CILIA teams for
discussions, M. Greenfield, G. Krijnen, C. Lazzari, E. McCauley and J.
Mogdans, and two reviewers for comments on the MS.
Author Contributions
Conceived and designed the experiments: JC TS OD. Performed the
experiments: TS. Analyzed the data: JC TS. Contributed reagents/
materials/analysis tools: JC TS. Wrote the paper: JC TS OD.
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The aerodynamic signature of running spiders.
Casas, Jérôme,Steinmann, Thomas,Dangles, Olivier