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First published online August 17, 2007
Journal of Experimental Biology 210, 3027-3035 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.007492
Assessment of repeated displays: a test of possible mechanisms
1 Centre for the Integrative Study of Animal Behaviour, Macquarie
University, Sydney, NSW 2109, Australia
2 Department of Psychology, Macquarie University, Sydney, NSW 2109,
Australia
* Author for correspondence (e-mail: daniel{at}galliform.bhs.mq.edu.au)
Accepted 20 June 2007
| Summary |
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Key words: visual signals, opponent assessment, Jacky dragon, Amphibolurus muricatus
| Introduction |
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Much of the research into opponent assessment has focused on establishing
links between signals/cues and predictors of fight outcome. The search for
predictors typically centres upon an individual's fighting ability and the
perceived value of contested resources
(Enquist, 1985
;
Hurd, 2006
;
Parker, 1974
). For assessment
to persist as a strategy, signals must reliably correlate with physical or
motivational attributes.
Reliability can be maintained through a number of different processes
(reviewed in Hurd and Enquist,
2005
). Index signals are reliable because their performance is
inextricably constrained. Examples of index signals include the acoustic
characteristics of anuran calls and of deer roars, both of which correlate
with body size (Bee et al.,
1999
; Davies and Halliday,
1978
; Reby et al.,
2005
). Handicap signals entail production costs
(Zahavi and Zahavi, 1997
). The
willingness of individuals to incur these costs is bound to components of
fighting ability and motivation. Production costs can include investment in
badges, energy expenditure during displays, exposure to predation and loss of
time. For instance, the temporal structure of shell rapping in hermit crabs
suggests that it functions as a signal of stamina
(Briffa and Elwood, 2000a
;
Briffa and Elwood, 2000b
). The
reliability of conventional signals is enforced by the opponent's response. If
a weak individual produces an exaggerated signal, it could be attacked by
stronger opponents. The costs of such attacks are thought to make bluffing an
unsuccessful strategy, and hence fights occur only when rivals signal at
similar levels. Colour patches and song type sharing in birds have been cited
as cases of conventional signalling
(Molles and Vehrencamp, 2001
;
Qvarnstrom, 1997
;
Vehrencamp, 2000
).
It is logical to suppose that if a signal is reliably linked to predictors
of contest outcome, then it is probably being assessed. This statement
represents a hypothesis, which is most unambiguously tested by the controlled
manipulation of potential signals. Static visual signals such as colour
patches can be altered relatively easily with paints, dyes or filters
(Göth and Evans, 2004
;
Hunt et al., 2001
;
Olsson, 1994
;
Veiga, 1993
). Dynamic visual
signals have presented a more recalcitrant problem. While our understanding of
acoustic communication such as deer roars, frog calls and bird song is well
advanced due to historical developments in sound acquisition, manipulation and
playback (Clutton-Brock and Albon,
1979
; Davies and Halliday,
1978
; Falls,
1963
), it is only recently that improvements in technology have
made dynamic visual signals similarly accessible. In particular, the
development of robotic models (Martins et
al., 2005
; Simpson,
1968
) and video playback
(Clark and Uetz, 1992
;
Evans and Marler, 1991
;
Ord et al., 2002
) has made the
experimental analysis of movement-based signals possible for the first
time.
An opponent observing a sequence of dynamic visual displays has access to
four potential sources of information: sender morphology, display motion
characteristics, choice of display type and display rate. In relation to
display rate, three mechanisms of assessing a single repeated behavioural
action have been considered (Payne and
Pagel, 1997
). First, the assessor may be averaging actions to
improve its estimate of signal characteristics. This is equivalent to a single
round within the sequential assessment model
(Enquist and Leimar, 1983
).
Here, signals constrained by physical limitations (i.e. index signals) are
expected to be transmitted with error. Repetition facilitates the gradual
reduction of error levels in a manner analogous to statistical sampling.
Second, competitors might be assessing the best action so far and ignoring all
previous actions (Payne and Pagel,
1996
). In this model, each superior action is, in effect, the
signal. Third, the signal might be a cumulative function of all the actions
performed (Payne, 1998
). This
mechanism is most likely to occur when repetition imposes a high time cost, as
in displays of endurance. Payne and Pagel described features of contests and
signals that could be used to infer the presence of one of these mechanisms
(Payne and Pagel, 1997
).
Iguanian lizards are an ideal model group for studying mechanisms of
opponent assessment. Intense selective pressure to reduce the risks of
male–male competition has contributed to a rich diversity of signals
(Carpenter, 1965
;
Ord et al., 2001
) designed to
exploit the well-developed iguanian visual system. Dynamic signals, involving
stereotyped movements of the head and body, are a prime example of this
(Carpenter and Ferguson, 1977
;
Stamps, 1977
). Many species
have evolved a repertoire of structurally distinct displays, as defined by the
cadence of head movements, and much of the work in this field is concerned
with quantifying the variation in display choice between different contexts
(DeCourcy and Jenssen, 1994
;
Hover and Jenssen, 1976
;
Lovern et al., 1999
;
Macedonia and Clark, 2003
;
Martins, 1993
;
McMann, 2000
;
Orrell and Jenssen, 2003
). In
captivity, dominant males are often observed displaying more than
subordinates, and high display rates in the field have been linked to
laboratory measures of endurance and contest success
(Carpenter, 1962
;
Carpenter, 1965
;
Deslippe et al., 1990
;
Perry et al., 2004
;
Prieto and Ryan, 1978
).
Endurance capacity is also correlated with display behaviour in an
anti-predator context (Leal,
1999
).
Here we explore the relationship between short-term changes in display rate
and opponent assessment in Jacky dragons Amphibolurus muricatus
(White 1790). Dynamic visual signals are commonly used by Jacky dragons to
mediate social interactions (Carpenter et
al., 1970
). Males threaten opponents with push-up displays, a
highly stereotyped sequence of motor patterns consisting of a rapid arm-wave
followed by one or more push-up/body-rocks
(Peters and Ord, 2003
).
Displays can occur in rapid succession, forming a bout. Lizards often modify
their displays by adding introductory tail-flicks
(Peters and Evans, 2003
), or
increasing their profile through lateral compression, gular expansion and
nuchal crest erection. Previous video playback experiments found that males
were sensitive to `moment-to-moment' variation in the display rate of
simulated opponents (Ord et al.,
2002
) and the social contingencies governing interactions
(Ord and Evans, 2002
). A
follow-up study identified overall display rate as a critical parameter, with
males displaying more when the stimulus lizard's inter-bout interval was
population-average than to shorter or longer intervals
(Ord and Evans, 2003
). These
findings suggest that males use the temporal properties of display sequences
to assess fighting ability or motivation. Jacky dragons also have two putative
submissive signals, the slow arm-wave and slow head-bow. These displays are
typically performed by subordinate individuals in both indoor pens and large
naturalistic outdoor enclosures (D.V.D., personal observation).
In the present study, we investigated which of the three possible mechanisms (average, `best-so-far' or cumulative) underlies the assessment of display rate. We conducted two video playback experiments, each simulating aggressive intruders engaging residents at close range, but examining different patterns of display behaviour over time. Digital video playback was used to control both the morphology of the simulated opponent and the motion characteristics of individual displays, while allowing precise manipulation of the moment-to-moment changes in display rate. This approach provides a uniquely sensitive test of assessment mechanisms.
| Materials and methods |
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Video stimuli
Recording
Video footage of lizards basking and performing push-up displays was
recorded according to the procedure detailed elsewhere
(Ord et al., 2002
). Briefly,
pens were modified by covering the floor with a thick layer of foliage and
inserting an artificial wooden perch directly under the heat lamp. Room
temperature was then lowered to between 18°C and 20°C to exaggerate
the thermal gradient within the pens, thereby encouraging the lizards to bask
on the perch. A piece of light blue cardboard was placed behind the perch to
standardise the contrast between the lizard and the background. Lizards were
allowed 1 week to acclimate to these new conditions before filming
commenced.
Illumination was provided by an 800-W photographic P2/11 tungsten–halogen lamp, which was angled to place the perch shadow out of camera frame. Recordings were made with a digital video camcorder (Canon XL1; optical resolution 625 lines; shutter speed 1/250 s; aperture F8). Focal length was then adjusted to ensure that the lizard appeared life-sized on the screen subsequently used for playback.
Recording and testing occurred between 08:00 h and 14:00 h, which
corresponds to the period of peak activity
(Ord, 2001
). A small aquarium
containing a male lizard was placed on the trolley below the camera and
concealed with a black cloth. When the subject lizard was visible on the
viewing monitor the tungsten–halogen lamp and video camera were switched
on and the black cloth removed. Filming continued until the subject lizard
left the perch.
Editing
Video footage of one lizard, (SVL 89 mm, mass 27 g), was used in
the playback experiment. This allowed us to manipulate the distribution of
displays over time without confounding variation in other parameters. Note
that this design is not pseudoreplicated because the domain of interest is
signalling rate, rather than morphology, display structure or other individual
characteristics. Our design hence maximises statistical power by controlling
irrelevant variation, although at the cost of not permitting tests for
possible interactions between signal rate and other attributes. Such questions
are outside the scope of the present study.
Footage was digitally transferred from a video editing program (Final Cut Pro 3.0, Apple Computer, Inc.) and assembled into sequences. Two clips were selected based on their consistent display structure (three push-up/body-rocks per display), giving 30 push-up/body-rocks with which to create playback stimuli. Displays were accompanied by tail-flicks and some gular expansion.
Eight sequences were created. Each was 14 min long and showed an empty
perch for the first 2 min, followed by the stimulus lizard inactive on the
perch for the next 2 min. The remaining 10 min showed the lizard performing a
series of push-up displays, separated by periods of inactivity. Each series
contained the same 30 unique push-up/body-rocks in the same order. The only
difference between them was the interval between displays, and hence the
number of push-up/body-rocks occurring per minute. Displays commenced in the
first 5 s of the minute and finished by 20 s. Intervals between
push-up/body-rocks in any 1 min fell within the range found in natural bouts,
as calculated by Ord and Evans (Ord and
Evans, 2003
). Thus, the displays within a single minute
constituted one bout.
The `constant', `initial' and `spike' sequences showed a display bout in each minute, but differed according to the number of push-up/body-rocks per bout (Table 1; Fig. 1A–C). In the `constant' sequence, each bout contained 3 push-up/body-rocks, whereas the first bout contained 6 push-up/body-rocks in the `initial' sequence and the fifth bout contained 9 push-up/body-rocks in the `spike sequence. The `pulsed' and `block' sequences both contained bouts of 6 push-up/body-rocks (Table 1, Fig. 1D,E). In the `pulsed' sequence, the bouts occurred in every second minute whereas in the `block' sequence they occurred every minute over the first 5 min. The escalation sequences consisted of 4 bouts containing 3, 6, 9 and 12 push-up/body-rocks (Table 2, Fig. 1F–H). In the `slow escalation' sequence, a bout occurred every third minute in increasing order of magnitude. The `fast escalation' sequence presented the same sequence, but with shorter intervals; bouts occurred every minute over the first 4 min. The `de-escalation' series was matched for rate of change to `slow escalation', but in the opposite direction; this presented a display bout every third minute, in decreasing order of magnitude.
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Playback experiment
Design
Experiment 1 tested for the effect of variation in the display rate/time
profile, while keeping the total number of push-up/body-rocks (PUBR) constant.
We systematically altered four display series parameters: initial rate,
maximum rate, concentration of displays within bouts and duration of display
behaviour, in five playback sequences (Fig.
1A–E).
Planned pair-wise comparisons between sequences allowed us to gauge the influence of each display series parameter. These were based on a priori predictions, as follows. If responses to sequences with an initial display rate of 6 PUBR min–1 differed from those to sequences with an initial display rate of 3 PUBR min–1, this would implicate initial display rate in opponent assessment. Similarly, if maximum display rate were important, then responses to the sequence with a maximum rate of 9 PUBR min–1 should differ from those to sequences with a maximum rate of 6 PUBR min–1, which in turn should differ from those to sequences with a maximum rate of 3 PUBR min–1. If opponent assessment were principally dependent upon the relative concentration of displays within bouts, then responses to sequences that averaged 6 PUBR/bout should differ from those to sequences that averaged 3 PUBR/bout. Finally, if the total duration of the display sequences (endurance) were an important factor, then responses to sequences that extended to 10 and 9 min should differ from those to the sequence that lasted only 5 min.
Experiment 2 tested for the effects of more global, monotonic change in display rate. We manipulated three display series parameters: presence of change, rate of change and direction of change, in four playback sequences (Table 2; Fig. 1D,F–H). As in the first experiment, playback sequences were designed to vary with respect to the three parameters, allowing us to assess the influence of each with planned pair-wise comparisons. The total number of push-up/body-rocks was held constant and the time in which displays occurred was kept between 4 and 5 min.
Planned comparisons were as follows. If monotonic rate change affected assessment, then responses to the sequence with no rate change should differ from those to the sequences with this characteristic. If the rate of change were a critical factor, then lizards would be expected to respond differently to the rapidly escalating sequence, compared to the other sequences. Similarly, if the direction of change were important, then responses to the positively escalating sequences should differ from those to the de-escalating sequence. Treatments also necessarily differed according to some of the parameters predicted in Experiment 1, allowing us to re-test these factors.
In both experiments, lizards viewed one playback sequence per day, with a 2-day break between presentations. This resulted in a 13-day testing period for Experiment 1 and an 11-day testing period for Experiment 2. In Experiment 1, each subject experienced a unique random presentation order. In Experiment 2, the number of subjects exceeded the number of possible combinations, so we ensured that no more than two lizards experienced any particular order of treatments.
Test procedure
Experiment 1 was carried out in March 2005 and Experiment 2 was conducted
in June of the same year. All subjects occupied their experimental pen for at
least 1 week prior to testing. Lizards typically exhibited normal
thermoregulatory and feeding behaviour within hours of being placed in a
pen.
We mounted some of the test equipment on a trolley, so that it could be positioned in front of each pen with minimal disruption to subjects. This included the stimulus presentation monitor (Sony PVM-14M2A; resolution >600 lines, screen size 34 cm measured diagonally), a CCTV camera (Panasonic WV-CP240) fitted with a wide-angle lens (Panasonic WV-LA210CSE) and a second monitor (Panasonic TC-1470Y) repeating the camera signal, to function as a viewfinder. Prior to testing, we calibrated the presentation monitor using PAL standard pluge bars (Final Cut Pro 3.0, Apple Computer).
The remaining test equipment remained static at one end of the room, allowing the experimenter to remain concealed behind the end wall of the lizard pens. This was linked by cables to the presentation system and included an S-VHS deck (Sony DVD Player/VCR SLV-D910) for recording subject responses and a computer (iMac G3) with a large external drive (LaCie 160GB) containing stimuli. Playback sequences were presented using Final Cut Pro 3.0 and transcoded back to S-video using a digital video converter (Canopus ADVC110).
Statistical analyses
Behavioural responses to the stimulus lizard were scored from test-session
video recordings. We measured the frequency of the following responses:
push-up/body-rocks, slow arm-waves, gular expansions, bouts of general
locomotion and `attacks', in which subjects touched the PerspexTM panel
in an apparent attempt to approach the stimulus. Gular expansion was often
sustained for many seconds; we therefore recorded duration to the nearest
second. Lizards that did not perform a social response (all behaviours except
general locomotion), during at least two stimulus presentations were excluded.
This criterion resulted in the removal from analyses of six animals in
Experiment 1 and five animals in Experiment 2. Another animal was excluded
from the analyses due to its extreme submissive behaviour.
Preliminary examination of the data revealed skewed distributions caused by
a high proportion of zero-counts. The resulting variances were greater than
their means (over-dispersed). The most appropriate method for analysing data
with these characteristics is negative binomial regression, a generalisation
of Poisson regression, which accounts for over-dispersion
(Gardner et al., 1995
;
Ridout et al., 1998
). We used
the statistical software package Stata (StataCorp LP, College Station, TX,
USA), which calculates negative binomial regression with a modified variance
estimate to account for within-subject correlations.
Playback type was entered as a dummy-coded explanatory variable in the model to directly examine the effects of varying the temporal properties of display sequences. We included the order of stimulus presentation as a second explanatory variable (also dummy-coded) to account for the potentially obscuring effects of habituation and sensitisation. Size is often an important determinant of agonistic behaviour. To control for this, we added individual SVL to the model.
The regression coefficients for the dummy codes and for the SVL
variables are interpreted as incidence-rate ratios (IRR), which are similar to
the odds-ratios of logistic regression. For example, an IRR of 0.5 for a
particular category means that response rates are 50% lower than those in the
reference category. The significance of the IRRs was examined using
Z-tests with P-values adjusted to control the proportion of
Type I errors across multiple comparisons (false discovery rate)
(Benjamini and Hochberg, 1995
).
This method is preferable to traditional Bonferroni-type procedures because it
retains statistical power and avoids Type II errors
(Garcia, 2004
;
Nakagawa, 2004
;
Verhoeven et al., 2005
). We
assessed the overall influence of the explanatory variables using the Wald
test (Sokal and Rohlf,
1995
).
| Results |
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The rate of push-up/body-rocks in the `pulsed' sequence was significantly less than the rate in both the `constant' and the `spike' sequences (pulsed:constant Z=–2.76, N=22, P=0.006; pulsed:spike Z=–2.68, N=22, P=0.007, critical P-value=0.01, Fig. 2B). The `block' sequence also suppressed the rate of push-up/body-rocks compared to the `constant' and `spike' sequence; however, these differences failed to reach statistical significance (block:constant Z=–2.19, N=22, P=0.028; block:spike Z=–2.30, N=22, P=0.022).
Duration of gular expansion seemed to be a particularly sensitive response assay, yielding several significant differences between treatments. The duration of gular expansion in the `initial', `pulsed' and `block' sequences was significantly less than that in the `constant' sequence (initial:constant Z=–2.75, N=22, P=0.006; pulsed:constant Z=–3.74, N=22, P<0.001; pulsed:spike Z=–3.07, N=22, P=0.002, critical P-value=0.025, Fig. 2C). Similarly, the duration of gular expansion in the `pulsed' and `block' sequences was significantly less than that in the `spike' sequence (block:constant Z=–3.87, N=22, P<0.001; block:spike Z=–3.22, N=22, P=0.001, Fig. 2C).
Consistent with assessment of the simulated opponent, there was a significant positive relationship between the subject's size and the rate of both slow arm-waves (Z=3.32, N=22, P=0.001) and gular expansion (Z=2.09, N=22, P=0.037). Presentation order was a significant factor in all behavioural responses except gular expansion (Table 3). The relationship between test day and response levels was generally curvilinear, with a peak over the middle days.
Experiment 2
Overall frequency of attacks and duration of gular expansion were
significantly influenced by playback treatment
(Table 4). Subsequent pair-wise
comparisons revealed significant differences, with subjects attacking the
stimulus at a lower rate in the `pulsed sequence compared to the `slow
escalation' sequence (pulsed:slow escalation Z=–3.02,
N=26, P=0.003, critical P-value=0.008,
Fig. 3A). Subjects also
attacked at a lower rate in the `fast escalation' sequence compared to the
`slow escalation' sequence; however, this difference did not reach statistical
significance (fast escalation:slow escalation Z=–2.15,
N=26, P=0.031).
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The duration of gular expansion in both the `fast escalation' and `de-escalation' sequences was significantly less than that in the `pulsed' sequence (fast escalation:pulsed Z=–2.72, N=26, P=0.007; de-escalation:pulsed Z=–2.87, N=26, P=0.004, critical P-value=0.017, Fig. 3B).
Locomotion and slow arm-waving exhibited a significant positive relationship with subject size (locomotion Z=2.79, N=26, P=0.005; slow arm-wave Z=2.11, N=26, P=0.035), whereas push-ups showed a significant negative relationship (Z=–2.81, N=26, P=0.005). In this experiment, which had fewer treatments, we did not detect effects for presentation order on any of our response measures, although gular expansion and attack approached significance (Table 4).
| Discussion |
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In Experiment 1 the two aggressive displays (gular expansion and push-up/body-rocks), provide the clearest response pattern with which to compare our predictions. The `pulsed', `block' and `initial' sequences suppressed the overall rate of aggressive displays, relative to the `constant' and `spike' sequences. In the case of gular expansion, all of these differences were highly significant, whereas for push-up/body-rocks, two differences were significant and another two approached significance (Fig. 2B,C). The most obvious distinction between these stimuli is the `concentration' (i.e. temporal clumping) of push-up/body-rocks. In the `pulsed' and `block' sequences, displays were arranged in fewer bouts, each containing more push-up/body-rocks (5 bouts with 6 PUBR/bout). In contrast, displays were more dispersed in the `constant' and `spike' sequences (10 bouts with 3 PUBR/bout).
These results are consistent with the idea that lizards were averaging the number of push-up/body-rocks per bout, such that highly concentrated sequences were perceived as more threatening. Note that the significant main effects for sequence type (Table 2) immediately exclude the cumulative assessment of push-up/body-rocks as a possibility; if subjects had simply been counting displays, then there would be no differences among the treatments. Similarly, responses were not influenced by the maximum number of push-up/body-rocks in any single bout. This allows us also to reject a `best-so-far' mechanism.
Our model of assessment processes can be further refined by examining the period in which a decision was made. The `block' sequence only showed displays in the first 5 min, yet responses differed from those to several other sequences (Fig. 3C). This implicates the first half of the display series as a likely assessment window. In addition, the `initial' sequence, which averaged 3.4 PUBR/bout over this period, triggered significantly lower levels of gular expansion that the `constant' treatment. This pattern of responses is precisely that which would be expected if opponent assessment were based upon the concentration of displays within the first few minutes of an interaction.
Results obtained in Experiment 2 lend qualified support to the idea of rapid assessment. Here, the rate of gular expansion was significantly lower in both the `fast escalation' and `de-escalation' treatments than in the `pulsed' treatment. Again, the concentration of displays in the first half of the sequence provides the key to understanding these differences. Push-up/body-rocks were highly concentrated in the first 5 min of the `fast escalation' and `de-escalation' sequences (7.5 and 10.5 PUBR/bout, respectively). In contrast, the `pulsed' sequence had a much lower level of display concentration during this period (6 PUBR/bout). The only anomaly in the pattern of responses is the lack of similar differences between the `slow-escalation' sequence and the `fast-escalation' and `de-escalation' sequences. It is possible that effect of the initially low display concentration (4.5 PUBR/bout) was eclipsed by subsequent increases in concentration.
The brief assessment window suggested by both experiments may in part reflect characteristics of the simulated interaction. Resident males viewed an intruder that was close, well lit and unobscured by vegetation. Errors associated with signal perception will hence have been minimised, relative to a natural signal exchange. Such conditions are optimal for rapid assessment. Playback studies in which signal perception was complicated by having the stimulus conspecific obscured to varying degrees and presented at greater distances would provide a direct test of the extent to which increased error rate prolongs assessment.
The pattern of results obtained in the present study implies an averaging
mechanism. As has already been argued
(Payne and Pagel, 1997
), the
averaging of actions to better estimate signal characteristics is evidence of
sequential assessment (Enquist and Leimar,
1983
). This model is based on the idea that information transfer
is inherently error-prone, such that repeated actions provide a more accurate
estimate of fighting ability. Models of the relation between relative fighting
ability, contest structure and the probability of winning necessarily fall
outside of the scope of the present study, because the behaviour of one
contestant was controlled and the interaction was unresolved. Note, however,
that most lizard contest studies designed to evaluate such models have
provided support for them (Earley et al.,
2002
; Jenssen et al.,
2005
; Lopez and Martin,
2001
; Molina-Borja et al.,
1998
; Olsson,
1992
).
Of particular relevance to our findings is the assumption that sequential
assessment requires signal reliability to be enforced by physical constraints
(Enquist and Leimar, 1983
). A
commonly used illustration of this type of signalling is the display behaviour
of cichlid fish (Enquist and Leimar,
1983
). A competitor's size is revealed by lateral displays, its
weight by tail beating, and its strength by mouth wrestling. Small, light,
weak, fish simply cannot perform these signals at the same level as large,
heavy, strong ones (Hurd and Enquist,
2005
). The responses of Jacky dragons were consistent with the
sequential assessment model, so we anticipate that the same logic is likely to
apply to push-up display sequences: only a subset of individuals within the
population should be capable of consistently performing highly concentrated
display bouts. Short-term temporal structure of display sequences might thus
reflect individual variation in a physical attribute such as strength.
Assessing an opponent's strength is likely to be important, as muscle capacity
(i.e. bite force) has been found to predict fight outcome in several lizard
species (Husak et al., 2006
;
Huyghe et al., 2005
;
Lailvaux et al., 2004
).
Current knowledge of lizard displays is not sufficient to identify the
physical constraints on short-term display rate, as this signalling parameter
has not been examined in physiological studies. The relationship between
overall display rate in a contest situation and endurance is not strong, at
least in the iguanian lizard species that have been tested in laboratory
studies (Brandt, 2003
;
Osborne, 2005
). For example,
halving the endurance capacity of male side-blotched lizards Uta
stansburiana significantly reduced the duration of lateral compression,
but not the number of push-ups (Brandt,
2003
). If this is a lineage-wide phenomenon, it may help to
explain why the Jacky dragons in our study did not rely on the cumulative
number of displays for opponent assessment. Perry et al.
(Perry et al., 2004
) did
report that field counts of `broadcast' displays performed by male crested
anoles Anolis cristatellus predicted both success in staged fights
and endurance levels. Broadcast displays are performed spontaneously, in the
absence of a visible opponent, and are therefore probably designed to
communicate over longer distances
(DeCourcy and Jenssen, 1994
).
Hence it is possible that assessment strategies might be distance-dependent,
in such a way that intra-bout characteristics only function as a useful
predictor of fighting ability in close-range encounters.
Most of the behavioural responses in Experiment 1 varied in a curvilinear
fashion over successive test days. This pattern, which was also observed in a
previous video playback study involving Jacky dragons
(Ord and Evans, 2003
),
probably reflects the competing forces of sensitisation and habituation.
Interactions necessarily ended with the intruder disappearing and the
residents remaining in their familiar pen. The perceived threat posed by the
video lizard may have therefore decreased over time, resulting in elevated
response levels. Conversely, each stimulus sequence depicted the same
individual, performing the same displays in the same order. The potential for
responses to decrease due to habituation was hence probably quite high
(Van Dyk and Evans, 2007
).
Order effects are a common feature of video playback studies
(Burford et al., 2000
) and of
the repeated presentation of stimuli more generally
(Peeke and Peeke, 1973
).
Experimenters should use caution when determining presentation order, so as to
avoid systematic biases (Rosenthal,
1999
). We selected presentation order at random and included it as
a factor in our analyses to prevent it from obscuring our results (see
Materials and methods).
Competing animals of many taxa are sensitive to the temporal
characteristics of repeated aggressive signals (see Introduction). Although
there has been much previous work with staged contests and signal playback
(Adhikerana and Slater, 1993
;
Briffa and Elwood, 2000a
;
Briffa and Elwood, 2000b
;
Burmeister et al., 2002
;
Clutton-Brock and Albon, 1979
;
Ord and Evans, 2003
), we
believe that the present study is the first experimental characterisation of
the mechanism underlying the assessment of a repeated threat display in any
modality. Understanding the way in which receivers perceive signals and
integrate information over time provides a new insight into the `rules'
governing aggressive interactions and the processes that constrain signal
reliability.
| Acknowledgments |
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| References |
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