Ecol Res (2006) 21:617–623
DOI 10.1007/s11284-006-0159-9
O R I GI N A L A R T IC L E
Marcelo N. Rossi Æ Carolina Reigada
Wesley A.C. Godoy
The effect of hunger level on predation dynamics in the spider
Nesticodes rufipes: a functional response study
Received: 23 August 2005 / Accepted: 10 January 2006 / Published online: 20 May 2006
! The Ecological Society of Japan 2006
Abstract It is well known that a predator has the potential to regulate a prey population only if the predator
responds to increases in prey density and inflicts greater
mortality rates. Predators may cause such densitydependent mortality depending on the nature of the
functional and numerical responses. As spiders are
usually faced with a shortage of prey, the killing
behavior of the spider Nesticodes rufipes at varying
densities of Musca domestica was examined here through
laboratory functional response experiments where spiders were deprived of food for 5 (well-fed) or 20 days
(hungry). An additional laboratory experiment was also
carried out to assess handling time of spiders. The
number of prey killed by spiders over 24- and 168-h
periods of predator–prey interaction was recorded. Logistic regression analyses revealed the type II functional
response for both well-fed and hungry spiders. We found
that the lower predation of hungry spiders during the
first hours of experimentation was offset later by an increase in predation (explained by estimated handling
times), resulting in similarity of functional response
curves for well-fed and hungry spiders. It was also observed that the higher number of prey killed by well-fed
spiders over a 24-h period of spider–prey interaction
probably occurred due to their greater weights than
hungry spiders. We concluded that hungry spiders may
be more voracious than well-fed spiders only over longer
time periods, since hungry spiders may spend more time
handling their first prey items than well-fed spiders.
M. N. Rossi (&)
Departamento de Botânica, IB, Universidade Estadual
Paulista (Unesp), Botucatu, Sao Paulo, Brazil
E-mail: mnrossi@ibb.unesp.br
Tel.: +55-1438116265
Fax: +55-1438153744
C. Reigada Æ W. A. Godoy
Departamento de Parasitologia, IB, Universidade Estadual
Paulista (Unesp), Botucatu, Sao Paulo, Brazil
Keywords Nesticodes rufipes Æ Musca domestica Æ
Functional response Æ Predator–prey interaction Æ
Poultry house Æ Shortage of prey
Introduction
To evaluate the role of spiders in regulating insect
populations in many natural systems, it is vital to know
their foraging response when faced with fluctuations in
prey population densities (Riechert and Lockley 1984;
Wise 1993). In the case of increasing prey populations,
spiders can react in two ways: either by increasing the
consumption by individuals (functional response) or by
increasing their own density (numerical response). These
concepts were proposed by Solomon (1949) and developed further by Holling (1959).
The functional response is defined as the temporal
rate at which an individual predator kills prey. Thus, the
functional response is a double rate: it is the average
number of prey killed per individual predator per unit of
time (Holling 1959; Turchin 2003). Most studies of this
response have been performed in the laboratory, since
field studies are technically difficult (Marc et al. 1999). In
type I functional responses, the number of prey killed
increases linearly to a maximum then remains constant
as prey density increases. This corresponds to a constant
proportion of available prey killed to the maximum
number (density independence), followed by a declining
proportion of prey killed. In type II functional responses, the number of prey killed approaches the
asymptote hyperbolically as prey density increases. This
corresponds to an asymptotically declining proportion
of prey killed (inverse density dependence). In type III
functional responses, the number of prey killed approaches the asymptote as a sigmoid function. This
corresponds to an increase in the proportion of prey
killed (density dependence) to the inflection point of the
sigmoid curve, followed by a decrease in the proportion
of prey killed (Juliano 2001).
618
The type II functional response is predominant for
spiders, whereas types I and III are less common (Heong
et al. 1991; Mansour and Heimbach 1993; Samu and
Biro 1993; Wise 1993; Denno et al. 2004). However, the
type of functional response exhibited by spiders is quite
variable. For example, Riechert and Lockley (1984)
observed the presence of type III functional response for
several spiders, even though of the five papers that they
cite, three provide no clear support for a type III response (Kiritani and Kakiya 1975; Mansour et al. 1980).
Nakamura (1977) found both type II and III responses
by lycosids, and the most pronounced type III response
occurred with leafhopper prey. The author argued that
accelerated rates of predation at higher densities resulted
from greater prey activity due to increased interference
among leafhoppers in the rice seedlings in the experimental container. Haynes and Sisojevic (1966) also observed type III functional response for a crab spider due
to increased activity of the prey at higher densities.
Shortage of prey seems to be a very important
selective factor in the evolution of foraging strategies of
spiders because spiders can survive for long periods
without eating (Framenau et al. 2000). Most researches
that have studied the effects of a varying food supply on
foraging spiders concentrate on energetic investment,
such as changes in foraging site, or adjustments to the
architecture of the web (Janetos 1982; Provencher and
Riechert 1991; Bradley 1993; Lubin and Henschel 1996;
Herberstein et al. 2000). However, only a few studies
have investigated the effect of different hunger levels on
the killing behavior of spiders (Holling et al. 1980;
Bridge and Wootton 1998; Framenau et al. 2000;
Herberstein et al. 1998, 2000).
Nesticodes rufipes (Lucas) (Araneae: Theridiidae)
(referred to as Theridion rufipes in references) is widely
distributed in tropical and subtropical regions, extending to temperate zones; the spiders construct irregular
webs with a disordered aspect (González 1989). Their
exact distribution is not easy to determine, since they are
strongly associated with humans (Downes 1988; González and Estévez 1988; González 1989). Behavioral and
ecological studies considering predation by N. rufipes are
scarce. Fox (1998) highlighted the strategic importance
of these spiders in the natural control of the mosquito
Aedes aegypti (L.) (Diptera: Culicidae), since the spiders
incorporate a paralyzing substance in their webs that
paralyzes the mosquitoes on contact, increasing their
capture efficiency. Barreto et al. (1987) also mentioned
the importance of N. rufipes as predators of Rhodnius
prolixus (Stal) (Hemiptera: Reduviidae).
Musca domestica (L.) (Diptera: Muscidae) has a
cosmopolitan distribution and high synanthropic indices
(Smith 1986; Ferreira and Lacerda 1993), and also is of
considerable medical and veterinary importance (Harwood and James 1979; Smith 1986; Levine and Levine
1991). This species lives in human dwellings, poultry
houses, supermarkets and garbage, being reared on a
wide variety of substrates such as food and vertebrate
excrement (Axtell and Arends 1990; Bowman 1995).
Although there are some chemical techniques aimed at
controlling M. domestica in poultry houses, inappropriate application of chemicals has intensified the search
for potential natural enemies of houseflies (Cunha and
Lomônaco 1996). Therefore, understanding the strength
of interspecific interactions between M. domestica and
its predators is of major importance.
As M. domestica (adults) is usually seen in N. rufipes
webs in poultry houses (Rossi and Godoy 2005), it is
necessary to characterize the type of functional response
exhibited by this predator when houseflies are offered as
prey in order to determine the inherent ability of this
predator to regulate densities of prey population. Yet,
since spiders are usually faced with prey shortage, it is
important to understand the underlying mechanisms of
the killing behavior that spiders experience at different
hunger levels. Thus, the specific objectives of this study
were to (1) investigate the ability of ‘‘well-fed’’ and
‘‘hungry’’ N. rufipes to kill housefly individuals (voracity) and assess characteristics of their predation
dynamics (functional response) during the course of
predator–prey interaction, and (2) estimate handling
time exhibited by well-fed and hungry spiders as a basis
for understanding the killing behavior observed.
Materials and methods
Sampling and rearing of houseflies and spiders
An experimental poultry house located in the city of
Botucatu, SP (Brazil) (22!52¢20¢¢S; 48!26¢37¢¢W) was
chosen to collect larvae of houseflies. We removed larvae
from small samples of chicken feces deposited below the
cages, and put them into small glass tubes. All insects
were then taken to the laboratory and reared in vials
containing wet ground animal ration (25!C under 12-h
light). After pupation, vials were kept in cages of nylon
mesh on a wood frame (30·30·30 cm) where water and
sugar were provided for adults.
Adult females of N. rufipes were captured in several
buildings located on the campus of the University of the
State of São Paulo (Botucatu, Brazil) from January–
March 2003, and kept individually in cylindrical plastic
containers (5.0 cm in height · 8.5 cm of diameter) in the
laboratory (25!C under 12-h light). All spiders were of
similar size (15 mm of body length) and were fed with
adult houseflies for 1 month (insects were randomly
offered twice a week) in order to attain similar
nutritional status.
Functional response study
For the functional response experiment, spiders were
placed individually in large cylindrical plastic containers [11.5 cm in height · 10.5 cm of diameter (900 ml)],
with one spider per container, with a nylon mesh
(10·3 cm) internally fixed in each container in order to
619
allow spiders to build their webs. As spiders usually
fixed their small webs right below the lids during the
period of experimentation, the containers were suitable
for carrying out the experiments. We observed that
larger containers would reduce predator–prey interaction significantly as only a small fraction of prey
available for consumption would be captured. The
experiment was a randomized complete block (5·2
factorial) with five prey densities (3, 5, 10, 15 or 20
adult flies per container) and two hunger levels of
spiders (deprived of food for 5 and 20 days). Each
treatment combination was repeated 15 times with
different spiders for each replicate.
After the respective periods without eating, spiders
were individually weighed (grams) by using a semianalytical scale, and a Student’s t-test (Zar 1999) was
run comparing the mean weights of spiders deprived of
food for 5 (well-fed) and 20 days (hungry). Immediately
before adding prey into the spider containers, flies were
immobilized by chilling in a freezer for 3 min, removed
from cages, and placed in a Petri dish. When flies started
to move, all insects were carefully dropped in the bottom
of a spider container, without touching the spider web.
This procedure prevented flies from being captured
quickly due to their flying ability and it insured that flies
could be easily separated prior to the experiments. In the
first 2 min (approximately) inside the spider containers,
flies just walked and then started flying.
Spider and prey interacted for 168 h (7 days), after
which we determined the number of prey killed (sucked
and wrapped insects) by subtracting the number of
remaining insects (living and intact dead individuals)
from the density of prey offered. To reduce the mortality
of flies during the experiment, water and sugar were
provided ad libitum for adults (piece of cotton soaked in
honeydew solution). Dead flies fixed on the web that
were not sucked or not even wrapped were also computed as intact dead individuals. In order to keep densities of flies constant, intact dead individuals were
replaced with new living flies in each container at 24-h
intervals during the 168 h of experimentation. As spiders
generally kill more prey than they consume, we defined
functional response in terms of the number of prey
individuals killed, rather than eaten. We also recorded
the number of prey killed over 24 h of predator–prey
interaction because it was expected that all spiders
would be well-fed after consumption of the first prey
items, even those spiders deprived of food for 20 days.
Therefore, we predicted that the handling time and
consumption of prey by spiders from different hunger
levels could vary during experimentation, changing the
predation dynamic. The time of 168 h for predator–prey
interaction was necessary because it provided enough
data (number of prey killed) for fitting to the functional
response model.
To assess possible variation in the predation dynamic
during the course of spider–prey interaction, three
ANOVA [5·2 factorial design (see above)] were run. The
first two ANOVA compared the mean number of prey
killed over 24 and 168 h of spider–prey interaction,
respectively (Zar 1999). The third ANOVA also compared the mean number of prey killed by spiders over
168 h of interaction; however, data from the first 24 h of
interaction were not considered in this case. Therefore,
we could compare the voracity (the ability of spiders to
kill prey) between well-fed and hungry spiders at distinct
moments. When significant differences were found
between hunger levels, Student’s t-tests (Zar 1999) were
run to compare mean values.
We determined the relationship between prey density
and the number of prey killed (functional response) by
spiders at both hunger levels by performing logistic
regressions (PROC CATMOD) on the proportion of
prey killed vs. density of prey offered (Trexler et al. 1988;
Juliano 2001; SAS 2001). For predator functional response, logistic regression is particularly useful in distinguishing between type II and type III responses,
which are not easily determined by nonlinear regressions
that use the number of prey eaten as the dependent
variable. The proportion of prey eaten declines monotonically with prey density in a type II response but is
positively density-dependent over some range of prey
densities in a type III response. The sign of the linear
coefficient estimated by the logistic regression can be
used to distinguish the shape of the functional response
curve. Significant negative or positive linear coefficients
from the regression indicate type II or type III, respectively (Trexler et al. 1988; Messina and Hanks 1998;
De Clercq et al. 2000; Juliano 2001).
Because logistic regression analysis indicated that our
data fit the type II response for spiders in both hunger
levels, further analysis was restricted to the type II response. The ‘‘random predator equation’’ (Royama
1971; Rogers 1972) was used to describe the functional
responses because it allows for prey depletion during the
course of the experiment. The form of the type II
equation is as follows:
Ne ¼ N f1 " exp ½"aðT " Th Ne Þ&g
where Ne is the number of prey killed; N, the number of
prey offered; T, the total time available for the predator,
which in this case is 168 h; a is the attack rate; and Th is
the handling time. Using the SAS statistical package
(SAS 2001) we carried out nonlinear regressions, using
the least squares method to estimate the predator’s attack rate (a) and handling time (Th) considering predation by spiders at both hunger levels. Further, plots
showing the observed and predicted number (data fitted
to random predator equation) of prey killed at a given
prey density were also determined for both hunger
levels.
Laboratory assessment of handling time
To estimate the handling time (Th) directly, an additional experiment was set up. As above, spiders were
removed from the plastic rearing containers, and placed
individually in large plastic containers [11.5·10.5 cm
(900 ml)]. Five prey densities (3, 5, 10, 15 or 20 adult flies
per container) were offered to spiders exposed to two
hunger levels (deprived of food for 5 and 20 days). Each
treatment combination was repeated five times with
different spiders for each replicate. Containers were
filmed for 24 h in the laboratory (25!C under 12-h light),
and images recorded on a Time Lapse videocassette. We
estimated handling time directly only during 24 h of
experimentation because it was the maximum time that
our cameras could shoot prey consumption accurately.
As nine-color cameras were available for shooting, a
multiplexer was coupled to the video. Therefore, the
monitor (29¢¢) was divided in nine quadrates with each
receiving images from a specific container. Each camera
was rested on an iron support positioned at a standard
distance of 5 cm from the top of the container. Thus,
images were obtained with accurate resolution. Immediately before shooting, prey was added to the containers as described above. As all containers could not be
shot simultaneously, each treatment combination was
selected randomly.
Time from the capture of prey until its abandonment
by the predator was considered handling time. Correlations of handling time with prey densities were run for
well-fed and hungry spiders. Finally, the nonparametric
Mann-Whitney U-test (Zar 1999) was computed, comparing the handling time between well-fed and hungry
spiders.
Results
Comparison of mean weights of spiders showed that
spiders deprived of food for 20 days weighed less than
spiders deprived of food for 5 days (t=5.992, df=148,
P<0.05, n=75 for each hunger level). During 24 h of
predator–prey interaction, the mean number of prey
killed by spiders differed between hunger levels
(F=18.140, MS=41.294, P<0.0001), as hungry spiders killed significantly less prey than did well-fed
spiders (Fig. 1a). Even though the mean number of
prey killed among densities was also significant
(F=5.550, MS=12.633, P<0.0005), data did not fit
well into the random predator model (r2<0.20 for
both hunger levels). Therefore, only data of prey killed
over 168 h of predator–prey interaction were fitted to
the model. During 168 h of predator–prey interaction,
differences in prey killed between hunger levels were
not significant when all data were considered
(F=2.220, MS=11.162, P=0.1386); however, after
removing data from the first 24 h of interaction, the
mean number of prey killed was significantly different
(F=22.861, MS=95.394, P<0.0001). Curiously, hungry spiders killed significantly more prey than well-fed
spiders in this case (Fig. 1b). The mean number of
prey killed among densities was significant for both
situations (F=62.467, MS=314.104, P<0.0001; and
F=49.851, MS=202.020, P<0.0001).
Mean (+/-SD) number of prey killed
620
10
a)
8
Well-fed spiders
Hungry spiders
b)
6
4
2
0
Hunger level
Fig. 1 Mean (±SD) number of adults of Musca domestica killed
by spiders deprived of food for 5 (well-fed) and 20 (hungry) days. a
Comparison computed over 24 h of predator–prey interaction.
Means differed statistically according to Student’s t-test (t=4.178,
df=142, P<0.05). b Comparison computed over 168 h of
predator–prey interaction without considering data from the first
24 h of interaction. Again, means differed statistically by Student’s
t-test (t=!2.770, df=142, P<0.05). For each hunger level, n=72
(three spiders died during experimentation)
Logistic regression analyses indicated a type II
functional response for both hunger level conditions
(Fig. 2), and estimates of the linear coefficients were
significantly different from zero (P<0.01; Table 1).
Model-estimated attack rates for well-fed and hungry
spiders were 0.20 and 0.40 h!1, respectively. Modelestimated handling times for well-fed and hungry spiders
were 18.22 and 14.09 h, respectively.
Correlations of direct estimation of handling times
with initial prey numbers offered were also not significant for well-fed (r2=0.1608, P=0.4426, n=25), and
hungry spiders (r2=!0.0548, P=0.7949, n=25). Handling times estimated directly were significantly different
between well-fed [3.68 h (median); 2.46 (quartile range)]
and hungry spiders [5.08 h (median); 3.32 (quartile
range)], and hungry spiders spent significantly more time
handling a prey item (U=209.0, P<0.05, n=25 for each
hunger level).
Discussion
Nesticodes rufipes exhibited a type II functional response
at both hunger levels against M. domestica. However,
parameters estimated by the random predator equation
demonstrated that the well-fed spiders had a lower attack rate and greater handling time than the hungry
spiders over 168 h of predator–prey interaction. Consequently, differences in attack rate and handling time
indicated that hungry spiders were more voracious while
capturing and killing prey. Nevertheless, the number of
prey killed by spiders at both hunger levels was not
significantly different over 168 h of interaction.
Although the same type of functional response was
observed for both hunger levels, predation data for
hungry spiders presented a greater coefficient of determination (Fig. 2b) than that of well-fed spiders
621
Number of prey killed
16 (a)
14
r2 = 0.46
12
10
8
6
4
2
0
0
4
8
12
16
Number of prey offered
20
24
20
24
Number of prey killed
16 (b)
14
r2 = 0.53
12
10
8
6
4
2
0
4
8
12
16
Number of prey offered
Fig. 2 Functional response of Nesticodes rufipes to increasing
densities of Musca domestica during 168-h period. Logistic
regressions showed that spiders at both hunger levels exhibited a
type II functional response across the range of prey densities
offered. a Spiders deprived of food for 5 days (well-fed). b Spiders
deprived of food for 20 days (hungry). Each data point represents
the observed number of M. domestica killed. Curves were fitted
using the random predator equation (see Materials and methods)
(Fig. 2a), indicating a higher variation of predation for
the latter. It may explain why many studies of functional
response set up in the laboratory keep predators under
deprivation of food for some pre-established periods,
since in this case, data may fit better to models. Hence, it
is very important to know how often specific predators
go without feeding in nature; otherwise there is a risk of
such experiments showing inaccurate data.
We observed that N. rufipes usually fixed their small
webs right below the lids of the containers during the
period of experimentation. With webs covering a limited
space, this particular container size enabled spiders to
catch good numbers of prey, therefore, data fitted
properly to the functional response model. As we were
interested in testing the effect of the hunger level on
predation dynamics of this spider, this container size was
suitable to investigate this question. According to Fox
(1998) this spider incorporates a paralyzing substance in
the webs, which increases prey capture. However, we did
not observe such an effect in our study. In fact, most flies
escaped from webs when not captured or bitten quickly
by spiders. It is possible that such a paralyzing substance
may have detectable effects only on small or lightweight
prey.
Physiological responses of spiders to starvation suggest they have experienced food shortages frequently
throughout their evolutionary history. Older instars of
numerous species can survive long periods without
feeding (Anderson 1974; Wise 1993). Spiders survive
when deprived of prey by maintaining a relatively
motionless sit-and-wait foraging strategy, and by
decreasing their metabolic rate (Nakamura 1972;
Anderson 1974; Tanaka and Itô 1982; Tanaka et al.
1985). Thus, in our study 20 days was the longest time
that spiders went without eating, which is much closer to
natural situations. Although our laboratory-measured
functional response of N. rufipes may not exactly correspond to field situations, this study presents important
results because females of N. rufipes may experience long
periods without consuming any prey in the field.
It is known that a predator has the potential to
regulate densities of its prey only if the mortality rate it
inflicts is density-dependent, which can occur if the
predator displays a type III functional response (Holling
1959; Wise 1993). However, robust type III functional
responses are probably not common among spiders.
Many results suggest that most type III responses by
spiders result from elevated prey activity at higher prey
densities rather than from learning or modification in
foraging behavior by spiders (Haynes and Sisojevic
1966; Nakamura 1977; Riechert and Lockley 1984). Our
data corroborate most studies of functional response by
spiders (Kajak 1978; Heong et al. 1991; Mansour and
Heimbach 1993; Samu and Biro 1993; Wise 1993; Finke
and Denno 2002) because we observed the type II
functional response, at least for the densities of prey
offered, which implies lack of regulation of M. domestica
population by N. rufipes.
Table 1 Results of logistic regression analysis of the proportion of adults of Musca domestica killed by Nesticodes rufipes at two hunger
levels over 168 h of predator–prey interaction against initial prey numbers offered (all analyses were significant at P<0.01)
Hunger level
Parameter
Estimate
SE
v2
P
Deprived of food for 5 days
Intercept
Linear
Quadratic
Cubic
Intercept
Linear
Quadratic
Cubic
9.2236
!1.7733
0.1350
!0.00354
14.1757
!2.9586
0.2285
!0.00584
2.4801
0.6208
0.0489
0.00121
4.1679
0.9715
0.0725
0.00173
13.83
8.16
7.61
8.54
11.57
9.27
9.93
11.42
0.0002
0.0043
0.0058
0.0035
0.0007
0.0023
0.0016
0.0007
Deprived of food for 20 days
622
As already discussed, the mean number of prey killed
did not differ between well-fed and hungry spiders over
168 h of predator–prey interaction (Fig. 2). However,
over 24 h of interaction, the risk of predation of
M. domestica adults by N. rufipes differed markedly
between spiders at both hunger levels. Well-fed spiders
killed significantly more prey than hungry spiders
(Fig. 1a), and this is explained by their significantly
lower handling times. Perhaps, as hungry spiders spent
more time on each captured prey, they ingested more
food from a lower number of prey than well-fed spiders,
resulting in different tactics of food ingestion between
the two spider groups.
Basically, data from this study indicated that the
killing behavior of N. rufipes toward M. domestica is
dynamic and may be dependent on the hunger level,
because during the first 24 h of interaction, well-fed
spiders spent less time handling prey, and consequently
killed more prey, while hungry spiders, according to the
model, spent less time handling prey during 168 h of
interaction. Therefore, if we had observed predation
only during the first 24 h of predator–prey interaction, it
would lead us to conclude that well-fed spiders were
more voracious than hungry spiders. However, lower
predation of hungry spiders during the first hours of
experimentation was offset later by an increase in predation, justifying similar functional response curves
(Fig. 2a, b).
In conclusion, we believe that the higher number of
prey killed by well-fed spiders during 24 h of predator–
prey interaction occurred due to their greater weights
than those of hungry spiders, which resulted in more
storage of resources and increasing fitness for prey
capture. However, after eating the first prey items,
hungry spiders also became well-fed and then killed
more prey than well-fed spiders due to having previously
experienced shortage of prey. This is a very interesting
finding, since it implies that hungry spiders may be more
voracious than well-fed spiders only over longer time
periods, since hungry spiders may spend more time
handling their first prey items than well-fed spiders.
Acknowledgements We thank Professors José Ricardo and James
Welsh for providing statistical advice and for revising the text of
the manuscript, respectively. M.N. Rossi and C. Reigada are particularly grateful to Fapesp (Fundação de Amparo à Pesquisa do
Estado de São Paulo) for financial support. W.A.C. Godoy has
been supported by a research fellowship from Conselho Nacional
de Desenvolvimento Cientı́fico e Tecnológico.
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