Anim Cogn (2016) 19:181–192
DOI 10.1007/s10071-015-0925-6
ORIGINAL PAPER
Evidence of self-organization in a gregarious land-dwelling
crustacean (Isopoda: Oniscidea)
Pierre Broly1 • Romain Mullier2 • Cédric Devigne2 • Jean-Louis Deneubourg1
Received: 11 June 2015 / Revised: 14 September 2015 / Accepted: 14 September 2015 / Published online: 21 September 2015
! Springer-Verlag Berlin Heidelberg 2015
Abstract How individuals modulate their behavior
according to social context is a major issue in the understanding of group initiation, group stability and the distribution of individuals. Herein, we investigated the
mechanisms of aggregation behavior in Porcellio scaber, a
terrestrial isopod member of the Oniscidea, a unique and
common group of terrestrial crustaceans. We performed
binary choice tests using shelters with a wide range of
population densities (from 10 to 150 individuals). First, the
observed collective choices of shelters strengthen the
demonstration of a social inter-attraction in terrestrial isopods; especially, in less than 10 min, the aggregation
reaches its maximal value, and in less than 100 s, the
collective choice is made, i.e., one shelter is selected. In
addition, the distribution of individuals shows the existence
of (1) quorum rules, by which an aggregate cannot emerge
under a threshold value of individuals, and (2) a maximum
population size, which leads to a splitting of the populations. These collective results are in agreement with the
individual’s probability of joining and leaving an aggregate
attesting to a greater attractiveness of the group to migrants
and greater retention of conspecifics with group size. In this
respect, we show that the emergence of aggregation in
terrestrial isopods is based on amplification mechanisms.
Electronic supplementary material The online version of this
article (doi:10.1007/s10071-015-0925-6) contains supplementary
material, which is available to authorized users.
& Pierre Broly
[email protected]
1
Unité d’Ecologie Sociale, Université Libre de Bruxelles,
Campus de la Plaine, Brussels, Belgium
2
Laboratoire Ecologie & Biodiversité, Faculté de Gestion,
Economie & Sciences, UCLILLE, Lille, France
And lastly, our results indicate how local cues about the
spatial organization of individuals may favor this emergence and how individuals spatiotemporally reorganize
toward a compact form reducing the exchange with the
environment. This study provides the first evidence of selforganization in a gregarious crustacean, similar as has been
widely emphasized in gregarious insects and eusocial
insects.
Keywords Woodlice ! Aggregation ! Collective
behavior ! Density-dependent ! Amplification
Introduction
Aggregation is one of the most basic and widespread
behaviors in the arthropods and frequently emerges from a
social origin (Parrish and Edelstein-Keshet 1999). In particular, the adaptive values of gregariousness have been
intensively studied in many contexts (Krause and Ruxton
2002; Courchamp et al. 2008), and aggregation behavior
has been shown to be an effective response to environmental pressures, such as predation, temperature and water
deficit (see the benefits of aggregation in terrestrial isopods
in Broly et al. 2013). The effects stemming from the group
vary at the group level according to group features such as
size and also at the individual level according to the spatial
position of an individual within the group (Krause 1994;
Morrell and Romey 2008).
In parallel, numerous studies focused on the mechanisms necessary to form aggregations and establish collective decisions, especially in eusocial insects (e.g.,
Deneubourg and Goss 1989; Bonabeau et al. 1997; Theraulaz et al. 2003; Couzin and Franks 2003; Detrain and
Deneubourg 2008). However, it is only recently that
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particular attention has been focused on lower levels of
insect sociality and especially to their collective choices,
i.e., to their ability to make consensus decisions, for
example to select an aggregation site (e.g., Jeanson et al.
2005; Costa 2006; Amé et al. 2006; Sempo et al. 2009;
Ringo and Dowse 2012; Boulay et al. 2013; Nilsen et al.
2013; Durieux et al. 2014). Included into the self-organization theory, these studies have described the rules—
based on mutual attraction to conspecifics—required for
the emergence and cohesion of groups in insects (Camazine et al. 2003; Jeanson et al. 2012). Nevertheless, the
knowledge about the influence of social interactions on
collective behaviors in other successful and ecologically
important groups of arthropods, such as Crustacea, is
sparser and rather descriptive (Berrill 1975; Farr 1978;
Jensen 1991; Eggleston and Lipcius 1992; Evans et al.
2007; Thiel 2011).
Gregarious terrestrial isopods (Crustacea: Isopoda:
Oniscidea), which are important primary macro-decomposers in soil ecosystems (Zimmer 2002), represent a particularly interesting model for the study of aggregation
mechanisms in successful land colonizer arthropods. First,
Oniscidea is the largest strictly terrestrial suborder among
the crustaceans and the establishment of their social system
is viewed as an important step in the process of terrestrialization (Warburg 1968; Broly et al. 2013). Thus, this
group provides a unique opportunity to perform a comparison of the proximal causes of pre-social behavior in
arthropods. This reflection raises important questions about
the diversity of behavioral rules in the living world. Second,
terrestrial isopods present variable abundance in the field,
frequently showing particularly high population density
(e.g., Sutton 1972; Paoletti and Hassall 1999; Gongalsky
et al. 2005; Topp et al. 2006; Quadros and Araujo 2008;
Tajovský et al. 2012). Thus, this group provides the
opportunity to explore, on a large scale, the density-dependent processes involved in the gatherings of arthropods.
This study is the first detailed description of the mechanisms governing collective decisions in aggregation
behavior in terrestrial isopods. The experimental results
were obtained using a particularly wide range of population
densities, which allowed us to assess the robustness of the
behavior according to the density context and the influence
of individual rules on the observed collective patterns;
especially, how the modulation of social context affects the
spatiotemporal distribution of individuals is a central issue.
We provide a series of indices that show how population
size affects the dynamics of the aggregation process, the
individual residence time within an aggregate and the
shape of the aggregate. The articulation and simplicity of
the mechanisms we describe, especially the density-dependent probabilities of joining and leaving an aggregate,
fit perfectly into the theory of self-organization applied to
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Anim Cogn (2016) 19:181–192
more or less complex social insects, such as cockroaches or
ants (e.g., Depickère et al. 2004; Jeanson et al. 2005).
Materials and methods
Biological material
This study makes use of the gregarious cosmopolite species
Porcellio scaber Latreille 1804 (Crustacea, Isopoda,
Oniscidea). Isopods were captured in the gardens of the
Catholic University of Lille (northern France; 50!37.580 N,
3!20.470 E) and reared under laboratory conditions [temperature: 22 ± 2 !C, relative humidity (RH) [80 % and
the natural photoperiod of the region] in boxes
(410 9 240 9 225 mm) containing one hundred of individuals per box. The sex ratio of the natural population was
maintained (not controlled). Individuals were fed leaf litter
consisting primarily of maple leaves. Poplar bark pieces
were also provided to offer shelters for woodlice.
Experimental setup and procedures
Groups of 10 (n = 20), 20 (n = 20), 40 (n = 29), 60
(n = 20), 80 (n = 20), 100 (n = 18) or 150 (n = 15)
woodlice were introduced (natural sex ratio) in a binary
choice setup. This setup consisted of a circular arena
(193 mm in diameter) containing two strictly identical
shelters (Fig. 1). Each shelter was a round glass (3.5 cm in
diameter) stuck to the wall of the arena (0.5 cm above the
ground), and the two were diametrically opposed. They
were covered with red filters (ROSCO" ref. Roscolux Fire
Fig. 1 Experimental setup including the groups of woodlice in the
binary choice test
Anim Cogn (2016) 19:181–192
# 19), which reduced the brightness under the shelters by a
factor of 4 (41 lux in the shelter vs. 166 lux in the arena). A
sheet of white paper covered the bottom of the setup and
was changed between each experiment. According to the
setup size, the density of population inside ranges between
340 and 5070 ind/m2.
The populations were first placed in a small removable
arena (65 mm diameter) in the center of the setup for 5 min
to calm the individuals (Fig. 1; Broly and Deneubourg
2015). Then, they are released into the binary choice
experimental setup by removing the inner retention arena
(performed in a quick movement perpendicular to the
support of the setup). Once the woodlice were released
(t = 0 s), the aggregation process was recorded for 45 min
by video; we used a Sony CCD FireWire camera—DMK
31BF03.
Experiments were carried out from February to June,
2009 (groups of 40, 60, 80, 100 and 150 woodlice), and in
June, 2011 (groups of 10 and 20 woodlice). For each group
size, there is no difference in the fraction of aggregated
individuals between the first chronological part and the
second part of experiments (Mann–Whitney test,
U C 39.50, P C 0.4807).
Measurements and analysis
Aggregation dynamics and distribution of individuals
Based on previous studies (Devigne et al. 2011; Broly et al.
2012), we consider an aggregate in any locality containing
for a minimum of 2 min a group of two or more woodlice
in contact, which avoids counting an extended crossing
between individuals as an aggregate. The aggregates
described as ‘‘under shelter’’ include the individuals actually under the shelter as well as those individuals in contact
but overflowing the limits of the shelter (see below). This is
in contrast to the secondary aggregates formed outside of
the direct influence of the shelters.
The distributions of the individuals in the setup were
recorded by counting the number of individuals in each
aggregate every minute during the 45-min experiment. Due
to the extreme difficulty of analyzing the aggregation
dynamics with 150 woodlice, only the final result (the
number of individuals in shelters at the 45th minute) was
recorded (directly in the setup) for this density.
To test the selection of the shelters by the populations at
the end of the experiments, binomial tests were carried out
with a null hypothesis assuming the distribution of woodlice between the two shelters would be equal. Irreversible
selection represents the moment where one of the two
shelters gathers more individuals than the other and
remains that way until the end of the experiment.
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A previous study, with a similar setup and similar
experimental conditions (Broly and Deneubourg 2015),
showed that the dispersion rate of a group is rapid but
decreases with group size. Such a phenomenon was also
observed here when the isopods, which had been retained
for 5 min, were released from the center of the arena (see
Fig. S1). To minimize this effect, which is a by-product of
amplified density-dependent social interactions (Broly and
Deneubourg 2015), two experiments with 100 individuals
and five with 150 individuals were excluded because central aggregates did not disperse after release. Also, the
aggregation dynamics presented here exclude the individuals that remained in the center of the arena.
Probability of joining and leaving the shelter
The experiments with only ten individuals allowed for the
monitoring of individual woodlice. With this experimental
condition, we analyzed the transition probabilities from one
behavior (moving) to another (stopping) as a function of
the presence of conspecifics. For this, the relation between
the probability of joining and leaving the aggregate and the
aggregate size is quantified.
First, the probability of joining a shelter is quantified
from the cumulative number of entries into a shelter
according to the cumulative number of individuals outside
shelter. The probability of joining shows a transition point
as function of sheltered individuals. The transition point
has been characterized for each experiment by using a
linear regression method (Draper and Smith 1981) that
splits a global set of values (of size L) into two subsets (of
sizes l1 and l2 = L - l1), calculates their linear regression
parameters and computes a global SD. This method is
based on the following equation:
y ¼ a0 þ b0 x þ a1 STAGE þ b1 STAGE x
where a0 and b0 are the linear regression line parameters of
the first subset (before transition) and a0 ? a1 = a2 and
b0 ? b1 = b2 are those of the second subset (after transition). STAGE is a binary variable whose value is 0 and 1
for points of the first and second subsets, respectively. The
first SD value is calculated with l1 = 1. For each subsequent calculation step (as long as l1 \ L - 1), the size of l1
is increased by adding the next point (in chronological
order), this value being removed from the l2 subset. The
transition point is the point at which the global SD is the
lowest.
Second, we encode the residence time(s) of each individual from the time of entrance into the shelter (in seconds) to the time of exit (in seconds). These residence
times are used to calculate the individual probability of
leaving a shelter according to the number of conspecifics
aggregated inside, assuming that this probability when
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Anim Cogn (2016) 19:181–192
perceiving N stopped conspecifics was constant per unit
time. Therefore, to avoid potential problems of variation in
group size during the residence period of a followed individual (related to the joining or leaving of a conspecific
under shelter), we only kept the data where individual
residence has not been disturbed by another event.
Aggregate shape
To analyze the modulation of behaviors and individual
distributions according to the spatial conformation of the
groups, the surface area of the aggregates (under the
shelters and the overflow) was measured at the 45th minute
for each experimental density (from 10 to 150 individuals)
and every 5 min during the experiments with 100 individuals. The measurements were taken from photographs
by counting the number of pixels occupied by the aggregate with Photoshop 7.0.1 (Adobe Systems Software) and
then converting the pixels to cm2 with the help of a reference with a known surface area.
The shape of the aggregate was approximated by a halfellipse form. Its length is its major axis (along the edge of
the arena), and its width (perpendicular to the edge of the
arena) is its semiminor axis (see Fig. S4F). The length/
width ratio is a measure of the compaction of the aggregate. When the ratio is equal to 2, the aggregate is
semicircular.
The statistical tests were performed using GraphPad
Instat 3.06 (GraphPad Software, Inc.). The figures and
regression analyses were produced using GraphPad Prism
5.01 (GraphPad Software, Inc.).
Fig. 2 Average proportion of woodlice aggregated under the shelters
with time (as the percent of woodlice that moved out of the initial
retention area) by the initial number of individuals introduced. For
readability, the inter-experimental distribution is only given in
supplementary Fig. S2
is a very stable phenomenon in woodlice, as evidenced by
the plateaus of the curves that persisted from the tenth
minute to the end of the experiments. Only the experiments
with ten woodlice showed greater variability between close
minutes (Fig. S2).
A large majority of the animals (between 80 and 90 %)
were aggregated under the shelters after 45 min (Fig. 2;
Table 1). The remainder were walking, especially in the
experiments that showed no aggregation (n = 10 ind.) in
which individuals were in constant movement. More
rarely, individuals gathered outside of the shelters in negligible secondary aggregates that were small and unstable
(short lifetime) and therefore disappeared by the end of the
experiments (Table 1; Tab. S1 in the supplementary
material).
Results
Distribution of individuals
Aggregation dynamics, distribution of individuals
and aggregate shape
The distribution of individuals between the two identical
shelters was not homogeneous at the end of the experiments. Indeed, under all density conditions, the woodlice
made a choice, i.e., the population presented an asymmetrical distribution between the two shelters in more than
75 % of the experiments (Table 1; binomial test,
P \ 0.05), except in those with 150 woodlice where the
majority of the experiments (87 %) present as no choice
(Table 1; binomial test, P [ 0.05).
Overall, at the end of the experiments, the distribution of
individuals in the binary choice tests can be synthesized
into three main patterns that were gradually observed with
increasing density (Fig. 3). (1) First, with ten woodlice, the
population distribution presents three peaks: One coincides
with the parts of the experiments without aggregation, and
the other two peaks coincide with the parts of the experiments resulting in aggregation under the right or left
shelter. There is no central peak signaling an absence of
Aggregation dynamics
First, the total number of woodlice aggregated under the
shelters was followed for 45 min (Fig. 2). Aggregation in
woodlice occurs quickly. In \5 min, more than half of the
individuals were aggregated, and 80–90 % of the individuals were aggregated in 10 min in all of the experiments,
except those with ten individuals. At this density, the
maximum average of the population that was aggregated is
approximately 60 %, which stems from the fact that
aggregations were systematically found in all of the
experiments with 20 or more woodlice, while with ten
woodlice, 85 % of the experiments showed systematical
aggregation and 15 % (four experiments) showed no
aggregation (the shelters are empty). Overall, aggregation
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185
Table 1 Data on the distributions of individuals at the end of the
experiments (45th minute): the proportion of woodlice aggregated
regardless of their location in the setup; the proportion of woodlice
aggregated out of the two shelters; the proportion of experiments
showing a statistical choice by the population of one of the two
shelters (binomial test); the mean number of individuals under the
most populated shelter just before its irreversible selection by the
entire population
10 woodlice
(n = 20)
20 woodlice
(n = 20)
40 woodlice
(n = 28)
60 woodlice
(n = 20)
80 woodlice
(n = 20)
100 woodlice
(n = 18)
150 woodlice
(n = 15)
Percentage of population
aggregated
64.0 (±38.3)
87.5 (±9.3)
86.1 (±13.2)
87.5 (±7.5)
88.4 (±6.9)
89.1 (±5.6)
89.6 (±5.0)
Percentage of aggregated out of
shelters
Percentage of experiments
showing statistical choice of one
of the two shelters
0.0
0.0
1.2 (±4.0)
0.0
0.0
0.0
–
80
90
78.6
75
80
77.8
13.3
Percentage of individuals under
winning shelter just before
choice
31.9 (±16.4)
24.0 (±13.5)
16.1 (±9.9)
19.6 (±12.3)
13.2 (±11.1)
12.9 (±9.9)
–
For this last analysis, the few experiments (3 exp. with 40 woodlice; 1 exp. with 60 woodlice; 2 exp. with 100 woodlice) were there were never
choice of one of the two shelters (i.e., parallel growth during the 45 min) were excluded from the calculation of the mean
Fig. 3 Distribution of the population fraction between the right and left shelters at the end of the experiments at four representative densities
equal segregation of the population between shelters (i.e.,
no choice). (2) With 20 woodlice, the peak representing the
absence of aggregation disappears, and we observe only
two peaks that are equally distributed between the right and
left shelter. This second pattern represents the experiments
with 20–100 woodlice. However, the central peaks (i.e.,
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Fig. 4 Time (a) and the number of individuals (b) necessary for the
irreversible selection of the most populated shelters according to the
number of initially introduced individuals. Bars represent the median
and interquartile range for each condition. In this figure, the few
Anim Cogn (2016) 19:181–192
experiments (3 exp. with 40 woodlice; 1 exp. with 60 woodlice; 2 exp.
with 100 woodlice) where there is no choice of one of the two shelters
(i.e., parallel growth during the 45 min) were excluded
equal segregation of the population between shelters)
progressively grow with increasing density. (3) Experiments with 150 individuals are the apogee of this trend
because the population was practically always evenly distributed between the shelters. They represent the third of
the primary patterns observed.
Regardless of the number of introduced individuals, the
irreversible selection of a shelter occured particularly
quickly (Fig. 4a; means of 103–371 s; no significant differences between conditions; Kruskal–Wallis test,
KS = 3.807, P = 0.5776) and included few individuals
(Fig. 4b; means of 3–13 individuals). The absolute number
of individuals necessary for the irreversible selection of
one shelter increases with the size of the introduced population (Fig. 4b; Kruskal–Wallis test, KS = 32.956,
P \ 0.001), but the necessary fraction of the population
decreases with population size (Table 1). Finally, just
before the irreversible selection of the shelter (i.e., when
the populations were still equal), the aggregate under the
future most-filled shelter presented the minimal length/
width ratio (Wilcoxon match-paired test, P = 0.0007;
Fig. S3).
Aggregate shape
Fig. 5 a Aggregate observed in an experiment with 40 individuals.
The shelter is partially filled with a small degree of overflow and
b aggregate observed in an experiment with 100 individuals. The
shelter is totally full (saturated) with large overflow
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In order to investigate the interplay between both environmental heterogeneity and group influences, we analyze
the spatiotemporal conformation of aggregates under the
shelters with a particular emphasis on the fraction of group
members aggregated under or out of the shelter. In addition
to Figs. 5 and 6, a complete analysis of the spatiotemporal
conformation of groups is given in the supplementary
material (Fig. S3 and Fig. S4).
Anim Cogn (2016) 19:181–192
187
Fig. 6 a Relationship between the filling of the shelter and the
number of individuals in the aggregate under the shelter at the end of
the experiments. Full black line represents the relationship between
the shelter filling and N according to an aggregate of a half-ellipse
form with a length/width ratio of 2 and centered on the shelter. Dotted
lines represent the theoretical cases of an aggregate with a length/
width ratio of 1 (up) and 3 (down) and b Relationship between the
filling of the shelter and the size of the aggregate overflowing the
limits of the shelter (surface area, in cm2) at the end of the
experiments. The degree of overflow (O) increases nonlinearly with
shelter filling (F) according to O = 0.0012 F1.89 (df = 170;
R2 = 0.6360)
First, the surface area of the most- and least-filled
aggregate increased sublinearly with the number of individuals inside (S = N3/4) (see ESM Fig. S4A). Interestingly, the same rule is at work for the selected/unselected
shelters and for the different population sizes. Furthermore, our analysis shows the gradual increase in the
shelter filling according to the density, up to more than
90 % of its carrying capacity at higher population densities (Figs. 5, 6a, S4B). However, aggregates also frequently overflowed the limits of the shelters, and the
degree of overflow increased as the shelter fills (Figs. 5,
6b, S4C). There was no difference between the spatial
patterns of the aggregates under the most- or least-filled
shelters (Fig. 6 and Fig. S4A–C). A simple model fits the
degree of shelter filling as a function of the aggregate
size (Fig. 6a). The model assumes that the aggregate is a
half-ellipse form with a length/width ratio of 2 and centered on the shelter. This value (2) is the experimental
value at the end of the experiment (see Fig. S4F–G).
In addition, we show that, regardless of the number of
individuals involved, the surface area per individual
(Fig. S4D, S4E) and the length/width ratio of the aggregate
(Fig. S4G) decrease during the course of the experiment
(about 30 %), both with the number of individuals and
time. These results indicate a spatiotemporal reorganization of the aggregated individuals toward a more compact
form.
Probability of joining a shelter
Probability of joining and leaving the shelter
In order to investigate the modulation of the individual
behaviors according to the social context, we calculate the
probability of joining or leaving an aggregate depending on
the group size.
Assuming that the probability of joining a shelter (Pj) is
proportional to the size of the population outside of the
shelters (O(t)) and depends on the size of the sheltered
population (N), the input flow, e(t), is:
eðtÞ ¼ Pj ðNðtÞÞOðtÞ;
ð1Þ
and the cumulative input flow at time t, (E(t)), is:
EðtÞ ¼
Zt
Pj ðNðtÞÞOðtÞdt
ð2Þ
0
If the probability of joining is constant, the cumulative
number of joining events is proportional to the cumulative
number of individuals outside of the shelters at time
t (O(t)):
EðtÞ ¼ Pi OðtÞ
ð3Þ
A break corresponds to a situation where the probability of
joining abruptly varies as a function of the size of the
sheltered population.
Figure S5a–b represents two of the four experiments
with ten individuals with no aggregation; the flow into the
entrance of the shelters is constant throughout the experiment. In contrast, Fig. S5c–h is examples of experiments
with ten woodlice where aggregation occurred. In these,
the curves show a clear break (i.e., the slope increases
drastically) and can be fitted by two different linear
regressions (Fig. S5c–h). The average slope of the first part
of the curve is Pj1 = 0.149 (±0.033), whereas that of the
second part is Pj2 = 0.490 (±0.158), which signifies that
the attractiveness of the shelter suddenly changes during
the experiment. This break seems to coincide with the start
of the aggregation (i.e., the number of individuals
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Anim Cogn (2016) 19:181–192
increases), although some time lags can occasionally be
observed (see Fig. S5).
The mean probability of joining the aggregate under the
shelter, P!j , is calculated for the size of each aggregate as
follows:
Pj1 " n1 þ Pj2 " n2
P!j ¼
n1 þ n2
ð4Þ
where n1 is the number of observations of an entrance into
the shelter, which has N individual(s) inside, during the
first phase of the cumulative curves shown in Fig. S5, and
n2 during the second phase.
The mean probability of an individual joining an
aggregate under shelter increases with the number of
individuals already aggregated inside (N) (Fig. 7) according to the Hill function:
!
"
Pj2 & Pj1 " N !
P!j ¼ Pj1 þ
ð5Þ
K! þ N!
Fig. 8 Logarithm of the fraction of an individual’s residence time in
an aggregate according to number of aggregated conspecifics
where e = 6.145 (95 % CI 5.242–7.048); K = 5.499
(95 % CI 0–6.415); df = 8; R2 = 0.9959.
Probability of leaving a shelter
Experiments with ten individuals allowed the individual
monitoring of woodlice. Figure 8 presents the residence
time of an individual depending on the size of the aggregates in the experiments at this density.
The larger the group, the greater the residence time
inside that group. For the size of each group shown in
Fig. 8, the residence time is fitted by an exponential law as
follows:
Y ¼ a " e&bt
ð6Þ
The goodness of fit for each group size falls between
R2 = 0.9732 and R2 = 0.9968, and the values of a and b
by group size are given in Fig. S6 and Fig. 9, respectively.
The values of parameter a are constant (&100) with group
Fig. 9 Individual probability of leaving an aggregate (Pl) with the
number of individuals in the aggregate. The data are fitted by Eq. (7)
size (Fig. S6; F = 1.535, P = 0.2505), and the values of
parameter b represent the individual probability of leaving
the aggregate (Pl) (Fig. 9). This probability decreases with
group size (N) according to the following power law:
b ¼ Pl ¼
A
B þ NC
ð7Þ
where A = 1845 (95 % CI 0–15,144), B = 6569 (95 % CI
0–54,615), C = 4.916 (95 % CI 1.081–8.751), df = 7 and
R2 = 0.9011.
Discussion
The process of aggregation in terrestrial isopods:
a trade-off between social and environmental cues
Fig. 7 Mean probability of joining a shelter according to the number
of individuals already inside. The data are fitted by Eq. (5)
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Aggregation in animals results from their response to
environmental heterogeneity and/or the inter-attractions
between individuals (Camazine et al. 2003). In our study,
the systematic aggregation of woodlice under shelters
highlights the role of individual preferences for the environmental heterogeneities (Friedlander 1964; Warburg
Anim Cogn (2016) 19:181–192
1964). In addition, the collective choice of one of the two
identical shelters by the majority of the populations confirms the importance of inter-attraction in the aggregation
process of P. scaber (Devigne et al. 2011; Broly et al.
2012). In summary, the collective patterns observed here
result from individual preferences (most of the aggregates
are formed under the shelters) and the inter-attraction
between individuals (most of the population distributions
are asymmetrical), as seen in many social arthropod models
(Camazine et al. 2003; Jeanson and Deneubourg 2007,
2009; Sumpter and Pratt 2009; Jeanson et al. 2012; Robert
et al. 2013; Durieux et al. 2014).
Minimal number of individuals and the mechanisms
initiating the aggregation process
If variation in population density weakly impacts aggregation dynamics, it strongly affects the probability of
observing an aggregation. In the experiments with ten
woodlice, in particular, 20 % of the experiments showed
no aggregation (i.e., all of the individuals were mobile
during the entire duration of the experiment), and it took
more than 30 min in 15 % of the experiments to obtain an
aggregate under a shelter. The analysis of the probabilities
of joining and leaving the aggregates indicates (1) an
increased attractiveness of the group to migrants and (2)
increased retention of conspecifics in the group with group
size. These results, and especially their sigmoidal forms,
support that the initiation of the aggregation process
involves a quorum rule, in which individuals cannot
aggregate under a specific threshold of individuals (Conradt and Roper 2005; Sempo et al. 2009; Sumpter and Pratt
2009). This threshold is predicted by the shape of the
probability curve of joining and leaving the group. In our
study, the introduction of only ten individuals into the
binary choice test decreases the probability of obtaining a
critical mass under one of the two shelters and generating a
stable aggregate by chance. This could explain why many
of the experiments with a small number of individuals
presented difficulty to establish a clear aggregation pattern,
while all of the experiments with higher densities (130
experiments) showed significant aggregation. Similarly, in
the experiments with 10 and 20 individuals, the formation
of a stable aggregate under a shelter ‘‘monopolizes’’ the
majority of the population. Thus, there are not enough
woodlice available (i.e., a critical number) to initiate a
secondary aggregate under the other shelter. With the
introduction of 40 woodlice or more, a stable secondary
aggregate is able to form (25 % of the experiments do not
show a choice of a shelter) because two critical numbers
for the initiation of two aggregates can be reached by
splitting the population.
189
Group size is a key factor in the collective organization
of social groups primarily because collective behaviors are
not simply a linear addition of individual behaviors. Thus,
variation in group size is often associated with non-intuitive and profound changes in the organization of social
systems and the effectiveness of behaviors (Anderson and
McShea 2001; Sumpter 2006; Amé et al. 2006; Buhl et al.
2006; Sempo et al. 2009; Sumpter and Pratt 2009; De
Meester and Bonte 2010; Dornhaus et al. 2012). In selforganized groups, collective patterns are governed by
simple rules and local information at the individual level,
so no leadership or knowledge of the global structure is
needed (Bonabeau et al. 1997; Seeley 2002; Camazine
et al. 2003; Theraulaz et al. 2003; Jeanson et al. 2012). In
self-organized systems, aggregation emerges from amplification processes based on positive feedback loops so that
as the number of individuals engaged in a behavior
increases, the greater the probability that individuals will
exhibit similar behaviors (Camazine et al. 2003; Sumpter
2006; Jeanson et al. 2012). In this respect, these systems do
not necessarily involve subunits with high cognitive abilities for the acquisition and the processing of the information (Seeley 2002).
In our study, we showed that terrestrial isopods modulate their individual behaviors according to social context;
especially, the analysis of the residence time of individuals
in a shelter clearly shows that residence time increases with
group size due to the increasing probability of joining and
the decreasing probability of leaving the group. These
results are critical to the generation of positive feedback
loops in a self-organized system (Camazine et al. 2003;
Sumpter 2006; Jeanson et al. 2012). In other words, our
analysis strongly supports the existence of self-organization in the aggregation process of terrestrial isopods.
Because of the social component of the aggregation
process, each individual integrates social information along
with environmental signals when selecting a preferred site
(Jeanson and Deneubourg 2007). Our study reveals that the
irreversible selection of the shelter is made in the first
5 min of the experiment. The rapid and irreversible choice
of shelter that occurs when a small fraction of the population is sheltered (a mean of eight individuals) suggests
that collective decision making in woodlice is not the result
of a shared consensus decision or a democratic vote of the
entire population (Conradt and Roper 2005), but of an
amplification of small variation(s) in the early stages of one
of the randomly emergent aggregates. If our analysis shows
that the number of clustered individuals affects the probabilities of leaving and joining a cluster, we have also
shown that the shape of the cluster (i.e., the compactness of
individuals) plays an important role at least at the beginning of the process. How individuals assess aggregation
sites may be explained by several and non-exclusive
123
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Anim Cogn (2016) 19:181–192
hypotheses, including the presence of contact chemoreception (see Takeda 1984; Beauché and Richard 2013) and/
or physical markers (present study). Because long-distance
perception is probably low in terrestrial isopods (Harzsch
et al. 2011), local cues seem therefore particularly important to understand the initiation of their social groups and
deserve more attention. For example, in the context of the
public information (Wagner and Danchin 2003; Valone
2007; Canonge et al. 2011), the aggregation could be initiated by the rapid assessment of the compaction of individual then reinforced and stabilized by the conspecific
body odors.
disturbed over a longer experimental timeframe. Supplementary studies over longer timescales could determine
whether the large fraction of individuals overflowing the
shelters is due to the rapidity of the phenomenon and
whether such patterns may be reversible with time. In any
case, this first analysis of the spatiotemporal characteristics
of the aggregate, which show compaction and a reorganization of individuals toward the center of the shelters
during the experiments (see Fig. S4D, E, G), argues in
favor of temporal modulation of the social and environmental influences.
Maximum number of individuals
Adaptive values
The shelter gathering the most individuals reaches a plateau of approximately 80 % of the total population introduced in the experiments with 10, 20, 40, 60 and 80
woodlice. Interestingly, this trend does not persist at higher
densities (100 and 150 ind.) where a shelter no longer fills
up with more than 70 individuals attesting to an important
splitting of the population.
Three hypotheses could explain this pattern and the
notably low carrying capacities of the shelters. Indeed, our
shelters quickly fill with a high number of individuals (see
Fig. 5 and Fig. S4). Cockroaches (Blattella germanica) in
similar choice-test experiments respond to shelter saturation by distributing equitably under the two shelters (i.e.,
50 % of individuals under one shelter and 50 % under the
other; Amé et al. 2006). In our study, terrestrial isopods
clearly do not follow the same pattern but instead form one
large aggregate and another smaller one when densities are
less than 150 individuals. However, woodlice are able to
overflow the limits of their shelters (see Fig. 5 and Fig. S4).
This spatial conformation argues in favor of a maximum
aggregate size weakly dependent on the heterogeneities or
mechanical constraints of the experimental setup. Secondly, if the absolute value of the maximum number of
individuals per aggregate is certainly related to our
experimental conditions, the observed phenomenon of
population splitting could be the result of an underlying
mechanism inherent in the self-organized aggregation
process. Self-amplification with positive feedbacks must
induce negative feedbacks (e.g., physical constraints, such
as site saturation, and competitive social interactions, such
as long-range inter-aggregate competition; see Theraulaz
et al. 2002) to prevent the runaway of the system (Camazine et al. 2003; Jeanson and Deneubourg 2009; Jeanson
et al. 2012). Lastly, splitting the population into two equal
subpopulations could be a by-product of the rapid
dynamics of the process. Indeed, we cannot conclude that
the system has reached its steady state after 1 h, so the
asymmetrical distribution between shelters could be
Ultimately, it is obvious that group-member fitness
strongly varies according to the individual spatial position
in the group (Krause 1994; Morrell and Romey 2008). The
spatial conformation of the terrestrial isopods overflowing
the limits of their shelter, and therefore being exposed to
light and without cover, represents a total contradiction of
individual preferences (Friedlander 1964; Warburg 1964).
This is a strong demonstration of the critical importance of
the social component in the distribution of terrestrial isopods. Such a phenomenon highlights the interesting
dilemma, during individual choice in social organisms,
involving the management of cues from conspecifics and
environmental preferences according to the context and the
adaptiveness of choice resulting. The remarkable cohesion
and compaction of individuals in our experiments may be
explained by the strong group effect previously observed in
terrestrial isopods, leading to a reduction in individual
water losses and therefore increasing individual survival
over very short timescales (Allee 1926, 1931; Takeda
1984; Broly et al. 2014). In particular, during the aggregation process, the spatiotemporal rearrangements of
individuals toward a more compact form (see Fig. S4) lead
to a decrease in the surface area/volume ratio of the group
and a reduction in individual desiccation (Broly et al.
2014). However, if the gain per individual is important in
small groups, it stagnates in larger groups due to geometric
constraints on the shape of the aggregate and the nonlinearity of the phenomenon (individual water loss decreases
with group size-0.13; Broly et al. 2014). Such a result
argues for the adaptiveness of the observed split in the
large population. Nevertheless, maximum group size
observed deserves greater study at both the proximal and
ultimate levels. Similar studies using species with greater
resistance to desiccation and less gregariousness, such as
Armadillidium vulgare (Hassall et al. 2010), should address
the important question of the robustness of collective
mechanisms under different environmental conditions and
their conservation across phylogenies.
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Anim Cogn (2016) 19:181–192
Conclusion
The demonstration of self-organized behavior in social
animals must meet several criteria, including a decentralization of the information processing and an amplification
process from local interactions that leads to the emergence
of social structures (Camazine et al. 2003; Sumpter 2006;
Jeanson et al. 2012). One of the results raised in this study
is the increasing individual probability of joining and the
decreasing individual probability of leaving an aggregate
with increasing aggregate size. Our hypothesis is that such
mechanisms are at the basis of the emergence of groups in
terrestrial isopods, and are therefore self-organized. Such
individual decisions based on local information and their
amplification do not require a complex assessment of the
environment and high computational abilities, i.e., a complex cognition (Seeley 2002). Therefore, many gregarious
species, despite a strong difference in their social organization, obey these simple rules for the emergence of
aggregation or a wide range of collective activities, such as
in the cockroach B. germanica (Jeanson et al. 2005), the
ants Lasius niger (Depickère et al. 2004) or Oecophylla
(Lioni et al. 2001; Lioni and Deneubourg 2004), or the
earthworm Eisenia fetida (Zirbes et al. 2012). Furthermore,
invertebrates seem to share a limited number of simple
behavioral rules regardless of their level of social organization and the diversity of patterns observed. In other
words, one (or a few) generic laws could be at work, but
the diversity of parameters involved across species may be
high. Such trans-phylum homogeneity suggests a particular
adaptiveness of the self-assemblages, especially in organisms with limited cognitive abilities.
Acknowledgments P. Broly is supported by a FRIA grant (Fonds
pour la Recherche dans l’Industrie et dans l’Agriculture, FRS-FNRS).
J-L. Deneubourg is a Senior Research Associate at the FRS-FNRS.
Authors thank the American Journal Experts for revising language of
the manuscript.
Compliance with ethical standards
Conflict of interest
peting interests.
The authors declare that they have no com-
Ethical standard The experiments comply with the current laws of
the country in which they were performed.
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