Behavioral
Ecology
The official journal of the
ISBE
International Society for Behavioral Ecology
Behavioral Ecology (2014), 25(5), 1240–1247. doi:10.1093/beheco/aru117
Original Article
Roosting behavior and group decision making in
2 syntopic bat species with fission–fusion societies
Daniela Fleischmann and Gerald Kerth
Zoological Institute & Museum, Ernst-Moritz-Arndt University of Greifswald, J.-S.-Bach-Str. 11/12,
D-17489 Greifswald, Germany
Received 24 February 2014; revised 4 June 2014; accepted 5 June 2014; Advance Access publication 22 July 2014.
In many social species, individuals make group decisions to coordinate their actions. Despite the importance of group decisions for
successful group living, few studies investigated how wild animals make group decisions in situations where group members have
conflicting interests. This lack of empirical data is most evident for animal groups that regularly split into subgroups for some time. In
groups with high fission–fusion dynamics, individuals can avoid group decisions that are not in their interest without foregoing benefits
from being social. Here, we compare group decision making about communal day roosts in 2 syntopic bat species with a similar ecology and life history but a different fission–fusion behavior of their colonies. Daily roost monitoring during 3 breeding seasons showed
that Bechstein’s bats formed subgroups 5 times more often than brown long-eared bats although both species occupied a similar number of bat boxes per colony and year. Bechstein’s bats were also significantly faster in discovering newly installed boxes and explored
them further away from their established roosting areas compared with brown long-eared bats. In a field experiment where we created a conflict of interests among colony members where to roost, brown long-eared bats always achieved a colony-wide consensus
about communal roosts. On the contrary, in Bechstein’s bats, individuals with conflicting interests often formed subgroups in different
roosts according to their individual interests instead of reaching a consensus on a single communal roost. Our findings show that even
ecologically similar species can use different group decision-making rules for solving an identical coordination problem.
Key words: chiroptera, collective decisions, conflict of interest, fission–fusion, roosting behavior.
Introduction
Most social species need to make group decisions to ensure the
coordination of their groups (Conradt and Roper 2005). The way
animals make group decisions therefore can strongly influence the
functioning of their groups (Kerth 2010a). If individuals obtain
grouping benefits only when forming a single cohesive group, they
need to find a consensus whenever they have to choose between
alternative collective actions. Consensus decisions are thus defined
as decisions in which all members of a group agree on the same
option (Britton et al. 2002; Conradt and Roper 2005). They are
well studied in eusocial insects in the context of nest site choice
(Visscher and Camazine 1999; Pratt et al. 2002; Jeanson et al.
2004; Seeley et al. 2006; Visscher 2007), where group members
typically diverge little in their interests and where obeying to a consensus decision thus involves no or only little costs to the individual.
In contrast, in many other animal species, for example, in most
vertebrates, group members often have considerable conflicts of
interests about the outcome of collective decisions due to individual differences in age, sex, dominance status, reproductive status, or
Address correspondence to D. Fleischmann. E-mail: daniela.fleischmann@
uni-greifswald.de.
© The Author 2014. Published by Oxford University Press on behalf of
the International Society for Behavioral Ecology. All rights reserved. For
permissions, please e-mail: [email protected]
genetic relatedness (Kerth 2010a). Studying group decision making in the context of conflicts of interests between group members
is particularly interesting as differences in individual interests may
pertain to the fitness of group members and the evolution of group
decision making (Conradt and Roper 2009).
Several theoretical studies have explored animal group decision
making in situations where group members have conflicting interests (Conradt 2012). However, only few empirical studies investigated group decisions of wild animals in situations with conflicting
individual interests, as studying group decision making experimentally in the field is associated with considerable logistic difficulties
(Kerth 2010a). This lack of empirical data is most evident for animal societies that show fission–fusion dynamics which means that
they repeatedly split into subgroups that regularly remerge (Kerth
et al. 2006; Fleischmann et al. 2013). Such fission–fusion behavior exists, for example, in elephants and some primates, carnivores,
dolphins, and bats (Kerth and König 1999; Aureli et al. 2008). It
enables individuals with diverging interests to avoid group decisions
that are not in their favor without foregoing benefits that arise from
being in a group (Kerth 2010b; Sueur et al. 2011; Fleischmann
et al. 2013).
For a more complete understanding of animal group decision
making, it is thus important to compare how animal societies with
Fleischmann and Kerth • Group decisions in 2 syntopic bat species
different degrees of fission–fusion dynamics make group decisions
in situations with conflicting individual interests. The replication of
a given standardized experiment with different species is rarely performed (but see Scholes and Suarez 2009) even though this could
highlight the possibility of alternative decision-making rules in similar species. Due to the large number of confounding variables, it,
however, may be inconclusive to directly compare group decision
making between species that differ to a great extent from another
in their ecology, social structure, cognitive abilities, and further lifehistory parameters. In this study, we therefore compared group
decision making about communal roosts in 2 syntopic bat species
that differ in the degree of the fission–fusion dynamics of their
colonies but that otherwise have a very similar ecology and life history. In many bat species, particularly those roosting in tree cavities,
colony members switch their communal day roosts almost every
day and colonies frequently split into subgroups for some time (e.g.,
Kerth and König 1999; O’Donnell 2000; Willis and Brigham 2004;
Popa-Lisseanu et al. 2008; Kerth et al. 2011). This roost switching
and fission–fusion behavior make forest-dwelling bats well suited
for studies on group decision making (Kerth et al. 2006).
Our objective was to compare the fission–fusion behavior and
group decision making about communal day roosts between
Bechstein’s bats (Myotis bechsteinii) and brown long-eared bats
(Plecotus auritus). They are both medium-sized bats, with a wingspan
ranging from 250 to 300 mm and 220 to 250 mm and a weight from
7 to 14 g and 6 to 15 g for Bechstein’s bats and brown long-eared
bats, respectively (Schober and Grimmberger 1989). Both species
are widespread in Europe (Dietz et al. 2007) and their life cycles are
typical for temperate zone vespertilionid bats (Racey 1982). During
summer, in both species, about 10–50 females form maternity colonies where they give birth and raise their young. In both species,
females are philopatric to their natal colonies that comprise one to
several matrilines of maternally closely related females (Burland
et al. 1999; Kerth et al. 2000; Kerth and van Schaik 2012). Females
of both species typically forage within less than 1 km from their
day roosts (Entwistle et al. 1996, 1997; Kerth et al. 2001; Kerth
and Melber 2009). Moreover, both species feed mainly on moths
and flies and also on nonflying arthropods, which they glean from
the vegetation in woodland (Dietz et al. 2007; Andreas et al. 2012).
Like in many other forest-living bats (Lewis 1995), brown longeared bats frequently switch roosts within their colony home range
(Heise and Schmidt 1988). In Bechstein’s bats, roost switching has
been studied in much more detail and colonies are known to use
about 50 different communal roosts during 1 summer (Kerth and
König 1999; Kerth et al. 2011).
During 3 subsequent summers, we investigated 2 colonies of
brown long-eared bats and 1 Bechstein’s bat colony, living syntopically in the same forest. The 3 colonies have been continuously
monitored since 2002 and all their adult members were individually marked with radio-frequency identification (RFID) tags. All 3
colonies used the same type of bat boxes as day roosts and automatic RFID-tag readers attached to occupied bat boxes allowed
for the daily monitoring of the bats’ individual roosting behavior without disturbing them (Kerth and König 1999; Kerth et al.
2011). Based on a preliminary inspection of these long-term data,
we expected that brown long-eared bats show a lower degree of
fission–fusion behavior than Bechstein’s bats. In each year, we supplied all 3 colonies with additional new bat boxes and monitored
how long it took individual bats to discover and occupy these boxes.
Following the approach of Fleischmann et al. (2013), we also experimentally manipulated the quality of the newly installed bat boxes
1241
to generate conflicts of interests among individual colony members
(see Materials and Methods for details). Subsequently, we compared
the group decision making concerning communal roosts in the 3
bat colonies. We expected that the species (presumably Bechstein’s
bats) that more often split into subgroups during the daily switching
of not manipulated roosts (original boxes) would also depend less
on consensus decisions about new communal roosts (newly installed
boxes) in situations where we experimentally induced conflicting
interests among group members.
Materials and Methods
The study was conducted from 2009 to 2011 in the home ranges
of 1 Bechstein’s bat colony and 2 brown long-eared bat colonies.
The 3 colonies live close to each other in the same deciduous forest,
southwest of the city of Wurzburg (Germany). All colonies mainly
roost in bat boxes (type 2FN, Schwegler, Germany) and to a lesser
degree in natural tree cavities. The roosting areas of all 3 colonies
overlap to some extent and occasionally the colonies use the same
boxes in succession. However, on a given day, only bats belonging
to the same colony share a given roost. Each year the presence of
bats in 125 bat boxes (and 1 accessible tree cavity) was monitored
on a daily basis from mid-May to mid-September. Mid-May all
colony members had returned to the study site from their hibernacula. Each year at this time, all colonies were caught for biometric
measurement and all bats that had been born in the previous year
and thus had not been marked yet received an individual RFID-tag
(Trovan, Germany). The regular roost monitoring ended when the
bats left the study sites to fly to their swarming (mating) places and/
or hibernacula. We identified individual bats in their day roosts
using mobile RFID-tag readers (Kerth and Reckardt 2003; Kerth
et al. 2011).
At the beginning of the study, about 100 “old” bat boxes were
available for the bats. Those boxes have been in the study area for
more than 10 years and are used by the same colonies of bats from
year to year. If we found bats during the daily checks in some of
these boxes, those boxes were equipped with automatic RFID-tag
reading devices to identify the individual bats occupying them.
Each year we installed an additional 20–32 “new” bat boxes. In
contrast to the old boxes, which were only equipped with RFID-tag
readers when bats used them as day roosts, the new boxes were permanently equipped with automatic RFID-tag readers from the day
the boxes had been installed (overall 125 boxes were always available for the bats; Fleischmann et al. 2013). This way we were able
to monitor the bats’ nightly visits to the “new” boxes continuously
from their installation until they were used as day roosts.
We provided the bats with 3 different categories of “new” boxes:
1) “Control boxes” that were only equipped with automatic reading devices. 2) “Repelling boxes” where predetermined bats (onethird, two-thirds, or all bats of a colony) experienced a repelling
stimulus (a brief air puff) when they explored these boxes at night
(Fleischmann et al. 2013). Repelling boxes where one-third or twothirds of the bats received an air puff while visiting at night allowed
us to experimentally create a conflict of interest among colony
members whether or not to use such a box as day roost, depending
on whether an individual had received an air puff there. Repelling
boxes were subdivided into the abovementioned 3 subcategories to
be able to discriminate among 4 possible decision rules (individual,
minority, majority, and unanimous; for details, see Fleischmann
et al. 2013). 3) “Heat boxes” were equipped with heating foils
that warmed the boxes (average temperature increases about 2 °C
Behavioral Ecology
1242
relative to a normal box). We assumed that heat boxes might be
most attractive to the bats (Kerth et al. 2001).
We installed the new boxes in the study area in 4 sets, each of
which consisted of 1 box of each category (“control,” “one-third,”
“two-thirds,” “all,” and “heat”). Within sets, the distance between
boxes was about 20–40 m to ensure that the probability to be discovered was similar for all boxes. When at least 2 bats (minimum number
for a group decision) used a new box as a day roost, this box was considered occupied by a group of bats. After the bats moved to another
day roost, the RFID-tag reader was removed and a new box of the
same category was installed within the area of that given set (compare Fleischmann et al. 2013). At each of the occupied “repelling
boxes,” we determined how many of the visiting bats had received
a stimulus to ensure that at a “one-third” box indeed a minority of
colony members received a stimulus. If this was not the case, because,
for example, only bats predetermined to receive an air puff visited a
“one-third” box and none of the other colony members, this box was
regrouped and analyzed as an “all” box in the given example.
To quantify the individual roosting and fission–fusion behavior of
the bats, we assessed how many subgroups were formed by the different colonies each day. We also analyzed how often each member
of the 3 different colonies was found in bat boxes and how many
day roosts (old and new boxes) each individual used. When assessing the number of different boxes used per individual, we divided
the absolute number of boxes each individual used by the number
of days it was found in boxes to correct for individual differences
in the overall presence in bat boxes. Furthermore, to quantify the
exploration behavior of the bats, we evaluated how many nights it
took for new boxes to be discovered and, subsequently, how many
more nights it took until the box was used as day roost. To compare
the time between discovery and occupation of new boxes between
the different colonies, we only used “control boxes.” This way we
attempted to exclude any bias from species-specific reactions of the
colonies toward “repelling boxes” and “heat boxes.”
The new boxes were placed in the general roosting areas of the
3 colonies, based on their roost occupancy during previous years
(e.g., Kerth et al. 2011 for Bechstein’s bats and unpublished data
for brown long-eared bats). In order to assess whether the colonies
were more likely to discover new boxes that were placed within
their roosting areas of the respective year, we defined the “current”
roosting areas. Current roosting areas were the areas surrounding the locations of all occupied old bat boxes of a given colony
in a given year (100% minimum convex polygon, MCP 100). To
examine the individual exploration of new boxes and the subsequent decision whether or not to use these boxes as day roosts, we
compared how many new boxes the bats discovered and occupied
inside respectively outside of their current roosting areas. MCPs of
the roosting areas were generated in ARCVIEW GIS 3.3 (ESRI)
with the “Home Range Extension” (Rodgers and Carr 1998).
In a last step, we analyzed which new boxes were actually used
as day roosts to draw conclusions about the way group decisions
are made in the different colonies. According to Fleischmann
et al. (2013), we discriminated among 4 possible decision-making
rules (individual, minority, majority, and unanimous). Data of the
Bechstein’s bats’ occupation of experimental boxes in the years
2009 and 2010 were taken from Fleischmann et al. (2013).
All statistical analyses were performed using R (version 2.11.1;
R Development Core Team 2010). The level of statistical significance was set to α < 0.05. Data were tested using the Levene’s
test for homogeneity of group variances (results not shown). If the
data were homoscedastic (P > 0.05), we used Kruskal–Wallis tests
for testing differences between groups. If the Kruskal–Wallis tests
were significant, we used Bonferroni-corrected Mann–Whitney U
tests for pairwise comparisons. Contingency tables were analyzed
using Fisher’s Exact tests. Furthermore, we applied multivariate
linear mixed-effect models (generalized linear mixed-effect models
[GLMERs]), allowing for the use of repeated measurements. This
way we examined the effect of different factors (e.g., species, colony,
year, colony size, and box category as fixed variables) on the time
until boxes were discovered respectively occupied (response variables) and the effect of the factors on the occupation of new boxes
(response variable) while including the boxes’ IDs as a random factor into the models. All possible combinations of factors with additive as well as interactive effects were tested. Models were fit using
the package lme4 (Bates 2007a, 2007b) in R. We compared the
models using Akaike´s information criterion (AIC; Burnham and
Anderson 2002). Multiple comparisons among factor levels were
calculated with Turkey’s post hoc tests using the ghlt function in the
package multcomp (Hothorn et al. 2008).
Results
Roosting behavior
During our study period, the 3 colonies contained only females and
the juveniles born in a given year. The number of adult females per
colony varied somewhat between years, but the size of the 3 colonies
was more or less within the same range in a given year (Table 1). Even
though all 3 colonies used bat boxes frequently, individual Bechstein’s
bats were more often present in the boxes (mean of 90.6% of the
census days) than individual brown long-eared bats (colony A: 60.1%
of days; colony B: 67.2% of days). Bechstein’s bats formed subgroups
Table 1
Number of bats present in the different colonies
Myotis bechsteinii
Year
N bats
N days
N days present
% days present
Days in 1 box (no fission of the colony)
Days in more than 1 box (fission of the colony)
% present in more than 1 box
2009
2010
2011
17
24
7
123
123
117
116
104
109
94.3
87.0
93.2
72
78
95
44
26
14
37.9
25.0
12.8
Plecotus auritus (colony A)
Total
363
329
90.6
245
84
25.5
2009
2010
2011
17
17
9
123
123
117
65
64
89
52.8
52.0
76.1
60
59
88
5
5
1
7.7
7.8
1.1
Plecotus auritus (colony B)
Total
363
218
60.1
207
11
5.0
2009
2010
2011
10
17
15
123
123
117
88
79
77
71.5
64.2
65.8
78
77
73
10
2
4
11.4
2.5
5.2
Total
363
244
67.2
228
16
6.6
For each year, it is stated on how many days we were checking for the presence of bats and on how many days we found bats in roosts (divided in number of
days bats spent in one or more than 1 roost, respectively).
Fleischmann and Kerth • Group decisions in 2 syntopic bat species
about 5 times more often (25.5%) on the days they were present
in the boxes than brown long-eared bats (P. auritus colony A: 5.1%;
colony B: 6.6%). In agreement with this finding, averaged over all
3 years, individual Bechstein’s bats used more boxes per day present in boxes (median: 0.41) than individual brown long-eared bats of
colony B (median: 0.20). However, also individual brown long-eared
bats of colony A used a larger number of boxes (median: 0.48) than
members of colony B, and in 2010, they even used a larger number
of boxes than the Bechstein’s bats (medians: 0.53 vs. 0.39).
Individual Bechstein’s bats spent on average 39.0% of the days
they were present in bat boxes in new boxes, whereas individual
brown long-eared bats spent on average only 6.5% and 3.7% (colony A and colony B, respectively) of the time in new boxes. If new
boxes would have been occupied according to their relative frequency (compared with old boxes) in the different study years, they
should have been used on 16.0–25.6% of the days.
In conclusion, our analyses of the roosting behavior of the 2
species revealed that Bechstein’s bats showed a 5 times stronger fission–fusion behavior than brown long-eared bats. Moreover, the 2
species differed in their relative presence in bat boxes. Contrastingly,
we found no consistent difference between Bechstein’s bats and
brown long-eared bats in the number of boxes used per individual
bat. Finally, Bechstein’s bats consistently spent more days in new
boxes than brown long-eared bats. This suggests that even though
both species use a large number of different day roosts, Bechstein’s
bats are more likely to occupy novel roosts than brown long-eared
bats.
Time from installation to discovery and until
occupation
Bechstein’s bats needed a median of 4 nights to discover a new box
(all new boxes), whereas brown long-eared bats needed 17 and 11
nights (median, colony A and colony B respectively; Figure 1). Using
1243
GLMERs, a model with interactive and additive effects of colony
and year had the lowest AICc score (581.7) and thus best explained
the data. Based on this model, members of the Bechstein’s bat
colony discovered boxes significantly faster than members of both
colonies of brown long-eared bats (Tukey’s pairwise comparisons:
M. bechsteinii vs. P. auritus colony A: z = 6.760, P < 0.001; M. bechsteinii vs. P. auritus colony B: z = 6.172, P < 0.001), whereas no significant difference in the discovery speed was found between the 2
brown long-eared bat colonies (z = −1.678, P = 0.203). The influence of the study year on the exploration was apparently small as
the second best model (colony × colony size) that did not include
the year had a ΔAICc < 2 when compared with the best model.
Indeed, the time until the boxes were discovered differed between
only 2 years (Tukey’s all pairwise comparisons: 2010 vs. 2011:
z = −3.079, P = 0.005).
After discovering a box, Bechstein’s bats needed a median of
33 nights to use it as a day roost, whereas brown long-eared bats
needed a median of 6 nights to occupy a previously discovered new
box (only control boxes analyzed). Presumably due to the low number of occupied boxes, the species did not significantly differ in the
time they needed to occupy a previously discovered box (data not
shown).
Exploration and occupation of new boxes
relative to the location of roosting areas
When we analyzed the discovery of potential roosts over the entire
study period, the Bechstein’s bat colony did not discover more
new boxes inside or outside their current roosting area (Fisher’s
Exact test: P = 0.628; see also Table 2). On the contrary, both
brown long-eared bat colonies discovered significantly more new
boxes inside of their current roosting areas than outside of them
(Fisher’s Exact test: colony A: P = 0.013; colony B: P = 0.000; see
also Table 2). This suggests that the members of the Bechstein’s
Figure 1
Number of nights the 3 studied colonies needed to discover a new box. Boxplots show median, upper and lower quartiles, minima and maxima, and outliers.
Different line types symbolize different years (2009, 2010, 2011, and all 3 years combined as total).
Behavioral Ecology
1244
Table 2
Size of the MCPs (current roosting areas) for each colony. For each year, it is stated how many boxes were discovered and whether
those were used as day roosts. Furthermore, it is specified whether the boxes were located inside or outside of the MCPs,
respectively.
Species
Myotis bechsteinii
Plecotus auritus (colony A)
Year
MCP 100 (ha)
Inside of MCP
Boxes not discovered
Boxes discovered (but not occupied)
Boxes discovered and occupied
Ʃ
Outside of MCP
Boxes not discovered
Boxes discovered (but not occupied)
Boxes discovered and occupied
Ʃ
2009
220.2
2010
146.9
1
7
12
20
8
5
3
16
1
0
4
5
3
5
4
12
6
6
4
16
4
6
5
15
2011
183.6
Total
2009
209.7
2010
251.4
2011
468.2
10
12
19
41
11
9
3
23
13
4
3
20
8
4
1
13
13
17
13
43
7
1
1
9
10
1
1
12
7
0
0
7
bat colony were more explorative outside their established roosting range compared with the members of both brown long-eared
bat colonies. Furthermore, Bechstein’s bats regularly occupied new
boxes that were installed outside of the current roosting area (13
boxes occupied outside compared with 19 boxes inside; Table 2),
whereas brown long-eared bats did this only rarely (2 boxes occupied outside of the current roosting area compared with 9 boxes
inside; Table 2).
Group decision making
When we analyzed the outcome of group decisions about communal occupation of bat boxes, we found that the treatment category
of the experimental “new” boxes strongly influenced the bats’ decisions to use a box as day roost. Figure 2 shows that both bat species used high percentages of “control” and “heat” boxes but rarely
“repelling” boxes (Figure 2). These results were confirmed by using
general mixed-effect models. All best fit models included category
as a fixed variable and a GLMER with additive effects between category and colony had the lowest AICc score (121.2). However, a
model with additive effects between category and species was the
most parsimonious model (AICc = 124.9) and confirmed that both
species roosted more often in “control boxes” and “heat boxes”
compared with “repelling boxes” (Tukey’s all pairwise comparisons: “control boxes” vs. “repelling boxes”: z = −4.161, P < 0.001;
“repelling boxes” vs. “heat boxes”: z = 4.552, P < 0.001; “control
boxes” vs. “heat boxes”: z = 0.767, P = 0.722). Nevertheless, the
models also revealed significant differences between the 2 bat species (z = −2.162, P = 0.031) due to the occasional use of “repelling” boxes by Bechstein’s bats.
To analyze the impact of the experimentally induced conflicting
interests on group decisions where to roost communally, we investigated the occupation of the “repelling boxes” belonging to the
subcategories “one-third” and “two-thirds” where we had experimentally induced a conflict of interest. Members of the Bechstein’s
bat colony occupied 5 boxes out of 14 discovered ones where we
had created a conflict of interest among colony members, whereas
brown long-eared bats discovered 12 of such boxes but did not
occupy a single box where we had created a conflict of interest
among colony members (Figure 2).
In both species, the number of bats that had visited a box at
night before they later used it as day roosts ranged for the occupied
boxes from 2 individuals to up to all colony members. Furthermore,
boxes that were not used as a day roost were also visited by up to
Plecotus auritus (colony B)
Total
2009
540.9
2010
97.1
2011
189.1
Total
32
17
7
56
7
4
1
12
5
6
0
11
10
2
1
13
22
12
2
36
24
2
2
28
19
1
0
20
20
1
0
21
6
1
0
7
45
3
0
48
all individuals for Bechstein’s bats and up to 86.7% of colony members for brown long-eared bats. Therefore, we can exclude that
the brown long-eared bats did not occupy the “repelling” boxes
because not enough individuals had visited the boxes before occupying. These findings also offer little indication that a certain number of bats (quorum; Conradt and Roper 2005; Sumpter and Pratt
2009) needed to visit a box before it was used as a communal roost.
Overall, the 5 “one-third” boxes were occupied by a total of 30
Bechstein’s bats (19 different individuals some of which occupied
more than 1 “one-third” box) that did not receive a stimulus and
only 1 Bechstein’s bat that did. Thus, individual Bechstein’s bats
that had received an air puff when visiting the “one-third” boxes
at night later avoided roosting in the respective boxes during the
day, whereas individuals that had not received an air puff during
their nightly visits at a “one-third” box often later roosted there.
In agreement with this finding, we observed on 4 out of the 5
times (80%) where “one-third” boxes were used as a day roost,
Bechstein’s bats roosting in more than 1 bat box. In contrast, when
using “control” boxes, Bechstein’s bats only split into subgroups
using different boxes on 18.2% of the days. This confirms previous results (Fleischmann et al. 2013) that Bechstein’s bats react to
a situation with strongly conflicting individual interest by splitting
into subgroups that represent their individual interests (individual
decision). In contrast to the Bechstein’s bats, in the brown longeared bats, even individuals that had not experienced an air puff at
a given box where we had induced conflicting interests (“one-third”
and “two-thirds” boxes) never used such a box as a day roosts. This
suggests that brown long-eared bats, unlike Bechstein’s bats, sought
a consensus of all group members (unanimous decision) even in
a situation with conflicting individual interests and only occupied
boxes where none of the colony members had received a repelling
stimulus.
Discussion
Our daily monitoring of the individual roosting behavior over 3
breeding seasons revealed that Bechstein’s bats discovered newly
installed bat boxes significantly faster than brown long-eared bats.
Bechstein’s bats also discovered new boxes outside of their current
roosting area significantly more often than the brown long-eared
bats. This species-specific difference in exploratory behavior cannot be explained by the foraging behavior of the 2 species. Both
are gleaners that typically forage within 1 km from their roosts
Fleischmann and Kerth • Group decisions in 2 syntopic bat species
1245
Figure 2
Percentage of discovered boxes that were used as day roosts. Different shades symbolize different colonies. Control boxes were only monitored with automatic
reading devices and served as control. At repelling boxes, predetermined bats experienced a repelling stimulus. Heat boxes were heated by means of heating
foils. N states the number of boxes that were discovered by the different colonies.
(Entwistle et al. 1996, 1997; Kerth and Melber 2009). For comparison, in our study, the new boxes were placed within 20 m of
previously used roosts. Furthermore, at least for Bechstein’s bats, it
is known that even those individuals that have overlapping foraging
areas (the foraging areas of most colony members show no overlap) do not forage in close proximity (Melber et al. 2013). We can
therefore exclude that the spread of information about the presence of potential new communal roosts depends on proximity of
foraging individuals. Instead, there is strong experimental evidence
that Bechstein’s bats lead colony members specifically to suitable
potential roosts (Kerth and Reckardt 2003).
Our analyses also confirmed that the 2 studied species differed substantially in the degree of their fission–fusion behavior.
Bechstein’s bats formed subgroups on 5 times as many days than
brown long-eared bats, which is in agreement with the reported
high fission–fusion dynamics of Bechstein’s bat colonies (Kerth and
König 1999; Kerth et al. 2011). Several hypotheses have been proposed to explain fission–fusion dynamics in animals involving ecological factors such as resource availability as well as social factors
such as information sharing and social bonds (Sueur et al. 2011).
Accordingly, in bats, fission–fusion behavior might facilitate maintaining social bonds between individuals belonging to a colony that
is widespread over a forest for ecological reasons (O’Donnell 2000;
O’Donnell and Sedgeley 2006; Kerth et al. 2011). In addition, fission–fusion and the associated roost switching behavior may allow
colony members to gather and share information about a high
number of potential day roosts (Kerth and Reckardt 2003; Russo
et al. 2005; O’Donnell and Sedgeley 2006). Finally, fission–fusion
behavior may allow individual colony members to avoid group
decisions about communal roosts that are not in their favor without losing grouping benefits such as social warming (Kerth 2010b;
Fleischmann et al. 2013).
In our study, we found little evidence that the lower degree of
fission–fusion behavior in brown long-eared bats was linked to a
lower degree of roost switching in this species. We observed no
consistent differences in the number of boxes used as day roosts
between Bechstein’s bats and brown long-eared bats. Moreover, as
both species have a very similar roosting and feeding ecology and
as we studied them in the identical habitat where they used the
same type of day roosts, ecological factors seem unlikely to explain
their different fission–fusion behavior. At the same time, Bechstein’s
bats were more explorative than brown long-eared bats and roosted
significantly more often in new boxes. Thus, the higher degree of
fission–fusion behavior in Bechstein’s bats may be explained with
benefits arising from a high rate of information gathering and
information sharing about new potential communal day roosts
within the colony. In Bechstein’s bats, roost switching and a preference for novel roosts are probably at least in part triggered by
the avoidance of roosts infested with bat flies (Reckardt and Kerth
2006, 2007). Interestingly, bat flies are largely absent in the brown
long-eared bat colonies in our study area (unpublished data). This
may explain why brown long-eared bats could afford to roost
Behavioral Ecology
1246
mainly in old boxes and be relatively slow in finding new potential
roosts. Moving between different roosts due to parasite infection is
not only known in bats but also in badgers, Meles meles, that spent
more consecutive days in borrows when they were experimentally
treated with antiparasitic spray (Butler and Roper 1996). Similarly,
Brant’s whistling rats, Parotomys brantsii, start moving between daytime sleeping chambers when the parasitic pressure amasses (Roper
et al. 2002).
The few existing studies on animal group decision making in
situations with conflicting individual interests showed that temporary group fission instead of consensus decisions can occur under
certain circumstances. For example, in chacma baboons, Papio
ursius, groups split up when following individuals had weak social
links to the individual initiating group foraging decisions (King
et al. 2008). In homing pigeons, Colomba livia, fission only took place
when the birds differed strongly among each other in which homing flight route they preferred (Biro et al. 2006). Previous studies
on group decision making about communal roosts in Bechstein’s
bats revealed that the actual decision rule used depended on how
strongly individual interests diverged among the colony members
(Kerth et al. 2006; Fleischmann et al. 2013). In situations with low
levels of conflict of interest, Bechstein’s bats have been found to
make consensus decisions. However, in situations with high levels of
conflict, Bechstein’s bats no longer sought a consensus, but individuals followed their own interests and formed subgroups accordingly.
In an identical setup as in our field experiment, Fleischmann
et al. (2013) found that 3 Bechstein’s bat colonies, whose sizes
ranged from 12 to 42 colony members, consistently formed subgroups according to the individual interests of their colony members. Because we studied one of the colonies of Fleischmann et al.
(2013) and only added 1 further year to their data, it is not surprising that we obtained similar result for Bechstein’s bats. Taken
together, our findings and that of Fleischmann et al. (2013) suggest
that Bechstein’s bats (based on data of 3 colonies) only refrained
occupying repelling boxes when the majority or all of the colony
members experienced a repelling stimulus. Boxes where a small
part of the colony experienced repelling stimuli were used as day
roosts, but Bechstein’s bats often formed subgroups instead of
reaching a consensus on a single communal roost when individuals
diverge too much in their interest where to roost.
No previous study investigated group decision making about
communal roosts in brown long-eared bats. Our study suggests
that brown long-eared bats use a different decision rule than the
Bechstein’s bats when deciding about communal roosts in situations
with conflicting individual interests. The results of our field experiment indicate that in brown long-eared bats, unlike in Bechstein’s
bats, group decision making about communal roost were made
unanimously, always leading to a consensus decision even in situations with a strong conflict of interest among colony members.
We are aware that the number of bat colonies (1 for Bechstein’s
bats and 2 for brown long-eared bats) in our study is rather low.
However, as we conducted the same experiment as Fleischmann
et al. (2013), we can use their results on 2 additionally studied
Bechstein’s bat colonies as a reference, increasing the number of
Bechstein’s bat colonies to 3 in total. Furthermore, due to the fact
that studying group decision making experimentally in the field
involves considerable logistic difficulties, there still is a dearth of
experimental field data, which makes our study valuable. For comparison, other studies of group decision making in wild mammals
have similar sample sizes to ours for logistic reasons (e.g., Bourjade
et al. 2009; King et al. 2011; Pyritz et al. 2013).
In conclusion, our study shows that the rules applied to make
group decisions about communal day roosts can differ between 2
ecologically similar bat species even in situations where they experience an identical coordination problem. Our study thus underlines
the importance of using a comparative approach to study group
decision making in more species to gain a more complete understanding of the flexibility of group decision making in animals. In
this context, it should be highly interesting to conduct more standardized experiments on different species. For instance, Scholes
and Suarez (2009) were able to show that 2 ant species show different decision rules in a standardized lab experiment. To assess the
generality of our results with respect to fission–fusion dynamics,
it will be important to compare group decision making between
more species that differ in their fission–fusion behavior, for example, among primates, carnivores, or dolphins (Aureli et al. 2008).
Finally, to fully understand group decision making, we also have to
study the contribution each individual makes to the group’s decision to find out how genetic and social relationships among group
members or different “personalities” (King et al. 2008; Sueur and
Petit 2008; Aplin et al. 2013) influence the way group decisions are
made in situations with different degrees of conflicting interests.
Funding
The German Science Foundation (KE 746/4-1) provided financial
support to G.K.
We thank L. Conradt, M. Melber, S. Puechmaille, D. Farine, and 1 anonymous reviewer for useful comments on the manuscript. This study was carried out under license from the nature conservancy department of Lower
Franconia.
Handling editor: Madeleine Beekman
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