Quantifying individual influence in leading-following behavior of Bechstein's bats

Changes in roosting decisions and group structure following parturition in little brown myotis (Myotis lucifugus)

In many temperate animals, reproductive cycles coincide with seasonal weather changes resulting in behaviour changes such as movement and habitat selection. In social species, these physiological and environmental changes can alter the costs and benefits of social interactions, impacting the structure of animal groups. In little brown myotis (Myotis lucifugus), a gregarious bat occupying much of North America, the pregnancy and lactation phases present different challenges to energy balance and maternal movement, and reduced forage distance has been observed during the lactation period. As such, we hypothesized that differences between reproductive phases alter the roost switching decisions of individual bats and therefore the overall group structure of little brown myotis maternity colonies. We observed that adult females were less likely to switch roosts during the lactation period even when accounting for changing weather conditions. This shift in roost switching behaviour may be the source of observed differences in group structure between reproductive periods. We reported a decline in network cohesiveness, but no meaningful variation in individual roost fidelity and association strengths of dyads between reproductive phases. These results support the contention that reproductive processes in female little brown myotis influence sociality and overall roosting patterns within maternity groups.

Demographic characteristics shape patterns of dawn swarming during roost switching in tree-dwelling Daubenton's bat

Frequent roost switching in fission-fusion societies of tree-dwelling bats is closely associated with swarming behaviour entailing ritualised night-time displays around the roost tree and/or at the roost entrance to signal its actual location, particularly immediately prior to sunrise. However, effects of demographic characteristics of individuals in this social behaviour remain unanswered. Using passive integrated transponders (PIT) and automatic readers, we recorded swarming activity of members of a Daubenton's bat (Myotis daubentonii) maternity colony in the vicinity of their roosts. In total, 59,622 activity events of 281 PIT-tagged individuals were recorded on ten monitored roosts during three summer seasons. We found a gradual increase of swarming activity from midnight to sunrise in old adult females, whereas young females and juveniles primarily swarmed later at dawn. We attribute this difference to the learning status of younger bats, which are not yet able to perform a defined pattern of swarming activity, whereas older bats likely take a more active role in signalling the position of the roost. Old males exhibited the least swarming activity at maternity roosts, which mostly occurred between crepuscular periods, presumably due to their solitary lives. A negative correlation between genetic distance and swarming activity suggests an important role of kinship in the formation of the maternity colony as well as group cohesion during roost switching.

Data-driven modelling of group formation in the fission-fusion dynamics of Bechstein's bats

Communal roosting in Bechstein’s bat colonies is characterized by the formation of several groups that use different day roosts and that regularly dissolve and re-merge (fission–fusion dynamics). Analysing data from two colonies of different sizes over many years, we find that (i) the number of days that bats stay in the same roost before changing follows an exponential distribution that is independent of the colony size and (ii) the number and size of groups that bats formed for roosting depend on the size of the colony, such that above a critical colony size two to six groups of different sizes are formed. To model these two observations, we propose an agent-based model in which agents make their decisions about roosts based on both random and social influences. For the latter, they copy the roost preference of another agent which models the transfer of the respective information. Our model is able to reproduce both the distribution of stay length in the same roost and the emergence of groups of different sizes dependent on the colony size. Moreover, we are able to predict the critical system size at which the formation of different groups emerges without global coordination. We further comment on dynamics that bridge the roosting decisions on short time scales (less than 1 day) with the social structures observed at long time scales (more than 1 year).

Influence of number of individuals and observations per individual on a model of community structure

Social network analysis is increasingly applied to understand animal groups. However, it is rarely feasible to observe every interaction among all individuals in natural populations. Studies have assessed how missing information affects estimates of individual network positions, but less attention has been paid to metrics that characterize overall network structure such as modularity, clustering coefficient, and density. In cases such as groups displaying fission-fusion dynamics, where subgroups break apart and rejoin in changing conformations, missing information may affect estimates of global network structure differently than in groups with distinctly separated communities due to the influence single individuals can have on the connectivity of the network. Using a bat maternity group showing fission-fusion dynamics, we quantify the effect of missing data on global network measures including community detection. In our system, estimating the number of communities was less reliable than detecting community structure. Further, reliably assorting individual bats into communities required fewer individuals and fewer observations per individual than to estimate the number of communities. Specifically, our metrics of global network structure (i.e., graph density, clustering coefficient, Rcom) approached the 'real' values with increasing numbers of observations per individual and, as the number of individuals included increased, the variance in these estimates decreased. Similar to previous studies, we recommend that more observations per individual should be prioritized over including more individuals when resources are limited. We recommend caution when making conclusions about animal social networks when a substantial number of individuals or observations are missing, and when possible, suggest subsampling large datasets to observe how estimates are influenced by sampling intensity. Our study serves as an example of the reliability, or lack thereof, of global network measures with missing information, but further work is needed to determine how estimates will vary with different data collection methods, network structures, and sampling periods.