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

Leading-following behavior as a way of transferring information about the location of resources is wide-spread in many animal societies. It represents active information transfer that allows a given social species to reach collective decisions in the presence of limited information. Although leading-following behavior has received much scientific interest in the form of field studies, there is a need for systematic methods to quantify and study the individual contributions in this information transfer, which would eventually lead us to hypotheses about the individual mechanisms underlying this behaviour. In this paper we propose a general methodology that allows us to (a) infer individual leading-following behaviour from discrete observational data and (b) quantify individual influence based on methods from social network analysis. To demonstrate our methodology, we analyze longitudinal data of the roosting behavior of two different colonies of Bechstein's bats in different years. Regarding (a) we show how the inference of leading-following events can be calibrated from data making it a general approach when only discrete observations are available. This allows us to address (b) by constructing social networks in which nodes represent individual bats and directed and weighted links-the leading-following events. We then show how social network theory can be used to define and quantify individual influence in a way that reflects the dynamics of the specific social network. We find that individuals can be consistently ranked regarding their influence in the information transfer. Moreover, we identify a small set of individuals that play a central role in leading other bats to roosts. In the case of Bechstein's bats this finding can direct future studies on the individual-level mechanisms that result in such collective pattern. More generally, we posit that our data-driven methodology can be used to quantify leading-following behavior and individual impact in other animal systems, solely based on discrete observational data.

Female Bechstein's bats adjust their group decisions about communal roosts to the level of conflict of interests.

Most social animals depend on group decisions for coordination. Recent models suggest that the level of interindividual conflict strongly influences whether groups reach a consensus during decision making. However, few experimental studies have explored how wild animals make group decisions in situations with conflicting interests. Such experimental data are particularly lacking for animal societies with regular fission and fusion of subgroups. In this long-term study, we varied the level of conflict of interest among members of three wild Bechstein's bat (Myotis bechsteinii) colonies with high fission-fusion dynamics experimentally to explore whether the bats adapt their group decisions about communal roosts accordingly. In situations with low levels of conflict of interest, a minority of bats experiencing a roost as suitable was sufficient for a group consensus to use it communally. In contrast, if their interests diverged strongly, the bats no longer sought a compromise, but based their roosting decisions on individual preferences instead. Our results demonstrate that the rules applied to make group decisions can vary with the level of conflict among the individual interests of group members. Our findings are in agreement with predictions of the models and provide evidence for highly flexible group decisions within species.