Bayesian Model Selection with Network Based Diffusion Analysis

A number of recent studies have used Network Based Diffusion Analysis (NBDA) to detect the role of social transmission in the spread of a novel behavior through a population. In this paper we present a unified framework for performing NBDA in a Bayesian setting, and demonstrate how the Watanabe Akaike Information Criteria (WAIC) can be used for model selection. We present a specific example of applying this method to Time to Acquisition Diffusion Analysis (TADA). To examine the robustness of this technique, we performed a large scale simulation study and found that NBDA using WAIC could recover the correct model of social transmission under a wide range of cases, including under the presence of random effects, individual level variables, and alternative models of social transmission. This work suggests that NBDA is an effective and widely applicable tool for uncovering whether social transmission underpins the spread of a novel behavior, and may still provide accurate results even when key model assumptions are relaxed

Investigating the Impact of Observation Errors on the Statistical Performance of Network-based Diffusion Analysis

Experiments in captivity have provided evidence for social learning, but it remains challenging to demon- strate social learning in the wild. Recently, we developed network-based diffusion analysis (NBDA; 2009) as a new approach to inferring social learning from observational data. NBDA fits alternative models of asocial and social learning to the diffusion of a behavior through time, where the potential for social learning is related to a social network. Here, we investigate the performance of NBDA in relation to variation in group size, network heterogeneity, observer sampling errors, and duration of trait diffusion. We find that observation errors, when severe enough, can lead to increased Type I error rates in detecting social learning. However, elevated Type I error rates can be prevented by coding the observed times of trait acquisition into larger time units. Collectively, our results provide further guidance to applying NBDA and demonstrate that the method is more robust to sampling error than initially expected. Supplemental materials for this article may be downloaded from http:// lb.psychonomic-journals.org/content/supplemental.Human Evolutionary Biolog

Environmental complexity influences association network structure and network-based diffusion of foraging information in fish shoals

This project was funded by grants from the Natural Environment Research Council (NE/D010365/1) and the European Research Council (EVOCULTURE 232823) to K.N.L.Socially transmitted information can significantly affect the ways in which animals interact with their environments. We used network-based diffusion analysis, a novel and powerful tool for exploring information transmission, to model the rate at which sticklebacks (Gasterosteus aculeatus) discovered prey patches, comparing shoals foraging in open and structured environments. We found that for groups in the open environment, individuals tended to recruit to both the prey patch and empty comparison patches at similar times, suggesting that patch discovery was not greatly affected by direct social transmission. In contrast, in structured environments we found strong evidence that information about prey patch location was socially transmitted and moreover that the pathway of information transmission followed the shoals' association network structures. Our findings highlight the importance of considering habitat structure when investigating the diffusion of information through populations and imply that association networks take on greater ecological significance in structured than open environments.Publisher PDFPeer reviewe

Multi-network-based diffusion analysis reveals vertical cultural transmission of sponge tool use within dolphin matrilines

Behavioural differences among social groups can arise from differing ecological conditions, genetic predispositions and/or social learning. In the past, social learning has typically been inferred as responsible for the spread of behaviour by the exclusion of ecological and genetic factors. This ‘method of exclusion’ was used to infer that ‘sponging’, a foraging behaviour involving tool use in the bottlenose dolphin (Tursiops aduncus) population in Shark Bay, Western Australia, was socially transmitted. However, previous studies were limited in that they never fully accounted for alternative factors, and that social learning, ecology and genetics are not mutually exclusive in causing behavioural variation. Here, we quantified the importance of social learning on the diffusion of sponging, for the first time explicitly accounting for ecological and genetic factors, using a multi-network version of ‘network-based diffusion analysis'. Our results provide compelling support for previous findings that sponging is vertically socially transmitted from mother to (primarily female) offspring. This research illustrates the utility of social network analysis in elucidating the explanatory mechanisms behind the transmission of behaviour in wild animal populations

Cultural transmission modes of music sampling traditions remain stable despite delocalization in the digital age

Music sampling is a common practice among hip-hop and electronic producers that has played a critical role in the development of particular subgenres. Artists preferentially sample drum breaks, and previous studies have suggested that these may be culturally transmitted. With the advent of digital sampling technologies and social media the modes of cultural transmission may have shifted, and music communities may have become decoupled from geography. The aim of the current study was to determine whether drum breaks are culturally transmitted through musical collaboration networks, and to identify the factors driving the evolution of these networks. Using network-based diffusion analysis we found strong evidence for the cultural transmission of drum breaks via collaboration between artists, and identified several demographic variables that bias transmission. Additionally, using network evolution methods we found evidence that the structure of the collaboration network is no longer biased by geographic proximity after the year 2000, and that gender disparity has relaxed over the same period. Despite the delocalization of communities by the internet, collaboration remains a key transmission mode of music sampling traditions. The results of this study provide valuable insight into how demographic biases shape cultural transmission in complex networks, and how the evolution of these networks has shifted in the digital age

Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals

Numerous factors affect the fine-scale social structure of animal groups, but it is unclear how important such factors are in determining how individuals encounter resources. Familiarity affects shoal choice and structure in many social fishes. Here, we show that familiarity between shoal members of sticklebacks (Gasterosteus aculeatus) affects both fine-scale social organization and the discovery of resources. Social network analysis revealed that sticklebacks remained closer to familiar than to unfamiliar individuals within the same shoal. Network-based diffusion analysis revealed that there was a strong untransmitted social effect on patch discovery, with individuals tending to discover a task sooner if a familiar individual from their group had previously done so than if an unfamiliar fish had done so. However, in contrast to the effect of familiarity, the frequency with which individuals had previously associated with one another had no effect upon the likelihood of prey patch discovery. This may have been due to the influence of fish on one another's movements; the effect of familiarity on discovery of an empty ‘control’ patch was as strong as for discovery of an actual prey patch. Our results demonstrate that factors affecting fine-scale social interactions can also influence how individuals encounter and exploit resources.Publisher PDFPeer reviewe

The conceptual foundations of Network-Based Diffusion Analysis: choosing networks and interpreting results

Network-based diffusion analysis (NBDA) is a statistical technique for detecting the social transmission of behavioural innovations in groups of animals, including humans. The strength of social transmission is inferred from the extent to which the diffusion (spread) of the innovation follows a social network. NBDA can have two goals: a) to establish whether social transmission is occurring and how strong its effects are; and/or b) to establish the typical pathways of information transfer. The technique has been used in a range of taxa, including primates, cetaceans, birds and fish, using a range of different types of network.  Here I investigate the conceptual underpinnings of NBDA, in order to establish the meaning of results using different networks. I develop a model of the social transmission process whereby observation of performance of the behaviour offers a naïve individual the opportunity to learn that behaviour pattern for themselves. I then establish how NBDAs using different networks relate to this underlying process, and thus how we can interpret the results of each. My analysis shows that different network or networks are appropriate depending on the specific goal or goals of the study, and establishes how the parameter estimates yielded from an NBDA can be interpreted for different networks

Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees

The authors are grateful to the Royal Zoological Society of Scotland for providing core funding for the Budongo Conservation Field Station. The fieldwork of CH was funded by the Leverhulme Trust, the Lucie Burgers Stichting, and the British Academy. TP was funded by the Canadian Research Chair in Continental Ecosystem Ecology, and received computational support from the Theoretical Ecosystem Ecology group at UQAR. The research leading to these results has received funding from the People Programme (Marie Curie Actions) and from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007–2013) REA grant agreement n°329197 awarded to TG, ERC grant agreement n° 283871 awarded to KZ. WH was funded by a BBSRC grant (BB/I007997/1).Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition-that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, "moss-sponging'' and "leaf-sponge re-use,'' in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most "cultural'' of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.Publisher PDFPeer reviewe

Multi-network-based diffusion analysis reveals vertical cultural transmission of sponge tool use within dolphin matrilines

Behavioural differences among social groups can arise from differing ecological conditions, genetic predispositions and/or social learning. In the past, social learning has typically been inferred as responsible for the spread of behaviour by the exclusion of ecological and genetic factors. This 'method of exclusion' was used to infer that 'sponging', a foraging behaviour involving tool use in the bottlenose dolphin (Tursiops aduncus) population in Shark Bay, Western Australia, was socially transmitted. However, previous studies were limited in that they never fully accounted for alternative factors, and that social learning, ecology and genetics are not mutually exclusive in causing behavioural variation. Here, we quantified the importance of social learning on the diffusion of sponging, for the first time explicitly accounting for ecological and genetic factors, using a multi-network version of 'network-based diffusion analysis'. Our results provide compelling support for previous findings that sponging is vertically socially transmitted from mother to (primarily female) offspring. This research illustrates the utility of social network analysis in elucidating the explanatory mechanisms behind the transmission of behaviour in wild animal populations