The use of multilayer network analysis in animal behaviour

Abstract

Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as multilayer network analysis, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour through connected ‘layers’ of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.

A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques

“…Given that members of a society interact in different ways using different social behaviors, each interaction type can represent a different layer of a multiplex social network. Multilayer network approaches unify information across separate interaction networks or social domains (Barrett, Henzi & Lusseau, 2012;Finn et al, 2019) to address questions about both individual-level (e.g., individual social role) and higher-order (e.g., group-level social structure) social patterns. For instance, using a single network layer to identify the individual(s) of greatest influence, importance, and/or centrality runs the risk of missing truly influential individuals by relying on incomplete social information.…”

“…Methods to perform multilayer network analysis have only recently been developed, and their application to understanding animal social relationships and social structure has only just begun (Barrett, Henzi & Lusseau, 2012;Chan et al, 2013;Beisner et al, 2015;Silk et al, 2018;Finn et al, 2019). Some approaches focus on network-level patterns such as characterizing interdependence between network layers (Barrett, Henzi & Lusseau, 2012;Chan et al, 2013;Beisner et al, 2015) and others focus on individual or node-level position such as centrality or clustering (Barrett, Henzi & Lusseau, 2012;De Domenico et al, 2013;Smith-Aguilar et al, 2018).…”

Primate Infectious Disease Ecology: Insights and Future Directions at the Human-Macaque Interface

“…This may be the reason why most epidemiological studies implementing network approaches to model heterogeneity in contact patterns have focused on either human systems or more recently wildlife systems (reviewed above), but almost never at the human-wildlife interface. Bipartite and multimodal networks, which establish connections between different interlinked components of a system, may prove especially useful in this regard (Dormann et al 2017;Kane and Alavi 2008;Latapy et al 2008;Finn et al 2019). Recently, bipartite networks are beginning to feature in ecological and evolutionary research (reviewed in Bascompte and Jordano 2014;Cagnolo et al 2011;Dormann et al 2017), as illustrated by their being used to model marine food webs (Rezende et al 2009), mutualistic interactions between flowers and seed-dispersing animal pollinators (Spiesman and Gratton 2016;Stang et al 2009;Vazquez et al 2009), and, more pertinently, host-parasitoid relationships (Laliberte and Tylianakis 2010;Poulin et al 2013).…”

“…Recently, bipartite networks are beginning to feature in ecological and evolutionary research (reviewed in Bascompte and Jordano 2014;Cagnolo et al 2011;Dormann et al 2017), as illustrated by their being used to model marine food webs (Rezende et al 2009), mutualistic interactions between flowers and seed-dispersing animal pollinators (Spiesman and Gratton 2016;Stang et al 2009;Vazquez et al 2009), and, more pertinently, host-parasitoid relationships (Laliberte and Tylianakis 2010;Poulin et al 2013). For networks that combine links both within and across system components, some researchers have coined the term "multimodal networks," aka "multilayer" or "multislice networks" (Kane and Alavi 2008;Finn et al 2019).…”

A multilayer perspective for inferring spatial and social functioning in animal movement networks

“…locations) based on their centrality, these 81 networks may be misleading for interpreting processes that are facilitated by sociality. For example, 82 monolayer movement networks do not consider contact rates between individuals, that is they 83 typically cannot differentiate between animals using the same location at the same or at different 84 times and this can have important implications for the probabilities of disease or information transfer 85 between individuals (Silk et al, 2019). Therefore, there remains a number of analytical challenges 86 associated with how best to amalgamate data to draw population-level inferences or to divide 87 movement network data to explore individual-and group-level variation in behaviours.…”