Network analysis has driven key developments in animal behavior research by providing quantitative methods to study the social structure of animal groups and populations. A recent advancement in network science, multilayer network analysis, the study of network structures of multiple interconnected `layers' , offers a novel way to represent and analyze the structure of animal behavior, and help strengthen links to broader ecological and evolutionary contexts . We outline the potential uses of these new methods at individual-, group-, population-, and evolutionary-levels, and we highlight their potential to advance behavioral ecology research . This novel quantitative approach makes it possible to address classic research questions from a new perspective and opens a diversity of new questions that previously have been out of reach.
Network analysis has driven key developments in animal behavior research by providing quantitative methods to study the social structures of animal groups and populations. A recent advancement in network science, multilayer network analysis, the study of network structures of multiple interconnected 'layers' and associated dynamical processes , offers a novel way to represent and analyze animal behavior. It also helps strengthen the links between animal social behavior and broader ecological and evolutionary contexts and processes. In this article, we describe how to encode animal behavior data as different types of multilayer networks, and we link recently-developed multilayer methods to individual-, group-, population-, and evolutionary-level questions in behavioral ecology. We outline a variety of examples for how to apply multilayer methods in behavioral ecology research , including examples that demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. These new insights have consequences for ecological processes such as disease transmission. We also discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we outline methodological challenges for the application of these approaches. Multilayer network analysis offers a promising approach for tackling classical research questions from a new perspective , and it opens a plethora of new questions that have thus far been out of reach.
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. This novel quantitative approach makes it possible to address classic
, including examples that demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. These new insights have consequences for ecological processes such as disease transmission. We also discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we outline methodological challenges for the application of these approaches. Multilayer network analysis offers a promising approach for tackling classical
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