Insights from the study of complex systems for the ecology and evolution of animal populations

Populations of animals comprise many individuals,interacting in multiple contexts,and displaying heterogeneous behaviors.The interactions among individuals can often create population dynamics that are fundamentally deterministic yet display unpredictable dynamics.Animal populations can,therefore,be thought of as complex systems.Complex systems display properties such as nonlinearity and uncertainty and show emergent properties that cannot be explained by a simple sum of the interacting components.Any system where entities compete,cooperate,or interfere with one another may possess such qualities,making animal populations similar on many levels to complex systems.Some fields are already embracing elements of complexity to help understand the dynamics of animal populations,but a wider application of complexity science in ecology and evolution has not occurred.We review here how approaches from complexity science could be applied to the study of the interactions and behavior of individuals within animal populations and highlight how this way of thinking can enhance our understanding of population dynamics in animals.We focus on 8 key characteristics of complex systems:hierarchy,heterogeneity,selforganization,openness,adaptation,memory,nonlinearity,and uncertainty.For each topic we discuss how concepts from complexity theory are applicable in animal populations and emphasize the unique insights they provide.We finish by outlining outstanding questions or predictions to be evaluated using behavioral and ecological data.Our goal throughout this article is to familiarize animal ecologists with the basics of each of these concepts and highlight the new perspectives that they could bring to variety of subfields.

Using multilayer network analysis to explore the temporal dynamics of collective behavior

Social organisms often show collective behaviors such as group foraging or movement.Collective behaviors can emerge from interactions between group members and may depend on the behavior of key individuals.When social interactions change over time,collective behaviors may change because these behaviors emerge from interactions among individuals.Despite the importance of,and growing interest in,the temporal dynamics of social interactions,it is not clear how to quantify changes in interactions over time or measure their stability.Furthermore,the temporal scale at which we should observe changes in social networks to detect biologically meaningful changes is not always apparent.Here we use multilayer network analysis to quantify temporal dynamics of social networks of the social spider Stegodyphus dumicola and determine how these dynamics relate to individual and group behaviors.We found that social interactions changed over time at a constant rate.Variation in both network structure and the identity of a keystone individual was not related to the mean or variance of the collective prey attack speed.Individuals that maintained a large and stable number of connections,despite changes in network structure,were the boldest individuals in the group.Therefore,social interactions and boldness are linked across time,but group collective behavior is not influenced by the stability of the social network.Our work demonstrates that dynamic social networks can be modeled in a multilayer framework.This approach may reveal biologically important temporal changes to social structure in other systems.

Multilayer network analysis:new opportunities and challenges for studying animal social systems

Introduction Many behavioral,ecological,and evolutionary processes are closely intertwined with patterns of social interactions,such as the evolution of cooperation(Croft et al.2006),information and disease transmission(VanderWaal et al.2014;Aplin et al.2015),predator-prey dynamics(Ioannou et al.2012),and dispersal decisions(Blumstein et al.2009).Even in species where individuals are traditionally viewed as leading a relatively solitary existence,interac-tions occur across diverse contexts,including territorial defense,resource competition,and courtship.