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Collective Animal Behavior
Animal Behaviour 82 (2011) 608
Contents lists available at ScienceDirect
Animal Behaviour journal homepage: www.elsevier.com/locate/anbehav
Book Review Collective Animal Behavior. By David J. T. Sumpter. Princeton, New Jersey: Princeton University Press (2011). Pp. 312. Price £55 hardback, £27.95 paperback. Collective Animal Behavior is a fascinating and inspiring book. Collective phenomena are ubiquitous in physical, biological and social systems and understanding them represents a major issue in several areas of research. Animal groups provide paradigmatic examples of collective phenomena, from bird flocks to fish schools, ant trails and honeybee dances. The aim of this book is to study how and why collective patterns emerge in animal groups. At the mechanistic level, this means unveiling the dynamics leading from interactions between individuals to the collective behaviour of the group. From an evolutionary perspective, this implies investigating whether collective behaviour has functional motivations and why interactions have evolved in a specific way. The approach described in the book is based on mathematical modelling. I would say that an additional objective of the book is to demonstrate how mathematical modelling is indispensable to understanding collective animal behaviour. As the author comments in the conclusions, models are not useless toys for the benefit of theorists but, when used with feedback from experimental data, they represent crucial tools to give quantitative descriptions, test hypotheses and make predictions. The book offers a remarkable overview of collective phenomena in animal groups, providing a wide variety of examples and bringing together literature from very diverse areas. Using an intelligent organization of these examples according to key concepts, the author succeeds in giving a unifying description, while still devoting a lot of attention to the detailed aspects of the mathematical formulation. The author makes wide use of mathematical techniques from different areas of science, from dynamical systems (the Kuramoto model and the logistic equation) to physics (selfpropelled particle models and preferential attachment), network theory and evolutionary game theory, to name just a few. In doing so, he emphasizes and demonstrates the need for a multidisciplinary approach to complex systems. The book is divided into thematic chapters, each focusing on a particular aspect of collective animal behaviour: group formation, information transfer, collective movement, synchronization, structures, regulation, complicated interactions and evolution of cooperation. In many cases, several of these aspects may be present in the same animal group. For example, schools of fish represent a typical case of emergence of collective motion from individual rules, and also exhibit a nontrivial aggregation dynamics between groups. The rationale of the book’s structure is to group together phenomena, or manifestations, that can be attributed to the same mechanism, and can therefore be described with the same class
of models. For example, positive feedback and nonlinear responses can explain different recruitment systems, and the Kuramoto model is used to describe several kinds of synchronized activity, from the renowned simultaneous flashing of fireflies to the dynamics of foraging chickens. In each chapter, there is a thorough discussion of the mathematical models that have been introduced in the literature to address the subject under consideration. Particular attention is devoted to presenting the modelling approach in a way accessible to most readers: simplified versions of more complicated models are often introduced, to pinpoint the main components and make the model more intuitive. At the same time, the author never loses contact with real biological systems and the feedback with experiments is always underlined. Throughout the book, the author has tried to link mechanistic and functional approaches. When possible, the same problem is addressed from the two perspectives to provide combined explanations. While more emphasis is, in general, dedicated to the mechanistic approach, the final chapter is devoted entirely to the evolution of cooperation. The author presents a synthetic and effective description of evolutionary games, and uses simple models to classify behavioural strategies and make predictions about the degree of cooperation and conflict in animal societies. I very much enjoyed reading this book and would certainly recommend it to anyone willing to approach the fascinating subject of collective animal behaviour. As discussed previously, a remarkable feature of this work is the way the author pools ideas, concepts and models from theoretical biology, physics, game theory and microeconomics. The reader is provided with a stimulating ensemble of techniques and perspectives. At the same time, collective animal behaviour is addressed as a problem deeply rooted in behavioural ecology. Animal groups, flocks of birds and schools of fish, in particular, have attracted enormous interest in recent years as typical examples of efficient distributed coordination and offequilibrium-activated systems. As such, they have been studied by control theorists and statistical physicists. These aspects are not addressed in this book, and the reader will not find links and references to decentralized algorithms and active matter. As a statistical physicist working in this field, my hope is that the approach of statistical physics to animal groups may, in the future, be summarized in the same insightful, broad and inspiring way as in this book. Irene Giardinaa,b Institute for Complex Systems – CNR, Via dei Taurini 19, 00185 Rome, Italy
a
b
Department of Physics, University of Rome La Sapienza, P.le A. Moro 2, 00185 Rome, Italy
0003-3472/$38.00 Ó 2011 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.anbehav.2011.06.005
Contents lists available at ScienceDirect
Animal Behaviour journal homepage: www.elsevier.com/locate/anbehav
Book Review Collective Animal Behavior. By David J. T. Sumpter. Princeton, New Jersey: Princeton University Press (2011). Pp. 312. Price £55 hardback, £27.95 paperback. Collective Animal Behavior is a fascinating and inspiring book. Collective phenomena are ubiquitous in physical, biological and social systems and understanding them represents a major issue in several areas of research. Animal groups provide paradigmatic examples of collective phenomena, from bird flocks to fish schools, ant trails and honeybee dances. The aim of this book is to study how and why collective patterns emerge in animal groups. At the mechanistic level, this means unveiling the dynamics leading from interactions between individuals to the collective behaviour of the group. From an evolutionary perspective, this implies investigating whether collective behaviour has functional motivations and why interactions have evolved in a specific way. The approach described in the book is based on mathematical modelling. I would say that an additional objective of the book is to demonstrate how mathematical modelling is indispensable to understanding collective animal behaviour. As the author comments in the conclusions, models are not useless toys for the benefit of theorists but, when used with feedback from experimental data, they represent crucial tools to give quantitative descriptions, test hypotheses and make predictions. The book offers a remarkable overview of collective phenomena in animal groups, providing a wide variety of examples and bringing together literature from very diverse areas. Using an intelligent organization of these examples according to key concepts, the author succeeds in giving a unifying description, while still devoting a lot of attention to the detailed aspects of the mathematical formulation. The author makes wide use of mathematical techniques from different areas of science, from dynamical systems (the Kuramoto model and the logistic equation) to physics (selfpropelled particle models and preferential attachment), network theory and evolutionary game theory, to name just a few. In doing so, he emphasizes and demonstrates the need for a multidisciplinary approach to complex systems. The book is divided into thematic chapters, each focusing on a particular aspect of collective animal behaviour: group formation, information transfer, collective movement, synchronization, structures, regulation, complicated interactions and evolution of cooperation. In many cases, several of these aspects may be present in the same animal group. For example, schools of fish represent a typical case of emergence of collective motion from individual rules, and also exhibit a nontrivial aggregation dynamics between groups. The rationale of the book’s structure is to group together phenomena, or manifestations, that can be attributed to the same mechanism, and can therefore be described with the same class
of models. For example, positive feedback and nonlinear responses can explain different recruitment systems, and the Kuramoto model is used to describe several kinds of synchronized activity, from the renowned simultaneous flashing of fireflies to the dynamics of foraging chickens. In each chapter, there is a thorough discussion of the mathematical models that have been introduced in the literature to address the subject under consideration. Particular attention is devoted to presenting the modelling approach in a way accessible to most readers: simplified versions of more complicated models are often introduced, to pinpoint the main components and make the model more intuitive. At the same time, the author never loses contact with real biological systems and the feedback with experiments is always underlined. Throughout the book, the author has tried to link mechanistic and functional approaches. When possible, the same problem is addressed from the two perspectives to provide combined explanations. While more emphasis is, in general, dedicated to the mechanistic approach, the final chapter is devoted entirely to the evolution of cooperation. The author presents a synthetic and effective description of evolutionary games, and uses simple models to classify behavioural strategies and make predictions about the degree of cooperation and conflict in animal societies. I very much enjoyed reading this book and would certainly recommend it to anyone willing to approach the fascinating subject of collective animal behaviour. As discussed previously, a remarkable feature of this work is the way the author pools ideas, concepts and models from theoretical biology, physics, game theory and microeconomics. The reader is provided with a stimulating ensemble of techniques and perspectives. At the same time, collective animal behaviour is addressed as a problem deeply rooted in behavioural ecology. Animal groups, flocks of birds and schools of fish, in particular, have attracted enormous interest in recent years as typical examples of efficient distributed coordination and offequilibrium-activated systems. As such, they have been studied by control theorists and statistical physicists. These aspects are not addressed in this book, and the reader will not find links and references to decentralized algorithms and active matter. As a statistical physicist working in this field, my hope is that the approach of statistical physics to animal groups may, in the future, be summarized in the same insightful, broad and inspiring way as in this book. Irene Giardinaa,b Institute for Complex Systems – CNR, Via dei Taurini 19, 00185 Rome, Italy
a
b
Department of Physics, University of Rome La Sapienza, P.le A. Moro 2, 00185 Rome, Italy
0003-3472/$38.00 Ó 2011 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.anbehav.2011.06.005