Animal Social Networks PDF
Preview Animal Social Networks
Animal Social Networks EditEd by Jens Krause Professor of Fish Biology and Ecology, Humboldt University, Berlin, Germany and Professor of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany Richard James Senior Lecturer, University of Bath, UK Daniel W. Franks Reader in Complex Systems, University of York, UK Darren P. Croft Associate Professor of Animal Behaviour, University of Exeter, UK 1 Animal Social Networks. Edited by Jens Krause, Richard James, Daniel W. Franks and Darren P. Croft. © Oxford University Press 2015. Published 2015 by Oxford University Press. 9780199679058-Krause.indb 3 26/11/14 4:53 PM 3 Great Clarendon Street, Oxford, OX2 6DP, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. 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Oxford disclaims any responsibility for the materials contained in any third party website referenced in this work. 9780199679058-Krause.indb 4 26/11/14 4:53 PM Foreword Thirty five years ago, David Attenborough con- nevertheless have important implications both for cluded his landmark television series “Life on Earth” their own welfare and for population biology. with a programme on humans. For its title he chose However, the importance of networks for social “The Compulsive Communicators”, suggesting that behaviour has emerged from a change in thinking, our passion to communicate is as much a key to too. The reductionist, bottom up, approach of be- our success as fins for fish or feathers for birds. This havioural ecology emphasised how the behaviour compulsion is especially evident in our modern so- of individuals, selected to maximise their inclusive ciety, not just in gossiping groups but also lone in- fitness, led to various outcomes for social organisa- dividuals, busily networking even as they walk or tion. But as Robert Hinde pointed out, forty years drive around town. ago, we need to consider the two-way interaction This inspiring collection of chapters reveals that between individuals and social systems. Social sys- although fish, birds and other animals might not tems are just as much part of the stage on which share such compulsion to communicate, never- individuals play their behaviour as ecological fac- theless their associations and interactions create tors, so they are an essential part of the selective intricate social networks which play a central role landscape which determines how decisions are in their lives too. The book is a marvellous intro- moulded by natural selection. Individual decision duction to a newly discovered world. It shows how making influences social organisation, but the ar- “network thinking” - involving nodes, edges, close- row also goes the other way, feeding back from so- ness and clustering – can help illuminate many as- cial systems to influence how individual might best pects of social life, from the collective behaviour behave. of groups, as shoals and flocks form and move in The book serves as an excellent primer for those extraordinary synchrony, to the evolution of co- who want to master the new terminology and operation, and to how ideas and diseases are trans- understand how networks are measured, analysed mitted through populations. and interpreted. As many of the authors point out, The discovery of these social networks is partly a a static depiction of a network tells only part of the result of new techniques. Individuals can now eas- story; interactions change through time, dynamics ily be tracked with loggers and their positions and which are often key to understanding how disease associations mapped in space and time. This often and information spreads. Spread might take place results in millions of data points, which would have through direct interaction (grooming or fighting, for been overwhelming just a few years ago, but these example) or merely by spatial association (individ- can now be readily analysed, thanks to advances in uals using the same sites). The nodes in a network computational power and methodology. The result- might change behaviour too, as individuals are ma- ing network diagrams and metrics reveal how in- nipulated by parasites or react to neighbours. Fol- dividuals are connected to others not only by their lowing such changes through space and time will direct interactions with mates, family and imme- be a challenge, especially if keystone individuals in diate neighbours, but via linked chains to distant a network (so called “super-spreaders” of traits) are individuals who they will never meet, links which hard to find. v 9780199679058-Krause.indb 5 26/11/14 4:53 PM vi FOREWORD There are wonderful examples, too, of network co-operators to cluster and hence promote the analysis providing novel insights: how competitors evolution of cooperative behaviour? How can we jostle for position to enhance their relative attract- manipulate networks to minimise the spread of iveness to prospective mates, predicting who will disease, enhance the spread of information or max- first discover a novel food source, and how social imise welfare? How can we avoid destabilising learning spreads innovations and establishes cul- social groups when individuals are added or re- tural traditions in the wild. moved for conservation? So the book is not only a The chapters also point to fertile fields for fu- marvellous introduction to this exciting new field, ture research. How do differences in personality it will also help to inspire the next generation of and developmental history influence individual studies. positions in a network and their influence on Nicholas B. Davies the spread of traits? What mechanisms cause 9780199679058-Krause.indb 6 26/11/14 4:53 PM Acknowledgements Publishing an edited book is always a huge under- funding for an international workshop which helped taking and we would like to thank all those col- kick-start this book. Their organizational and finan- leagues who reviewed chapters in this book or who cial support is gratefully acknowledged. In addition, contributed in other ways: Lucy Aplin, Natasha we would like to thank Ian Sherman from Oxford Boyland, Lauren Brent, Julien Cote, Torben Dabel- University Press for his help with the book proposal steen, Daniel Charbonneau, Mathew Edenbrow, when the project was at an early stage and Lucy Mathias Franz, Stephanie Godfrey, Charlotte Hemel- Nash, also from Oxford University Press, for her rijk, Vincent Janik, Robert Jeanne, Raphael Jeanson, help, support, and patience throughout the entire Susanne Joop, Stefan Krause, Ralf Kurvers, Shuyan publishing process. Funding was provided to JK by Liu, Christof Neumann, Paul Rose, Bernhard Voelkl, the Leibniz Competition (SAW-2013-IGB-2) and the Ashley Ward, Mike Webster, and Max Wolf. Leibniz-Institute of Freshwater Ecology and Inland The Zentrum für interdisziplinäre Forschung, Fisheries, and to DPC by the Leverhulme Trust and Bielefeld University, provided us with generous the Natural Environment Research Council. vii 9780199679058-Krause.indb 7 26/11/14 4:53 PM 9780199679058-Krause.indb 8 26/11/14 4:53 PM List of Contributors Brianne A. Beisner Animal Behavior Laboratory Camilla A. Hinde Behavioural Ecology Group, for Welfare & Conservation, School of Veterinary Wageningen University, The Netherlands Medicine, University of California, Davis, USA Andrew G. Horn Department of Biology, Life Nikolai W. F. Bode Department of Mathematical Science Centre, Dalhousie University, Halifax, Sciences, University of Essex, UK Nova Scotia, Canada Neeltje J. Boogert Bute Building, University of Will Hoppitt Department of Life Sciences, Anglia St Andrews, UK Ruskin University, Cambridge, UK Darren P. Croft Centre for Research in Animal Richard James Department of Physics, University Behaviour, College of Life and Environmental of Bath, UK Sciences, University of Exeter, UK Jens Krause Faculty of Life Sciences, Humboldt Safi K. Darden Centre for Research in Animal University, Berlin, Germany, and Leibniz-Institute Behaviour, College of Life and Environmental of Freshwater Ecology and Inland Fisheries, Sciences, University of Exeter, UK Berlin, Germany Nicholas B. Davies Department of Zoology, Kevin N. Laland Centre for Social Learning and University of Cambridge, UK Cognitive Evolution, School of Biology, University Michael E. Dillon Department of Zoology and of St. Andrews, UK Physiology, University of Wyoming, USA Sally Macdonald Courant Research Centre Evolution Julian A. Drewe The Royal Veterinary College, of Social Behaviour, Georg-August-Universität, London, UK Goettingen, Germany Mathew Edenbrow Centre for Research in Animal Brenda McCowan Animal Behavior Laboratory Behaviour, College of Life and Environmental for Welfare & Conservation, School of Veterinary Sciences, University of Exeter, UK Medicine, University of California, Davis, USA Daniel W. Franks York Centre for Complex Sys- tems Analysis, Departments of Biology and David B. McDonald Department of Zoology and Computer Science, University of York, UK Physiology, University of Wyoming, USA Colin J. Garroway Edward Grey Institute, Depart- Grant C. McDonald Edward Grey Institute, Depart- ment of Zoology, University of Oxford, UK ment of Zoology, University of Oxford, UK Shane Gero Sea Mammal Research Unit and Cen- Peter K. McGregor Centre for Applied Zoology, tre for Social Learning and Cognitive Evolution, Cornwall College, UK School of Biology, University of St. Andrews, Dhruba Naug Department of Biology, Colorado UK, and Department of Zoophysiology, Institute State University, USA for Bioscience, Aarhus University, Denmark Glenna Nightingale Centre for Social Learning and Stephanie S. Godfrey School of Veterinary and Cognitive Evolution, School of Biology, University Life Sciences, Murdoch University, Western of St. Andrews, UK Australia Sarah E. Perkins Cardiff School of Biosciences, UK xvi 9780199679058-Krause.indb 16 26/11/14 4:53 PM LIST OF CONTRIBUTORS xvii Tommaso Pizzari Edward Grey Institute, Depart- Daniel I. Rubenstein Department of Ecology and ment of Zoology, University of Oxford, UK Evolutionary Biology, Princeton University, USA Reinder Radersma Edward Grey Institute, Depart- Bernhard Voelkl Edward Grey Institute, Depart- ment of Zoology, University of Oxford, UK ment of Zoology, University of Oxford, UK Luke Rendell Sea Mammal Research Unit Alexander D. M. Wilson Department of Biology, and Centre for Social Learning and Cognitive Carleton University, Canada Evolution, School of Biology, University A. Jamie Wood Department of Biology, University of St. Andrews, UK of York, UK 9780199679058-Krause.indb 17 26/11/14 4:53 PM Contteennttss Section 1Introduction to Animal Social Networks Page 1 1. General Introduction Jens Krauses, Richard James, Daniel W. Franks, and Darren P. Croft . . . . . . . .3 What is social network and why is it important? 3 Book structure and content 3 2. A network primer Richard James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Basics 5 Measuring network structure 6 Node-based measures of structure —6 • Network-Level measures of structure — 7 Clusters or communities 7 Model networks and network models 8 Section 2Patterns and Processes in Animal Social Networks Page 9 Patterns and Processes in Animal Social Networks Darren P. Croft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3. Assortment in social networks and the evolution of cooperation Darren P. Croft, Matthew Edenbrow, and Safi K. Darden . . . . . . . . . . . . . . . 13 Introduction to cooperation 13 Theoretical work on the evolution of cooperation in structured populations 14 Pathways to assortment by cooperation in social networks 17 Non-random distribution of individuals in space and time — 17 • Social structuring in the absence of spatial segregation — 18 •Spatial and temporal assortment by simple bahavioural rules — 18 • Conditional cooperation — 20 Cooperation in social networks: conclusions and future directions 22 Acknowledgements 23 4. Mating behaviour : sexual networks and sexual selection Grant C. McDonald and Tommaso Pizzari . . . . . . . . . . . . . . . . . . . . . . . 24 Introduction 24 Sexual selection 24 Sexual selection in structured populations 26 The logic of sexual networks 27 Intrasexual interactions and the measurement of sexual selection 28 Precopulatory selection — 30 • Postcopulatory selection — 30 Intersexual interactions, mating patterns, and the operation of selection 32 Mating system ecology 35 Individual network measures 36 Sexual selection and sexual networks: conclusions 37 Acknowledgements 37 5. Quantifying diffusion in social networks: a Bayesian approach Glenna Nightingale, Neeltje J. Boogert, Kevin N. Laland, and Will Hoppitt . . . . . 38 1
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