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Author  |
Allcroft, D. J.; Tolkamp, B. J.; Glasbey, C. A.; Kyriazakis, I. | ||||
| Title | The importance of `memory' in statistical models for animal feeding behaviour | Type | Journal Article | ||
| Year | 2004 | Publication | Behavioural Processes | Abbreviated Journal | Behav. Process. |
| Volume | 67 | Issue | 1 | Pages | 99-109 |
| Keywords | Cow; Feeding data; Bouts; Memory; Satiety; Latent structure; Model comparison | ||||
| Abstract | We investigate models for animal feeding behaviour, with the aim of improving understanding of how animals organise their behaviour in the short term. We consider three classes of model: hidden Markov, latent Gaussian and semi-Markov. Each can predict the typical `clustered' feeding behaviour that is generally observed, however they differ in the extent to which `memory' of previous behaviour is allowed to affect future behaviour. The hidden Markov model has `lack of memory', the current behavioural state being dependent on the previous state only. The latent Gaussian model assumes feeding/non-feeding periods to occur by the thresholding of an underlying continuous variable, thereby incorporating some `short-term memory'. The semi-Markov model, by taking into account the duration of time spent in the previous state, can be said to incorporate `longer-term memory'. We fit each of these models to a dataset of cow feeding behaviour. We find the semi-Markov model (longer-term memory) to have the best fit to the data and the hidden Markov model (lack of memory) the worst. We argue that in view of effects of satiety on short-term feeding behaviour of animal species in general, biologically suitable models should allow `memory' to play a role. We conclude that our findings are equally relevant for the analysis of other types of short-term behaviour that are governed by satiety-like principles. | ||||
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| Notes | Approved | no | |||
| Call Number | Equine Behaviour @ team @ | Serial | 2350 | ||
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| Author |
Croft, D. P.; James, R..; Krause, J. | ||||
| Title | Comparing Networks | Type | Book Chapter | ||
| Year | 2008 | Publication | Exploring Animal Social Networks | Abbreviated Journal | |
| Volume | Issue | Pages | 141-162 | ||
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| Abstract | Social network analysis is used widely in the social sciences to study interactions among people, groups, and organizations, yet until now there has been no book that shows behavioral biologists how to apply it to their work on animal populations. Exploring Animal Social Networks provides a practical guide for researchers, undergraduates, and graduate students in ecology, evolutionary biology, animal behavior, and zoology. Existing methods for studying animal social structure focus either on one animal and its interactions or on the average properties of a whole population. This book enables researchers to probe animal social structure at all levels, from the individual to the population. No prior knowledge of network theory is assumed. The authors give a step-by-step introduction to the different procedures and offer ideas for designing studies, collecting data, and interpreting results. They examine some of today's most sophisticated statistical tools for social network analysis and show how they can be used to study social interactions in animals, including cetaceans, ungulates, primates, insects, and fish. Drawing from an array of techniques, the authors explore how network structures influence individual behavior and how this in turn influences, and is influenced by, behavior at the population level. Throughout, the authors use two software packages--UCINET and NETDRAW--to illustrate how these powerful analytical tools can be applied to different animal social organizations. Darren P. Croft is lecturer in animal behavior at the University of Wales, Bangor. Richard James is senior lecturer in physics at the University of Bath. Jens Krause is professor of behavioral ecology at the University of Leeds. Reviews: “Exploring Animal Social Networks shows behavioral biologists how to apply social network theory to animal populations. In doing so, Croft, James, and Krause illustrate the connections between an animal's individual behaviors and how these, in turn, influence and are influenced by behavior at the population level. . . . Valuable for readers interested in using quantitative analyses to study animal social behaviors.”--Choice “[T]his volume provides an engaging, accessible, and timely introduction to the use of network theory methods for examining the social behavior of animals.”--Noa Pinter-Wollman, Quarterly Review of Biology “The book is a useful 'handbook' providing detailed, stepwise procedures sufficient to allow the reader to address a broad range of questions about social interactions. . . . The book includes numerous examples of the kind of research questions one might ask, and, thus, it allows the reader to find the analysis that best fits the data set to be analyzed. Thus, even readers with minimal prior knowledge of social network analysis will be able to apply this approach. And if further assistance is needed, the authors provide numerous references to specific procedures that have been used by others.”--Thomas R. Zentall, PsycCRITIQUES Endorsements: “An important and timely addition to the literature. This book should be readily accessible to researchers who are interested in animal social organization but who have little or no experience in conducting network analysis. The book is well-written in an engaging style and contains a good number of examples drawn from a range of taxonomic groups.”--Paul R. Moorcroft, Harvard University More Endorsements Table of Contents: Preface vii Chapter 1: Introduction to Social Networks 1 Chapter 2: Data Collection 19 Chapter 3: Visual Exploration 42 Chapter 4: Node-Based Measures 64 Chapter 5: Statistical Tests of Node-Based Measures 88 Chapter 6: Searching for Substructures 117 Chapter 7: Comparing Networks 141 Chapter 8: Conclusions 163 Glossary of Frequently Used Terms 173 References 175 Index 187 Subject Area: * Biological Sciences |
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| Publisher | Princton University Press | Place of Publication | Princeton, NY | Editor | |
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| Notes | Approved | no | |||
| Call Number | Equine Behaviour @ team @ | Serial | 4955 | ||
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| Author |
Croft, D. P.; James, R..; Krause, J. (eds) | ||||
| Title | Exploring Animal Social Networks | Type | Book Whole | ||
| Year | 2008 | Publication | Abbreviated Journal | ||
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| Publisher | Princton University Press | Place of Publication | Princton | Editor | Croft, D. P.; James, R..; Krause, J. |
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| ISSN | ISBN | 9780691127521 | Medium | ||
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| Notes | Approved | no | |||
| Call Number | Equine Behaviour @ team @ | Serial | 5139 | ||
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| Author |
James, R.; Croft, D.; Krause, J. | ||||
| Title | Potential banana skins in animal social network analysis | Type | Journal Article | ||
| Year | 2009 | Publication | Behavioral Ecology and Sociobiology | Abbreviated Journal | Behav. Ecol. Sociobiol. |
| Volume | 63 | Issue | 7 | Pages | 989-997-997 |
| Keywords | Biomedical and Life Sciences | ||||
| Abstract | Social network analysis is an increasingly popular tool for the study of the fine-scale and global social structure of animals. It has attracted particular attention by those attempting to unravel social structure in fission–fusion populations. It is clear that the social network approach offers some exciting opportunities for gaining new insights into social systems. However, some of the practices which are currently being used in the animal social networks literature are at worst questionable and at best over-enthusiastic. We highlight some of the areas of method, analysis and interpretation in which greater care may be needed in order to ensure that the biology we extract from our networks is robust. In particular, we suggest that more attention should be given to whether relational data are representative, the potential effect of observational errors and the choice and use of statistical tests. The importance of replication and manipulation must not be forgotten, and the interpretation of results requires care. | ||||
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| Publisher | Springer Berlin / Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0340-5443 | ISBN | Medium | ||
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| Notes | Approved | no | |||
| Call Number | Equine Behaviour @ team @ | Serial | 5206 | ||
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| Author |
Krause, J.; Croft, D.; James, R. | ||||
| Title | Social network theory in the behavioural sciences: potential applications | Type | Journal Article | ||
| Year | 2007 | Publication | Behavioral Ecology and Sociobiology | Abbreviated Journal | Behav. Ecol. Sociobiol. |
| Volume | 62 | Issue | 1 | Pages | 15-27 |
| Keywords | Social networks – Social organisation – Mate choice – Disease transmission – Information transfer – Cooperation | ||||
| Abstract | Abstract Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies. | ||||
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| Call Number | Equine Behaviour @ team @ | Serial | 5171 | ||
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| Author |
Krause, J.; James, R.; Franks, D.W.; Croft, D. P. | ||||
| Title | Animal Social Networks. | Type | Book Whole | ||
| Year | 2015 | Publication | Abbreviated Journal | ||
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| Publisher | Oxford University Press | Place of Publication | Oxford | Editor | |
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| Notes | Approved | no | |||
| Call Number | Equine Behaviour @ team @ | Serial | 5883 | ||
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