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Showing 1 - 9 of 9 matches in All Departments
Studies of the evolution of animal signals and sensory behaviour have more recently shifted from considering 'extrinsic' (environmental) determinants to 'intrinsic' (physiological) ones. The drive behind this change has been the increasing availability of neural network models. With contributions from experts in the field, this book provides a complete survey of artificial neural networks. The book opens with two broad, introductory level reviews on the themes of the book: neural networks as tools to explore the nature of perceptual mechanisms, and neural networks as models of perception in ecology and evolutionary biology. Later chapters expand on these themes and address important methodological issues when applying artificial neural networks to study perception. The final chapter provides perspective by introducing a neural processing system in a real animal. The book provides the foundations for implementing artificial neural networks, for those new to the field, along with identifying potential research areas for specialists.
Written primarily for students embarking on an undergraduate bioscience degree, this primer provides an accessible, straightforward, and approachable guide to data presentation using R. It offers valuable and widely applicable advice on how to choose the most appropriate type of graph for different types of data, and guides readers from the basics of plotting clear figures to producing polished and effective visuals, illustrating the core concepts and features of excellent graphing. This primer uses simple and engaging biology-based example data sets to take readers from the essential aspects of basic plots to more advanced graphing techniques and details. Digital formats and resources The book is available for students and institutions to purchase in a variety of formats, and is supported by online resources: - The e-book offers a mobile experience and convenient access along with functionality tools, navigation features, and links that offer extra learning support: www.oxfordtextbooks.co.uk/ebooks - Online resources include extended supplementary resources to guide use of R, multiple choice questions for students to check their understanding, and, for registered adopters, figures and tables from the book
The careful design of experiments lies at the core of good research. Experimental Design for the Life Sciences equips you with the skills you need to effectively design experiments, making this essential aspect of the research process readily understandable. It demonstrates how good experimental design relies on clear thinking and biological understanding, not mathematical or statistical complexity. With a refreshingly approachable and articulate style, the book walks you through the considerations that go into designing an experiment in clear, practical terms. Using examples drawn from across the life sciences - from ecology, biochemistry, molecular biology, genetics, and health sciences - the authors illustrate how these concepts are applied within the broad context of real biological research. Online Resource Centre The Online Resource centre to accompany Experimental Design for the Life Sciences features: For students: * Self-test questions and answers * Additional examples * Supplementary sections discuss complex concepts and statistical issues in more depth * Links to useful websites and free software For lecturers: * Suggested course structures, complete with practical exercises * Figures from the book, available to download
Communication is an essential factor underpinning the interactions
between species and the structure of their communities.
Plant-animal interactions are particularly diverse due to the
complex nature of their mutualistic and antagonistic relationships.
However the evolution of communication and the underlying
mechanisms responsible remain poorly understood.
Written primarily for mid-to-upper level undergraduates, this compelling introduction to power analysis in a biological context offers a clear, conceptual understanding of the factors that influence statistical power, and emphasises the importance of high power in experiments. It also explains how to improve the power of an experiment and offers guidance on how to present the outcomes of power analyses to justify experimental design decisions. Digital formats and resources The book is available for students and institutions to purchase in a variety of formats, and is supported by online resources: * The e-book offers a mobile experience and convenient access along with functionality tools, navigation features, and links that offer extra learning support: www.oxfordtextbooks.co.uk/ebooks * Online resources include multiple choice questions for students to check their understanding, and, for registered adopters, figures and tables from the book
Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.
Communication is an essential factor underpinning the interactions
between species and the structure of their communities.
Plant-animal interactions are particularly diverse due to the
complex nature of their mutualistic and antagonistic relationships.
However the evolution of communication and the underlying
mechanisms responsible remain poorly understood.
Avoiding Attack discusses the diversity of mechanisms by which prey avoid predator attacks and explores how such defensive mechanisms have evolved through natural selection. It considers how potential prey avoid detection, how they make themselves unprofitable to attack, how they communicate this status, and how other species have exploited these signals. Using carefully selected examples of camouflage, mimicry, and warning signals drawn from a wide range of species and ecosystems, the authors summarise the latest research into these fascinating adaptations, developing mathematical models where appropriate and making recommendations for future study. This second edition has been extensively rewritten, particularly in the application of modern genetic research techniques which have transformed our recent understanding of adaptations in evolutionary genomics and phylogenetics. The book also employs a more integrated and systematic approach, ensuring that each chapter has a broader focus on the evolutionary and ecological consequences of anti-predator adaptation. The field has grown and developed considerably over the last decade with an explosion of new research literature, making this new edition timely.
Avoiding Attack discusses the diversity of mechanisms by which prey avoid predator attacks and explores how such defensive mechanisms have evolved through natural selection. It considers how potential prey avoid detection, how they make themselves unprofitable to attack, how they communicate this status, and how other species have exploited these signals. Using carefully selected examples of camouflage, mimicry, and warning signals drawn from a wide range of species and ecosystems, the authors summarise the latest research into these fascinating adaptations, developing mathematical models where appropriate and making recommendations for future study. This second edition has been extensively rewritten, particularly in the application of modern genetic research techniques which have transformed our recent understanding of adaptations in evolutionary genomics and phylogenetics. The book also employs a more integrated and systematic approach, ensuring that each chapter has a broader focus on the evolutionary and ecological consequences of anti-predator adaptation. The field has grown and developed considerably over the last decade with an explosion of new research literature, making this new edition timely.
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