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Quantitative analysis of ecological networks / Mark Randall Thomas Dale

Titre : Quantitative analysis of ecological networks Type de document : texte imprimÃ© Auteurs : Mark Randall Thomas Dale, Auteur ; Marie-JosÃ©e Fortin, Auteur Editeur : Cambridge University Press AnnÃ©e de publication : 2021 Importance : 1 vol. (221 p.) PrÃ©sentation : ill. Format : 25 cm ISBN/ISSN/EAN : 978-1-108-49184-6 Note gÃ©nÃ©rale : Bibliog. Index Langues : FranÃ§ais ( fre)Tags : Ecology -- Statistical methods Ã©cologie--mÃ©thodes statistiques System analysis Quantitative research recherche quantitative RÃ©sumÃ© : Ecology is about understanding how organisms interact with other organisms and the environment they inhabit (i.e. fundamental and realised niches). It is easy to imagine an individual organism of any kind as a dot with all sorts of arrows impinging upon it, an arrow can represent abiotic factors (temperature, light, etc.), as well as many arrows for all the other organisms (biotic factors, intra- and inter-specific interactions) that affect it. Ecology aims therefore to determine the magnitude and rate associated with some of the arrows, and which are the most important and why. Each organism also has its own effects on the same list of factors, even if the effects may be small, so we can also imagine arrows going out from the same dot, one to each of the same list of factors (they can be dots too). Again, a challenge is to determine the associated weights and importance for the arrows, some of which are directed toward other organisms. As soon as we consider more than a single organism, even just a few, we immediately have a complex structure of dots and arrows: an ecological network! It is an obvious step to consider ecological systems as ecological networks, and as such to assess how network theory (concepts and methods) might be applied to them. Network theory and the mathematics of graph theory that underlie network analysis provide simple concepts that can applied to systems that are complex both in structure and dynamics. It is those concepts that allow us to provide a sorted set of methods for the quantitative analysis of 10 ecological networks, along with thoughts and advice on how best to proceed. Through the years, the need to take a network analysis framework to study complex system has arisen in many fields (physics, computer science, communication science (transportation, electricity, social), and bio- and ecoinformatics), and there is a challenging diversity of approaches, methods, and measures that should be understood, or at least sorted, before applying them to our own data. The overarching goal of this book is to help ecologists in selecting the appropriate network methods to represent, analyse, and model their ecological system using network theory. Publication de Théma : Non Quantitative analysis of ecological networks [texte imprimÃ©] / Mark Randall Thomas Dale, Auteur ; Marie-JosÃ©e Fortin, Auteur . - Cambridge University Press, 2021 . - 1 vol. (221 p.) : ill. ; 25 cm.ISBN: 978-1-108-49184-6

Bibliog. Index

Langues : FranÃ§ais (fre)

Tags : Ecology -- Statistical methods Ã©cologie--mÃ©thodes statistiques System analysis Quantitative research recherche quantitative RÃ©sumÃ© : Ecology is about understanding how organisms interact with other organisms and the environment they inhabit (i.e. fundamental and realised niches). It is easy to imagine an individual organism of any kind as a dot with all sorts of arrows impinging upon it, an arrow can represent abiotic factors (temperature, light, etc.), as well as many arrows for all the other organisms (biotic factors, intra- and inter-specific interactions) that affect it. Ecology aims therefore to determine the magnitude and rate associated with some of the arrows, and which are the most important and why. Each organism also has its own effects on the same list of factors, even if the effects may be small, so we can also imagine arrows going out from the same dot, one to each of the same list of factors (they can be dots too). Again, a challenge is to determine the associated weights and importance for the arrows, some of which are directed toward other organisms. As soon as we consider more than a single organism, even just a few, we immediately have a complex structure of dots and arrows: an ecological network! It is an obvious step to consider ecological systems as ecological networks, and as such to assess how network theory (concepts and methods) might be applied to them. Network theory and the mathematics of graph theory that underlie network analysis provide simple concepts that can applied to systems that are complex both in structure and dynamics. It is those concepts that allow us to provide a sorted set of methods for the quantitative analysis of 10 ecological networks, along with thoughts and advice on how best to proceed. Through the years, the need to take a network analysis framework to study complex system has arisen in many fields (physics, computer science, communication science (transportation, electricity, social), and bio- and ecoinformatics), and there is a challenging diversity of approaches, methods, and measures that should be understood, or at least sorted, before applying them to our own data. The overarching goal of this book is to help ecologists in selecting the appropriate network methods to represent, analyse, and model their ecological system using network theory. Publication de Théma : Non ## RÃ©servation

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Code-barres Cote Support Section DisponibilitÃ© 01151001948940 A23.DAL Livre Centre de Documentation DisponibleNetworks: an introduction / Mark Newman

Titre : Networks: an introduction Type de document : texte imprimÃ© Auteurs : Mark Newman, Auteur Editeur : Oxford University Press AnnÃ©e de publication : 2010 Importance : (XI-772 p.) ISBN/ISSN/EAN : 978-0-19-920665-0 Langues : Anglais ( eng)Tags : system analysis network analysis (planning) systems biology Engineering systems Social systems RÃ©seaux d'ordinateurs RÃ©seaux (mathÃ©matiques) Analyse de rÃ©seau (planification) SystÃ¨mes, Analyse de RÃ©sumÃ© : The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.

Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.Publication de Théma : Non Networks: an introduction [texte imprimÃ©] / Mark Newman, Auteur . - Oxford University Press, 2010 . - (XI-772 p.).ISBN: 978-0-19-920665-0

Langues : Anglais (eng)

Tags : system analysis network analysis (planning) systems biology Engineering systems Social systems RÃ©seaux d'ordinateurs RÃ©seaux (mathÃ©matiques) Analyse de rÃ©seau (planification) SystÃ¨mes, Analyse de RÃ©sumÃ© : The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.

Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.Publication de Théma : Non ## RÃ©servation

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Code-barres Cote Support Section DisponibilitÃ© 01151001945116 A23.NEW Livre Centre de Documentation Sorti jusqu'au 06/12/2021