Designed for researchers in ecology at all levels and career stages, from students and postdoctoral fellows to seasoned professionals, this third edition reflects the significant advances in quantitative analysis of the past decade. It provides updated examples and methods, with reduced emphasis on older techniques that have seen limited use in recent ecological literature. The authors cover new and emerging approaches, including Hierarchical Bayesian analysis and spatio-temporal methods. A key feature is the integration of ecological and statistical concepts, highlighting the critical role that this type of analysis plays in ecological understanding. The book provides up-to-date summaries of methodological advancements in spatial and spatio-temporal analysis, along with insights into future developments in areas such as spatial graphs, multi-level networks, and machine learning applications. It also offers practical examples and guidance to help researchers select, apply, and interpret the appropriate methods.
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Mark R. T. Dale is Professor of Ecosystem Science and Management at the University of Northern British Columbia, Canada, where he has served in several administrative roles. His research interests are based on the spatial structure of plant communities and include the development of quantitative methods to answer ecological questions. His work on plant community structure and the dynamics of spatial pattern development has led to significant contributions in the application of graph theory and the study of ecological networks. Mark is the author of Applying Graph Theory in Ecological Research (2017) and co-author of Quantitative Analysis of Ecological Networks (2021), both published by Cambridge University Press.
Marie-Josée Fortin is a University Professor in the Department of Ecology and Evolutionary Biology at the University of Toronto. She is a Fellow of the Royal Society of Canada and holds a Tier 1 Canada Research Chair in Spatial Ecology. Her research is at the interface of spatial ecology and conservation biology including modelling connectivity in urban environments, ecosystem services, and forest resilience. Marie-Josée is co-author of Quantitative Analysis of Ecological Networks (Cambridge University Press, 2021).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : new. Paperback. Designed for researchers in ecology at all levels and career stages, from students and postdoctoral fellows to seasoned professionals, this third edition reflects the significant advances in quantitative analysis of the past decade. It provides updated examples and methods, with reduced emphasis on older techniques that have seen limited use in recent ecological literature. The authors cover new and emerging approaches, including Hierarchical Bayesian analysis and spatio-temporal methods. A key feature is the integration of ecological and statistical concepts, highlighting the critical role that this type of analysis plays in ecological understanding. The book provides up-to-date summaries of methodological advancements in spatial and spatio-temporal analysis, along with insights into future developments in areas such as spatial graphs, multi-level networks, and machine learning applications. It also offers practical examples and guidance to help researchers select, apply, and interpret the appropriate methods. A comprehensive guide to analyzing spatial and spatio-temporal phenomena in ecological research. The authors provide methodological insights, practical examples, and expert advice to help researchers select, apply, and interpret the appropriate methods. Designed for students and researchers, this is an essential resource for ecological research. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781009158671
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Paperback. Etat : New. Designed for researchers in ecology at all levels and career stages, from students and postdoctoral fellows to seasoned professionals, this third edition reflects the significant advances in quantitative analysis of the past decade. It provides updated examples and methods, with reduced emphasis on older techniques that have seen limited use in recent ecological literature. The authors cover new and emerging approaches, including Hierarchical Bayesian analysis and spatio-temporal methods. A key feature is the integration of ecological and statistical concepts, highlighting the critical role that this type of analysis plays in ecological understanding. The book provides up-to-date summaries of methodological advancements in spatial and spatio-temporal analysis, along with insights into future developments in areas such as spatial graphs, multi-level networks, and machine learning applications. It also offers practical examples and guidance to help researchers select, apply, and interpret the appropriate methods. N° de réf. du vendeur LU-9781009158671
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Paperback. Etat : New. Designed for researchers in ecology at all levels and career stages, from students and postdoctoral fellows to seasoned professionals, this third edition reflects the significant advances in quantitative analysis of the past decade. It provides updated examples and methods, with reduced emphasis on older techniques that have seen limited use in recent ecological literature. The authors cover new and emerging approaches, including Hierarchical Bayesian analysis and spatio-temporal methods. A key feature is the integration of ecological and statistical concepts, highlighting the critical role that this type of analysis plays in ecological understanding. The book provides up-to-date summaries of methodological advancements in spatial and spatio-temporal analysis, along with insights into future developments in areas such as spatial graphs, multi-level networks, and machine learning applications. It also offers practical examples and guidance to help researchers select, apply, and interpret the appropriate methods. N° de réf. du vendeur LU-9781009158671
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