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The predictability of the physical arrangement of plants, at whatever scale it is viewed, is referred to as their spatial pattern. Spatial pattern is a crucial aspect of vegetation which has important implications not only for the plants themselves, but also for other organisms which interact with plants, such as herbivores and pollinators, or those animals for which plants provide a habitat. This book describes and evaluates methods for detecting and quantifying a variety of characteristics of spatial pattern. As well as discussing the concepts on which these techniques are based, examples from real field studies and worked examples are included, which, together with numerous line figures, help guide the reader through the text. The result is a book that will be of value to graduate students and research workers in the fields of vegetation science, conservation biology and applied ecology.

Plant ecology --- Spatial analysis (Statistics) --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Botany --- Phytoecology --- Plants --- Vegetation ecology --- Ecology --- Statistical methods. --- Floristic ecology

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Graph theory can be applied to ecological questions in many ways, and more insights can be gained by expanding the range of graph theoretical concepts applied to a specific system. But how do you know which methods might be used? And what do you do with the graph once it has been obtained? This book provides a broad introduction to the application of graph theory in different ecological systems, providing practical guidance for researchers in ecology and related fields. Readers are guided through the creation of an appropriate graph for the system being studied, including the application of spatial, spatio-temporal, and more abstract structural process graphs. Simple figures accompany the explanations to add clarity, and a broad range of ecological phenomena from many ecological systems are covered. This is the ideal book for graduate students and researchers looking to apply graph theoretical methods in their work.

Ecology --- Graph theory. --- Research.

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"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."

Ecology - Statistical methods --- System analysis --- Quantitative research

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Network thinking and network analysis are rapidly expanding features of ecological research. Network analysis of ecological systems include representations and modelling of the interactions in an ecosystem, in which species or factors are joined by pairwise connections. This book provides an overview of ecological network analysis including generating processes, the relationship between structure and dynamic function, and statistics and models for these networks. Starting with a general introduction to the composition of networks and their characteristics, it includes details on such topics as measures of network complexity, applications of spectral graph theory, how best to include indirect species interactions, and multilayer, multiplex and multilevel networks. Graduate students and researchers who want to develop and understand ecological networks in their research will find this volume inspiring and helpful. Detailed guidance to those already working in network ecology but looking for advice is also included.

Ecology --- Quantitative research. --- System analysis. --- Statistical methods.