2016Oxford University Press eBooksRequires access

Quantitative Ecology and Evolutionary Biology

Otso Ovaskainen, Henrik Johan de Knegt, María del Mar Delgado

Open publisher page 21 citations

Abstract

This book presents an integrative approach tomathematical and statistical modelling in ecology and evolutionary biology. After an introductory chapter, the book devotes one chapter for movement ecology, one for population ecology, one for community ecology, and one for genetics and evolutionary ecology. Each chapter starts with a conceptual section, which provides the necessary biological background and motivates the modelling approaches. The next three sections present mathematical modelling approaches, followed by one section devoted to statistical approaches. Each chapter ends with a perspectives section, which summarizes the key messages and discusses the limitations of the approaches considered. To illustrate how the very same modelling approaches apply in different fields of ecology and evolutionary biology, the book uses movement models as a building block to construct single-species models of population dynamics, the models of which are further expanded to models of species communities and to models of evolutionary dynamics. In all chapters, the book starts by making assumptions at the level of individuals, leading to individual-based simulationmodels. To derive analytical insights and to compare the behaviours of different types of models, the book shows how the individual-based models can be simplified, e.g. to yield models formulated directly at the population level. The book has a special emphasis on the integration of models with data. To achieve this, it applies statistical methods to data generated by mathematical models, and thus asks to what extent does the data contain signals of the underlying mechanisms.

About this research paper

What this paper is about

This book presents an integrative approach tomathematical and statistical modelling in ecology and evolutionary biology. After an introductory chapter, the book devotes one chapter for movement ecology, one for population ecology, one for community ecology, and one for genetics and evolutionary ecology. Each chapter starts with a conceptual section, which provides the necessary biological background and motivates the modelling approaches. The next three sections present mathematical modelling approaches, followed by one section devoted to statistical approaches. Each chapter ends with a perspectives section, which summarizes the key messages and discusses the limitations of the approaches considered. To illustrate how the very same modelling approaches apply in different fields of ecology and evolutionary biology, the book uses movement models as a building block to construct single-species models of population dynamics, the models of which are further expanded to models of species communities and to models of evolutionary dynamics. In all chapters, the book starts by making assumptions at the level of individuals, leading to individual-based simulationmodels. To derive analytical insights and to compare the behaviours of different types of models, the book shows how the individual-based models can be simplified, e.g. to yield models formulated directly at the population level. The book has a special emphasis on the integration of models with data. To achieve this, it applies statistical methods to data generated by mathematical models, and thus asks to what extent does the data contain signals of the underlying mechanisms.

Why it matters

OpenAlex reports 21 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

This book presents an integrative approach tomathematical and statistical modelling in ecology and evolutionary biology. After an introductory chapter, the book devotes one chapter for movement ecology, one for population ecology, one for community ecology, and one for genetics and evolutionary ecology. Each chapter starts with a conceptual section, which provides the necessary biological background and motivates the modelling approaches. The next three sections present mathematical modelling approaches, followed by one section devoted to statistical approaches. Each chapter ends with a perspectives section, which summarizes the key messages and discusses the limitations of the approaches considered. To illustrate how the very same modelling approaches apply in different fields of ecology and evolutionary biology, the book uses movement models as a building block to construct single-species models of population dynamics, the models of which are further expanded to models of species communities and to models of evolutionary dynamics. In all chapters, the book starts by making assumptions at the level of individuals, leading to individual-based simulationmodels. To derive analytical insights and to compare the behaviours of different types of models, the book shows how the individual-based models can be simplified, e.g. to yield models formulated directly at the population level. The book has a special emphasis on the integration of models with data. To achieve this, it applies statistical methods to data generated by mathematical models, and thus asks to what extent does the data contain signals of the underlying mechanisms.

Key concepts: Evolutionary ecology, Ecology, Theoretical ecology, Population ecology, Population biology, Population, Construct (python library), Computer science

Related papers

Back to paper searchBrowse research topicsOriginal source
Quantitative Ecology and Evolutionary Biology — Research Paper | ScholarLens