Quantitative ecology and evolutionary biology : integrating models with data / Otso Ovaskainen, Henrik Johan de Knegt, Maria del Mar Delgado.

Format:

Book

Author/Creator:

Ovaskainen, Otso, author.

Knegt, Henrik Johan de, author.

Delgado, Maria del Mar, author.

Series:

Oxford series in ecology and evolution.

Oxford Series in Ecology and Evolution

Language:

English

Subjects (All):

Ecology--Statistical methods--Data processing.

Ecology.

Evolution (Biology)--Statistical methods--Data processing.

Evolution (Biology).

Ecology--Mathematical models.

Physical Description:

1 online resource (301 p.)

Edition:

First edition.

Place of Publication:

Oxford : Oxford University Press, 2016.

Summary:

This is an integration of empirical data and theory in quantitative ecology and evolution through the use of mathematical models and statistical methods.

Contents:

Cover; Preface; Contents; 1 Approaches to ecological modelling; 1.1 Forward and inverse approaches ; 1.2 The interplay between models and data ; 1.3 The many choices with mathematical and statistical models and methods ; 1.4 What a biologist should learn about modelling ; 2 Movement ecology; 2.1 Why, where, when, and how do individual organisms move ; 2.1.1 Internal state: why to move ; 2.1.2 Motion capacity: how to move ; 2.1.3 Navigation capacity: when and where to move ; 2.1.4 Different types of movement ; 2.1.5 Approaches to movement research

2.1.6 Outline of this chapter2.2 Movement models in homogeneous environments ; 2.2.1 The Lagrangian approach; 2.2.2 Translating the Lagrangian model into an Eulerian model; 2.2.3 Dispersal kernels; 2.2.4 Adding directional persistence: correlated random walk models; 2.2.5 Adding directional bias: home-range models; 2.3 Movement models in heterogeneous environments; 2.3.1 Random walk simulations in heterogeneous space; 2.3.2 Diffusion models with continuous spatial variation in movement parameters; 2.3.3 Diffusion models with discrete spatial variation in movement parameters

2.3.4 Using movement models to define and predict functional connectivity2.3.5 The influence of a movement corridor; 2.4 Movements in a highly fragmented landscape; 2.4.1 The case of a single habitat patch; 2.4.2 The case of a patch network; 2.5 Statistical approaches to analysing movement data; 2.5.1 Exploratory data analysis of GPS data; 2.5.2 Fitting a diffusion model to capture-mark-recapture data; 2.6 Perspectives; 2.6.1 Limitations and extensions of random walk and diffusion models; 2.6.2 The many approaches of analysing movement data; 3 Population ecology

3.1 Scaling up from the individual level to population dynamics3.1.1 Factors influencing population growth through birth and death rates; 3.1.2 How movements influence population dynamics; 3.1.3 How population structure influences population dynamics; 3.1.4 The outline of this chapter; 3.2 Population models in homogeneous environments; 3.2.1 Individual-based stochastic and spatial model; 3.2.2 Simplifying the model: stochasticity without space; 3.2.3 Simplifying the model further: without stochasticity and space; 3.2.4 Another way of simplifying the model: space without stochasticity

3.3 Population models in heterogeneous environments3.3.1 Environmental stochasticity; 3.3.2 Spatial heterogeneity in continuous space: the plant population model; 3.3.3 Spatial heterogeneity in discrete space: the butterfly metapopulation model; 3.3.4 The Levins metapopulation model and its spatially realistic versions; 3.4 The persistence of populations under habitat loss and fragmentation; 3.4.1 Habitat loss and fragmentation in the plant population model; 3.4.2 Habitat loss and fragmentation in the butterfly metapopulation model

3.4.3 Habitat loss and fragmentation in the Levins metapopulation model

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

0-19-871487-4

0-19-178321-8

0-19-102422-8