Data-driven Modelling of Structured Populations A Practical Guide to
This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to c
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Stephen P. Ellner Dylan Z. Childs Mark Rees
Data-driven Modelling of Structured Populations A Practical Guide to the Integral Projection Model
Lecture Notes on Mathematical Modelling in the Life Sciences
Series Editors: Michael Mackey Angela Stevens
More information about this series at http://www.springer.com/series/10049
Stephen P. Ellner • Dylan Z. Childs • Mark Rees
Data-driven Modelling of Structured Populations A Practical Guide to the Integral Projection Model
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Stephen P. Ellner Ecology and Evolutionary Biology Cornell University, Corson Hall Ithaca, NY, USA
Dylan Z. Childs Animal and Plant Sciences University of Sheffield Yorkshire, UK
Mark Rees Animal and Plant Sciences University of Sheffield Yorkshire, UK
ISSN 2193-4789 ISSN 2193-4797 (electronic) Lecture Notes on Mathematical Modelling in the Life Sciences ISBN 978-3-319-28891-8 ISBN 978-3-319-28893-2 (eBook) DOI 10.1007/978-3-319-28893-2 Library of Congress Control Number: 2016933253 Mathematics Subject Classification (2010): 92D25; 92D40; 92C80; 92-02; 62P10; 97M60 © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
Over the past 30 years, one of the most rapidly expanding areas in ecology has been the development of structured population models, where individuals have attributes such as size, age, spatial location, sex, or disease status that affect their interactions and fate. These models can be roughly divided into conceptual models where the effects of biological structure are explored in the simplest possible setting to expose general principles and data-driven models in which the parameters and functions are estimated from observations of actual individuals, allowing inferences about population behavior. By far the most popular data-driven models are matrix projection models, w
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