Modelling Population Dynamics

Model Formulation, Fitting and Assessment using State-Space Methods

  • K. B. Newman
  • S. T. Buckland
  • B. J. T. Morgan
  • R. King
  • D. L. Borchers
  • D. J. Cole
  • P. Besbeas
  • O. Gimenez
  • L. Thomas
Part of the Methods in Statistical Ecology book series (MISE)

Table of contents

  1. Front Matter
    Pages i-xii
  2. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 1-5
  3. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 7-37
  4. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 39-50
  5. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 51-82
  6. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 83-121
  7. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 123-145
  8. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 147-158
  9. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 159-168
  10. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 169-195
  11. K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole et al.
    Pages 197-200
  12. Back Matter
    Pages 201-215

About this book

Introduction

This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations.  The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity,  population (within a metapopulation), or species (for multi-species models).

The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models.  The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.

 

Authors and affiliations

  • K. B. Newman
    • 1
  • S. T. Buckland
    • 2
  • B. J. T. Morgan
    • 3
  • R. King
    • 4
  • D. L. Borchers
    • 5
  • D. J. Cole
    • 6
  • P. Besbeas
    • 7
  • O. Gimenez
    • 8
  • L. Thomas
    • 9
  1. 1.Pacific Southwest Region, U.S. Fish and Wildlife ServiceStockton Fish and Wildlife OfficeLodiUSA
  2. 2.The Observatory, Buchanan GdnsCentre for Research into Ecological and Environmental ModellingSt. AndrewsUnited Kingdom
  3. 3.School of Mathematics, Statistics and Actuarial ScienceUniversity of KentCanterburyUnited Kingdom
  4. 4.The Observatory, Buchanan GdnsCentre for Research into Ecological and Environmental ModellingSt. AndrewsUnited Kingdom
  5. 5.The Observatory, Buchanan GdnsCentre for Research into Ecological and Environmental ModellingSt. AndrewsUnited Kingdom
  6. 6.School of Mathematics, Statistics and Actuarial ScienceUniversity of KentCanterburyUnited Kingdom
  7. 7.Department of Statistics, and School of Mathematics, Statistics and Actuarial ScienceAthens University of Economics and Business, and University of KentAthensGreece
  8. 8.Campus du CNRSCentre d'Écologie Fonctionnelle et Evolutive, UMR 5175Montpellier Cedex 5France
  9. 9.The Observatory, Buchanan GdnsCentre for Research into Ecological and Environmental ModellingSt. AndrewsUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-0977-3
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4939-0976-6
  • Online ISBN 978-1-4939-0977-3
  • Series Print ISSN 2199-319X
  • Series Online ISSN 2199-3203
  • About this book