rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Modelling Population Dynamics
    sub title: Model Formulation, Fitting and Assessment using State-Space Methods
  name:
    name part: Newman, K. B.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Buckland, S. T.
    role:
      role term: author.
  name:
    name part: Morgan, B. J. T.
    role:
      role term: author.
  name:
    name part: King, R.
    role:
      role term: author.
  name:
    name part: Borchers, D. L.
    role:
      role term: author.
  name:
    name part: Cole, D. J.
    role:
      role term: author.
  name:
    name part: Besbeas, P.
    role:
      role term: author.
  name:
    name part: Gimenez, O.
    role:
      role term: author.
  name:
    name part: Thomas, L.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 215 p. 38 illus., 21 illus. in color. online resource.
  abstract: 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. .
  table of contents: Introduction -- Matrices as Building Blocks -- State-space Models -- Fitting State-space models -- Model Formulation and Evaluation -- Modelling Population Dynamics Using Closed-population Abundance Estimates -- Estimating Survival Probabilities from Mark-re-encounter Data -- Estimating Abundance from Mark-recapture Data -- Integrated Population Modelling -- Concluding Remarks.
  note: by K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole, P. Besbeas, O. Gimenez, L. Thomas.
  subject:
    topic: Statistics
  subject:
    topic: Statistics
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Methods in Statistical Ecology
  identifier: 9781493909773
  identifier: http://dx.doi.org/10.1007/978-1-4939-0977-3
  record info:
    record creation date: 140716
    record change date: 20150521143445.0
    record identifier: 978-1-4939-0977-3