Cargando…

Modelling population dynamics: model formulation, fitting and assessment using state-space methods

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 withi...

Descripción completa

Detalles Bibliográficos
Autores principales: Newman, K B, Buckland, S T, Morgan, B J T, King, R, Borchers, D L, Cole, D J, Besbeas, P, Gimenez, O, Thomas, L
Lenguaje:eng
Publicado: Springer 2014
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4939-0977-3
http://cds.cern.ch/record/1748027
_version_ 1780942964809269248
author Newman, K B
Buckland, S T
Morgan, B J T
King, R
Borchers, D L
Cole, D J
Besbeas, P
Gimenez, O
Thomas, L
author_facet Newman, K B
Buckland, S T
Morgan, B J T
King, R
Borchers, D L
Cole, D J
Besbeas, P
Gimenez, O
Thomas, L
author_sort Newman, K B
collection CERN
description 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.  
id cern-1748027
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2014
publisher Springer
record_format invenio
spelling cern-17480272021-04-21T20:55:52Zdoi:10.1007/978-1-4939-0977-3http://cds.cern.ch/record/1748027engNewman, K BBuckland, S TMorgan, B J TKing, RBorchers, D LCole, D JBesbeas, PGimenez, OThomas, LModelling population dynamics: model formulation, fitting and assessment using state-space methodsMathematical Physics and MathematicsThis 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.  Springeroai:cds.cern.ch:17480272014
spellingShingle Mathematical Physics and Mathematics
Newman, K B
Buckland, S T
Morgan, B J T
King, R
Borchers, D L
Cole, D J
Besbeas, P
Gimenez, O
Thomas, L
Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title_full Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title_fullStr Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title_full_unstemmed Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title_short Modelling population dynamics: model formulation, fitting and assessment using state-space methods
title_sort modelling population dynamics: model formulation, fitting and assessment using state-space methods
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-1-4939-0977-3
http://cds.cern.ch/record/1748027
work_keys_str_mv AT newmankb modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT bucklandst modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT morganbjt modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT kingr modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT borchersdl modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT coledj modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT besbeasp modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT gimenezo modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods
AT thomasl modellingpopulationdynamicsmodelformulationfittingandassessmentusingstatespacemethods