Sensitivity analysis: matrix methods in demography and ecology

Sensitivity analysis addresses one of the most persistent of all questions: what would happen if ? Within the field of demography, sensitivity analysis might be said to have originated with the groundbreaking, yet very different, papers of Hamilton (1966) and Keyfitz (1971). Hamilton calculated the...

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Autores:
Tipo de recurso:
Book
Fecha de publicación:
2018
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/15865
Acceso en línea:
http://hdl.handle.net/20.500.12010/15865
https://doi.org/10.1007/978-3-030-10534-1
Palabra clave:
Demography
Ecology
Sensitivity analysis
Ciencias sociales
Ecología humana
Demografía
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License
Abierto (Texto Completo)
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dc.title.spa.fl_str_mv Sensitivity analysis: matrix methods in demography and ecology
title Sensitivity analysis: matrix methods in demography and ecology
spellingShingle Sensitivity analysis: matrix methods in demography and ecology
Demography
Ecology
Sensitivity analysis
Ciencias sociales
Ecología humana
Demografía
title_short Sensitivity analysis: matrix methods in demography and ecology
title_full Sensitivity analysis: matrix methods in demography and ecology
title_fullStr Sensitivity analysis: matrix methods in demography and ecology
title_full_unstemmed Sensitivity analysis: matrix methods in demography and ecology
title_sort Sensitivity analysis: matrix methods in demography and ecology
dc.subject.spa.fl_str_mv Demography
Ecology
Sensitivity analysis
topic Demography
Ecology
Sensitivity analysis
Ciencias sociales
Ecología humana
Demografía
dc.subject.lemb.spa.fl_str_mv Ciencias sociales
Ecología humana
Demografía
description Sensitivity analysis addresses one of the most persistent of all questions: what would happen if ? Within the field of demography, sensitivity analysis might be said to have originated with the groundbreaking, yet very different, papers of Hamilton (1966) and Keyfitz (1971). Hamilton calculated the sensitivity of the intrinsic rate of increase, r, to changes in age-specific mortality. He interpreted r as a measure of individual fitness, capturing the effects of the phenotype on mortality and fertility. The resulting sensitivities are measures of the strength of natural selection on aging and senescence. Keyfitz calculated sensitivities of population growth rate, life expectancy, and other quantities. Taking a demographic perspective, he interpreted the results as showing the linkage between age-specific rates at the individual level and the “intrinsic” rates expressed at the population level. Both these perspectives on sensitivity analysis continue to play major roles in demography and population biology. Connecting traits to individual rates, and those rates to measures of fitness, is the foundation of evolutionary demography. Understanding linkages between individual rates and population outcomes informs population projections, policy and spending, conservation, health demography, ecotoxicology, and so on. Fast forward to today. The diversity of demographic models, of the outcomes that can be calculated, and the power of the mathematical tools available to analyze them far exceed those of 50 years ago. Much of this progress is due to the formulation of demographic models in terms of matrices. P. H. Leslie formulated matrix models in the 1940s (Leslie 1945), but they were mostly ignored for two decades until revitalized by a series of studies in the 1960s (Keyfitz 1964; Lefkovitch 1965; Rogers 1968). In the very first issue of the first volume of the new journal Demography, Nathan Keyfitz described population projection as a matrix operator (Keyfitz 1964). This book relies on matrix formulations generalized beyond projections to age-structured and stage-structured populations, to linear and nonlinear dynamics, to time-invariant and time-varying vital rates, and to multistate models that combine age and stage information.
publishDate 2018
dc.date.created.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-11-20T17:21:02Z
dc.date.available.none.fl_str_mv 2020-11-20T17:21:02Z
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dc.identifier.isbn.none.fl_str_mv 978-3-030-10534-1
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/15865
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-10534-1
identifier_str_mv 978-3-030-10534-1
url http://hdl.handle.net/20.500.12010/15865
https://doi.org/10.1007/978-3-030-10534-1
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
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rights_invalid_str_mv Abierto (Texto Completo)
https://creativecommons.org/licenses/by/4.0/legalcode
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dc.format.extent.spa.fl_str_mv 308
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dc.publisher.spa.fl_str_mv Springer
institution Universidad de Bogotá Jorge Tadeo Lozano
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spelling 2020-11-20T17:21:02Z2020-11-20T17:21:02Z2018978-3-030-10534-1http://hdl.handle.net/20.500.12010/15865https://doi.org/10.1007/978-3-030-10534-1Sensitivity analysis addresses one of the most persistent of all questions: what would happen if ? Within the field of demography, sensitivity analysis might be said to have originated with the groundbreaking, yet very different, papers of Hamilton (1966) and Keyfitz (1971). Hamilton calculated the sensitivity of the intrinsic rate of increase, r, to changes in age-specific mortality. He interpreted r as a measure of individual fitness, capturing the effects of the phenotype on mortality and fertility. The resulting sensitivities are measures of the strength of natural selection on aging and senescence. Keyfitz calculated sensitivities of population growth rate, life expectancy, and other quantities. Taking a demographic perspective, he interpreted the results as showing the linkage between age-specific rates at the individual level and the “intrinsic” rates expressed at the population level. Both these perspectives on sensitivity analysis continue to play major roles in demography and population biology. Connecting traits to individual rates, and those rates to measures of fitness, is the foundation of evolutionary demography. Understanding linkages between individual rates and population outcomes informs population projections, policy and spending, conservation, health demography, ecotoxicology, and so on. Fast forward to today. The diversity of demographic models, of the outcomes that can be calculated, and the power of the mathematical tools available to analyze them far exceed those of 50 years ago. Much of this progress is due to the formulation of demographic models in terms of matrices. P. H. Leslie formulated matrix models in the 1940s (Leslie 1945), but they were mostly ignored for two decades until revitalized by a series of studies in the 1960s (Keyfitz 1964; Lefkovitch 1965; Rogers 1968). In the very first issue of the first volume of the new journal Demography, Nathan Keyfitz described population projection as a matrix operator (Keyfitz 1964). This book relies on matrix formulations generalized beyond projections to age-structured and stage-structured populations, to linear and nonlinear dynamics, to time-invariant and time-varying vital rates, and to multistate models that combine age and stage information.308application/pdfengSpringerDemographyEcologySensitivity analysisCiencias socialesEcología humanaDemografíaSensitivity analysis: matrix methods in demography and ecologyAbierto (Texto Completo)https://creativecommons.org/licenses/by/4.0/legalcodehttp://purl.org/coar/access_right/c_abf2http://purl.org/coar/resource_type/c_2f33Caswell, HalORIGINAL1007058.pdf1007058.pdfVer libroapplication/pdf4775096https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/15865/1/1007058.pdffc592c4b2addd3b8e80d4a8a334fddbcMD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/15865/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessTHUMBNAIL1007058.pdf.jpg1007058.pdf.jpgIM Thumbnailimage/jpeg16292https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/15865/3/1007058.pdf.jpg60defdc53bd58a9104fbb217e88a8717MD53open access20.500.12010/15865oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/158652020-11-20 12:21:58.683open accessRepositorio Institucional - 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