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Variance in animal longevity: contributions of heterogeneity and stochasticity
Variance in longevity among individuals may arise as an effect of heterogeneity (differences in mortality rates experienced at the same age or stage) or as an effect of individual stochasticity (the outcome of random demographic events during the life cycle). Decomposing the variance into components...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Japan
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435164/ https://www.ncbi.nlm.nih.gov/pubmed/30996674 http://dx.doi.org/10.1007/s10144-018-0616-7 |
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author | Hartemink, Nienke Caswell, Hal |
author_facet | Hartemink, Nienke Caswell, Hal |
author_sort | Hartemink, Nienke |
collection | PubMed |
description | Variance in longevity among individuals may arise as an effect of heterogeneity (differences in mortality rates experienced at the same age or stage) or as an effect of individual stochasticity (the outcome of random demographic events during the life cycle). Decomposing the variance into components due to heterogeneity and stochasticity is crucial for evolutionary analyses.In this study, we analyze longevity from ten studies of invertebrates in the laboratory, and use the results to partition the variance in longevity into its components. To do so, we fit finite mixtures of Weibull survival functions to each data set by maximum likelihood, using the EM algorithm. We used the Bayesian Information Criterion to select the most well supported model. The results of the mixture analysis were used to construct an age × stage-classified matrix model, with heterogeneity groups as stages, from which we calculated the variance in longevity and its components. Almost all data sets revealed evidence of some degree of heterogeneity. The median contribution of unobserved heterogeneity to the total variance was 35%, with the remaining 65% due to stochasticity. The differences among groups in mean longevity were typically on the order of 30% of the overall life expectancy. There was considerable variation among data sets in both the magnitude of heterogeneity and the proportion of variance due to heterogeneity, but no clear patterns were apparent in relation to sex, taxon, or environmental conditions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10144-018-0616-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6435164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Japan |
record_format | MEDLINE/PubMed |
spelling | pubmed-64351642019-04-15 Variance in animal longevity: contributions of heterogeneity and stochasticity Hartemink, Nienke Caswell, Hal Popul Ecol Special Feature: Original Article Variance in longevity among individuals may arise as an effect of heterogeneity (differences in mortality rates experienced at the same age or stage) or as an effect of individual stochasticity (the outcome of random demographic events during the life cycle). Decomposing the variance into components due to heterogeneity and stochasticity is crucial for evolutionary analyses.In this study, we analyze longevity from ten studies of invertebrates in the laboratory, and use the results to partition the variance in longevity into its components. To do so, we fit finite mixtures of Weibull survival functions to each data set by maximum likelihood, using the EM algorithm. We used the Bayesian Information Criterion to select the most well supported model. The results of the mixture analysis were used to construct an age × stage-classified matrix model, with heterogeneity groups as stages, from which we calculated the variance in longevity and its components. Almost all data sets revealed evidence of some degree of heterogeneity. The median contribution of unobserved heterogeneity to the total variance was 35%, with the remaining 65% due to stochasticity. The differences among groups in mean longevity were typically on the order of 30% of the overall life expectancy. There was considerable variation among data sets in both the magnitude of heterogeneity and the proportion of variance due to heterogeneity, but no clear patterns were apparent in relation to sex, taxon, or environmental conditions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10144-018-0616-7) contains supplementary material, which is available to authorized users. Springer Japan 2018-05-28 2018 /pmc/articles/PMC6435164/ /pubmed/30996674 http://dx.doi.org/10.1007/s10144-018-0616-7 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Special Feature: Original Article Hartemink, Nienke Caswell, Hal Variance in animal longevity: contributions of heterogeneity and stochasticity |
title | Variance in animal longevity: contributions of heterogeneity and stochasticity |
title_full | Variance in animal longevity: contributions of heterogeneity and stochasticity |
title_fullStr | Variance in animal longevity: contributions of heterogeneity and stochasticity |
title_full_unstemmed | Variance in animal longevity: contributions of heterogeneity and stochasticity |
title_short | Variance in animal longevity: contributions of heterogeneity and stochasticity |
title_sort | variance in animal longevity: contributions of heterogeneity and stochasticity |
topic | Special Feature: Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435164/ https://www.ncbi.nlm.nih.gov/pubmed/30996674 http://dx.doi.org/10.1007/s10144-018-0616-7 |
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