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Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar

1. Individuals are heterogeneous in many ways. Some of these differences are incorporated as individual states (e.g. age, size, breeding status) in population models. However, substantial amounts of heterogeneity may remain unaccounted for, due to unmeasurable genetic, maternal or environmental fact...

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Autores principales: Jenouvrier, Stéphanie, Aubry, Lise M., Barbraud, Christophe, Weimerskirch, Henri, Caswell, Hal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765524/
https://www.ncbi.nlm.nih.gov/pubmed/28886208
http://dx.doi.org/10.1111/1365-2656.12752
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author Jenouvrier, Stéphanie
Aubry, Lise M.
Barbraud, Christophe
Weimerskirch, Henri
Caswell, Hal
author_facet Jenouvrier, Stéphanie
Aubry, Lise M.
Barbraud, Christophe
Weimerskirch, Henri
Caswell, Hal
author_sort Jenouvrier, Stéphanie
collection PubMed
description 1. Individuals are heterogeneous in many ways. Some of these differences are incorporated as individual states (e.g. age, size, breeding status) in population models. However, substantial amounts of heterogeneity may remain unaccounted for, due to unmeasurable genetic, maternal or environmental factors. 2. Such unobserved heterogeneity (UH) affects the behaviour of heterogeneous cohorts via intra‐cohort selection and contributes to inter‐individual variance in demographic outcomes such as longevity and lifetime reproduction. Variance is also produced by individual stochasticity, due to random events in the life cycle of wild organisms, yet no study thus far has attempted to decompose the variance in demographic outcomes into contributions from UH and individual stochasticity for an animal population in the wild. 3. We developed a stage‐classified matrix population model for the southern fulmar breeding on Ile des Pétrels, Antarctica. We applied multievent, multistate mark–recapture methods to estimate a finite mixture model accounting for UH in all vital rates and Markov chain methods to calculate demographic outcomes. Finally, we partitioned the variance in demographic outcomes into contributions from UH and individual stochasticity. 4. We identify three UH groups, differing substantially in longevity, lifetime reproductive output, age at first reproduction and in the proportion of the life spent in each reproductive state. –14% of individuals at fledging have a delayed but high probability of recruitment and extended reproductive life span. –67% of individuals are less likely to reach adulthood, recruit late and skip breeding often but have the highest adult survival rate. –19% of individuals recruit early and attempt to breed often. They are likely to raise their offspring successfully, but experience a relatively short life span. Unobserved heterogeneity only explains a small fraction of the variances in longevity (5.9%), age at first reproduction (3.7%) and lifetime reproduction (22%). 5. UH can affect the entire life cycle, including survival, development and reproductive rates, with consequences over the lifetime of individuals and impacts on cohort dynamics. The respective role of UH vs. individual stochasticity varies greatly among demographic outcomes. We discuss the implication of our finding for the gradient of life‐history strategies observed among species and argue that individual differences should be accounted for in demographic studies of wild populations.
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spelling pubmed-57655242018-02-01 Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar Jenouvrier, Stéphanie Aubry, Lise M. Barbraud, Christophe Weimerskirch, Henri Caswell, Hal J Anim Ecol Life Histories 1. Individuals are heterogeneous in many ways. Some of these differences are incorporated as individual states (e.g. age, size, breeding status) in population models. However, substantial amounts of heterogeneity may remain unaccounted for, due to unmeasurable genetic, maternal or environmental factors. 2. Such unobserved heterogeneity (UH) affects the behaviour of heterogeneous cohorts via intra‐cohort selection and contributes to inter‐individual variance in demographic outcomes such as longevity and lifetime reproduction. Variance is also produced by individual stochasticity, due to random events in the life cycle of wild organisms, yet no study thus far has attempted to decompose the variance in demographic outcomes into contributions from UH and individual stochasticity for an animal population in the wild. 3. We developed a stage‐classified matrix population model for the southern fulmar breeding on Ile des Pétrels, Antarctica. We applied multievent, multistate mark–recapture methods to estimate a finite mixture model accounting for UH in all vital rates and Markov chain methods to calculate demographic outcomes. Finally, we partitioned the variance in demographic outcomes into contributions from UH and individual stochasticity. 4. We identify three UH groups, differing substantially in longevity, lifetime reproductive output, age at first reproduction and in the proportion of the life spent in each reproductive state. –14% of individuals at fledging have a delayed but high probability of recruitment and extended reproductive life span. –67% of individuals are less likely to reach adulthood, recruit late and skip breeding often but have the highest adult survival rate. –19% of individuals recruit early and attempt to breed often. They are likely to raise their offspring successfully, but experience a relatively short life span. Unobserved heterogeneity only explains a small fraction of the variances in longevity (5.9%), age at first reproduction (3.7%) and lifetime reproduction (22%). 5. UH can affect the entire life cycle, including survival, development and reproductive rates, with consequences over the lifetime of individuals and impacts on cohort dynamics. The respective role of UH vs. individual stochasticity varies greatly among demographic outcomes. We discuss the implication of our finding for the gradient of life‐history strategies observed among species and argue that individual differences should be accounted for in demographic studies of wild populations. John Wiley and Sons Inc. 2017-10-10 2018-01 /pmc/articles/PMC5765524/ /pubmed/28886208 http://dx.doi.org/10.1111/1365-2656.12752 Text en © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Life Histories
Jenouvrier, Stéphanie
Aubry, Lise M.
Barbraud, Christophe
Weimerskirch, Henri
Caswell, Hal
Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title_full Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title_fullStr Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title_full_unstemmed Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title_short Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
title_sort interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar
topic Life Histories
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765524/
https://www.ncbi.nlm.nih.gov/pubmed/28886208
http://dx.doi.org/10.1111/1365-2656.12752
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