Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild
The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed in...
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ftdans:oai:easy.dans.knaw.nl:easy-dataset:82185 2023-07-02T03:31:43+02:00 Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild Buoro, Mathieu Prévost, Etienne Gimenez, Olivier 2012-07-06T22:03:53.000+02:00 http://nbn-resolving.org/urn:nbn:nl:ui:13-1u-tr0m https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:82185 unknown doi:10.5061/dryad.f05mk/1 doi:10.5061/dryad.f05mk/2 doi:10.1111/j.1420-9101.2012.02590.x PMID:22901099 http://nbn-resolving.org/urn:nbn:nl:ui:13-1u-tr0m doi:10.5061/dryad.f05mk https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:82185 OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf Life sciences medicine and health care 2012 ftdans https://doi.org/10.5061/dryad.f05mk/110.5061/dryad.f05mk/210.1111/j.1420-9101.2012.02590.x10.5061/dryad.f05mk 2023-06-13T12:26:21Z The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life histories components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies. Other/Unknown Material Atlantic salmon Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen) |
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Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen) |
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Life sciences medicine and health care |
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Life sciences medicine and health care Buoro, Mathieu Prévost, Etienne Gimenez, Olivier Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
topic_facet |
Life sciences medicine and health care |
description |
The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life histories components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies. |
author |
Buoro, Mathieu Prévost, Etienne Gimenez, Olivier |
author_facet |
Buoro, Mathieu Prévost, Etienne Gimenez, Olivier |
author_sort |
Buoro, Mathieu |
title |
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
title_short |
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
title_full |
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
title_fullStr |
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
title_full_unstemmed |
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
title_sort |
data from: digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild |
publishDate |
2012 |
url |
http://nbn-resolving.org/urn:nbn:nl:ui:13-1u-tr0m https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:82185 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
doi:10.5061/dryad.f05mk/1 doi:10.5061/dryad.f05mk/2 doi:10.1111/j.1420-9101.2012.02590.x PMID:22901099 http://nbn-resolving.org/urn:nbn:nl:ui:13-1u-tr0m doi:10.5061/dryad.f05mk https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:82185 |
op_rights |
OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf |
op_doi |
https://doi.org/10.5061/dryad.f05mk/110.5061/dryad.f05mk/210.1111/j.1420-9101.2012.02590.x10.5061/dryad.f05mk |
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