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Using incidental mark‐encounter data to improve survival estimation

1. Obtaining robust survival estimates is critical, but sample size limitations often result in imprecise estimates or the failure to obtain estimates for population subgroups. Concurrently, data are often recorded on incidental reencounters of marked individuals, but these incidental data are often...

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Autores principales: Harju, Seth M., Cambrin, Scott M., Averill‐Murray, Roy C., Nafus, Melia, Field, Kimberleigh J., Allison, Linda J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972812/
https://www.ncbi.nlm.nih.gov/pubmed/31988732
http://dx.doi.org/10.1002/ece3.5900
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author Harju, Seth M.
Cambrin, Scott M.
Averill‐Murray, Roy C.
Nafus, Melia
Field, Kimberleigh J.
Allison, Linda J.
author_facet Harju, Seth M.
Cambrin, Scott M.
Averill‐Murray, Roy C.
Nafus, Melia
Field, Kimberleigh J.
Allison, Linda J.
author_sort Harju, Seth M.
collection PubMed
description 1. Obtaining robust survival estimates is critical, but sample size limitations often result in imprecise estimates or the failure to obtain estimates for population subgroups. Concurrently, data are often recorded on incidental reencounters of marked individuals, but these incidental data are often unused in survival analyses. 2. We evaluated the utility of supplementing a traditional survival dataset with incidental data on marked individuals that were collected ad hoc. We used a continuous time‐to‐event exponential survival model to leverage the matching information contained in both datasets and assessed differences in survival among adult and juvenile and resident and translocated Mojave desert tortoises (Gopherus agassizii). 3. Incorporation of the incidental mark‐encounter data improved precision of all annual survival point estimates, with a 3.4%–37.5% reduction in the spread of the 95% Bayesian credible intervals. We were able to estimate annual survival for three subgroup combinations that were previously inestimable. Point estimates between the radiotelemetry and combined datasets were within |0.029| percentage points of each other, suggesting minimal to no bias induced by the incidental data. 4. Annual survival rates were high (>0.89) for resident adult and juvenile tortoises in both study sites and for translocated adults in the southern site. Annual survival rates for translocated juveniles at both sites and translocated adults in the northern site were between 0.73 and 0.76. At both sites, translocated adults and juveniles had significantly lower survival than resident adults. High mortality in the northern site was driven primarily by a single pulse in mortalities. 5. Using exponential survival models to leverage matching information across traditional survival studies and incidental data on marked individuals may serve as a useful tool to improve the precision and estimability of survival rates. This can improve the efficacy of understanding basic population ecology and population monitoring for imperiled species.
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spelling pubmed-69728122020-01-27 Using incidental mark‐encounter data to improve survival estimation Harju, Seth M. Cambrin, Scott M. Averill‐Murray, Roy C. Nafus, Melia Field, Kimberleigh J. Allison, Linda J. Ecol Evol Original Research 1. Obtaining robust survival estimates is critical, but sample size limitations often result in imprecise estimates or the failure to obtain estimates for population subgroups. Concurrently, data are often recorded on incidental reencounters of marked individuals, but these incidental data are often unused in survival analyses. 2. We evaluated the utility of supplementing a traditional survival dataset with incidental data on marked individuals that were collected ad hoc. We used a continuous time‐to‐event exponential survival model to leverage the matching information contained in both datasets and assessed differences in survival among adult and juvenile and resident and translocated Mojave desert tortoises (Gopherus agassizii). 3. Incorporation of the incidental mark‐encounter data improved precision of all annual survival point estimates, with a 3.4%–37.5% reduction in the spread of the 95% Bayesian credible intervals. We were able to estimate annual survival for three subgroup combinations that were previously inestimable. Point estimates between the radiotelemetry and combined datasets were within |0.029| percentage points of each other, suggesting minimal to no bias induced by the incidental data. 4. Annual survival rates were high (>0.89) for resident adult and juvenile tortoises in both study sites and for translocated adults in the southern site. Annual survival rates for translocated juveniles at both sites and translocated adults in the northern site were between 0.73 and 0.76. At both sites, translocated adults and juveniles had significantly lower survival than resident adults. High mortality in the northern site was driven primarily by a single pulse in mortalities. 5. Using exponential survival models to leverage matching information across traditional survival studies and incidental data on marked individuals may serve as a useful tool to improve the precision and estimability of survival rates. This can improve the efficacy of understanding basic population ecology and population monitoring for imperiled species. John Wiley and Sons Inc. 2019-12-08 /pmc/articles/PMC6972812/ /pubmed/31988732 http://dx.doi.org/10.1002/ece3.5900 Text en © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd This article has been contributed to by US Government employees and their work is in the public domain in the USA. This is an open access article under the terms of the 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 Original Research
Harju, Seth M.
Cambrin, Scott M.
Averill‐Murray, Roy C.
Nafus, Melia
Field, Kimberleigh J.
Allison, Linda J.
Using incidental mark‐encounter data to improve survival estimation
title Using incidental mark‐encounter data to improve survival estimation
title_full Using incidental mark‐encounter data to improve survival estimation
title_fullStr Using incidental mark‐encounter data to improve survival estimation
title_full_unstemmed Using incidental mark‐encounter data to improve survival estimation
title_short Using incidental mark‐encounter data to improve survival estimation
title_sort using incidental mark‐encounter data to improve survival estimation
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972812/
https://www.ncbi.nlm.nih.gov/pubmed/31988732
http://dx.doi.org/10.1002/ece3.5900
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