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An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data

Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack con...

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Autores principales: Davis, Amy J, Hooten, Mevin B, Phillips, Michael L, Doherty, Paul F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267864/
https://www.ncbi.nlm.nih.gov/pubmed/25540687
http://dx.doi.org/10.1002/ece3.1290
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author Davis, Amy J
Hooten, Mevin B
Phillips, Michael L
Doherty, Paul F
author_facet Davis, Amy J
Hooten, Mevin B
Phillips, Michael L
Doherty, Paul F
author_sort Davis, Amy J
collection PubMed
description Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.
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spelling pubmed-42678642014-12-24 An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data Davis, Amy J Hooten, Mevin B Phillips, Michael L Doherty, Paul F Ecol Evol Original Research Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years. Blackwell Publishing Ltd 2014-11 2014-10-22 /pmc/articles/PMC4267864/ /pubmed/25540687 http://dx.doi.org/10.1002/ece3.1290 Text en © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Davis, Amy J
Hooten, Mevin B
Phillips, Michael L
Doherty, Paul F
An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title_full An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title_fullStr An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title_full_unstemmed An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title_short An integrated modeling approach to estimating Gunnison sage-grouse population dynamics: combining index and demographic data
title_sort integrated modeling approach to estimating gunnison sage-grouse population dynamics: combining index and demographic data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267864/
https://www.ncbi.nlm.nih.gov/pubmed/25540687
http://dx.doi.org/10.1002/ece3.1290
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