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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2014
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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. |
format | Online Article Text |
id | pubmed-4267864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
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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