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Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors

Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities a...

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Autores principales: Rodhouse, Thomas J., Rodriguez, Rogelio M., Banner, Katharine M., Ormsbee, Patricia C., Barnett, Jenny, Irvine, Kathryn M.
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/PMC6802066/
https://www.ncbi.nlm.nih.gov/pubmed/31641456
http://dx.doi.org/10.1002/ece3.5612
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author Rodhouse, Thomas J.
Rodriguez, Rogelio M.
Banner, Katharine M.
Ormsbee, Patricia C.
Barnett, Jenny
Irvine, Kathryn M.
author_facet Rodhouse, Thomas J.
Rodriguez, Rogelio M.
Banner, Katharine M.
Ormsbee, Patricia C.
Barnett, Jenny
Irvine, Kathryn M.
author_sort Rodhouse, Thomas J.
collection PubMed
description Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (Myotis lucifugus) and the hoary bat (Lasiurus cinereus). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat ([Formula: see text]  = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ([Formula: see text]  = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.
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spelling pubmed-68020662019-10-22 Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors Rodhouse, Thomas J. Rodriguez, Rogelio M. Banner, Katharine M. Ormsbee, Patricia C. Barnett, Jenny Irvine, Kathryn M. Ecol Evol Original Research Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (Myotis lucifugus) and the hoary bat (Lasiurus cinereus). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat ([Formula: see text]  = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ([Formula: see text]  = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining. John Wiley and Sons Inc. 2019-09-11 /pmc/articles/PMC6802066/ /pubmed/31641456 http://dx.doi.org/10.1002/ece3.5612 Text en © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 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
Rodhouse, Thomas J.
Rodriguez, Rogelio M.
Banner, Katharine M.
Ormsbee, Patricia C.
Barnett, Jenny
Irvine, Kathryn M.
Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title_full Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title_fullStr Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title_full_unstemmed Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title_short Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors
title_sort evidence of region‐wide bat population decline from long‐term monitoring and bayesian occupancy models with empirically informed priors
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802066/
https://www.ncbi.nlm.nih.gov/pubmed/31641456
http://dx.doi.org/10.1002/ece3.5612
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