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Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)

Imperfect detection is an important problem when counting wildlife, but new technologies such as unmanned aerial systems (UAS) can help overcome this obstacle. We used data collected by a UAS and a Bayesian closed capture-mark-recapture model to estimate abundance and distribution while accounting f...

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Autores principales: Edwards, Holly H., Hostetler, Jeffrey A., Stith, Bradley M., Martin, Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217521/
https://www.ncbi.nlm.nih.gov/pubmed/34155318
http://dx.doi.org/10.1038/s41598-021-92437-z
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author Edwards, Holly H.
Hostetler, Jeffrey A.
Stith, Bradley M.
Martin, Julien
author_facet Edwards, Holly H.
Hostetler, Jeffrey A.
Stith, Bradley M.
Martin, Julien
author_sort Edwards, Holly H.
collection PubMed
description Imperfect detection is an important problem when counting wildlife, but new technologies such as unmanned aerial systems (UAS) can help overcome this obstacle. We used data collected by a UAS and a Bayesian closed capture-mark-recapture model to estimate abundance and distribution while accounting for imperfect detection of aggregated Florida manatees (Trichechus manatus latirostris) at thermal refuges to assess use of current and new warmwater sources in winter. Our UAS hovered for 10 min and recorded 4 K video over sites in Collier County, FL. Open-source software was used to create recapture histories for 10- and 6-min time periods. Mean estimates of probability of detection for 1-min intervals at each canal varied by survey and ranged between 0.05 and 0.92. Overall, detection probability for sites varied between 0.62 and 1.00 across surveys and length of video (6 and 10 min). Abundance varied by survey and location, and estimates indicated that distribution changed over time, with use of the novel source of warmwater increasing over time. The highest cumulative estimate occurred in the coldest winter, 2018 (N = 158, CI 141–190). Methods here reduced survey costs, increased safety and obtained rigorous abundance estimates at aggregation sites previously too difficult to monitor.
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spelling pubmed-82175212021-06-22 Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS) Edwards, Holly H. Hostetler, Jeffrey A. Stith, Bradley M. Martin, Julien Sci Rep Article Imperfect detection is an important problem when counting wildlife, but new technologies such as unmanned aerial systems (UAS) can help overcome this obstacle. We used data collected by a UAS and a Bayesian closed capture-mark-recapture model to estimate abundance and distribution while accounting for imperfect detection of aggregated Florida manatees (Trichechus manatus latirostris) at thermal refuges to assess use of current and new warmwater sources in winter. Our UAS hovered for 10 min and recorded 4 K video over sites in Collier County, FL. Open-source software was used to create recapture histories for 10- and 6-min time periods. Mean estimates of probability of detection for 1-min intervals at each canal varied by survey and ranged between 0.05 and 0.92. Overall, detection probability for sites varied between 0.62 and 1.00 across surveys and length of video (6 and 10 min). Abundance varied by survey and location, and estimates indicated that distribution changed over time, with use of the novel source of warmwater increasing over time. The highest cumulative estimate occurred in the coldest winter, 2018 (N = 158, CI 141–190). Methods here reduced survey costs, increased safety and obtained rigorous abundance estimates at aggregation sites previously too difficult to monitor. Nature Publishing Group UK 2021-06-21 /pmc/articles/PMC8217521/ /pubmed/34155318 http://dx.doi.org/10.1038/s41598-021-92437-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Edwards, Holly H.
Hostetler, Jeffrey A.
Stith, Bradley M.
Martin, Julien
Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title_full Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title_fullStr Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title_full_unstemmed Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title_short Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)
title_sort monitoring abundance of aggregated animals (florida manatees) using an unmanned aerial system (uas)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217521/
https://www.ncbi.nlm.nih.gov/pubmed/34155318
http://dx.doi.org/10.1038/s41598-021-92437-z
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