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The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras

Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones and thermal infrared cameras can detect wildlife, though the ability to detect individuals is dependent on weather conditions. While we have a good understanding of local weather conditions, we do not ha...

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Autores principales: Camacho, Annalysa M., Perotto-Baldivieso, Humberto L., Tanner, Evan P., Montemayor, Amanda L., Gless, Walter A., Exum, Jesse, Yamashita, Thomas J., Foley, Aaron M., DeYoung, Randy W., Nelson, Shad D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023802/
https://www.ncbi.nlm.nih.gov/pubmed/36932162
http://dx.doi.org/10.1038/s41598-023-31150-5
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author Camacho, Annalysa M.
Perotto-Baldivieso, Humberto L.
Tanner, Evan P.
Montemayor, Amanda L.
Gless, Walter A.
Exum, Jesse
Yamashita, Thomas J.
Foley, Aaron M.
DeYoung, Randy W.
Nelson, Shad D.
author_facet Camacho, Annalysa M.
Perotto-Baldivieso, Humberto L.
Tanner, Evan P.
Montemayor, Amanda L.
Gless, Walter A.
Exum, Jesse
Yamashita, Thomas J.
Foley, Aaron M.
DeYoung, Randy W.
Nelson, Shad D.
author_sort Camacho, Annalysa M.
collection PubMed
description Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones and thermal infrared cameras can detect wildlife, though the ability to detect individuals is dependent on weather conditions. While we have a good understanding of local weather conditions, we do not have a broad-scale assessment of ambient temperature to plan drone wildlife surveys. Climate change will affect our ability to conduct thermal surveys in the future. Our objective was to determine optimal annual and daily time periods to conduct surveys. We present a case study in Texas, (United States of America [USA]) where we acquired and compared average monthly temperature data from 1990 to 2019, hourly temperature data from 2010 to 2019 and projected monthly temperature data from 2021 to 2040 to identify areas where surveys would detect a commonly studied ungulate (white-tailed deer [Odocoileus virginianus]) during sunny or cloudy conditions. Mean temperatures increased when comparing the 1990–2019 to 2010–2019 periods. Mean temperatures above the maximum ambient temperature in which white-tailed deer can be detected increased in 72, 10, 10, and 24 of the 254 Texas counties in June, July, August, and September, respectively. Future climate projections indicate that temperatures above the maximum ambient temperature in which white-tailed deer can be detected will increase in 32, 12, 15, and 47 counties in June, July, August, and September, respectively when comparing 2010–2019 with 2021–2040. This analysis can assist planning, and scheduling thermal drone wildlife surveys across the year and combined with daily data can be efficient to plan drone flights.
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spelling pubmed-100238022023-03-19 The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras Camacho, Annalysa M. Perotto-Baldivieso, Humberto L. Tanner, Evan P. Montemayor, Amanda L. Gless, Walter A. Exum, Jesse Yamashita, Thomas J. Foley, Aaron M. DeYoung, Randy W. Nelson, Shad D. Sci Rep Article Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones and thermal infrared cameras can detect wildlife, though the ability to detect individuals is dependent on weather conditions. While we have a good understanding of local weather conditions, we do not have a broad-scale assessment of ambient temperature to plan drone wildlife surveys. Climate change will affect our ability to conduct thermal surveys in the future. Our objective was to determine optimal annual and daily time periods to conduct surveys. We present a case study in Texas, (United States of America [USA]) where we acquired and compared average monthly temperature data from 1990 to 2019, hourly temperature data from 2010 to 2019 and projected monthly temperature data from 2021 to 2040 to identify areas where surveys would detect a commonly studied ungulate (white-tailed deer [Odocoileus virginianus]) during sunny or cloudy conditions. Mean temperatures increased when comparing the 1990–2019 to 2010–2019 periods. Mean temperatures above the maximum ambient temperature in which white-tailed deer can be detected increased in 72, 10, 10, and 24 of the 254 Texas counties in June, July, August, and September, respectively. Future climate projections indicate that temperatures above the maximum ambient temperature in which white-tailed deer can be detected will increase in 32, 12, 15, and 47 counties in June, July, August, and September, respectively when comparing 2010–2019 with 2021–2040. This analysis can assist planning, and scheduling thermal drone wildlife surveys across the year and combined with daily data can be efficient to plan drone flights. Nature Publishing Group UK 2023-03-17 /pmc/articles/PMC10023802/ /pubmed/36932162 http://dx.doi.org/10.1038/s41598-023-31150-5 Text en © The Author(s) 2023 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
Camacho, Annalysa M.
Perotto-Baldivieso, Humberto L.
Tanner, Evan P.
Montemayor, Amanda L.
Gless, Walter A.
Exum, Jesse
Yamashita, Thomas J.
Foley, Aaron M.
DeYoung, Randy W.
Nelson, Shad D.
The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title_full The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title_fullStr The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title_full_unstemmed The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title_short The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
title_sort broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023802/
https://www.ncbi.nlm.nih.gov/pubmed/36932162
http://dx.doi.org/10.1038/s41598-023-31150-5
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