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Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal

Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detection (physical sighting) of individuals is required to improve conservation management strategies. We provide a comparative assessment of three survey methods for the direct detection of koalas: syste...

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Autores principales: Witt, Ryan R., Beranek, Chad T., Howell, Lachlan G., Ryan, Shelby A., Clulow, John, Jordan, Neil R., Denholm, Bob, Roff, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668579/
https://www.ncbi.nlm.nih.gov/pubmed/33196649
http://dx.doi.org/10.1371/journal.pone.0242204
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author Witt, Ryan R.
Beranek, Chad T.
Howell, Lachlan G.
Ryan, Shelby A.
Clulow, John
Jordan, Neil R.
Denholm, Bob
Roff, Adam
author_facet Witt, Ryan R.
Beranek, Chad T.
Howell, Lachlan G.
Ryan, Shelby A.
Clulow, John
Jordan, Neil R.
Denholm, Bob
Roff, Adam
author_sort Witt, Ryan R.
collection PubMed
description Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detection (physical sighting) of individuals is required to improve conservation management strategies. We provide a comparative assessment of three survey methods for the direct detection of koalas: systematic spotlighting (Spotlight), remotely piloted aircraft system thermal imaging (RPAS), and the refined diurnal radial search component of the spot assessment technique (SAT). Each survey method was repeated on the same morning with independent observers (03:00–12:00 hrs) for a total of 10 survey occasions at sites with fixed boundaries (28–76 ha) in Port Stephens (n = 6) and Gilead (n = 1) in New South Wales between May and July 2019. Koalas were directly detected on 22 occasions during 7 of 10 comparative surveys (Spotlight: n = 7; RPAS: n = 14; and SAT: n = 1), for a total of 12 unique individuals (Spotlight: n = 4; RPAS: n = 11; SAT: n = 1). In 3 of 10 comparative surveys no koalas were detected. Detection probability was 38.9 ± 20.03% for Spotlight, 83.3 ± 11.39% for RPAS and 4.2 ± 4.17% for SAT. Effective detectability per site was 1 ± 0.44 koalas per 6.75 ± 1.03 hrs for Spotlight (1 koala per 6.75 hrs), 2 ± 0.38 koalas per 4.35 ± 0.28 hrs for RPAS (1 koala per 2.18 hrs) and 0.14 ± 0.14 per 6.20 ± 0.93 hrs for SAT (1 koala per 43.39 hrs). RPAS thermal imaging technology appears to offer an efficient method to directly survey koalas comparative to Spotlight and SAT and has potential as a valuable conservation tool to inform on-ground management of declining koala populations.
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spelling pubmed-76685792020-11-19 Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal Witt, Ryan R. Beranek, Chad T. Howell, Lachlan G. Ryan, Shelby A. Clulow, John Jordan, Neil R. Denholm, Bob Roff, Adam PLoS One Research Article Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detection (physical sighting) of individuals is required to improve conservation management strategies. We provide a comparative assessment of three survey methods for the direct detection of koalas: systematic spotlighting (Spotlight), remotely piloted aircraft system thermal imaging (RPAS), and the refined diurnal radial search component of the spot assessment technique (SAT). Each survey method was repeated on the same morning with independent observers (03:00–12:00 hrs) for a total of 10 survey occasions at sites with fixed boundaries (28–76 ha) in Port Stephens (n = 6) and Gilead (n = 1) in New South Wales between May and July 2019. Koalas were directly detected on 22 occasions during 7 of 10 comparative surveys (Spotlight: n = 7; RPAS: n = 14; and SAT: n = 1), for a total of 12 unique individuals (Spotlight: n = 4; RPAS: n = 11; SAT: n = 1). In 3 of 10 comparative surveys no koalas were detected. Detection probability was 38.9 ± 20.03% for Spotlight, 83.3 ± 11.39% for RPAS and 4.2 ± 4.17% for SAT. Effective detectability per site was 1 ± 0.44 koalas per 6.75 ± 1.03 hrs for Spotlight (1 koala per 6.75 hrs), 2 ± 0.38 koalas per 4.35 ± 0.28 hrs for RPAS (1 koala per 2.18 hrs) and 0.14 ± 0.14 per 6.20 ± 0.93 hrs for SAT (1 koala per 43.39 hrs). RPAS thermal imaging technology appears to offer an efficient method to directly survey koalas comparative to Spotlight and SAT and has potential as a valuable conservation tool to inform on-ground management of declining koala populations. Public Library of Science 2020-11-16 /pmc/articles/PMC7668579/ /pubmed/33196649 http://dx.doi.org/10.1371/journal.pone.0242204 Text en © 2020 Witt et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Witt, Ryan R.
Beranek, Chad T.
Howell, Lachlan G.
Ryan, Shelby A.
Clulow, John
Jordan, Neil R.
Denholm, Bob
Roff, Adam
Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title_full Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title_fullStr Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title_full_unstemmed Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title_short Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
title_sort real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668579/
https://www.ncbi.nlm.nih.gov/pubmed/33196649
http://dx.doi.org/10.1371/journal.pone.0242204
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