Evidence map›Paper›PMID 33196649›Full record

ArticlePloS one2020

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

Ryan R Witt, Chad T Beranek, Lachlan G Howell, Shelby A Ryan, John Clulow, Neil R Jordan, Bob Denholm, Adam Roff

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  3. Thermal drone surveys to detect arboreal fauna: Improving population estimates and threatened species monitoring.Ecological applications : a publication of the Ecological Society of America · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ryan R WittSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.ORCID 0000-0003-3696-6395
Chad T BeranekSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.
Lachlan G HowellSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.
Shelby A RyanSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.
John ClulowSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.
Neil R JordanCentre for Ecosystem Science, School of BEES, University of New South Wales (UNSW Sydney), Sydney, New South Wales, Australia.
Bob DenholmScience Division, NSW Department of Planning, Industry and Environment, Newcastle, New South Wales, Australia.
Adam RoffSchool of Environmental and Life Sciences, University of Newcastle, Callaghan, New South Wales, Australia.ORCID 0000-0002-0457-8251

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AircraftPopulation DensityAnimalsForestsPhascolarctidaeTelemetry

Identifiers

PMID33196649
PMCPMC7668579

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.