Evidence map›Paper›PMID 30020938›Full record

ArticlePloS one2018

Passive acoustic surveys for predicting species' distributions: Optimising detection probability.

Stiele V Hagens, Anthony R Rendall, Desley A Whisson

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In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

3 authors.

Stiele V HagensSchool of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Geelong, Australia.
Anthony R RendallSchool of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Geelong, Australia.ORCID 0000-0002-7286-9288
Desley A WhissonSchool of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Geelong, Australia.ORCID 0000-0002-4221-0706

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surveying terrestrial species across diverse habitats is important for predicting species' distributions and implementing conservation actions. For vocalising species, passive acoustic monitoring (PAM) is increasing in popularity; however, survey design rarely considers the factors influencing the timing and occurrence of vocalisations and in turn, how they may influence detectability of the species. Here, we use the koala (Phascolarctos cinereus) as a case study to show how PAM can be used to first examine the factors influencing vocalisations, and then use occupancy modelling to make recommendations on survey design for the species. We used automated recording units to monitor koala vocalisations at ten sites between August 2016 and January 2017. The timing of male koala vocalisations was linked to time of sunset with vocalisations increasing two hours prior to sunset and peaking at four hours after sunset. Vocalisations had a seasonal trend, increasing from the early to middle stage of the breeding season. Koala population density and stage of the breeding season had more influence on detection probability than daily sampling schedule. Where population density was low, and during the early stage of the breeding season, 7 survey nights (recording for 6 hours from 20:00h to 02:00h; i.e. the period of peak bellowing activity) were required to be 95% confident of a site-specific absence. Our study provides an approach for designing effective passive acoustic surveys for terrestrial species.

Indexed as

AcousticsBiodiversityEcosystemAnimalsPhascolarctidaePopulation DensityPopulation DynamicsVocalization, Animal

Identifiers

PMID30020938
PMCPMC6051584

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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.