Evidence map›Paper›PMID 30619599›Full record

ArticleEcology and evolution2018

Observer-free experimental evaluation of habitat and distance effects on the detection of anuran and bird vocalizations.

Andrew R MacLaren, Paul S Crump, J Andrew Royle, Michael R J Forstner

Open access · goldAbstract read
In one paragraph

Article in Ecology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

7 citing papers in PubMed, 22 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Andrew R MacLarenDepartment of Biology Texas State University San Marcos Texas.ORCID 0000-0002-9793-7240
Paul S CrumpDepartment of Biology Texas State University San Marcos Texas.ORCID 0000-0002-0495-4771
J Andrew RoyleUSGS Patuxent Wildlife Research Center Laurel Maryland.ORCID 0000-0003-3135-2167
Michael R J ForstnerDepartment of Biology Texas State University San Marcos Texas.
Texas State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acoustic surveys of vocalizing animals are conducted to determine density, distribution, and diversity. Acoustic surveys are traditionally performed by human listeners, but automated recording devices (ARD) are becoming increasingly popular. Signal strength decays, or attenuates, with increasing distance between source and receiver and some habitat types may differentially increase attenuation beyond the effects of distance alone. These combined effects are rarely accounted for in acoustic monitoring programs. We evaluated the performance of three playback devices and three ARD models using the calls of six anurans, six birds, and four pure tones. Based on these evaluations, we determined the optimal playback and recording devices. Using these optimal devices, we broadcast and recorded vocalizations in five habitat types along 1,000 m transects. We used generalized linear models to test for effects of habitat, distance, species, environmental, and landscape variables. We predicted detection probabilities for each vocalization, in each habitat type, from 0 to 1,000 m. Among playback devices, only a remote predator caller simulated vocalizations consistently. Differences of ~10 dB were observed among ARDs. For all species, we found differences in detectability between open and closed canopy habitats. We observed large differences in predicted detection probability among species in each habitat type, as well as along 1,000 m transects. Increases in temperature, barometric pressure, and wind speed significantly decreased detection probability. However, aside from differences among species, habitat, and distance, topography impeding a line-of-sight between sound source and receiver had the greatest negative influence on detections. Our results suggest researchers should model the effects of habitat, distance, and frequency on detection probability when performing acoustic surveys. To optimize survey design, we recommend pilot measurements among varying habitats.

Indexed as

audio recording devicedetection probabilitygeneralized linear modelsobserver freesound attenuationvocalization

Identifiers

PMID30619599
PMCPMC6308863
OpenAlexW2904625057

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.