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Fletcherview Tropical Rangeland Acoustic Data Collection - A2O Project 

Ver: 1.0
Status of Data: onGoing
Update Frequency: asNeeded
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 93 times
Accessed 5 times
Dataset Created: 2020-08-10
Dataset Published: 2023-02-20
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTPAudio files - A2OHTTPro-crate-metadata.json
How to cite this collection:
Schwarzkopf, L. & Allen-Ankins, S. (2023). Fletcherview Tropical Rangeland Acoustic Data Collection - A2O Project. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/4c88c650-269f-4ba3-a297-e22ede100196 
This dataset contains audio files for TERN Fletcherview Tropical Rangeland SuperSite. Long-term recordings of the environment can be used to identify sound sources of interest, characterise the soundscape, aid in the assessment of fauna biodiversity, monitor temporal trends and track environmental changes. Fletcherview Tropical Rangeland SuperSite was established in 2021 at James Cook University’s Fletcherview Research Station, a fully operational outback cattle station located 50 km west of Townsville, Queensland. The site is used for cattle grazing and is characterised by tall open savanna. The vegetation is dominated by native grasses such as blackspear and kangaroo grasses, as well as introduced species like buffel grass, signal grass and leucaena. Fletcherview typically experiences a dry and wet season, with most rainfall occurring between January and April. In 2020 four acoustic recorders were set up to collect audio data continuously as part of the Australian Acoustic Observatory (A2O) project. Two recorders were placed in relatively wet habitats and two in relatively dry habitats. 
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. The Fletcherview Tropical Rangeland SuperSite is managed by James Cook University. Infrastructure at the site was funded under the Queensland Government’s Research Infrastructure Co-Investment Fund (RICF) for co-investment to the Terrestrial Ecosystem Research Network (TERN), a project of the Commonwealth’s National Collaborative Research Infrastructure Strategy (NCRIS). Australian Acoustic Observatory: A Network to Monitor Biodiversity Project Team, with funding from the Australian Government through the Australian Research Council (LE170100033) (2018). Brisbane, QLD: QUT [www.acousticobservatory.org]  
Purpose
Long-term acoustic recordings are collected to characterise the acoustic sources in the ecosystem. Recordings can be used to estimate biodiversity, monitor temporal changes in the soundscape, compare the acoustic characteristics of different locations, and assess the effect of particular events such as bushfires and floods. 
Lineage
Four acoustic sensors are set up to collect audio data continuosly as part of the A2O project. Sensors are Frontier Labs Solar BAR. Each sensor has a Primo EM172 microphone with an 80 dB signal-to-noise ratio, 14 dBA self-noise, -28 dB sensitivity, and a flat response (+2 dB between 80 Hz and 20 kHz). Sensors have a gain of 50 dB. They are mounted on 1.8 m star pickets and powered by solar panels. Data are recorded continuously. Recordings are made as single channel, two-hour long flac files. They have a sampling rate of 22,050 Hz and a depth of 16 bits. The four sensors are deployed in pairs. Each pair contains a wet and a dry sensor. Wet sensors are located within 50 m from the edge of a body of water. Dry sensors are located between 500 m and 5 km from their corresponding wet sensors. Wet–wet and dry–dry sensor points are at a distance between 500 m and 5 km. 
Method DocumentationA2O information brochureDeployment manual for solar powered acoustic sensors
Procedure StepsData not provided.
Temporal Coverage
From 2020-08-10 to on going 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Australian Faunal Directory
AVES
INSECTA
MAMMALIA
ANZSRC - FOR
Acoustics and acoustical devices; waves
Animal behaviour
Behavioural ecology
Conservation and biodiversity
Environmental management
GCMD Sciences
AGRICULTURE - ANIMAL ECOLOGY AND BEHAVIOR
BIOLOGICAL CLASSIFICATION - BIRDS
BIOLOGICAL CLASSIFICATION - INSECTS
OCEANS - ACOUSTIC FREQUENCY
OCEANS - AMBIENT NOISE
Horizontal Resolution
Point Resolution
Instruments
Fletcherview Research Station Dry A 00003715
Fletcherview Research Station Dry B 00003056
Fletcherview Research Station Wet A 00003476
Fletcherview Research Station Wet B 00003944
Parameters
sound pressure in air
Platforms
Fletcherview Tropical Rangeland
Temporal Resolution
< 1 second
Topic
environment
User Defined
Acoustic recordings
fletch
Author
Schwarzkopf, Lin
Allen-Ankins, Slade
Contact Point
Schwarzkopf, Lin
Allen-Ankins, Slade
Publisher
Terrestrial Ecosystem Research Network
Roe et al. (2021). The Australian acoustic observatory. Methods in ecology and evolutions. 00:1-7. DOI: 10.1111/2041-210X.13660.
Export to DCATExport to BibTeXExport to EndNote/Zotero
Terrestrial Ecosystem Research Network
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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/
TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.
Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting 
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}. 

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