Data

Sampling RUV

Name: Sampling RUV
Published: 2026

Australian Institute of Marine Science

Australian Institute of Marine Science (AIMS)

Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]

ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://apps.aims.gov.au/metadata/view/a56ba272-b0d7-402d-94ce-3b289186d9df&rft.title=Sampling RUV&rft.identifier=https://apps.aims.gov.au/metadata/view/a56ba272-b0d7-402d-94ce-3b289186d9df&rft.publisher=Australian Institute of Marine Science (AIMS)&rft.description=This dataset is to replicate analyses in the publication titled “Optimizing remote underwater video sampling to quantify relative abundance, richness, and corallivory rates of reef fish” in Coral Reefs (2025). https://doi.org/10.1007/s00338-024-02613-6.This study was conducted as part of the Ecological Intelligence for Reef Restoration and Adaptation Program (EcoRRAP) (https://gbrrestoration.org/program/ecorrap/).Data were video annotations from remote underwater videos (1080p, 60fps) recorded at 5 m depth at eight reef sites from Apr 2021 to Jan 2022. The optimal sampling strategies were developed by examining the precision and accuracy of estimates to enhance video analysis efficiency while minimizing the sampling errors of relative abundance, richness, and corallivory rates of reef fish.Data and an R markdown are stored on the Sydney eScholarship (https://hdl.handle.net/2123/33520), and videos are stored on the AIMS data server and available on request due to large file sizes.Maintenance and Update Frequency: notPlanned&rft.creator=Australian Institute of Marine Science (AIMS) &rft.date=2026&rft.coverage=westlimit=143.4; southlimit=-9.75; eastlimit=143.4; northlimit=-9.75&rft.coverage=westlimit=143.4; southlimit=-9.75; eastlimit=143.4; northlimit=-9.75&rft.coverage=westlimit=143.41; southlimit=-9.88; eastlimit=143.41; northlimit=-9.88&rft.coverage=westlimit=143.41; southlimit=-9.88; eastlimit=143.41; northlimit=-9.88&rft.coverage=westlimit=145.45; southlimit=-14.65; eastlimit=145.45; northlimit=-14.65&rft.coverage=westlimit=145.45; southlimit=-14.65; eastlimit=145.45; northlimit=-14.65&rft.coverage=westlimit=146.49; southlimit=-18.54; eastlimit=146.49; northlimit=-18.54&rft.coverage=westlimit=146.49; southlimit=-18.54; eastlimit=146.49; northlimit=-18.54&rft.coverage=westlimit=147.63; southlimit=-18.83; eastlimit=147.63; northlimit=-18.83&rft.coverage=westlimit=147.63; southlimit=-18.83; eastlimit=147.63; northlimit=-18.83&rft.coverage=westlimit=147.71; southlimit=-18.65; eastlimit=147.71; northlimit=-18.65&rft.coverage=westlimit=147.71; southlimit=-18.65; eastlimit=147.71; northlimit=-18.65&rft.coverage=westlimit=150.97; southlimit=-23.2; eastlimit=150.97; northlimit=-23.2&rft.coverage=westlimit=150.97; southlimit=-23.2; eastlimit=150.97; northlimit=-23.2&rft.coverage=westlimit=151.95; southlimit=-23.43; eastlimit=151.95; northlimit=-23.43&rft.coverage=westlimit=151.95; southlimit=-23.43; eastlimit=151.95; northlimit=-23.43&rft_rights=Creative Commons Attribution-NonCommercial 3.0 Australia License http://creativecommons.org/licenses/by-nc/3.0/au/&rft_rights=Use Limitation: All AIMS data, products and services are provided as is and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights=Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: Australian Institute of Marine Science (AIMS). (2025). Sampling RUV. https://apps.aims.gov.au/metadata/view/a56ba272-b0d7-402d-94ce-3b289186d9df, accessed[date-of-access].&rft_subject=oceans&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution-NonCommercial 3.0 Australia License
http://creativecommons.org/licenses/by-nc/3.0/au/

Use Limitation: All AIMS data, products and services are provided "as is" and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: "Australian Institute of Marine Science (AIMS). (2025). Sampling RUV. https://apps.aims.gov.au/metadata/view/a56ba272-b0d7-402d-94ce-3b289186d9df, accessed[date-of-access]".

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Full description

This dataset is to replicate analyses in the publication titled “Optimizing remote underwater video sampling to quantify relative abundance, richness, and corallivory rates of reef fish” in Coral Reefs (2025). https://doi.org/10.1007/s00338-024-02613-6.

This study was conducted as part of the Ecological Intelligence for Reef Restoration and Adaptation Program (EcoRRAP) (https://gbrrestoration.org/program/ecorrap/).

Data were video annotations from remote underwater videos (1080p, 60fps) recorded at 5 m depth at eight reef sites from Apr 2021 to Jan 2022. The optimal sampling strategies were developed by examining the precision and accuracy of estimates to enhance video analysis efficiency while minimizing the sampling errors of relative abundance, richness, and corallivory rates of reef fish.

Data and an R markdown are stored on the Sydney eScholarship (https://hdl.handle.net/2123/33520), and videos are stored on the AIMS data server and available on request due to large file sizes.

Lineage

Maintenance and Update Frequency: notPlanned

Notes

Credit
Gordon, S. Australian Institute of Marine Science (AIMS)

Credit
Ferrari, R. (AIMS)

Credit
Hoey, AS. James Cook University (JCU)

Credit
Figueira, WF. (USYD)

Credit
The Reef Restoration and Adaptation Program is funded by the partnership between the Australian Government’s Reef Trust and the Great Barrier Reef Foundation.

Credit
Hsu, T-HT. The University of Sydney (USYD)

Modified: 11 09 2026

This dataset is part of a larger collection

Click to explore relationships graph

text: westlimit=143.4; southlimit=-9.75; eastlimit=143.4; northlimit=-9.75

text: westlimit=143.41; southlimit=-9.88; eastlimit=143.41; northlimit=-9.88

text: westlimit=145.45; southlimit=-14.65; eastlimit=145.45; northlimit=-14.65

text: westlimit=146.49; southlimit=-18.54; eastlimit=146.49; northlimit=-18.54

text: westlimit=147.63; southlimit=-18.83; eastlimit=147.63; northlimit=-18.83

text: westlimit=147.71; southlimit=-18.65; eastlimit=147.71; northlimit=-18.65

text: westlimit=150.97; southlimit=-23.2; eastlimit=150.97; northlimit=-23.2

text: westlimit=151.95; southlimit=-23.43; eastlimit=151.95; northlimit=-23.43

Subjects

oceans |

User Contributed Tags

Other Information

Hsu, TH.T., Gordon, S., Ferrari, R. et al. Optimizing remote underwater video sampling to quantify relative abundance, richness, and corallivory rates of reef fish. Coral Reefs (2025). https://doi.org/10.1007/s00338-024-02613-6

doi : https://doi.org/10.1007/s00338-024-02613-6 DOI Link

Data and R markdown to replicate analyses in “Optimizing remote underwater video sampling to quantify relative abundance, richness, and corallivory rates of reef fish”

doi : https://doi.org/10.25910/agvq-3f82 DOI Link

global : fe9659f1-12d6-4acf-ab89-67acdd37efe5

Identifiers

global : a56ba272-b0d7-402d-94ce-3b289186d9df