Eight-fjords shallow underwater videos
Citation
Green L, Svensson L, Burman E, Germishuys J, Anton V, Obst M (2024). Eight-fjords shallow underwater videos. Version 1.2. Wildlife.ai. Occurrence dataset https://doi.org/10.15468/8m29p6 accessed via GBIF.org on 2024-12-14.Description
Dataset of species records extracted via Yolov8 model from 1 hour-recordings using baited remote underwater video at a depth of between 0.6-3.2 meters in the coastal zone of the 8-fjords area at the Swedish west-coast.Sampling Description
Study Extent
At each site, an average of 4 recordings were made, with each camera recording video for 1 hour, resulting in a total recording time of 4 hours per site. Records in this data are per video. Each video is fitted with a unique identifier.Sampling
Sampling with video cameras is a relatively common method for investigating flora and fauna in marine environments. When it comes to fish census, baited camera systems are often used (abbreviated as BRUV after the English "Baited Remote Underwater Video"), which can be placed on the seabed or freely suspended in the water column with the help of a buoy on the surface (see e.g., Sherman et al., 2020, and Cambra et al., 2021). An advantage of these systems compared to, for example, ROVs (remotely operated underwater vehicles) or drop-video (a type of "camera sled" dragged across the seabed) is that they are stationary and do not scare away fish through movements and sounds. However, this means that the camera covers a smaller area of water, and therefore bait is used to attract the fish nearby to move in front of the camera. The bait used is often scented food such as fish scraps and shrimp. For the detection of cryptobenthic fish (small, bottom-dwelling species that often hide in crevices or among vegetation), the BRUV method is still in the developmental stage. Because such small fish (especially bullheads) can be difficult to distinguish and identify on video, it is valuable to design camera systems that visualize their characteristics as effectively as possible. In this study, a system with neutral-colored "background boards" has been used, which the fish need to swim in front of to reach the bait. This way, characteristics such as color, pattern, and fin shape are visualized, improving the possibility of species identification. Video cameras baited with frozen shrimp (4 per camera, approximately 45 grams each in wet weight) were placed on the seabed either directly from a pier/dock when possible, or with the help of snorkelling. Each camera system was placed at a minimum distance of 30 meters from each other to avoid fish moving between the cameras during filming. The depth at which the cameras were placed varied between 0.6 – 3.2 meters. To control for lighting conditions, the video rig was always oriented so that the camera filmed northward (and thus received ample light against the background).Method steps
- The team followed the methodology described in the SUBSIM software to analyse and publish the occurrences
Taxonomic Coverages
All fish were identified to species or family level, Brachyuran crabs were identified to species level.
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Carcinus maenascommon name: European Green Crab rank: species
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Ctenolabrus rupestriscommon name: Goldsinny Wrasse rank: species
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Gobius nigercommon name: Black Goby rank: species
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Neogobius melanostomuscommon name: Round Goby rank: species
Geographic Coverages
These records cover shallow bays in Sweden's first test-bed for marine ecosystem-based management: The 8-fjords+ area. This area is a freshwater-influenced fjord system containing multiple Natura-2000 sites and a range of habitats including shallow and deep soft and hard bottoms. Records in the dataset are from 3-1 meters in depth, mainly centred around small marinas.
Bibliographic Citations
Contacts
Leon Greenoriginator
position: Researcher
University of Gothenburg
email: leon.green@bioenv.gu.se
userId: https://orcid.org/0000-0002-3328-3655
Linnéa Svensson
originator
position: Research assistant
University of Gothenburg
email: linnea.svensson@bioenv.gu.se
Emil Burman
originator
position: Project Assistant
University of Gothenburg
email: burman.emil4@gmail.com
userId: https://www.linkedin.com/profile/view?id=emil-burman-480139114
Jannes Germishuys
originator
position: Data Scientist
Combine
userId: https://www.linkedin.com/profile/view?id=jannesg
Victor Anton
metadata author
position: GM
WILDLIFE.AI
NZ
email: victor@wildlife.ai
userId: https://orcid.org/0000-0002-1471-5571
Leon Green
metadata author
position: Researcher
University of Gothenburg
email: leon.green@bioenv.gu.se
userId: https://orcid.org/0000-0002-3328-3655
Matthias Obst
metadata author
position: Researcher
University of Gothenburg
email: matthias.obst@marine.gu.se
homepage: https://www.gu.se/om-universitetet/hitta-person/matthiasobst
userId: https://orcid.org/0000-0003-0264-9631
Victor Anton
publisher
position: GM
Wildlife.ai
NZ
email: victor@wildlife.ai
userId: https://orcid.org/0000-0002-1471-5571
Leon Green
principal investigator
position: Researcher
University of Gothenburg
email: leon.green@bioenv.gu.se
userId: https://orcid.org/0000-0002-3328-3655
Matthias Obst
content provider
position: Researcher
University of Gothenburg
email: matthias.obst@marine.gu.se
homepage: https://www.gu.se/om-universitetet/hitta-person/matthiasobst
userId: https://orcid.org/0000-0003-0264-9631
Jannes Germishuys
programmer
position: Data Scientist
Combine
userId: https://www.linkedin.com/profile/view?id=jannesg
Victor Anton
administrative point of contact
position: GM
WILDLIFE.AI
NZ
email: victor@wildlife.ai
userId: https://orcid.org/0000-0002-1471-5571
Leon Green
administrative point of contact
position: Researcher
University of Gothenburg
email: leon.green@bioenv.gu.se
userId: https://orcid.org/0000-0002-3328-3655
Matthias Obst
administrative point of contact
position: Researcher
University of Gothenburg
email: matthias.obst@marine.gu.se
homepage: https://www.gu.se/om-universitetet/hitta-person/matthiasobst
userId: https://orcid.org/0000-0003-0264-9631