DOI: 10.14466/CefasDataHub.115

Fish observation and length data derived from stereo-baited remote underwater videos collected around Saint Lucia in 2019

Description

Analysed stereo-Baited Remote Underwater Videos (BRUVs) from the 2019 survey in the north west of St. Lucia. In total 87 1-hour BRUV stations were successfully deployed to a maximum depth of 100m. Video classification assessed fish MaxN (number of visible individuals in a single frame) by species and measured all fish lengths at MaxN. This data holding contains: The exported files from Eventmeasure for all 87 stations (3DPoints, ImagePtPair, Info, Lengths, MovieSeq, Period, Points and Source); Metadata for each deployment as a csv file (including station summary statistic of: Number of taxa, total MaxN, diversity metrics, biomass and cluster groups; and a GIS shapefile containing the same summary information. Data were collected as part of the Commonwealth Marine Economies Programme in collaboration with the St. Lucia Department of Fisheries. The survey was conducted in accordance with the standardised field and video annotation guide (DOI: 10.1111/2041-210X.13470). Videos were classified by either of two analysts with 10% duplicated for quality control and to ensure consistency. Errors or issues raised were addressed for all stations. Footage were analysed within the SeaGIS Eventmeasure software, classifying all fish species based on MaxN (number of visible individuals in a single frame), and measuring all individual fish at MaxN.

Contributors

Mitchell, Peter / Bolam, Stefan G. / Close, Hayden / Garcia, Clement / Monk, Jacquomo / Alliji, Khatija

Subject

Fish abundance in water bodies / Biodiversity / Biodiversity indices / Fish biomass in water bodies / Fish / Biota abundance, biomass and diversity

Start Date

01/02/2019

End Date

10/02/2019

Year Published

2020

Version

1

Citation

Mitchell et al (2020). Fish observation and length data derived from stereo-baited remote underwater videos collected around Saint Lucia in 2019. Cefas, UK. V1. doi: https://doi.org/10.14466/CefasDataHub.115

DOI

10.14466/CefasDataHub.115