Integrated hydroacoustic data from the unmanned surface vehicle USV Sailbuoy, from 2019-2023. Including environmental variable estimates from Copernicus Marine Services Information Open data Service https://www.copernicus.eu
More information in ReadMe_datastatement and publication: Autonomous data sampling for high-resolution spatiotemporal fish biomass estimates. R Code available in Github: https://github.com/Astidac/Autonomous-data-sampling-for-high-resolution-spatiotemporal-fish-biomass-estimates.git (the repo with latest commit 856ad58 added to documentation files as 2024-517_code.zip).

Preprint of paper available:
Carlsen, Astrid Anette and Casini, Michele and Masnadi, Francesco and Olsson, Olof and Hejdstöm, Aron and Hentati-Sundberg, Jonas, Autonomous Data Sampling for High-Resolution Spatiotemporal Fish Biomass Estimates. Available at SSRN: https://ssrn.com/abstract=4808045 or http://dx.doi.org/10.2139/ssrn.4808045

Dimensions of data files:
xdat.21-23.csv: 25319 rows ✕ 17 columns
xdat.Agg.csv: 1899 rows ✕ 24 columns
xdat.Full.csv: 41292 rows ✕ 14 columns

Data contains personal data

Language

English

Method and outcome

Time period(s) investigated

2019-04-21 – 2023-08-02

Data format / data structure

Numeric

Data collection

Mode of collection: Non-participant field observation
Description of the mode of collection: Hydroacoustic (echosounder) data collected by wind/soral driven unmanned surface vehicle.
Time period(s) for data collection: 2019-04-21 – 2023-08-02
Data collector: Swedish University of Agricultural Sciences
Instrument: SIMRAD EK80 wideband - See paper: Carlsen, Astrid Anette and Casini, Michele and Masnadi, Francesco and Olsson, Olof and Hejdstöm, Aron and Hentati-Sundberg, Jonas, Autonomous Data Sampling for High-Resolution Spatiotemporal Fish Biomass Estimates. Available at SSRN: https://ssrn.com/abstract=4808045 or http://dx.doi.org/10.2139/ssrn.4808045

Geographic coverage

Geographic spread

Geographic location: Gotland County, Baltic Sea

Geographic description: The study was performed in the Central Baltic Sea (International Council for the Exploration of the Sea, ICES, subdivision 27; statistical squares 42G7-44G7), off the island of Stora Karlsö, Sweden

Administrative information

Responsible department/unit

Department of Aquatic Resources

Contributor(s)

Jonas Hentati-Sundberg - Swedish University of Agricultural Sciences, Department of Aquatic Resources

Funding 1

Funding agency: Marianne and Marcus Wallenberg Foundation
Funding agency's reference number: 2018–0093
Funding information: For PhD- position

Funding 2

Funding agency: Swedish Research Council
Funding agency's reference number: 2021–03892
Funding information: JHS was supported by Vetenskapsrådet (grant number 2021–03892)

Funding 3

Funding agency: Swedish Research Council for Environment Agricultural Sciences and Spatial Planning
Funding agency's reference number: 2021–02639
Funding information: Formas (grant number 2021–02639).

Topic and keywords

Research area

Environmental sciences (Standard för svensk indelning av forskningsämnen 2011)

Bioinformatics and systems biology (Standard för svensk indelning av forskningsämnen 2011)

Behavioural sciences biology (Standard för svensk indelning av forskningsämnen 2011)

Fish and wildlife management (Standard för svensk indelning av forskningsämnen 2011)

Biota (INSPIRE topic categories)

Oceans (INSPIRE topic categories)

Environment (INSPIRE topic categories)

Keywords

Species distribution, Statistical units, Hydroacoustics, Sdm, Sdmtmb, Usv, Nasc, Biomass, Fish, Hydroacoustic integration, Sailbuoy, Sailor

Publications

Carlsen, Astrid Anette and Casini, Michele and Masnadi, Francesco and Olsson, Olof and Hejdstöm, Aron and Hentati-Sundberg, Jonas, Autonomous Data Sampling for High-Resolution Spatiotemporal Fish Biomass Estimates. Available at SSRN: https://ssrn.com/abstract=4808045 or http://dx.doi.org/10.2139/ssrn.4808045
DOI: https://doi.org/10.1016/j.ecoinf.2024.102852