Atlantic bluefin tuna (Thunnus thynnus) presence and pseudoabsence locations with 13 remotely sensed environmental variables
Data files
Jul 09, 2024 version files 104.57 MB
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ABFT_dataset.csv
104.56 MB
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README.md
2.05 KB
Abstract
Atlantic bluefin tuna (Thunnus thynnus; ABFT) are a highly important fisheries species of economic and conservation concern. Understanding their distributions, particularly under climate change is imperative for effective management. Here we assemble a dataset of 4,216 true presence locations for ABFT tagged with pop-up satellite archival tags off the west coast of Ireland between 2016-2021 and 392,009 pseudoabsence locations simulated by a series of correlated random walk modelling. The dataset also contains remotely sensed data at each location for 13 environmental variables including: bathymetry (m), rugosity (m), absolute dynamic topography (m) and it’s spatial standard deviation, log surface chlorophyll-a (Log mg m-3), mixed layer depth (m), mean primary productivity over the top 200m of the water column (mg m-3), mean oxygen over the top 200m of the water column (mmol m-3), sea level height anomaly (m) and it’s standard deviation, sea surface temperature (°C) and it's spatial standard deviation, and log eddy kinetic energy (Log m2 s-2).
https://doi.org/10.5061/dryad.qfttdz0q7
The dataset contains true presence and modelled pseudoabsence location data for Atlantic bluefin tuna (Thunnus thynnus; ABFT). At each location data for 13 remotely sensed environmental variables is provided, including: bathymetry (m), rugosity (m), absolute dynamic topography (m) and it’s spatial standard deviation, log surface chlorophyll-a (mg m-3), mixed layer depth (m), mean primary productivity over the top 200m of the water column (mg m-3), mean oxygen over the top 200m of the water column (mmol m-3), sea level anomaly (m) and it’s standard deviation, sea surface temperature (°C) and it’s spatial standard deviation, and log eddy kinetic energy (m2 s-2).
Description of the data and file structure
The data is provided as a .csv file and can easily be read into R. The data may be used to produce further species distribution models.
The .csv file has 18 columns:
- TagID - identification of the individual pop-up satellite archival tag
- Longitude
- Latitude
- Presence - ‘0’ represents modelled psuedoabsence data and ‘1’ represents true presence data
- Date
- bathy - Bathymetry (m)
- bathy_sd - Rugosity (m)
- adt - Absolute dynamic topography (m)
- adt_sd - Absolute dynamic topography standard deviation (m)
- l.chl - Log surface chlorophyll-a (mg m-3)
- mld - Mixed layer depth (m)
- PPupper200m - mean primary productivity over the top 200m of the water column (mg m-3)
- sla - Sea level anomaly (m)
- sla_sd - Sea level anomaly standard deviation (m)
- eke - Log eddy kinetic energy (m2 s-2)
- oxy200m - Mean oxygen over the top 200m of the water column (mmol m-3)
- sst - Sea surface temperature (°C)
- sst_sd - Sea surface temperature standard deviation (°C)
NAs indicate gaps in the data frame whereby remotely sensed environmental data was unavailable.