Data from: Terrestrial spatial distribution and summer abundance of Antarctic fur seals (Arctocephalus gazella) near Palmer Station, Antarctica, from drone surveys
Data files
Jan 21, 2025 version files 13.51 MB
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drone_survey_dates_times.csv
3.44 KB
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exposed_land_mask.zip
469.40 KB
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fur_seal_locations_all_surveys.csv
188.02 KB
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fur_seal_locations_d72_d46.csv
60.93 KB
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maxent_prediction.zip
7.06 MB
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README.md
2.81 KB
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satellite_dem_mosaicked_masked.zip
5.60 MB
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surveyed_regions_land_mask.zip
118.01 KB
Abstract
The shifting climatic regime of maritime Antarctica is driving complex changes across trophic levels that manifest differentially across species and regions. Subantarctic pinnipeds have increased their seasonal attendance near Palmer Station, Anarctica, since earliest observations in the mid-1900s, and Antarctic fur seals (Arctocephalus gazella) now represent a significant but unstudied predator population in the area during the austral summer. To characterize the timing of abundance and fine-scale distribution of this seasonal attendance, we carried out regular drone surveys of terrestrial habitats near Palmer Station in the austral summer of 2020. Using repeat animal counts and photogrammetric data products, we modeled fur seal abundance at survey sites over the period of observation, we modeled habitat suitability based on fine-scale topographic habitat characteristics from satellite imagery, and we estimated abundance across terrestrial habitats near Palmer Station as a function of date and site suitability. This data repository contains the seal locations and a custom-prepared elevation satellite product used to model habitat suitability, as well as the predicted suitability from that model applied to all exposed land in the study region. Seal locations and survey metadata are provided in tabular form, whereas satellite elevation products and model predictions are provided in raster formats, and shapefiles are provided that delineate exposed land and surveyed regions, respectively. These data enable the replication or customized adaptation of our research methods, or other uses exploring terrestrial habitats near Palmer Station, Antarctica using our prepared elevation map.
README: Palmer Station, January–March 2020, Antarctic fur seal habitat modeling inputs and results
https://doi.org/10.5061/dryad.qv9s4mwp0
This dataset includes the inputs and results needed to reproduce or adapt an analysis of Antarctic fur seal habitat suitability near Palmer Station, Antarctica, based on drone surveys of Antarctic fur seals conducted in January–March 2020. The repository includes tabular summaries of (1) all drone surveys flown during that season (file "drone_survey_dates_times.csv"), (2) all fur seal locations identified from those surveys (file "fur_seal_locations_all_surveys.csv"), and (3) the subset of fur seal locations that we used to model habitat suitability (file "fur_seal_locations_d72_d46.csv"). The repository also includes a custom satellite digital elevation model (DEM) product of exposed land near Palmer Station, Antarctica (folder "satellite_dem_mosaicked_masked") that we used to generate a set of topographic variables to model habitat suitability, vector datasets that we used to subset that DEM (folders "exposed_land_mask" and "surveyed_regions_land_mask"), and a map of terrestrial habitat suitability near Palmer Station, predicted from a maximum entropy model across all exposed land in the study region (folder "maxent_prediction").
Description of the data and file structure
Drone survey metadata and Antarctic fur seal locations are provided in tabular form as CSV files. The DEM and MaxEnt prediction map are provided in folders containing TIF raster files with accompanying XML metadata files. Vector datasets are provided in folders containing shapefiles sets. All datasets and coordinates are in projected coordinate system UTM 20S, and elevation data are in vertical datum EGM96. These file formats can all be readily imported into a GIS software or spatial programming systems.
Sharing/Access information
Source drone data for Antarctic fur seal locations can be accesed at the following repository: https://doi.org/10.7924/r4sf2xs2w.
Elevation data was mosaicked from DEM products provided by the Polar Geospatial Center (https://www.pgc.umn.edu/ ) using Maxar imagery collected in 2012 and 2019.
Code/Software
We do not provide specific code to analyze these data, but our analyses used assorted tools from ArcGIS and SAGA (System for Automated Geoscientific Analyses) to convert elevation data into different topographic products, and we used the package "Dismo" in the R programming language to fit a MaxEnt model. MaxEnt modeling used the subsetted seal locations ("fur_seal_locations_d72_d46.csv") with raster layers of topographic products to yield the map of predicted habitat suitability ("maxent_prediction").
Methods
Antarctic fur seal locations were identified from a series of drone surveys conducted near Palmer Station in January-March, 2020 (data available at https://doi.org/10.7924/r4sf2xs2w). Satellite DEMs were obtained from the Polar Geospatial Center, which prepared the products using SETSM (Surface Extraction from TIN-Based Searchspace Minimization) from satellite imagery products provided by Maxar. The DEM in our repository is a composite of two scenes, collected in 2012 and 2019 (‘WV01_20121020_102001001D99B900_102001001EB08100_2m_lsf_v040306’ and 'WV03_20191119_104001005589A700_1040010054AE7700_2m_lsf_v040307’), which we mosaicked together to represent all exposed land in our study region. We then removed all areas covered by glaciers or ocean; the final product, which we include in this repository, was then used to generate a set of topographic variables that we used to model suitable habitats for Antarctic fur seals. We modeled habitat suitability using these topographic products with a subset of fur seal locations, included in the repository, with Maximum Entropy Modeling (MaxEnt), which yielded a map of habitat suitability values predicted across all exposed land in our study region, which we also include in the repository.