Data from: Influence of device accuracy and choice of algorithm for species distribution modelling of seabirds: a case study using black-browed albatrosses

Species distribution models (SDM) based on tracking data from different
devices are used increasingly to explain and predict seabird
distributions. However, different tracking methods provide different data
resolutions, ranging from < 10m to >100km. To better
understand the implications of this variation, we modeled the potential
distribution of black-browed albatrosses Thalassarche melanophris from
South Georgia that were simultaneously equipped with a Platform Terminal
Transmitter (PTT) (high resolution) and a Global Location Sensor (GLS)
logger (coarse resolution), and measured the overlap of the respective
potential distribution for a total of nine different SDM algorithms. We
found slightly better model fits for the PTT than for GLS data (AUC values
0.958±0.048 vs. 0.95±0.05) across all algorithms. The overlaps of the
predicted distributions were higher between device types for the same
algorithm, than among algorithms for either device type. Uncertainty
arising from coarse-resolution location data is therefore lower than that
associated with the modeling technique. Consequently, the choice of an
appropriate algorithm appears to be more important than device type when
applying SDMs to seabird tracking data. Despite their low accuracy, GLS
data appear to be effective for analyzing the habitat preferences and
distribution patterns of pelagic species.