GPS data of little owls

Advances in bio-logging technology for wildlife monitoring have expanded
our ability to study space use and behavior of many animal species at
increasingly detailed scales. However, such data can be challenging to
analyze due to autocorrelation of GPS positions. As a case study, we
investigated spatiotemporal movements and habitat selection in the little
owl (Athene noctua), a bird species that is declining in central Europe
and verges on extinction in Denmark. We equipped 6 Danish
food-supplemented little owls and 6 non-supplemented owls in the Czech
Republic with high-resolution GPS loggers that recorded one position per
minute. Nightly home ranges, measured as 95% kernel density estimates, of
Danish male owls were on average 62 ha (± 64 SD, larger than any found in
previous studies) compared to 2 ha (± 1) in females, and to 3 ± 1 ha
(males) versus 3 ± 5 ha (females) in the Czech Republic. Foraging Danish
male owls moved on average 4-fold further from their nest and at almost
double the distance per hour than Czech males. To create availability data
for the habitat selection analysis, we accounted for high spatiotemporal
autocorrelation of the GPS data by simulating correlated random walks with
the same autocorrelation structure as the actual little owl movement
trajectories. We found that habitat selection was similar between Danish
and Czech owls, with individuals selecting for short vegetation and areas
with high structural diversity. Our limited sample size did not allow us
to infer patterns on a population level, but nevertheless demonstrates how
high-resolution GPS data can help to identify critical habitat
requirements to better formulate conservation actions on a local scale.