10.5061/DRYAD.PQ622
Morelle, Kevin
University of Liège
Bunnefeld, Nils
University of Stirling
Lejeune, Philippe
University of Liège
Oswald, Steve A.
Division of Science Penn State University Berks Campus Reading PA 19610 USA
Data from: From animal tracks to fine-scale movement modes: a
straightforward approach for identifying multiple, spatial movement
patterns
Dryad
dataset
2018
wild boar
2012
Sus scrofa
2018-03-31T00:00:00Z
2018-03-31T00:00:00Z
en
https://doi.org/10.1111/2041-210x.12787
1575133 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1. Thanks to developments in animal tracking technology, detailed data on
the movement tracks of individual animals are now attainable for many
species. However, straightforward methods to decompose individual tracks
into high-resolution, spatial modes are lacking but are essential to
understand what an animal is doing. 2. We developed an analytical approach
that combines separately-validated methods into a straightforward tool for
converting animal GPS tracks to short-range movement modes. Our three-step
analytical process comprises: (1) decomposing data into separate movement
segments using behavioural change point analysis; (2) defining candidate
movement modes and translating them into non-linear or linear equations
between net squared displacement (NSD) and time; and (3) fitting each
candidate equation to NSD segments and determining the best-fitting modes
using Concordance Criteria, Akaike’s Information Criteria and other
fine-scale segment characteristics. We illustrate our approach for three
sub-adults, male wild boar Sus scrofa tracked at 15 min intervals over 4
months using GPS collars. We defined five candidate movement modes based
on previously published studies of short-term movements: encamped,
ranging, round trips (complete and partial), and wandering. 3. Our
approach successfully classified over 80% of the tracks into these
movement modes lasting between 5 and 54 hours and covering between 300 m
to 20 km. Repeated analyses of GPS data resampled at different rates
indicated that one positional fix every 3-4 h was sufficient for
>70% classification success. Classified modes were consistent with
published observations of wild boar movement, further validating our
method. 4. The proposed approach advances the status quo by permitting
classification into multiple movement modes (where these are adequately
discernable from spatial fixes) facilitating analyses at high temporal and
spatial resolutions, and is straightforward, largely objective, and
without restrictive assumptions, necessary parameterizations or visual
interpretation. Thus, it should capture the complexity and variability of
tracked animal movement mode for a variety of taxa across a wide range of
spatial and temporal scales.
SubAdults_BoarsThe csv file contains the GPS tracks of three
("gilbert", "leopold" and "lactose")
sub-adult males wild boar (Sus scrofa). The three individuals were tracked
in agroecosystems of Southern Belgium in the framework of the PhD Thesis
of Kevin Morelle.
Belgium