Chisholm, S;
Stein, AB;
Jordan, NR;
Hubel, TM;
Shawe-Taylor, J;
Fearn, T;
McNutt, JW;
... Hailes, S; + view all
(2019)
Parsimonious test of dynamic interaction.
Ecology and Evolution
, 9
(4)
pp. 1654-1664.
10.1002/ece3.4805.
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Abstract
In recent years, there have been significant advances in the technology used to col‐ lect data on the movement and activity patterns of humans and animals. GPS units, which form the primary source of location data, have become cheaper, more accu‐ rate, lighter and less power‐hungry, and their accuracy has been further improved with the addition of inertial measurement units. The consequence is a glut of geospa‐ tial time series data, recorded at rates that range from one position fix every several hours (to maximize system lifetime) to ten fixes per second (in high dynamic situa‐ tions). Since data of this quality and volume have only recently become available, the analytical methods to extract behavioral information from raw position data are at an early stage of development. An instance of this lies in the analysis of animal move‐ ment patterns. When investigating solitary animals, the timing and location of in‐ stances of avoidance and association are important behavioral markers. In this paper, a novel analytical method to detect avoidance and association between individuals is proposed; unlike existing methods, assumptions about the shape of the territories or the nature of individual movement are not needed. Simulations demonstrate that false positives (type I error) are rare (1%–3%), which means that the test rarely sug‐ gests that there is an association if there is none.
| Type: | Article |
|---|---|
| Title: | Parsimonious test of dynamic interaction |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/ece3.4805 |
| Publisher version: | https://doi.org/10.1002/ece3.4805 |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | African wild dogs, analysis, association, avoidance theory, ecology, GPS, leopards, permutations, statistics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10069651 |
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