Cleasby, IR, Wakefield, ED, Morrissey, BJ et al. (4 more authors) (2019) Using time-series similarity measures to compare animal movement trajectories in ecology. Behavioral Ecology and Sociobiology, 73. ARTN: 151. ISSN 0340-5443
Abstract
Identifying and understanding patterns in movement data are amongst the principal aims of movement ecology. By quantifying the similarity of movement trajectories, inferences can be made about diverse processes, ranging from individual specialisation to the ontogeny of foraging strategies. Movement analysis is not unique to ecology however, and methods for estimating the similarity of movement trajectories have been developed in other fields but are currently under-utilised by ecologists. Here, we introduce five commonly used measures of trajectory similarity: dynamic time warping (DTW), longest common subsequence (LCSS), edit distance for real sequences (EDR), Fréchet distance and nearest neighbour distance (NND), of which only NND is routinely used by ecologists. We investigate the performance of each of these measures by simulating movement trajectories using an Ornstein-Uhlenbeck (OU) model in which we varied the following parameters: (1) the point of attraction, (2) the strength of attraction to this point and (3) the noise or volatility added to the movement process in order to determine which measures were most responsive to such changes. In addition, we demonstrate how these measures can be applied using movement trajectories of breeding northern gannets (Morus bassanus) by performing trajectory clustering on a large ecological dataset. Simulations showed that DTW and Fréchet distance were most responsive to changes in movement parameters and were able to distinguish between all the different parameter combinations we trialled. In contrast, NND was the least sensitive measure trialled. When applied to our gannet dataset, the five similarity measures were highly correlated despite differences in their underlying calculation. Clustering of trajectories within and across individuals allowed us to easily visualise and compare patterns of space use over time across a large dataset. Trajectory clusters reflected the bearing on which birds departed the colony and highlighted the use of well-known bathymetric features. As both the volume of movement data and the need to quantify similarity amongst animal trajectories grow, the measures described here and the bridge they provide to other fields of research will become increasingly useful in ecology.
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Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The authors 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Funding Information: | Funder Grant number NERC NE/H007466/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Oct 2019 13:05 |
Last Modified: | 25 Apr 2022 19:26 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s00265-019-2761-1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152280 |
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