Using time-series similarity measures to compare animal movement trajectories in ecology

Cleasby, I. R., Wakefield, E. D. , Morrissey, B. J., Bodey, T. W., Votier, S. C., Bearhop, S. and Hamer, K. C. (2019) Using time-series similarity measures to compare animal movement trajectories in ecology. Behavioral Ecology and Sociobiology, 73(11), 151. (doi: 10.1007/s00265-019-2761-1)

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.

• Item Type: Articles
• Additional Information: Gannet data was collected as part of a Natural Environment Research Council (Standard Grant NE/H007466/1) to KCH, SB, and SCV .
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wakefield, Dr Ewan
• Authors: Cleasby, I. R., Wakefield, E. D., Morrissey, B. J., Bodey, T. W., Votier, S. C., Bearhop, S., and Hamer, K. C.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: Behavioral Ecology and Sociobiology
• Publisher: Springer
• ISSN: 0340-5443
• ISSN (Online): 1432-0762
• Published Online: 21 November 2019
• Copyright Holders: Copyright © The Authors 2019
• First Published: First published in Behavioral Ecology and Sociobiology 73(11): 151
• Publisher Policy: Reproduced under a Creative Commons license

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
171561		Seabirds and wind - the consequences of extreme prey taxis in a changing climate	Ewan Wakefield	Natural Environment Research Council (NERC)	NE/M017990/1	Institute of Biodiversity, Animal Health and Comparative Medicine