Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns

Increased availability of high-resolution movement data has led to the development of numerous methods for studying changes in animal movement behavior. Path segmentation methods provide basics for detecting movement changes and the behavioral mechanisms driving them. However, available path segmentation methods differ vastly with respect to underlying statistical assumptions and output produced. Consequently, it is currently difficult for researchers new to path segmentation to gain an overview of the different methods, and choose one that is appropriate for their data and research questions.Here, we provide an overview of different methods for segmenting movement paths according to potential changes in underlying behavior. To structure our overview, we outline three broad types of research questions that are commonly addressed through path segmentation: 1) the quantitative description of movement patterns, 2) the detection of significant change-points, and 3) the identification of underlying processes or ‘hidden states’. We discuss advantages and limitations of different approaches for addressing these research questions using path-level movement data, and present general guidelines for choosing methods based on data characteristics and questions. Our overview illustrates the large diversity of available path segmentation approaches, highlights the need for studies that compare the utility of different methods, and identifies opportunities for future developments in path-level data analysis.

[1]  Robert Weibel,et al.  Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement , 2014, J. Spatial Inf. Sci..

[2]  Tabitha A. Graves,et al.  Understanding the Causes of Missed Global Positioning System Telemetry Fixes , 2006 .

[3]  Nova Scotia.  The VFractal: a new estimator for fractal dimension of animal movement paths , 1996 .

[4]  Eliezer Gurarie,et al.  A novel method for identifying behavioural changes in animal movement data. , 2009, Ecology letters.

[5]  C. Calenge.  Analysis of Animal Movements in R : the adehabitatLT Package , 2011 .

[6]  Hawthorne L. Beyer,et al.  The pitfalls of ignoring behaviour when quantifying habitat selection , 2014 .

[7]  Ian D. Jonsen,et al.  ROBUST STATE-SPACE MODELING OF ANIMAL MOVEMENT DATA , 2005 .

[8]  Tak-Chung Fu,et al.  A review on time series data mining , 2011, Eng. Appl. Artif. Intell..

[9]  Ian D. Jonsen,et al.  State-space methods for more completely capturing behavioral dynamics from animal tracks , 2012 .

[10]  Douglas Steinley,et al.  K-means clustering: a half-century synthesis. , 2006, The British journal of mathematical and statistical psychology.

[11]  Chris J. Johnson,et al.  Movement parameters of ungulates and scale‐specific responses to the environment , 2002 .

[12]  D. Brillinger,et al.  An exploratory data analysis (EDA) of the paths of moving animals , 2004 .

[13]  Peter Leimgruber,et al.  Non‐Markovian maximum likelihood estimation of autocorrelated movement processes , 2014 .

[14]  Ian D. Jonsen,et al.  META‐ANALYSIS OF ANIMAL MOVEMENT USING STATE‐SPACE MODELS , 2003 .

[15]  Daniel P. Costa,et al.  Fractal landscape method: an alternative approach to measuring area-restricted searching behavior , 2007, Journal of Experimental Biology.

[16]  Dean P. Anderson,et al.  State-space models link elk movement patterns to landscape characteristics in Yellowstone National Park , 2007 .

[17]  Daniel P. Costa,et al.  Accuracy of ARGOS Locations of Pinnipeds at-Sea Estimated Using Fastloc GPS , 2010, PloS one.

[18]  E. V. van Loon,et al.  From Sensor Data to Animal Behaviour: An Oystercatcher Example , 2012, PloS one.

[19]  Robert Weibel,et al.  Towards a taxonomy of movement patterns , 2008, Inf. Vis..

[20]  Mark S Boyce,et al.  Habitat selection during ungulate dispersal and exploratory movement at broad and fine scale with implications for conservation management , 2014, Movement Ecology.

[21]  R. Kays,et al.  Animal behavior, cost-based corridor models, and real corridors , 2013, Landscape Ecology.

[22]  Floris M. van Beest,et al.  Behavioural Responses to Thermal Conditions Affect Seasonal Mass Change in a Heat-Sensitive Northern Ungulate , 2013, PloS one.

[23]  Zhihai He,et al.  A new 'view' of ecology and conservation through animal-borne video systems. , 2007, Trends in ecology & evolution.

[24]  Leah Edelstein-Keshet,et al.  Inferring resource distributions from Atlantic bluefin tuna movements: an analysis based on net displacement and length of track. , 2007, Journal of theoretical biology.

[25]  S. Benhamou.  How to reliably estimate the tortuosity of an animal's path: straightness, sinuosity, or fractal dimension? , 2004, Journal of theoretical biology.

[26]  E. Batschelet.  Circular statistics in biology , 1981 .

[27]  M. W. Jones,et al.  Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning , 2015, Movement Ecology.

[28]  Robin Freeman,et al.  Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviour , 2013, Journal of The Royal Society Interface.

[29]  Brandon L Southall,et al.  A multivariate mixed hidden Markov model to analyze blue whale diving behaviour during controlled sound exposures , 2016, 1602.06570.

[30]  Stephen P. Ellner,et al.  SCALING UP ANIMAL MOVEMENTS IN HETEROGENEOUS LANDSCAPES: THE IMPORTANCE OF BEHAVIOR , 2002 .

[31]  N. Bunnefeld,et al.  A model-driven approach to quantify migration patterns: individual, regional and yearly differences. , 2011, The Journal of animal ecology.

[32]  D. Haydon,et al.  Multiple movement modes by large herbivores at multiple spatiotemporal scales , 2008, Proceedings of the National Academy of Sciences.

[33]  Roland Langrock,et al.  moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models , 2016 .

[34]  Peter Turchin,et al.  Fractal Analyses of Animal Movement: A Critique , 1996 .

[35]  Roland Langrock,et al.  Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions. , 2012, Ecology.

[36]  David Ganskopp,et al.  GPS Collar Sampling Frequency: Effects on Measures of Resource Use , 2008 .

[37]  Roland Langrock,et al.  Using mixed hidden Markov models to examine behavioral states in a cooperatively breeding bird , 2015 .

[38]  Bettina Speckmann,et al.  Efficient detection of motion patterns in spatio-temporal data sets , 2004, GIS '04.

[39]  Len Thomas,et al.  A path reconstruction method integrating dead-reckoning and position fixes applied to humpback whales , 2015, Movement ecology.

[40]  F. Cagnacci,et al.  Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  Yang Liu,et al.  Bias correction and uncertainty characterization of Dead-Reckoned paths of marine mammals , 2015, Animal Biotelemetry.

[42]  S. Cushman.  Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis [chapter 7] , 2010 .

[43]  Lucas N Joppa,et al.  Understanding movement data and movement processes: current and emerging directions. , 2008, Ecology letters.

[44]  Torkild Tveraa,et al.  USING FIRST‐PASSAGE TIME IN THE ANALYSIS OF AREA‐RESTRICTED SEARCH AND HABITAT SELECTION , 2003 .

[45]  Sabine Timpf,et al.  Advances in Spatial Data Handling: Geospatial Dynamics, Geosimulation and Exploratory Visualization , 2012 .

[46]  Paul G. Blackwell,et al.  Bayesian inference for Markov processes with diffusion and discrete components , 2003 .

[47]  Kathleen M. O’Reilly,et al.  Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor) , 2015, PloS one.

[48]  C. Gaucherel,et al.  Wavelet analysis to detect regime shifts in animal movement , 2011 .

[49]  R. Sibly,et al.  Splitting behaviour into bouts , 1990, Animal Behaviour.

[50]  A. Saalfeld.  Topologically Consistent Line Simplification with the Douglas-Peucker Algorithm , 1999 .

[51]  Stephen Roberts,et al.  Positional entropy during pigeon homing I: application of Bayesian latent state modelling. , 2004, Journal of theoretical biology.

[52]  Toby A Patterson,et al.  Classifying movement behaviour in relation to environmental conditions using hidden Markov models. , 2009, The Journal of animal ecology.

[53]  Claire M Postlethwaite,et al.  A new multi-scale measure for analysing animal movement data. , 2013, Journal of theoretical biology.

[54]  Ian D Jonsen,et al.  Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles. , 2006, The Journal of animal ecology.

[55]  John R Fieberg,et al.  Could you please phrase “home range” as a question? , 2012 .

[56]  Roland Kays,et al.  Observing the unwatchable through acceleration logging of animal behavior , 2013, Animal Biotelemetry.

[57]  Andrew K. Skidmore,et al.  Change detection in animal movement using discrete wavelet analysis , 2014, Ecol. Informatics.

[58]  A. Kölzsch,et al.  Segmenting Trajectories by Movement States , 2013 .

[59]  Claire M. Postlethwaite,et al.  Effects of Temporal Resolution on an Inferential Model of Animal Movement , 2013, PloS one.

[60]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[61]  Eliezer Gurarie,et al.  Characteristic Spatial and Temporal Scales Unify Models of Animal Movement , 2011, The American Naturalist.

[62]  M. Hooten,et al.  Statistical Agent-Based Models for Discrete Spatio-Temporal Systems , 2010 .

[63]  H. Lange.  Time-series Analysis in Ecology , 2006 .

[64]  Manuela Royer-Carenzi,et al.  The exploratory analysis of autocorrelation in animal-movement studies , 2010, Ecological Research.

[65]  Trisalyn A. Nelson,et al.  A review of quantitative methods for movement data , 2013, Int. J. Geogr. Inf. Sci..

[66]  S. Benhamou,et al.  Spatial analysis of animals' movements using a correlated random walk model* , 1988 .

[67]  Corey J A Bradshaw,et al.  Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data. , 2007, Ecological applications : a publication of the Ecological Society of America.

[68]  Richard W. Brill,et al.  Horizontal movements of bigeye tuna (Thunnus obesus) near Hawaii determined by Kalman filter analysis of archival tagging data , 2003 .

[69]  J. Hopcraft,et al.  Competition, predation, and migration: Individual choice patterns of Serengeti migrants captured by hierarchical models , 2014 .

[70]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[71]  R. Davis,et al.  Response of African Elephants (Loxodonta africana) to Seasonal Changes in Rainfall , 2014, PloS one.

[72]  R. Byrne,et al.  Change point analysis of travel routes reveals novel insights into foraging strategies and cognitive maps of wild baboons , 2014, American journal of primatology.

[73]  Miles L. Logsdon,et al.  Fractal analysis of narwhal space use patterns. , 2004, Zoology.

[74]  Ian D. Jonsen,et al.  Identifying leatherback turtle foraging behaviour from satellite telemetry using a switching state-space model , 2007 .

[75]  Edward A. Codling,et al.  Random walk models in biology , 2008, Journal of The Royal Society Interface.

[76]  E. Gese,et al.  Beyond use versus availability: behaviour-explicit resource selection , 2012 .

[77]  Jiawei Han,et al.  The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data , 2013, Movement Ecology.

[78]  Henrik Madsen,et al.  Estimating animal behavior and residency from movement data , 2011 .

[79]  Simon Benhamou,et al.  Animal movements in heterogeneous landscapes: identifying profitable places and homogeneous movement bouts. , 2008, Ecology.

[80]  Michael Dowd,et al.  Estimating behavioral parameters in animal movement models using a state-augmented particle filter. , 2011, Ecology.

[81]  Vilis O Nams,et al.  Combining animal movements and behavioural data to detect behavioural states. , 2014, Ecology letters.

[82]  Fiona K. A. Schmiegelow,et al.  Movement pathways and habitat selection by woodland caribou during spring migration , 2005 .

[83]  Roland Langrock,et al.  Statistical modelling of animal movement: a myopic review and a discussion of good practice , 2016, 1603.07511.

[84]  Johannes Ledolter,et al.  State-Space Analysis of Wildlife Telemetry Data , 1991 .

[85]  Len Thomas,et al.  Author ' s personal copy State – space models of individual animal movement , 2008 .

[86]  R. Langrock,et al.  Hidden Markov models with arbitrary state dwell-time distributions , 2011, Comput. Stat. Data Anal..

[87]  Michael E. Byrne,et al.  Using first-passage time to link behaviour and habitat in foraging paths of a terrestrial predator, the racoon , 2012, Animal Behaviour.

[88]  Jane Hunter,et al.  An open Web-based system for the analysis and sharing of animal tracking data , 2015, Animal Biotelemetry.

[89]  Kevin McGarigal,et al.  Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: pumas as a case study , 2014, Landscape Ecology.

[90]  R. W. Byrne,et al.  How did they get here from there? Detecting changes of direction in terrestrial ranging , 2009, Animal Behaviour.

[91]  Paul R Moorcroft,et al.  Mechanistic home range models and resource selection analysis: a reconciliation and unification. , 2006, Ecology.

[92]  Keith Harris,et al.  Flexible continuous-time modelling for heterogeneous animal movement , 2013 .

[93]  Markus Neteler,et al.  Wildlife tracking data management: a new vision , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[94]  Leo Polansky,et al.  Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses , 2008, Proceedings of the National Academy of Sciences.

[95]  Marie-Josée Fortin,et al.  The effectiveness of Bayesian state‐space models for estimating behavioural states from movement paths , 2013 .

[96]  Eliezer Gurarie,et al.  What is the animal doing? Tools for exploring behavioural structure in animal movements. , 2016, The Journal of animal ecology.

[97]  Roland Langrock,et al.  Nonparametric inference in hidden Markov models using P‐splines , 2013, Biometrics.

[98]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[99]  Philippe Gaspar,et al.  A state-space model to derive bluefin tuna movement and habitat from archival tags , 2005 .

[100]  N. Sapir,et al.  Commuting fruit bats beneficially modulate their flight in relation to wind , 2014, Proceedings of the Royal Society B: Biological Sciences.

[101]  Wayne M. Getz,et al.  A framework for generating and analyzing movement paths on ecological landscapes , 2008, Proceedings of the National Academy of Sciences.

[102]  Amy Hurford,et al.  GPS Measurement Error Gives Rise to Spurious 180° Turning Angles and Strong Directional Biases in Animal Movement Data , 2009, PloS one.

[103]  J. M. Fryxell,et al.  Foraging theory upscaled: the behavioural ecology of herbivore movement , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[104]  Alastair Franke,et al.  Analysis of movements and behavior of caribou (Rangifer tarandus) using hidden Markov models , 2004 .

[105]  Ian D. Jonsen,et al.  Hierarchical State-Space Estimation of Leatherback Turtle Navigation Ability , 2010, PloS one.

[106]  M. Hindell,et al.  Using GPS data to evaluate the accuracy of state-space methods for correction of Argos satellite telemetry error. , 2010, Ecology.

[107]  P. Turchin.  Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants , 1998 .

[108]  P. Fearnhead,et al.  Optimal detection of changepoints with a linear computational cost , 2011, 1101.1438.

[109]  Paul G. Blackwell,et al.  Exact Bayesian inference for animal movement in continuous time , 2016 .

[110]  Sophie Bestley,et al.  Predicting feeding success in a migratory predator: integrating telemetry, environment, and modeling techniques. , 2010, Ecology.

[111]  Andrew D. Lowther,et al.  The Argos-CLS Kalman Filter: Error Structures and State-Space Modelling Relative to Fastloc GPS Data , 2015, PloS one.

[112]  Mark S Boyce,et al.  Applications of step-selection functions in ecology and conservation , 2014, Movement Ecology.

[113]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[114]  Bettina Speckmann,et al.  Analysis and visualisation of movement: an interdisciplinary review , 2015, Movement Ecology.

[115]  Devin S Johnson,et al.  Continuous-time correlated random walk model for animal telemetry data. , 2008, Ecology.

[116]  Laurent Gueguen,et al.  Segmentation by Maximal Predictive Partitioning According to Composition Biases , 2000, JOBIM.

[117]  Darcy R. Visscher,et al.  GPS MEASUREMENT ERROR INFLUENCES ON MOVEMENT MODEL PARAMETERIZATION , 2005 .

[118]  M. Lavielle.  Detection of multiple changes in a sequence of dependent variables , 1999 .

[119]  Peter Dalgaard,et al.  R Development Core Team (2010): R: A language and environment for statistical computing , 2010 .

[120]  I. Jonsen,et al.  Assessing Performance of Bayesian State-Space Models Fit to Argos Satellite Telemetry Locations Processed with Kalman Filtering , 2014, PloS one.

[121]  Y. Tremblay,et al.  Splitting animal trajectories into fine-scale behaviorally consistent movement units: breaking points relate to external stimuli in a foraging seabird , 2013, Behavioral Ecology and Sociobiology.

[122]  Horst Bornemann,et al.  All at sea with animal tracks; methodological and analytical solutions for the resolution of movement , 2007 .

[123]  Baoping Yan,et al.  Mining Common Spatial-Temporal Periodic Patterns of Animal Movement , 2013, 2013 IEEE 9th International Conference on e-Science.

[124]  Frederic Bartumeus,et al.  Expectation-Maximization Binary Clustering for Behavioural Annotation , 2015, PloS one.

[125]  B. J. Worton,et al.  A review of models of home range for animal movement , 1987 .

[126]  Maike Buchin,et al.  Segmenting trajectories: A framework and algorithms using spatiotemporal criteria , 2011, J. Spatial Inf. Sci..

[127]  D. Dechmann,et al.  High-resolution GPS tracking of Lyle's flying fox between temples and orchards in central Thailand , 2015 .

[128]  Stéphane Dray,et al.  The concept of animals' trajectories from a data analysis perspective , 2009, Ecol. Informatics.

[129]  Bettina Speckmann,et al.  Analysis and visualization of animal movement , 2012, Biology Letters.

[130]  Simon Benhamou,et al.  Of scales and stationarity in animal movements. , 2014, Ecology letters.

[131]  E. Revilla,et al.  A movement ecology paradigm for unifying organismal movement research , 2008, Proceedings of the National Academy of Sciences.

[132]  Mevin B. Hooten,et al.  Continuous-time discrete-space models for animal movement , 2012, 1211.1992.

[133]  Henrik Madsen,et al.  Estimation methods for nonlinear state-space models in ecology , 2011 .

[134]  Flavio Quintana,et al.  Selfies of Imperial Cormorants (Phalacrocorax atriceps): What Is Happening Underwater? , 2015, PloS one.

[135]  Darcy R. Visscher,et al.  Scales of movement by elk (Cervus elaphus) in response to heterogeneity in forage resources and predation risk , 2005, Landscape Ecology.

[136]  C. Cormack Gates,et al.  Ungulate foraging strategies: energy maximizing or time minimizing? , 2001 .

[137]  R. Weibel,et al.  Capability of movement features extracted from GPS trajectories for the classification of fine-grained behaviors , 2014 .

[138]  Bernie J. McConnell,et al.  The effects of interpolation error and location quality on animal track reconstruction , 2009 .

[139]  Darcy R. Visscher,et al.  Identifying Movement States From Location Data Using Cluster Analysis , 2010 .

[140]  Steeve D Côté,et al.  Detecting changes in the annual movements of terrestrial migratory species: using the first-passage time to document the spring migration of caribou , 2014, Movement Ecology.

[141]  David M. Williams,et al.  Impact of Habitat-Specific GPS Positional Error on Detection of Movement Scales by First-Passage Time Analysis , 2012, PloS one.

[142]  Dominic A. W. Henry,et al.  Exploring the environmental drivers of waterfowl movement in arid landscapes using first-passage time analysis , 2016, Movement ecology.

[143]  K. Eckert,et al.  Modeling loggerhead turtle movement in the Mediterranean: importance of body size and oceanography. , 2008, Ecological applications : a publication of the Ecological Society of America.

[144]  Martin Wæver Pedersen,et al.  State-space models for bio-loggers: A methodological road map , 2013 .

[145]  Stephen L. Webb,et al.  Incorporating within- and between-patch resource selection in identification of critical habitat for brood-rearing greater sage-grouse , 2015, Ecological Processes.

[146]  Frederic Bartumeus,et al.  Coupling instantaneous energy-budget models and behavioural mode analysis to estimate optimal foraging strategy: an example with wandering albatrosses , 2014, Movement ecology.

[147]  Peter A. Burrough,et al.  Using fractal dimensions for characterizing tortuosity of animal trails , 1988 .

[148]  Marc Lavielle,et al.  Using penalized contrasts for the change-point problem , 2005, Signal Process..

[149]  T. Jacobsen,et al.  Conditional daily and seasonal movement strategies of male Columbia black-tailed deer (Odocoileus hemionus columbianus) , 2013 .

[150]  Paul A. Iaizzo,et al.  Bears Show a Physiological but Limited Behavioral Response to Unmanned Aerial Vehicles , 2015, Current Biology.

[151]  Scott A. McKinley,et al.  Hidden semi-Markov models reveal multiphasic movement of the endangered Florida panther. , 2015, The Journal of animal ecology.

[152]  Deborah Austin,et al.  A THREE‐STAGE ALGORITHM FOR FILTERING ERRONEOUS ARGOS SATELLITE LOCATIONS , 2003 .

[153]  V. Urios,et al.  Autumn migration of Montagu’s harriers Circus pygargus tracked by satellite telemetry , 2007, Journal of Ornithology.

[154]  B. Madon,et al.  Deciphering behavioral changes in animal movement with a “multiple change point algorithm- classification tree” framework , 2014, Front. Ecol. Evol..

[155]  J. Neter,et al.  Applied linear statistical models : regression, analysis of variance, and experimental designs , 1974 .

[156]  Leo Polansky,et al.  Using diel movement behavior to infer foraging strategies related to ecological and social factors in elephants , 2013, Movement ecology.

[157]  M. Hindell,et al.  Foraging Parameters Influencing the Detection and Interpretation of Area-Restricted Search Behaviour in Marine Predators: A Case Study with the Masked Booby , 2013, PloS one.

[158]  T. Benton,et al.  Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics , 2005, Biological reviews of the Cambridge Philosophical Society.

[159]  Brett T McClintock,et al.  When to be discrete: the importance of time formulation in understanding animal movement , 2014, Movement Ecology.

[160]  Anders Nielsen,et al.  Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder. , 2015, Ecology.

[161]  Robert Weibel,et al.  Revealing the physics of movement: Comparing the similarity of movement characteristics of different types of moving objects , 2009, Comput. Environ. Urban Syst..

[162]  M. Lewis,et al.  First Passage Time Analysis of Animal Movement and Insights into the Functional Response , 2009, Bulletin of mathematical biology.

[163]  R. Kays,et al.  Terrestrial animal tracking as an eye on life and planet , 2015, Science.

[164]  Juan M. Morales,et al.  EXTRACTING MORE OUT OF RELOCATION DATA: BUILDING MOVEMENT MODELS AS MIXTURES OF RANDOM WALKS , 2004 .

[165]  Kevin McGarigal,et al.  Using step and path selection functions for estimating resistance to movement: pumas as a case study , 2015, Landscape Ecology.