Guest Editor’s Introduction to the Special Issue on “Animal Movement Modeling”

In this introduction, we provide a brief overview to statistical models for animal trajectories and then summarize the set of invited articles that comprise the issue.

[1]  Michael Li,et al.  Incorporating periodic variability in hidden Markov models for animal movement , 2017, Movement ecology.

[2]  Ephraim M. Hanks,et al.  Modeling Collective Animal Movement Through Interactions in Behavioral States , 2017 .

[3]  Joshua J. Millspaugh,et al.  Hierarchical Nonlinear Spatio-temporal Agent-Based Models for Collective Animal Movement , 2017, Journal of Agricultural, Biological and Environmental Statistics.

[4]  Jacob S. Ivan,et al.  Hierarchical animal movement models for population‐level inference , 2016, 1606.09585.

[5]  P. Turchin.  Quantitative Analysis Of Movement , 1998 .

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

[7]  John Calambokidis,et al.  A multivariate mixed hidden Markov model for blue whale behaviour and responses to sound exposure , 2017 .

[8]  Mevin B. Hooten,et al.  Reflected Stochastic Differential Equation Models for Constrained Animal Movement , 2017, Journal of Agricultural, Biological and Environmental Statistics.

[9]  Mevin B. Hooten,et al.  Animal Movement Models , 2017 .

[10]  A. Parton,et al.  Bayesian Inference for Multistate ‘Step and Turn’ Animal Movement in Continuous Time , 2017, 1701.05736.

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

[12]  Mevin B. Hooten,et al.  Agent-Based Inference for Animal Movement and Selection , 2010 .

[13]  Roland Langrock,et al.  Modelling group dynamic animal movement , 2013, 1308.5850.

[14]  Alison Parton,et al.  Bayesian inference for continuous time animal movement based on steps and turns , 2016 .

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

[16]  Otso Ovaskainen,et al.  Biased movement at a boundary and conditional occupancy times for diffusion processes , 2003, Journal of Applied Probability.

[17]  Jennifer Pohle,et al.  Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement , 2017, Journal of Agricultural, Biological and Environmental Statistics.

[18]  Otso Ovaskainen,et al.  A General Approach to Model Movement in (Highly) Fragmented Patch Networks , 2017 .

[19]  Mevin B. Hooten,et al.  Temporal variation and scale in movement-based resource selection functions , 2014 .

[20]  Mevin B. Hooten,et al.  Dynamic social networks based on movement , 2015, 1512.07607.

[21]  Murali Haran,et al.  A spatially varying stochastic differential equation model for animal movement , 2016, The Annals of Applied Statistics.

[22]  Mevin B Hooten,et al.  Animal movement constraints improve resource selection inference in the presence of telemetry error. , 2015, Ecology.

[23]  B. Hooten Mevin,et al.  Basis Function Models for Animal Movement , 2016 .

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

[25]  James E. Dunn,et al.  Analysis of Radio Telemetry Data in Studies of Home Range , 1977 .

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

[27]  Mevin B. Hooten,et al.  Imputation Approaches for Animal Movement Modeling , 2017, Journal of Agricultural, Biological and Environmental Statistics.

[28]  Brett T. McClintock,et al.  A general discrete‐time modeling framework for animal movement using multistate random walks , 2012 .

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

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

[31]  D. Brillinger.  Modeling Spatial Trajectories , 2010 .

[32]  Douglas H. Johnson.  THE COMPARISON OF USAGE AND AVAILABILITY MEASUREMENTS FOR EVALUATING RESOURCE PREFERENCE , 1980 .

[33]  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.

[34]  Roland Langrock,et al.  Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges , 2016, AStA Advances in Statistical Analysis.

[35]  Roland Langrock,et al.  Multi-scale Modeling of Animal Movement and General Behavior Data Using Hidden Markov Models with Hierarchical Structures , 2017, Journal of Agricultural, Biological and Environmental Statistics.

[36]  Mevin B Hooten,et al.  Estimating animal resource selection from telemetry data using point process models. , 2013, The Journal of animal ecology.

[37]  Brett T. McClintock,et al.  Animal Movement: Statistical Models for Telemetry Data , 2017 .

[38]  Brett T. McClintock,et al.  Incorporating Telemetry Error into Hidden Markov Models of Animal Movement Using Multiple Imputation , 2017 .

[39]  Aristotle Aristotle,et al.  Aristotle's De Motu Animalium: Text with Translation, Commentary, and Interpretive Essays , 1978 .

[40]  Roland Langrock,et al.  Analysis of animal accelerometer data using hidden Markov models , 2016, 1602.06466.

[41]  Jacob S. Ivan,et al.  A functional model for characterizing long‐distance movement behaviour , 2016 .

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

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

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