Agent-Based Inference for Animal Movement and Selection

Contemporary ecologists often find themselves with an overwhelming amount of data to analyze. For example, it is now possible to collect nearly continuous spatiotemporal data on animal locations via global positioning systems and other satellite telemetry technology. In addition, there is a wealth of readily available environmental data via geographic information systems and remote sensing. We present a modeling framework that utilizes these forms of data and builds on previous research pertaining to the quantitative analysis of animal movement. This approach provides additional insight into the environmental drivers of residence and movement as well as resource selection while accommodating path uncertainty. The methods are demonstrated in an application involving mule deer movement in the La Sal Range, Utah, USA. Supplemental materials for this article are available online.

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

[2]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[3]  W. Wong,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[4]  Steven F. Railsback,et al.  Individual-based modeling and ecology , 2005 .

[5]  Christopher K. Wikle,et al.  Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes , 2003 .

[6]  Catherine A Calder,et al.  Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. , 2009, Ecological applications : a publication of the Ecological Society of America.

[7]  J. Nichols,et al.  ESTIMATING SITE OCCUPANCY, COLONIZATION, AND LOCAL EXTINCTION WHEN A SPECIES IS DETECTED IMPERFECTLY , 2003 .

[8]  Jun Zhu,et al.  Modeling and inference of animal movement using artificial neural networks , 2011, Environmental and Ecological Statistics.

[9]  Stephen M. Krone,et al.  ANALYZING ANIMAL MOVEMENTS USING BROWNIAN BRIDGES 10 , 2007 .

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

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

[12]  W. Gilks.  Markov Chain Monte Carlo , 2005 .

[13]  Uta Berger,et al.  Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology , 2005, Science.

[14]  Murali Haran,et al.  Markov chain Monte Carlo: Can we trust the third significant figure? , 2007, math/0703746.

[15]  Galin L. Jones,et al.  Fixed-Width Output Analysis for Markov Chain Monte Carlo , 2006, math/0601446.

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

[17]  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.

[18]  Dale Wesley Usner.  Persistence and heterogeneity in habitat selection studies , 2000 .

[19]  J. Wickham,et al.  Completion of the 2001 National Land Cover Database for the conterminous United States , 2007 .

[20]  Peter Turchin,et al.  Translating Foraging Movements in Heterogeneous Environments into the Spatial Distribution of Foragers , 1991 .

[21]  B. Carlin,et al.  Measures of Bayesian learning and identifiability in hierarchical models , 2006 .

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

[23]  E. Revilla,et al.  Trends and missing parts in the study of movement ecology , 2008, Proceedings of the National Academy of Sciences.

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

[25]  R. O’Hara,et al.  A review of Bayesian variable selection methods: what, how and which , 2009 .

[26]  Robert G. D'Eon,et al.  MULE DEER SEASONAL MOVEMENTS AND MULTISCALE RESOURCE SELECTION USING GLOBAL POSITIONING SYSTEM RADIOTELEMETRY , 2005 .

[27]  Christopher A. Barnes,et al.  Completion of the 2006 National Land Cover Database for the conterminous United States. , 2011 .

[28]  Stephen M. Krone,et al.  Analyzing animal movements using Brownian bridges. , 2007, Ecology.

[29]  Leslie R. McFarlane,et al.  Breeding Behavior and Space Use of Male and Female Mule Deer: An Examination of Potential Risk Differences for Chronic Wasting Disease Infection , 2007 .

[30]  Jun Zhu,et al.  A set of nonlinear regression models for animal movement in response to a single landscape feature , 2005 .

[31]  N Thompson Hobbs,et al.  Dynamics of prion disease transmission in mule deer. , 2006, Ecological applications : a publication of the Ecological Society of America.

[32]  Dale L. Zimmerman,et al.  An animal movement model incorporating home range and habitat selection , 2008, Environmental and Ecological Statistics.

[33]  Richard Stillman,et al.  Individual‐based Modeling and Ecology.Princeton Series in Theoretical and ComputationalBiology.ByVolker Grimmand, Steven F Railsback.Princeton (New Jersey): Princeton University Press.$99.50 (hardcover); $49.50 (paper). xvi + 428 p; ill.; index. ISBN: 0–691–09665–1 (hc); 0–691–09666–X (pb). 2005. , 2006 .

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

[35]  S. Chib,et al.  Bayesian analysis of binary and polychotomous response data , 1993 .

[36]  Fred L Ramsey,et al.  Persistence and heterogeneity in habitat selection studies using radio telemetry. , 2003, Biometrics.

[37]  J. Andrew Royle,et al.  Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities , 2008 .

[38]  J. Andrew Royle,et al.  A Bayesian state-space formulation of dynamic occupancy models. , 2007, Ecology.