Stochastic modelling of animal movement (original) (raw)

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Review article| 27 Jul 2010

Stochastic modelling of animal movement_Available to Purchase_

Peter E. Smouse;

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

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Stefano Focardi;

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

2

Istituto Superiore per la Protezione e la Ricerca Ambientale, via Ca'

Fornacetta 9, 40064 Ozzano dell'Emilia, Italy

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Paul R. Moorcroft;

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

3

Department of Organismic and Evolutionary Biology

,

Harvard University

,

Cambridge, MA 02138, USA

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John G. Kie;

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

4

Department of Biological Sciences

,

Idaho State University

,

Pocatello, ID 83208, USA

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James D. Forester;

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

3

Department of Organismic and Evolutionary Biology

,

Harvard University

,

Cambridge, MA 02138, USA

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Juan M. Morales

1

Department of Ecology

,

Evolution and Natural Resources, Rutgers University

,

New Brunswick, NJ 08901-8551, USA

5

Laboratorio Ecotono

,

Centro Regional Universitario Bariloche, Universidad Nacional del Comahue

,

Comahue 8400, Argentina

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Publisher: The Royal Society

Online ISSN: 1471-2970

Print ISSN: 0962-8436

Philos Trans R Soc Lond B Biol Sci (2010) 365 (1550): 2201–2211 .

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Abstract

Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.

© 2010 The Royal Society

2010

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