Stochastic modelling of animal movement.
Philos Trans R Soc Lond B Biol Sci
; 365(1550): 2201-11, 2010 Jul 27.
Article
em En
| MEDLINE
| ID: mdl-20566497
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Modelos Estatísticos
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Migração Animal
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Sistemas de Informação Geográfica
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Animais Selvagens
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Revista:
Philos Trans R Soc Lond B Biol Sci
Ano de publicação:
2010
Tipo de documento:
Article
País de afiliação:
Estados Unidos