State-space models of individual animal movement

T.A. Patterson, Len Thomas, C Wilcox, O Ovaskainen, Jason Matthiopoulos

Research output: Contribution to journalArticlepeer-review

572 Citations (Scopus)

Abstract

Detailed observation of the movement of individual animals offers the potential to understand spatial population processes as the ultimate consequence of individual behaviour, physiological constraints and fine-scale environmental influences. However, movement data from individuals are intrinsically stochastic and often subject to severe observation error. Linking such complex data to dynamical models of movement is a major challenge for animal ecology. Here, we review a statistical approach, state-space modelling, which involves changing how we analyse movement data and draw inferences about the behaviours that shape it. The statistical robustness and predictive ability of state-space models make them the most promising avenue towards a new type of movement ecology that fuses insights from the study of animal behaviour, biogeography and spatial population dynamics.

Original languageEnglish
Pages (from-to)87-94
Number of pages8
JournalTrends in Ecology and Evolution
Volume23
Issue number2
DOIs
Publication statusPublished - Feb 2008

Keywords

  • HIDDEN MARKOV-MODELS
  • SEA-SURFACE TEMPERATURE
  • AREA-RESTRICTED SEARCH
  • ATLANTIC BLUEFIN TUNA
  • HABITAT-SELECTION
  • LEATHERBACK TURTLES
  • FORAGING MOVEMENTS
  • LOCATION ACCURACY
  • ARCHIVAL TAGS
  • TIME-SERIES

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