State-space models of individual animal movement

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

Research output: Contribution to journalArticlepeer-review

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

Fingerprint

Dive into the research topics of 'State-space models of individual animal movement'. Together they form a unique fingerprint.

Cite this