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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.

Item Type:	Article
Authors/Creators:	Patterson, TA and Thomas, L and Wilcox, C and Ovaskainen, O and Matthiopoulos, J
Journal or Publication Title:	Trends in Ecology & Evolution
ISSN:	0169-5347
DOI / ID Number:	10.1016/j.tree.2007.10.009
Additional Information:	The definitive version is available at http://www.sciencedirect.com
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