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Estimating animal behavior and residency from movement data

journal contribution
posted on 2023-05-19, 09:15 authored by Pedersen, MW, Patterson, TA, Thygesen, UH, Madsen, H
We present a process-based approach to estimate residency and behavior from uncertain and temporally correlated movement data collected with electronic tags. The estimation problem is formulated as a hidden Markov model (HMM) on a spatial grid in continuous time, which allows straightforward implementation of barriers to movement. Using the grid to explicitly resolve space, location estimation can be supplemented by or based entirely on environmental data (e.g. temperature, daylight). The HMM method can therefore analyze any type of electronic tag data. The HMM computes the joint posterior probability distribution of location and behavior at each point in time. With this, the behavioral state of the animal can be associated to regions in space, thus revealing migration corridors and residence areas. We demonstrate the inferential potential of the method by analyzing satellite-linked archival tag data from a southern bluefin tuna Thunnus maccoyii where longitudinal coordinates inferred from daylight are supplemented by latitudinal information in recorded sea surface temperatures.


Publication title

Oikos: A Journal of Ecology










Blackwell Munksgaard

Place of publication

35 Norre Sogade, Po Box 2148, Copenhagen, Denmark, Dk-1016

Rights statement

© 2011 The Authors. Oikos © 2011 Nordic Society Oikos

Repository Status

  • Restricted

Socio-economic Objectives

Other environmental management not elsewhere classified

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