e-journal

Modelling group dynamic animalmovement

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1. Group dynamics are a fundamental aspect of many species’ movements. The need to adequately model individuals’
interactions with other group members has been recognized, particularly in order to differentiate the role
of social forces in individual movement from environmental factors. However, to date, practical statisticalmethods,
which can include group dynamics in animal movement models, have been lacking.
2. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement
of the group’s centre, and an individual-levelmodel, such that each individual makes its movement decisions relative
to the group centroid. The basic idea is framed within the flexible class of hiddenMarkov models, extending
previous work on modelling animalmovement bymeans of multistate random walks.
3. While in simulation experiments parameter estimators exhibit some bias in non-ideal scenarios, we show that
generally the estimation ofmodels of this type is both feasible and ecologically informative.
4. We illustrate the approach using real movement data from 11 reindeer (Rangifer tarandus). Results indicate a
directional bias towards a group centroid for reindeer in an encamped state. Though the attraction to the group
centroid is relatively weak, our model successfully captures group-influenced movement dynamics. Specifically,
as compared to a regular mixture of correlated random walks, the group dynamic model more accurately
predicts the non-diffusive behaviour of a cohesive mobile group.
5. As technology continues to develop, itwill become easier and less expensive to tagmultiple individuals within a
group in order to follow their movements.Our work provides a first inferential framework for understanding the
relative influencesof individual versus group-levelmovementdecisions. Thisframeworkcanbe extendedto include
covariates corresponding to environmental influences or body condition. As such, this framework allows for a
broaderunderstandingof themanyinternal andexternal factors that can influenceanindividual’smovement.

Key-words: behavioural state, hiddenMarkov model, maximum likelihood, random walk

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Ketersediaan

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Informasi Detail

Judul Seri

Methods in Ecology and Evolution

No. Panggil

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Penerbit

: British Ecological Society., 2014

Deskripsi Fisik

Methods in Ecology and Evolution 2014, 5, 190–199

Bahasa

English

ISBN/ISSN

doi: 10.1111/2041-21

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

BIOLOGI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Wati/Agus

Versi lain/terkait

Lampiran Berkas

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