Movement in <scp>3D</scp>: Novel Opportunities for Understanding Animal Behaviour and Space Use

ABSTRACT Animals move in three spatial dimensions, but many animal movement tools have only focused on the use of 2D coordinates for modelling space use, habitat selection, behavioural classification, social interactions and movement. Here, we submit that many common movement ecology analyses can and should be extended to consider all three spatial dimensions to make more robust inferences about ecological processes. We provide an overview of how home range analysis, network analysis and social network analysis, hidden Markov models, resource selection and step selection functions and hierarchical linear and additive models are used for studying animal movement in two dimensions. Then, we explain how the third dimension, z, can be used within these existing frameworks to consider how depth and altitude affect key ecological inferences drawn from animal tracking data. Our position builds on empirical and theoretical work about how three‐dimensional methods can contribute to stronger inferences in movement ecology. Key limitations to operationalisation of this framework include calibration of uncertainty in pressure sensors used to measure depth and altitude, visualisation and rendering of three‐dimensional data to make them interpretable and understandable to end‐users and generally more conventional and accepted methods for using three dimensions when conducting standard animal movement analyses.

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Publication Details

Journal
Ethology
Published
2024-12-29
DOI
https://doi.org/10.1111/eth.13529
Citations
3
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
1.38

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article

Movement in 3D: Novel Opportunities for Understanding Animal Behaviour and Space Use

Christopher T. Monk, Natasha J. Klappstein, Milan Říha, Larissa T. Beumer et al.
3 citations
Ethology
Wildlife Ecology and Conservation
1.38
article

Movement in 3D: Novel Opportunities for Understanding Animal Behaviour and Space Use

Christopher T. Monk, Natasha J. Klappstein, Milan Říha, Larissa T. Beumer, Knut Wiik Vollset, Timo Adam, Robert J. Lennox
article en
3 citations

Abstract

ABSTRACT Animals move in three spatial dimensions, but many animal movement tools have only focused on the use of 2D coordinates for modelling space use, habitat selection, behavioural classification, social interactions and movement. Here, we submit that many common movement ecology analyses can and should be extended to consider all three spatial dimensions to make more robust inferences about ecological processes. We provide an overview of how home range analysis, network analysis and social network analysis, hidden Markov models, resource selection and step selection functions and hierarchical linear and additive models are used for studying animal movement in two dimensions. Then, we explain how the third dimension, z, can be used within these existing frameworks to consider how depth and altitude affect key ecological inferences drawn from animal tracking data. Our position builds on empirical and theoretical work about how three‐dimensional methods can contribute to stronger inferences in movement ecology. Key limitations to operationalisation of this framework include calibration of uncertainty in pressure sensors used to measure depth and altitude, visualisation and rendering of three‐dimensional data to make them interpretable and understandable to end‐users and generally more conventional and accepted methods for using three dimensions when conducting standard animal movement analyses.

EthologyVol. 131(3)
Dalhousie University (CA), Bielefeld University (DE), Czech Academy of Sciences (CZ), GEOMAR Helmholtz Centre for Ocean Research Kiel (DE), Ocean Tracking Network (CA), NORCE Research AS (NO), Senckenberg Biodiversity and Climate Research Centre (DE), Institute of Hydrobiology, Biology Centre, Academy of Sciences of the Czech Republic (CZ), Norwegian Institute for Nature Research (NO)
Canada Foundation for Innovation, European Cooperation in Science and Technology, Norges Forskningsråd, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 17%
Wildlife Ecology and Conservation
1.38
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