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Developing a deeper understanding of animal movements and spatial dynamics through novel application of network analyses
Article first published online: 20 FEB 2012
© 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society
Methods in Ecology and Evolution
Volume 3, Issue 3, pages 574–583, June 2012
How to Cite
Jacoby, D. M. P., Brooks, E. J., Croft, D. P. and Sims, D. W. (2012), Developing a deeper understanding of animal movements and spatial dynamics through novel application of network analyses. Methods in Ecology and Evolution, 3: 574–583. doi: 10.1111/j.2041-210X.2012.00187.x
- Issue published online: 7 JUN 2012
- Article first published online: 20 FEB 2012
- Received 9 October 2011; accepted 12 January 2012 Handling Editor: Sean Rands
- acoustic telemetry;
- animal movements;
- fish behaviour;
- network analysis;
- space use;
1. Determining how animals move within their environment is a fundamental knowledge that contributes to effective management and conservation. Continuous ‘round-the-clock’ animal movement data are frequently gathered using biotelemetry technology, providing discrete data packages on the presence–absence of animals at known locations through time. Current analyses of such data do not generally account for the interconnectivity of locations as animals move between them and consequently do not integrate graphically or statistically a temporal component to spatial changes.
2. Here, we describe the novel application of network analyses to electronic tag data whereby nodes represent locations and edges the movements of individuals. We demonstrate some of the descriptive and quantitative approaches for determining how an animal’s movement interconnects home range habitats. Telemetry data from arrays of recorders provide movement data of individual animals, and as examples of the method proposed, we examine the movements of two distinct shark species, the small-spotted catshark (Scyliorhinus canicula) and the Caribbean reef shark (Carcharhinus perezi). In doing so, we consider both local and global network properties from an animal movement perspective and simulate the effects of node disruption as a proxy for habitat disturbance.
3. Comparative visual representations of two catshark movement networks suggest, for example, potential differences in space use. Multiple regression quadratic assignment procedure shows that habitat is a significant predictor of movement behaviour.
4. Null modelling of C. perezi movement data, corrected for the spatial restriction of static nodes, demonstrated a significant, non-random distribution of directed movements among sites. Additionally, the connectivity of this animal’s movement network is significantly reduced through targeted disruption of a site of high centrality but not through disruption of a randomly selected site.
5. Network theory is a well-established theoretical framework and its integration into the fast developing field of animal movement and telemetry might improve significantly how we interpret animal space use from electronically recorded data. This technique has potentially wide application in animal behaviour but may also inform the management of habitat harbouring threatened or endangered species via the simulation, modelling and intuitive visualisation of animal movement interactions.