A wrap-around movement path randomization method to distinguish social and spatial drivers of animal interactions

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


There are no comments or no comments have been made public for this article.


Download Preprint


Kaija Gahm, Ryan Nguyen, Marta Acácio, Nili Anglister, Gideon Vaadia, Orr Spiegel, Noa Pinter-Wollman


Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses regarding the factors determining animal interactions often involves comparing observed interactions with reference or ’null’ models. One approach to accounting for spatial drivers of social interactions in reference models is randomizing animal movement paths to decouple spatial and social phenotypes while maintaining environmental effects on movements. Here, we update a reference model that detects social attraction above the effect of spatial constraints. We explore the utility of our 'wrap-around' method and compare its performance to the previous approach using agent-based simulations. The wrap-around method provides reference models that are more similar to the original tracking data, while still distinguishing between social and spatial drivers. Furthermore, the wrap-around approach results in fewer false-positives than its predecessor, especially when animals do not return to one place each night but change movement foci, either locally or directionally. Finally, we show that interactions among GPS-tracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from spatial constraints on their movements. We conclude by highlighting the biological situations in which the updated method might be most suitable for testing hypotheses about the underlying causes of social interactions.




Life Sciences


Null models, randomization, social network analysis, spatial constraints, animal movement, GPS telemetry


Published: 2024-05-08 04:15


CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata


Conflict of interest statement:

Data and Code Availability Statement:
R code, including for running the simulations and all analyses, can be found in the GitHub repository https://github.com/Collaborative-Vulture-Work/Vulture-Conveyor-Belt. Vulture data for summer 2022, along with a shapefile of roost sites, are available in the supplementary material. Simulation data is reproducible from the code contained in the github repository.