This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
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Abstract
The interconnecting links (edges) between individuals (nodes) in an animal social network are often defined by discrete, directed behaviours (interactions). However, where interactions are difficult to observe, a network edge is instead defined as individuals sharing space or overlapping in time (an association). Despite an increasingly accessible toolkit to assemble and analyse animal social networks, defining associations remains a challenge in behavioural ecology. While different study systems have used different ways to validate the definition of an association, an empirical comparison of how these different methods compare is lacking. Here, we apply three methods to define social associations, by 1) strict time-window, 2) co-occurrence in a group, and 3) arrival-time, in four bird systems. We first test the ability of each method to detect individually repeatable social traits. Then we describe the structure of each network using Jaccard similarity and Mantel tests, and finally, we test the sensitivity of network structure to changing parameters within the three definitions. We found that the network structure was largely robust to changing how associations were defined, with subtle differences. We suggest that these differences are the result of an inappropriate definition of association in the context of experimental design and system ecology. Researchers in ecology and evolution should carefully consider the biological relevance of association definition prior to starting research into animal social behaviour.
DOI
https://doi.org/10.32942/X2P890
Subjects
Animal Sciences, Behavior and Ethology, Ecology and Evolutionary Biology, Life Sciences, Ornithology
Keywords
animal behaviour, Gambit of the Group, sociality, RFID
Dates
Published: 2024-01-12 04:28
License
CC BY Attribution 4.0 International
Additional Metadata
Language:
English
Conflict of interest statement:
None
Data and Code Availability Statement:
All code scripts used to generate arrival networks are available on the Zenodo repository (Chan and Dunning 2023). All data and code that can be used to reproduce results are available here: https://doi.org/10.5281/zenodo.7892571
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