New preprint on Assessing bias and robustness of social network metrics using GPS based radio-telemetry data

Update: now published in Movement Ecology. See here.

Prabhleen Kaur, Simone Ciuti, Michael Salter-Townshend and coauthors have published a preprint on Assessing bias and robustness of social network metrics using GPS based radio-telemetry data. We hope that the animal ecology community agree that this can serve as a useful resource in designing studies that seek to answer questions on the structure of animal communities characterised using social networks. We use real datasets on five species of ungulates in differing environmental settings to see how robust social network summaries are to downsampling. Typically, researchers can only tag a sample of the individuals in a population and inferences about social structure are inferred from these. Knowing how reliable different estimates are at various sample sizes is a crucial consideration, made even more complex by factors such as overall population size, autocorrelation of observations, etc. We not only answer some of these questions, but provide a step-by-step methodology for analysis and software to perform each of the steps.

Click the tweet below to see a brief explainer thread.

Excited to see our work out as a preprint @PrabhleenKaur93 @UCD_Wildlife
"Assessing bias and robustness of social network metrics using GPS based radio-telemetry data" https://t.co/3P4AEEp6F2

— @mststats@mastodon.social (@mststats) April 3, 2023