1. Advances in datalogging technologies have provided a way to monitor the movement of individual animals at unprecedented spatial and temporal scales, both large and small. When used in conjunction with social network analyses, these data can provide insight into fine scale associative behaviors. The variety of technologies demand continuous progress in workflows to translate data streams from automated systems to social networks, based on biologically relevant metrics.
2. Here we present a workflow for generating flexible association matrices from automated radio-telemetry data that can be parsed into both spatial and temporal dimensions. These can then be used to generate and compare social networks across space and time.
3. We illustrate this workflow using data collected from an automated telemetry study of acorn woodpeckers (Melanerpes formicivorus), a cooperatively breeding bird. The data were collected continuously over two years at base stations placed within social group territories. We use this system to demonstrate how this flexible data structure can be used to answer a number of biological questions, specifically 1) how assortative are social associations at the population scale, 2) how do association patterns among territory visitors vary across territories, 3) and how does seasonality affect assortative affiliation within groups?
4. This flexible method allows one to generate social networks that can be used to ask a variety of biological questions pertinent to a wide range of animal systems, exploiting the investigative power that can be gained by using automated radio-telemetry in conjunction with social network analyses.
Published under a Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0).
Article states: Workflow for generating association matrices from automated radio-telemetry data (using sample data from one month of data collection), along with code, can be found in the Supplementary Material, available at https://osf.io/gwb6d/
Original Publication Citation
Shizuka, D., Barve, S., Johnson, A., & Walters, E. L. (2020). Workflow for constructing social networks from automated telemetry systems. EcoEvoRxiv. https://doi.org/10.32942/osf.io/8yv74
Shizuka, Daizaburo; Barve, Sahas; Johnson, Allison; and Walters, Eric L., "Workflow For Constructing Social Networks From Automated Telemetry Systems" (2020). Biological Sciences Faculty Publications. 551.
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This article is a pre-print and has not been peer reviewed.