A multi-species repository of social networks

Abstract

Social network analysis is an invaluable tool to understand the patterns, evolution, and consequences of sociality. Comparative studies over the spectrum of sociality across taxonomic groups are particularly valuable. Such studies however require quantitative information on social interactions across multiple species which is not easily available. We introduce the Animal Social Network Repository (ASNR) as the first multitaxonomic repository that collates more than 650 social networks from 47 species, including those of mammals, reptiles, fish, birds, and insects. The repository was created by consolidating social network datasets from the literature on wild and captive animals into a consistent and easy-to-use network data format. The repository is archived at https://bansallab.github.io/asnr/. ASNR has tremendous research potential, including testing hypotheses in the fields of animal ecology, social behavior, epidemiology and evolutionary biology.

Infected or informed? Social structure and the simultaneous transmission of information and infectious disease

“…Thus, combining these techniques for simulating transmission with evolutionary modelling will represent a key priority. In addition, tailoring theoretical network models to more accurately reflect typical contact behaviours of animals using recently established data repositories (Sah et al ) will help to provide more detailed predictions for different social systems. Combining theoretical and empirical work to develop data‐based evolutionary models will be important to fully understand the implications of these differences in the transmission of infection and information for the evolution of animal social systems.…”

Density dependence and disease dynamics: moving towards a predictive framework

“…For example, a recent analysis investigated how widespread anthropogenic disturbance altered animal space use using telemetry data from a wide variety of different systems (Doherty et al 2021). The ecological data revolution is becoming particularly fruitful at the intersection of disease and behavioural ecology: disease datasets are now being built up by data mining approaches (Han et al 2020; and there are a growing number of large, open-source datasets with available host-parasite association or prevalence data (Cohen et al 2020;Gibb et al 2021), as well as widely available behavioural datasets like the animal social network repository (ASNR; (Sah et al 2019)) and demographic datasets like the TetraDENSITY database of vertebrates' population density estimates (Santini et al 2018a). Datasets like these are already being integrated to answer questions at the sociality-disease interface: for example, combined the global mammal parasite database (GMPD; (Stephens et al 2017)) with the ASNR (Sah et al 2019) to investigate how primate species' social networks might have evolved in response to parasite pressure.…”

Graphery: Interactive Tutorials for Biological Network Algorithms

“…In neuroscience, connectomes describe the relationship among neurons in the brain, and have served as a rich avenue for modeling the brain's wiring diagram [9,10]. Graphs have also been used extensively to model social dynamics in animals [11][12][13] and energy flux in populations (e.g., food webs) [14,15].…”

“…As graphs have become a common way to model biological systems, we have also seen an explosion in network data that has been constructed from experiments or by carefully curating existing literature. Graph databases and repositories have been developed to store, query, and visualize biological networks [11,[16][17][18][19][20][21][22], and biological network visualization is a subfield in its own right [23][24][25]. Web-based network visualization has enabled a lightweight and interactive means for users to explore graphs without downloading a stand-alone application [26][27][28].…”