Social interactions generate complex selection patterns in virtual worlds
Data files
Apr 18, 2024 version files 11.90 MB
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df_social_selection.csv
11.89 MB
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README.md
1.72 KB
Abstract
Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer videogame as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual’s survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.
README: Social interactions generate complex selection patterns in virtual worlds
Year 2024 Journal Journal of Evolutionary Biology Authors F Santostefano, M Fraser Franco, PO Montiglio
file: df_social_selection.csv
Description of the data and file structure
#dt: date of match year-month-day
#game_duration: game duration (sec)
#crouching_duration: time spent hiding (sec)
#chase_duration: time spent in chase (sec)
#unhook_count: # times the player rescues another player
#points: points earned (0 to 32000)
#gen_duration: % resources acquired on a total of 500 (e.g. 100 1 generator, 200 2 generators, etc)
#escaped: has the player survived the match? (1 yes, 0 no)
#avg_social_crouching: average time spent hiding by the 3 social partners (sec)
#avg_social_chase: average time spent in chase by the 3 social partners (sec)
#avg_social_unhook:average # of times the 3 social partners unhook another player
#avg_social_gen :average % resources acquired done by the 3 social partners
#Zcrouching: Z transformed time spent hiding (sec)
#Zchase : Z transformed time spent in chase (sec)
#Zunhook: Z transformed # times the player rescues another player
#Zgen : Z transformed % resources acquired
#Zgame_duration Z transformed game duration (sec)
#Zsocial_crouching :Z transformed average time spent hiding by the 3 social partners (sec)
#Zsocial_chase : Z transformed average time spent in chase by the 3 social partners (sec)
#Zsocial_unhook : Z transformed average # of times the 3 social partners rescues another player
#Zsocial_gen : Z transformed average % resources acquired by the 3 social partners
#players_id: anonymized player id
#match_id: anonymized match id
#map_code: anonymized map code
Methods
See Methods section in the Main Text of the manuscript and ESM for additional information