Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity

TY - JOUR

T1 - Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity

AU - Ramos-Fernandez, Gabriel

AU - King, Andrew J

AU - Beehner, Jacinta C

AU - Bergman, Thore J

AU - Crofoot, Margaret C

AU - Di Fiore, Anthony

AU - Lehmann, Julia

AU - Schaffner, Colleen M

AU - Snyder-Mackler, Noah

AU - Zuberbühler, Klaus

AU - Aureli, Filippo

AU - Boyer, Denis

N1 - © 2017 The Author(s).

PY - 2018/5/30

Y1 - 2018/5/30

N2 - Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys (Ateles geoffroyi), chimpanzees (Pan troglodytes) and geladas (Theropithecus gelada). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics.© 2018, The Author(s). This is an author produced version of a paper published in PROCEEDINGS OF THE ROYAL SOCIETY B BIOLOGICAL SCIENCES uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link below. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.

AB - Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys (Ateles geoffroyi), chimpanzees (Pan troglodytes) and geladas (Theropithecus gelada). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics.© 2018, The Author(s). This is an author produced version of a paper published in PROCEEDINGS OF THE ROYAL SOCIETY B BIOLOGICAL SCIENCES uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link below. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.

KW - Journal Article

U2 - 10.1098/rspb.2018.0532

DO - 10.1098/rspb.2018.0532

M3 - Article

C2 - 29848648

SN - 0962-8452

VL - 285

JO - Proceedings of The Royal Society B Biological Sciences

JF - Proceedings of The Royal Society B Biological Sciences

IS - 1879

M1 - 20180532

ER -