Inferring longitudinal hierarchies: Framework and methods for studying the dynamics of dominance

Abstract

1. Social inequality is a consistent feature of animal societies, often manifesting as dominance hierarchies, in which each individual is characterized by a dominance rank denoting its place in the network of competitive relationships among group members. Most studies treat dominance hierarchies as static entities despite their true longitudinal, and sometimes highly dynamic, nature.2. To guide study of the dynamics of dominance, we propose the concept of a longitudinal hierarchy: the characterization of a single, latent hierarchy and its dynamics over time. Longitudinal hierarchies describe the hierarchy position (r) and dynamics (∆) associated with each individual as a property of its interaction data, the periods into which these data are divided based on a period delineation rule (p) and the method chosen to infer the hierarchy. Hierarchy dynamics result from both active (∆a) and passive (∆p) processes. Methods that infer longitudinal hierarchies should optimize accuracy of rank dynamics as well as of the rank orders themselves, but no studies have yet evaluated the accuracy with which different methods infer hierarchy dynamics.3. We modify three popular ranking approaches to make them better suited for inferring longitudinal hierarchies. Our three "informed" methods assign ranks that are informed by data from the prior period rather than calculating ranks de novo in each observation period and use prior knowledge of dominance correlates to inform placement of new individuals in the hierarchy. These methods are provided in an R package. 4. Using both a simulated dataset and a long-term empirical dataset from a species with two distinct sex-based dominance structures, we compare the performance of these methods and their unmodified counterparts. We show that choice of method has dramatic impacts on inference of hierarchy dynamics via differences in estimates of ∆a. Methods that calculate ranks de novo in each period overestimate hierarchy dynamics, but incorporation of prior information leads to more accurately inferred ∆a. Of the modified methods, Informed MatReorder infers the most conservative estimates of hierarchy dynamics and Informed Elo infers the most dynamic hierarchies. 5. This work provides crucially needed conceptual framing and methodological validation for studying social dominance and its dynamics.

Social alliances improve rank and fitness in convention-based societies

“…Identification of Rank Reversals. We used the longitudinal hierarchy framework we advanced in a previous paper (34) to study rank reversals. In this approach, interaction data are divided into study periods spanning the length of the study, ranks are determined for each individual present in each period, and hierarchy dynamics are inferred as the difference in rank each individual occupies from one period to the next.…”

Risk‐taking in free‐living spotted hyenas is associated with anthropogenic disturbance, predicts survivorship, and is consistent across experimental contexts

“…Rank relationships among adult females are usually stable over long periods (Holekamp et al, ; Vullioud et al, ). Here, we assigned each individual a social rank based on its wins and losses in dyadic agonistic interactions using informed MatReorder (Strauss & Holekamp, ); rank was standardized for natal animals between −1 and 1 for comparisons among clans. We then divided the standardized ranks into thirds for high‐, mid‐, and low‐rank categories for natal animals (females and their subadult offspring), and all immigrant males were categorized as “immigrant,” ranking below all natal animals.…”

Juvenile rank acquisition influences fitness independent of adult rank

“…Aggressive interactions among individuals of all age classes were collected using all-occurrence sampling [36]; aggressive interactions were collected up until June 2016 for two clans, December 2016 for one clan, and March 2017 for the fourth clan. We used the aggressive interactions among adult females to infer maternal ranks (i.e., rank of a juvenile’s mother relative to other mothers) as in [13,37]; we used the aggressive interactions among juveniles to measure variation in rank acquisition using the Elo-deviance method. In all cases we used, only aggressive interactions in which the recipient displayed submissive behavior.…”

“…In addition to Elo-deviance, we also included maternal rank (calculated as the rank the juvenile’s mother held in the year of the juvenile’s birth), and coded it categorically as ‘high’ and ‘low’ rank based on they were in the upper or lower half of the hierarchy. Rank relationships among females were inferred yearly for all adult females who were at least 1.5 years old at the start of the calendar year using the Informed MatReorder method, as in previous studies [13,37,39]. To control for the possible influence of variable sampling on Elo-deviance measures, we included the number of interactions used to calculate Elo-deviance as a predictor in each model.…”