DOI: 10.5061/dryad.n5tb2rc4w
title: Relationship between dominance hierarchy steepness and rank-relatedness of benefits in primates

description: In animal social groups, the extent to which individuals consistently win
 agonistic interactions and their ability to monopolize resources represent
 two core aspects of their competitive regime. However, whether these two
 aspects are closely correlated within groups has rarely been studied.
 Here, we tested the hypothesis that hierarchy steepness, which is
 generally used to represent power differentials between group members,
 predicts the variation in the distribution of fitness-related benefits
 (i.e., fecundity, infant survival, mating success and feeding success) in
 relation to individual dominance ranks. We tested this hypothesis in
 primate groups using comparative phylogenetic meta-analytical techniques.
 Specifically, we reviewed published and unpublished studies to extract
 data on individual dominance ranks, their access to fitness-related
 benefits and hierarchy steepness. We collected and included in our
 analysis a total of 153 data points, representing 27 species (including
 two chimpanzee sub-species). From these, we used four common methods to
 measure individual dominance ranks and hierarchy steepness, i.e.,
 Dij-based normalized David's scores, randomized Elo-ratings, and
 David's scores and Elo-ratings estimated in Bayesian frameworks. We
 found that hierarchy steepness had no effect on the strength of the
 relationship between dominance rank and access to fitness-related
 benefits. Our results suggest that hierarchy steepness does not reflect
 between-group variation in the extent to which individual dominance
 affects the acquisition of fitness-related benefits in primates. Although
 the ability to win agonistic encounters is essential, we speculate that
 other behavioral strategies adopted by individuals may play crucial roles
 in resource acquisition in animal competitive regimes.
description: Relationship between dominance hierarchy steepness and rank-relatedness of
 benefits in primates
 [https://doi.org/10.5061/dryad.n5tb2rc4w](https://doi.org/10.5061/dryad.n5tb2rc4w) We have submitted our raw data (**Supplementary Raw Data.csv**), phylogenetic tree (**consensusTree_Primates.nex**), R scripts (**Part 1 All data_Table2&TableS1-S10.R**) (**Part 2 All data_TableS11-S37.R**) (**Part 3 Restricted data_Table3&TableS38-S45.R**) (**Part 4 Simple models_TableS46-S47.R**) (**Part 5 Unpublished and published datasets_TableS48-S63.R**) and results produced by each R script (**Part 1 All data_Table2&TableS1-S10.txt**) (**Part 2 All data_TableS11-S37.txt**) (**Part 3 Restricted data_Table3&TableS38-S45.txt**) (**Part 4 Simple models_TableS46-S47.txt**) (**Part 5 Unpublished and published datasets_TableS48-S63.txt**). ## Descriptions ### **Supplementary Raw Data.csv** * *Authors*: For published data, it's authors of the paper; for unpublished data, the authors are we collect the data from. * *Study*: The study ID. For example, there maybe more than 1 datapoints collected from one study. * *Group*: The study group ID. One group could be studied in different papers. * *Year*: The year of publication. For unpublished data, I define the Year is the year of the sampling end time. * *Data_origin*: Whether the datapoint is from published papers or unpublished studies. * *Species*: The study species. * *Genus*: The genus of the study species. * *Dispersal_pattern*: Categorical variable. FP: Female philopatry; MP: Male philopatry; MFP: Both male and female disperse. * *Social_organization*: Categorical variable. OMG: One-male group; MMG: Multimale-multifemale group; MLS: Multilevel society. * *Study_setting*: Categorical variable: wild, provisioned and captive. * *Study_duration*: Study duration in months. * *Sex*: M: Male, F: Female; if the study group is mixed-sex, we indicate the number of males and females. * *Sex_category*: Categorical variable. M: Male, F: Female, Mixed: when it's mixed-sex group. * *Sample size*: The number of individuals sampled. * *Measure_category*: Categorical variable: FeedingSuccess, InfantSurviv, Fecundity, MatingSuccess. * *FitnessProxy*: Categorical variable. EcologicalSuccess (FeedingSuccess) and ReproductiveSuccess (InfantSurviv, Fecundity or MatingSucess). This variable is not included in our models. * *Benefit_category*: Categorical variable. Direct and Indirect. Fecundity and Infant survival are considered as direct measures for fitness-related benefits. Mating success and feeding success are considered as indirect measures for fitness-related benefits. * *Test*: Categorical variable. Whether the correlation coefficients are calculated using Pearson or Spearman method. * *rElo_r*: The correlation coefficients between fitness-related benefits and individual cardinal dominance rank (evaluated by randomized Elo-ratings). * *rElo.ordinal_r*: The correlation coefficients between fitness-related benefits and individual ordinal dominance rank (evaluated by randomized Elo-ratings). * *rElo_es*: Effect size derived from *rElo_r*. * *rElo.ordinal_es*: Effect size derived from *rElo.ordinal_r*. * *rElo_stp*: Hierarchy steepness evaluated by randomized Elo-ratings. * *NDS_r*: The correlation coefficients between fitness-related benefits and individual cardinal dominance rank (evaluated by Dij-based normalized David's scores). * *NDS.ordinal_r*: The correlation coefficients between fitness-related benefits and individual ordinal dominance rank (evaluated by Dij-based normalized David's scores). * *NDS_es*: Effect size derived from *NDS_r*. * *NDS.ordinal_es*: Effect size derived from *NDS.ordinal_r*. * *NDS_stp*: Hierarchy steepness evaluated by Dij-based normalized David's scores. * *BayesElo_r*: The correlation coefficients between fitness-related benefits and individual cardinal dominance rank (evaluated by Elo-ratings in Bayesian frameworks). * *BayesElo.ordinal_r*: The correlation coefficients between fitness-related benefits and individual ordinal dominance rank (evaluated by Elo-ratings in Bayesian frameworks). * *BayesElo_es*: Effect size derived from *BayesElo_r*. * *BayesElo.ordinal_es*: Effect size derived from *BayesElo.ordinal_r*. * *BayesElo_stp*: Hierarchy steepness evaluated by Elo-ratings in Bayesian frameworks. * *BayesDS_r*: The correlation coefficients between fitness-related benefits and individual cardinal dominance rank (evaluated by David's scores in Bayesian frameworks). * *BayesDS.ordinal_r*: The correlation coefficients between fitness-related benefits and individual ordinal dominance rank (evaluated by David's scores in Bayesian frameworks). * *BayesDS_es*: Effect size derived from *BayesDS_r*. * *BayesDS.ordinal_es*: Effect size derived from *BayesDS.ordinal_r*. * *BayesDS_stp*: Hierarchy steepness evaluated by David's scores in Bayesian frameworks. * *variance*: The sampling variance. A must-included for a meta-analysis study. Calculated by 1/(Sample size-3). * *Linearity*: The modified Landau's linearity index for each sampled group. * *significance*: The significance of the linearity above. * *Aggression and submission used for the win-loss matrix*: Aggressive and submissive behaviors used for the dominance matrix. ## \*\* R scripts and Results \*\* * *Part 1 All data_Table2&TableS1-S10.R* and *Part 1 All data_Table2&TableS1-S10.txt*: For the complete dataset, model statistics for the full meta-regression models with no interaction effect included. * *Part 2 All data_TableS11-S37.R* and *Part 2 All data_TableS11-S37.txt*: For the complete dataset, model statistics for the full meta-regression models with the interaction effect between each steepness measure and the dispersal pattern of the study species, the study setting and the sex category. * *Part 3 Restricted data_Table3&TableS38-S45.R* and *Part 3 Restricted data_Table3&TableS38-S45.txt*: For the restricted dataset including only groups in which the dominance hierarchy is significantly linear, model statistics for the full meta-regression models with no interaction effect included. * *Part 4 Simple models_TableS46-S47.R* and *Part 4 Simple models_TableS46-S47.txt*: Model statistics for the simpler models with only the predictor (i.e., steepness) included, and statistics of the likelihood ratio tests comparing the full model with the respective control model for the complete dataset and the restricted dataset including only groups in which the dominance hierarchy is significantly linear, respectively. * *Part 5 Unpublished and published datasets_TableS48-S63.R* and *Part 5 Unpublished and published datasets_TableS48-S63.txt*: For the published and unpublished data, respectively, model statistics for the full meta-regression models with no interaction effect included. ## Key Information Sources Dispersal pattern and Social organization were derived from the following sources: * Olivier et al., 2024; DOI:10.1073/pnas.2215401120 * Mitani et al., 2012; The evolution of primate societies. University of Chicago Press. * Shultz et al., 2011; DOI:10.1038/nature10601 ## Code/Software R is required to run all R scripts in which annotations are provided throughout; the scripts were created using version 4.1.3.