Assessing dominance hierarchies: validation and advantages of progressive evaluation with Elo-rating (original) (raw)
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Animal Behaviour, 2010
A plethora of indices have been proposed and used to construct dominance hierarchies in a variety of vertebrate and invertebrate societies, although the rationale for choosing a particular index for a particular species is seldom explained. In this study, we analysed and compared three such indices, viz Clutton-Brock et al.'s index (CBI), originally developed for red deer, Cervus elaphus, David's score (DS) originally proposed by the statistician H. A. David and the frequency-based index of dominance (FDI) developed and routinely used by our group for the primitively eusocial wasps Ropalidia marginata and Ropalidia cyathiformis. Dominance ranks attributed by all three indices were strongly and positively correlated for both natural data sets from the wasp colonies and for artificial data sets generated for the purpose. However, the indices differed in their ability to yield unique (untied) ranks in the natural data sets. This appears to be caused by the presence of noninteracting individuals and reversals in the direction of dominance in some of the pairs in the natural data sets. This was confirmed by creating additional artificial data sets with noninteracting individuals and with reversals. Based on the criterion of yielding the largest proportion of unique ranks, we found that FDI is best suited for societies such as the wasps belonging to Ropalidia, DS is best suited for societies with reversals and CBI remains a suitable index for societies such as red deer in which multiple interactions are uncommon. Ó
Measuring and testing the steepness of dominance hierarchies
Animal Behaviour, 2006
In the analysis of social dominance in groups of animals, linearity has been used by many researchers as the main structural characteristic of a dominance hierarchy. In this paper we propose, alongside linearity, a quantitative measure for another property of a dominance hierarchy, namely its steepness. Steepness of a hierarchy is defined here as the absolute slope of the straight line fitted to the normalized David's scores (calculated on the basis of a dyadic dominance index corrected for chance) plotted against the subjects' ranks. This correction for chance is an improvement of an earlier proposal by de Vries (appendix 2 in de Vries, Animal Behaviour, 1998, 55, 827-843). In addition, we present a randomization procedure for determining the statistical significance of a hierarchy's steepness, which can be used to test the observed steepness against the steepness expected under the null hypothesis of random win chances for all pairs of individuals. Whereas linearity depends on the number of established binary dominance relationships and the degree of transitivity in these relationships, steepness measures the degree to which individuals differ from each other in winning dominance encounters. Linearity and steepness are complementary measures to characterize a dominance hierarchy.
A comparison of dominance rank metrics reveals multiple competitive landscapes in an animal society
Proceedings of the Royal Society B: Biological Sciences
Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes and reproductive performance. Studies of how dominance rank predicts these traits typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here, we compare the ability of two dominance rank metrics—simple ordinal rank and proportional or ‘standardized’ rank—to predict 20 traits in a wild baboon population in Amboseli, Kenya. We propose that simple ordinal rank best predicts traits when competition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent. We found that for 75% of traits (15/20), one rank metric performed better than the other. Strikingly, all male traits were best predicted by simple ordinal rank, whereas female traits were evenly split between proportional and simple ordinal rank. Hence, male and female tra...
Behaviour, 2005
In studies of animal behaviour investigators correlate dominance with all kinds of behavioural variables, such as reproductive success and foraging success. Many methods are used to produce a dominance hierarchy from a matrix reflecting the frequency of winning dominance interactions. These different methods produce different hierarchies. However, it is difficult to decide which ranking method is best. In this paper, we offer a new procedure for this decision: we use an individual-based model, called DomWorld, as a test-environment. We choose this model, because it provides access to both the internal dominance values of artificial agents (which reflects their fighting power) and the matrix of winning and losing among them and, in addition, because its behavioural rules are biologically inspired and its group-level patterns resemble those of real primates. We compare statistically the dominance hierarchy based on the internal dominance values of the artificial agents with the dominance hierarchy produced by ranking individuals by (a) their total frequency of winning, (b) their average dominance index, (c) a refined dominance index, the David's score, (d) the number of subordinates each individual has and (e) a ranking method based on maximizing the linear order of the hierarchy. Because dominance hierarchies may differ depending on group size, type of society, and the interval of study, we compare these ranking methods for these conditions. We study complete samples as well as samples randomly chosen to resemble the limitations of observing real animals. It appears that two methods of medium complexity (the average dominance index and David's score) lead to hierarchical orders that come closest to the hierarchy based on internal dominance values of the agents. We advocate usage of the average dominance index, because of its computational simplicity.
2020
Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes, and reproductive performance. Studies of how dominance rank affects these outcomes typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here we compare the ability of two dominance rank metrics—ordinal rank and proportional or ‘standardized’ rank—to predict 20 distinct traits in a well-studied wild baboon population in Amboseli, Kenya. We propose that ordinal rank best predicts outcomes when competition is density-dependent, while proportional rank best predicts outcomes when competition is density-independent. We found that for 75% (15/20) of the traits, one of the two rank metrics performed better than the other. Strikingly, all male traits were better predicted by ordinal than by proportional rank, while female traits were evenly split between being better predicted ...
Data-Based Analysis of Winner-Loser Models of Hierarchy Formation in Animals
Bulletin of Mathematical Biology, 2009
We review winner-loser models, the currently popular explanation for the occurrence of linear dominance hierarchies, via a three-part approach. 1) We isolate the two most significant components of the mathematical formulation of three of the most widely-cited models and rigorously evaluate the components' predictions against data collected on hierarchy formation in groups of hens. 2) We evaluate the experimental support in the literature for the basic assumptions contained in winner-loser models. 3)