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Modeling Social Dominance: Elo-Ratings Prior History and the Intensity of Aggression

机译:建立社会主导地位的模型:等级先前的历史和侵略的强度

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摘要

Among studies of social species, it is common practice to rank individuals using dyadic social dominance relationships. The Elo-rating method for achieving this is powerful and increasingly popular, particularly among studies of nonhuman primates, but suffers from two deficiencies that hamper its usefulness: an initial burn-in period during which the model is unreliable and an assumption that all win–loss interactions are equivalent in their influence on rank trajectories. Here, I present R code that addresses these deficiencies by incorporating two modifications to a previously published function, testing this with data from a 9-mo observational study of social interactions among wild male chimpanzees (Pan troglodytes) in Uganda. I found that, unmodified, the R function failed to resolve a hierarchy, with the burn-in period spanning much of the study. Using the modified function, I incorporated both prior knowledge of dominance ranks and varying intensities of aggression. This effectively eliminated the burn-in period, generating rank trajectories that were consistent with the direction of pant-grunt vocalizations (an unambiguous demonstration of subordinacy) and field observations, as well as showing a clear relationship between rank and mating success. This function is likely to be particularly useful in studies that are short relative to the frequency of aggressive interactions, for longer-term data sets disrupted by periods of lower quality or missing data, and for projects investigating the relative importance of differing behaviors in driving changes in social dominance. This study highlights the need for caution when using Elo-ratings to model social dominance in nonhuman primates and other species.Electronic supplementary materialThe online version of this article (doi:10.1007/s10764-017-9952-2) contains supplementary material, which is available to authorized users.
机译:在社会物种研究中,通常的做法是使用二元社会优势关系对个人进行排名。采用Elo-rating的方法功能强大且日渐流行,尤其是在非人类灵长类动物的研究中,但存在两个缺陷,妨碍了其实用性:模型不可靠的初始老化期,以及所有人都获胜的假设–损失相互作用对等级轨迹的影响是等效的。在这里,我提出了R代码,通过对先前发布的功能进行两次修改来解决这些缺陷,并使用来自乌干达野生雄性黑猩猩(Pan troglodytes)社交互动的9个月观察研究的数据对此进行了测试。我发现,未经修改的R函数无法解析层次结构,其中老化期涵盖了大部分研究。使用修改后的功能,我结合了支配地位的先验知识和侵略强度的变化。这有效地消除了预热期,产生了与喘气声的发声方向(明确的次要表现)和实地观察的方向一致的等级轨迹,并显示了等级与交配成功之间的明确关系。对于相对于积极互动的频率而言相对较短的研究,因质量下降时期或数据缺失而中断的长期数据集以及调查不同行为在推动变革中的相对重要性的项目而言,此功能可能特别有用。在社会上占主导地位。这项研究突显了在使用Elo-ratings建模非人类灵长类动物和其他物种的社会支配地位时需要谨慎的情况。电子补充材料本文的在线版本(doi:10.1007 / s10764-017-9952-2)包含补充材料,其中可供授权用户使用。

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