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Models of social evolution: can we do better to predict ‘who helps whom to achieve what’?

机译:社会发展的模式:我们能更好地预测谁帮助谁实现了目标吗?

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摘要

Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking ‘who helps whom to achieve what’, from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap.
机译:社会发展和帮助发展的模型已经以多种方式分类。但是,有两种分类上的差异引起了现场的注意。模型往往无法说明为什么他们使用关于谁为谁提供帮助的特定假设结构:大量作者可能出于数学上的便利而对基本上相同的个人进行点对点合作进行了建模;其他人则受特定的合作繁殖物种的启发,并倾向于在下属更有效地帮助优势品种的情况下承担单向帮助。类似地做出关于帮助实现什么的选择(即,改善被帮助者的生活历史特征),而无需多加评论:尽管有证据表明,当被帮助者可以执行工作时,生育力收益比生存增强更为常见,但通常会模拟生育力收益生命历史重新分配(减轻负载和相关现象)。我们回顾了当前对显式询问“谁帮助谁来实现目标”所揭示的影响的理论理解,从合伙制互助模式到极少数能明显对比选择力量以帮助增强另一个人的生育力或生存力的模式。由于当代文学中特有的建模选择,包括不同程度地明确了人口统计学结果,令人惊讶的是,关于预测哪种类型的帮助最容易发展几乎没有共识。我们概述了有希望的未来方向,以填补这一空白。

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