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食物分享网络的模块化最大限度地降低了狩猎采集社会中个体和群体挨饿的风险。

Modularity of food-sharing networks minimises the risk for individual and group starvation in hunter-gatherer societies.

机构信息

Department of Computer Science, Universidad de Chile, Santiago, Chile.

Millennium Institute Foundational Research on Data, Santiago, Chile.

出版信息

PLoS One. 2023 May 10;18(5):e0272733. doi: 10.1371/journal.pone.0272733. eCollection 2023.

Abstract

It has been argued that hunter-gatherers' food-sharing may have provided the basis for a whole range of social interactions, and hence its study may provide important insight into the evolutionary origin of human sociality. Motivated by this observation, we propose a simple network optimization model inspired by a food-sharing dynamic that can recover some empirical patterns found in social networks. We focus on two of the main food-sharing drivers discussed by the anthropological literature: the reduction of individual starvation risk and the care for the group welfare or egalitarian access to food shares, and show that networks optimizing both criteria may exhibit a community structure of highly-cohesive groups around special agents that we call hunters, those who inject food into the system. These communities appear under conditions of uncertainty and scarcity in the food supply, which suggests their adaptive value in this context. We have additionally obtained that optimal welfare networks resemble social networks found in lab experiments that promote more egalitarian income distribution, and also distinct distributions of reciprocity among hunters and non-hunters, which may be consistent with some empirical reports on how sharing is distributed in waves, first among hunters, and then hunters with their families. These model results are consistent with the view that social networks functionally adaptive for optimal resource use, may have created the environment in which prosocial behaviors evolved. Finally, our model also relies on an original formulation of starvation risk, and it may contribute to a formal framework to proceed in this discussion regarding the principles guiding food-sharing networks.

摘要

有人认为,狩猎采集者的食物分享可能为各种社交互动提供了基础,因此对其进行研究可能有助于深入了解人类社会性的进化起源。受此观察结果的启发,我们提出了一个简单的网络优化模型,该模型受到食物分享动态的启发,可以恢复社交网络中发现的一些经验模式。我们重点研究了人类学文献中讨论的两个主要的食物分享驱动因素:降低个体饥饿风险和关心群体福利或平等获取食物份额,并表明同时优化这两个标准的网络可能会表现出高度内聚的群体社区结构,这些群体围绕着特殊的代理人(我们称之为猎人),他们向系统中注入食物。这些社区出现在食物供应不确定和稀缺的情况下,这表明它们在这种情况下具有适应性价值。我们还发现,最优福利网络类似于促进更平等收入分配的实验室实验中发现的社交网络,并且猎人之间以及猎人与其家庭之间的互惠分布也存在明显差异,这可能与关于分享如何在波浪中分布的一些经验报告一致,首先是在猎人之间,然后是在猎人及其家庭之间。这些模型结果与以下观点一致,即对于最优资源利用具有功能适应性的社交网络可能创造了促进亲社会行为进化的环境。最后,我们的模型还依赖于对饥饿风险的原始表述,并且可能有助于为指导食物分享网络的原则提供一个正式框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a285/10171659/b9582ddb6558/pone.0272733.g001.jpg

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