Research press release


Nature Communications

Evolution: Sexually transmitted infections may have fostered monogamy in humans



今回、Chris Bauchたちは、現実的な人口統計学的パラメーターと疾患伝播パラメーターを用いて、ヒト社会におけるさまざまな社会的配偶行動規範の進化のシミュレーションを行うことで、一夫一婦制への移行に最も大きな影響を与えた要因が何だったのかを調べた。その結果分かったのは、社会の規模が大きい場合(構成員が300人以下)にはSTIの有病率が集団内で風土病のレベルに達し、出生率が低下し、一夫一婦制をとらない社会の他の構成員(と集団)を罰する一夫一婦主義者の出現に有利に働いたということだ。これに対して、小規模な社会(構成員が30人以下)でのSTIは、短期間の疾患の集団発生にとどまり、集団内で風土病のレベルに達することはなかった。従って、一夫多妻主義者の集団における出生率が高くなり、時間の経過とともに一夫多妻制が支配的な社会規範となった。


The emergence of socially imposed monogamy in human societies may have been influenced by the prevalence of sexually transmitted infections (STIs), finds a study in Nature Communications. Increases in the transmission of STIs within larger groups of people highlight a potential mechanism for the emergence of monogamy among early settled agriculturalists.

Historically, most human societies have been polygynous, a form of polygamy where males are allowed to mate with multiple female partners. This is especially true of small hunter-gatherer societies, but less so among the larger societies that emerged with the advent of settled agriculture, in which monogamy is more likely to have been socially imposed on populations by means of threat of punishment.

Chris Bauch and colleagues investigate what factors most influenced this transition by simulating the evolution of different social mating norms in human societies, based on realistic demographic and disease transmission parameters. They find that when the size of a society is large (with a maximum of 300 individuals), the prevalence of STIs becomes endemic in the population, reducing fertility rates and favouring the emergence of monogamists who punish other group members that do not conform to the same social norm. In contrast, STIs in smaller groups (with a maximum of 30 individuals) are characterized by only short-lived disease outbreaks that do not become endemic in the population. Thus, the greater fertility rates of polygynists allow polygyny to become the dominant social norm over time.

These simulations may help to explain the emergence of contrasting social norms in human societies in the absence of first-hand data on disease prevalence in prehistoric populations.

doi: 10.1038/NCOMMS11219


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