Department of Biology, University of Turku, Turku, Finland.
J Evol Biol. 2013 Jun;26(6):1244-53. doi: 10.1111/jeb.12107. Epub 2013 May 16.
Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution.
定量系统发育方法已被用于研究生物物种的进化关系和分化时间,最近,这些方法也被应用于语言数据,以阐明语言家族的进化历史。在生物学中,驱动宏观进化过程的因素被认为主要是生物的(红皇后模型)或主要是非生物的(宫廷弄臣模型),或者两者的组合。这些模型的适用性被假设取决于所观察到的时间和空间尺度,因为生物因素在比非生物因素更小的空间尺度上更快地作用于物种的分化。在这里,我们使用乌拉尔语族来研究生物相互作用(即文化相互作用)和非生物变化(即气候波动)是否也与语言多样化有关。我们使用松弛时钟方法的贝叶斯系统发育学来估计分歧的时间,并将我们的结果与气候、历史和考古信息相关联。我们的时间结果与以前的语言学研究平行,但表明芬兰-乌戈尔语、芬兰语和萨米语的分化时间较晚。一些分歧与气候波动同时发生,一些与文化互动和人口迁移同时发生。因此,我们认为生物和非生物因素都直接或间接地促成了语言的多样化,并且在研究语言进化时可以应用这两种模型。