Color technology is not necessary for rich and efficient color language.

The evolution of basic color terms in language is claimed to be stimulated by technological development, involving technological control of color or exposure to artificially colored objects. Accordingly, technologically "simple" non-industrialized societies are expected to have poor lexicalization of color, i.e., only rudimentary lexica of 2, 3 or 4 basic color terms, with unnamed gaps in the color space. While it may indeed be the case that technology stimulates lexical growth of color terms, it is sometimes considered a sine qua non for color salience and lexicalization. We provide novel evidence that this overlooks the role of the natural environment, and people's engagement with the environment, in the evolution of color vocabulary. We introduce the Maniq-nomadic hunter-gatherers with no color technology, but who have a basic color lexicon of 6 or 7 terms, thus of the same order as large languages like Vietnamese and Hausa, and who routinely talk about color. We examine color language in Maniq and compare it to available data in other languages to demonstrate it has remarkably high consensual color term usage, on a par with English, and high coding efficiency. This shows colors can matter even for non-industrialized societies, suggesting technology is not necessary for color language. Instead, factors such as perceptual prominence of color in natural environments, its practical usefulness across communicative contexts, and symbolic importance can all stimulate elaboration of color language.

Dominant words rise to the top by positive frequency-dependent selection.

A puzzle of language is how speakers come to use the same words for particular meanings, given that there are often many competing alternatives (e.g., "sofa," "couch," "settee"), and there is seldom a necessary connection between a word and its meaning. The well-known process of random drift-roughly corresponding in this context to "say what you hear"-can cause the frequencies of alternative words to fluctuate over time, and it is even possible for one of the words to replace all others, without any form of selection being involved. However, is drift alone an adequate explanation of a shared vocabulary? Darwin thought not. Here, we apply models of neutral drift, directional selection, and positive frequency-dependent selection to explain over 417,000 word-use choices for 418 meanings in two natural populations of speakers. We find that neutral drift does not in general explain word use. Instead, some form of selection governs word choice in over 91% of the meanings we studied. In cases where one word dominates all others for a particular meaning-such as is typical of the words in the core lexicon of a language-word choice is guided by positive frequency-dependent selection-a bias that makes speakers disproportionately likely to use the words that most others use. This bias grants an increasing advantage to the common form as it becomes more popular and provides a mechanism to explain how a shared vocabulary can spontaneously self-organize and then be maintained for centuries or even millennia, despite new words continually entering the lexicon.

A Bayesian phylogenetic study of the Dravidian language family.

The Dravidian language family consists of about 80 varieties (Hammarström H. 2016 Glottolog 2.7) spoken by 220 million people across southern and central India and surrounding countries (Steever SB. 1998 In The Dravidian languages (ed. SB Steever), pp. 1-39: 1). Neither the geographical origin of the Dravidian language homeland nor its exact dispersal through time are known. The history of these languages is crucial for understanding prehistory in Eurasia, because despite their current restricted range, these languages played a significant role in influencing other language groups including Indo-Aryan (Indo-European) and Munda (Austroasiatic) speakers. Here, we report the results of a Bayesian phylogenetic analysis of cognate-coded lexical data, elicited first hand from native speakers, to investigate the subgrouping of the Dravidian language family, and provide dates for the major points of diversification. Our results indicate that the Dravidian language family is approximately 4500 years old, a finding that corresponds well with earlier linguistic and archaeological studies. The main branches of the Dravidian language family (North, Central, South I, South II) are recovered, although the placement of languages within these main branches diverges from previous classifications. We find considerable uncertainty with regard to the relationships between the main branches.

The evolution of language families is shaped by the environment beyond neutral drift.

There are more than 7,000 languages spoken in the world today1. It has been argued that the natural and social environment of languages drives this diversity2-13. However, a fundamental question is how strong are environmental pressures, and does neutral drift suffice as a mechanism to explain diversification? We estimate the phylogenetic signals of geographic dimensions, distance to water, climate and population size on more than 6,000 phylogenetic trees of 46 language families. Phylogenetic signals of environmental factors are generally stronger than expected under the null hypothesis of no relationship with the shape of family trees. Importantly, they are also-in most cases-not compatible with neutral drift models of constant-rate change across the family tree branches. Our results suggest that language diversification is driven by further adaptive and non-adaptive pressures. Language diversity cannot be understood without modelling the pressures that physical, ecological and social factors exert on language users in different environments across the globe.

Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms.

Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.