There are more than 7,000 languages spoken in the world today 1. It has been argued that the natural and social environment of languages drives this diversity 2-13. 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. Present-day linguistic diversity is non-randomly distributed across the globe, forming patterns at multiple levels. For example, more than 7,000 languages are currently spoken, and these can be classified into a few hundred language families 1. Each family contains (ideally) all-and only-descendants of a single ancestral protolanguage. Given that languages evolve through time in a manner similar to the evolution of biological species-through splits, extinctions and horizontal exchange-a language family can be approximated by a structured family tree (or phylogeny) that comprises a set of languages spoken by actual human groups occupying geographical space. An intriguing observation is that not only individual languages are non-randomly distributed across the globe; language families are too: some families are huge, spanning vast areas, while others are much more circumscribed. It has been proposed that this patterning reflects ancestral historical events and processes, such as demographic migrations and spreads, or language shift through elite dominance 14. Additionally, there is an emerging view that language diversification cannot be fully understood except in the wider context of physical, cultural and biological variation 15-17. A fundamental question, then, is why and how do language family trees unfold? Is linguistic diversification a self-contained process, or do pressures related to geographic and demographic dimensions drive diversification and shape language family trees? The classic view holds that explanations of diversity have to be sought 'first on the basis of recognized processes of internal change' 18. Here, 'internal' changes are either seen as a 'rather directionless pursuit of individual forms down the branches of the family tree' 19 or as regular phenomena such as sound change and analogy 19. Internal changes are often associated with the term 'linguistic drift' 20 , which

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.

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.

Here we present an expanded version of BDPROTO, a database comprising phonological inventory data from 257 ancient and reconstructed languages. These data were extracted from historical linguistic reconstructions and brought together into a single unified, normalized, accessible, and Unicode-compliant language resource. This dataset is publicly available and we aim to engage language scientists doing research on language change and language evolution. Furthermore, we identify a hitherto undiscussed temporal bias that complicates the simple comparison of ancient and reconstructed languages with present-day languages. Due to the sparsity of the data and the absence of statistical and computational methods that can adequately handle this bias, we instead directly target rates of change within and across families, thereby providing a case study to highlight BDPROTO's research viability; using phylogenetic comparative methods and high-resolution language family trees, we investigate whether consonantal and vocalic systems differ in their rates of change over the last 10,000 years. In light of the compilation of BDPROTO and the findings of our case study, we discuss the challenges involved in comparing the sound systems of reconstructed languages with modern day languages.