Socio-cultural similarity with host population rather than ecological similarity predicts success and failure of human migrations

Demographers argue that human migration patterns are shaped by people moving to better environments. More recently, however, evolutionary theorists have argued that people move to similar environments to which they are culturally adapted. While previous studies analysing which factors affect migration patterns have focused almost exclusively on successful migrations, here we take advantage of a natural experiment during World War II in which an entire population was forcibly displaced but were then allowed to return home to compare successful with unsuccessful migrations. We test two competing hypotheses: (1) individuals who relocate to environments that are superior to their place of origin will be more likely to remain-The Better Environment Hypothesis or (2) individuals who relocate to environments that are similar to their place of origin will be more likely to remain-The Similar Environment Hypothesis. Using detailed records recording the social, cultural, linguistic and ecological conditions of the origin and destination locations, we find that cultural similarity (e.g. linguistic similarity and marrying within one's own minority ethnic group)-rather than ecological differences-are the best predictors of successful migrations. These results suggest that social relationships, empowered by cultural similarity with the host population, play a critical role in successful migrations and provide limited support for the similar environment hypothesis. Overall, these results demonstrate the importance of comparing unsuccessful with successful migrations in efforts understand the engines of human dispersal and suggest that the primary obstacles to human migrations and successful range expansion are sociocultural rather than ecological.Peer reviewe

Evolution within a language: environmental differences contribute to divergence of dialect groups

Background: The processes leading to the diversity of over 7000 present-day languages have been the subject of scholarly interest for centuries. Several factors have been suggested to contribute to the spatial segregation of speaker populations and the subsequent linguistic divergence. However, their formal testing and the quantification of their relative roles is still missing. We focussed here on the early stages of the linguistic divergence process, that is, the divergence of dialects, with a special focus on the ecological settings of the speaker populations. We adopted conceptual and statistical approaches from biological microevolution and parallelled intra-lingual variation with genetic variation within a species. We modelled the roles of geographical distance, differences in environmental and cultural conditions and in administrative history on linguistic divergence at two different levels: between municipal dialects (cf. in biology, between individuals) and between dialect groups (cf. in biology, between populations).Results: We found that geographical distance and administrative history were important in separating municipal dialects. However, environmental and cultural differences contributed markedly to the divergence of dialect groups. In biology, increase in genetic differences between populations together with environmental differences may suggest genetic differentiation of populations through adaptation to the local environment. However, our interpretation of this result is not that language itself adapts to the environment Instead, it is based on Homo sapiens being affected by its environment, and its capability to adapt culturally to various environmental conditions. The differences in cultural adaptations arising from environmental heterogeneity could have acted as nonphysical barriers and limited the contacts and communication between groups. As a result, linguistic differentiation may emerge over time in those speaker populations which are, at least partially, separated.Conclusions: Given that the dialects of isolated speaker populations may eventually evolve into different languages, our result suggests that cultural adaptation to local environment and the associated isolation of speaker populations have contributed to the emergence of the global patterns of linguistic diversity

Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss

While global patterns of human genetic diversity are increasingly well characterized, the diversity of human languages remains less systematically described. Here we outline the Grambank database. With over 400,000 data points and 2,400 languages, Grambank is the largest comparative grammatical database available. The comprehensiveness of Grambank allows us to quantify the relative effects of genealogical inheritance and geographic proximity on the structural diversity of the world's languages, evaluate constraints on linguistic diversity, and identify the world's most unusual languages. An analysis of the consequences of language loss reveals that the reduction in diversity will be strikingly uneven across the major linguistic regions of the world. Without sustained efforts to document and revitalize endangered languages, our linguistic window into human history, cognition and culture will be seriously fragmented.Genealogy versus geography Constraints on grammar Unusual languages Language loss Conclusio

Phlorest phylogeny derived from Honkola et al. 2013 'Cultural and climatic changes shape the evolutionary history of the Uralic languages'

<p>Cite the source of the dataset as:</p> <blockquote> <p>Honkola T, Vesakoski O, Korhonen K, Lehtinen J, Syrjänen K & Wahlberg N. 2013. Cultural and climatic changes shape the evolutionary history of the Uralic languages. Journal of Evolutionary Biology, 26(6):1244–1253.</p> </blockquote&gt

Best practices in justifying calibrations for dating language families

The use of computational methods to assign absolute datings to language divergence is receiving renewed interest, as modern approaches based on Bayesian statistics offer alternatives to the discredited techniques of glottochronology. The datings provided by these new analyses depend crucially on the use of calibration, but the methodological issues surrounding calibration have received comparatively little attention. Especially, underappreciated is the extent to which traditional historical linguistic scholarship can contribute to the calibration process via loanword analysis. Aiming at a wide audience, we provide a detailed discussion of calibration theory and practice, evaluate previously used calibrations, recommend best practices for justifying calibrations, and provide a concrete example of these practices via a detailed derivation of calibrations for the Uralic language family. This article aims to inspire a higher quality of scholarship surrounding all statistical approaches to language dating, and especially closer engagement between practitioners of statistical methods and traditional historical linguists, with the former thinking more carefully about the arguments underlying their calibrations and the latter more clearly identifying results of their work which are relevant to calibration, or even suggesting calibrations directly

Best practices for spatial language data harmonization, sharing and map creation:a case study of Uralic

Abstract Despite remarkable progress in digital linguistics, extensive databases of geographical language distributions are missing. This hampers both studies on language spatiality and public outreach of language diversity. We present best practices for creating and sharing digital spatial language data by collecting and harmonizing Uralic language distributions as case study. Language distribution studies have utilized various methodologies, and the results are often available as printed maps or written descriptions. In order to analyze language spatiality, the information must be digitized into geospatial data, which contains location, time and other parameters. When compiled and harmonized, this data can be used to study changes in languages’ distribution, and combined with, for example, population and environmental data. We also utilized the knowledge of language experts to adjust previous and new information of language distributions into state-of-the-art maps. The extensive database, including the distribution datasets and detailed map visualizations of the Uralic languages are introduced alongside this article, and they are freely available

Archaeological Artefact Database of Finland (AADA)

Abstract This paper presents the Archaeological Artefact Database of Finland (AADA) of prehistoric (covering period of almost 11,000 years) artefacts in Finland that are categorised by type and are accompanied with photos of the artefacts. The database is intended to contain all typologically classifiable prehistoric artefacts found in Finland and held in Finnish collections. This dataset provides spatio-temporal context for artefacts across different time periods and regions, as it includes approximately 38,000 single artefacts and approximately 10,000 pottery type identifications from the Early Mesolithic to the end of the Iron Age in Finland (c. 8900 calBC - 1300/1500 calAD). In addition, the artefacts are given period-based (subperiod) dating to allow their chronological affiliation. To facilitate data usage, we also offer an R-script to replicate the data visualisation provided in this paper and a Python script to merge the artefact information to the pictures. We further work towards an interactive user interface for data download and visualization

Uralic typology in the light of a new comprehensive dataset

Abstract This paper presents the Uralic Areal Typology Online (UraTyp 1.0), a typological dataset of 35 Uralic languages and a total of 360 features, mainly covering the levels of morphology, syntax, and phonology. The features belong to two different datasets: 195 features’ definitions originate from the Grambank (GB) database, developed for comparison of world language typology, whereas 165 features (UT) have been designed specifically to describe the typological variation within the Uralic language family. We present a series of analyses of the dataset demonstrating its scope and possibilities. The complete data set correctly identifies the main Uralic subgroups in a Principal Components Analysis, whereas GB data alone is insufficiently granular to detect this family-internal structure. Similar analyses limited to various typological subdomains also give variable results. A model-based admixture analysis identifies four distinct areas of historical interaction: Saami, Finnic, the Volga area and Ob-Ugric