Author
Guus Kroonen
Other affiliations: Leiden University
Bio: Guus Kroonen is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Population & Steppe. The author has an hindex of 9, co-authored 25 publications receiving 658 citations. Previous affiliations of Guus Kroonen include Leiden University.
Topics: Population, Steppe, Kinship, Germanic languages, Corded Ware culture
Papers
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University of Copenhagen1, University of Cambridge2, Wellcome Trust Sanger Institute3, Leiden University4, Harvard University5, Technical University of Denmark6, Al-Farabi University7, University of Chicago8, Karagandy State University9, University of Alaska Fairbanks10, Istanbul University11, Hazara University12, University of Gothenburg13, Russian Academy of Sciences14, Gazi University15, Islamia College University16, University of Exeter17, Government of Khyber Pakhtunkhwa18, Irkutsk State University19, University of Alberta20, Paul Sabatier University21, University of California, Berkeley22
TL;DR: Analysis of ancient whole-genome sequences from across Inner Asia and Anatolia shows that the Botai people associated with the earliest horse husbandry derived from a hunter-gatherer population deeply diverged from the Yamnaya, and suggests distinct migrations bringing West Eurasian ancestry into South Asia before and after, but not at the time of, YamNaya culture.
Abstract: The Yamnaya expansions from the western steppe into Europe and Asia during the Early Bronze Age (~3000 BCE) are believed to have brought with them Indo-European languages and possibly horse husbandry. We analyze 74 ancient whole-genome sequences from across Inner Asia and Anatolia and show that the Botai people associated with the earliest horse husbandry derived from a hunter-gatherer population deeply diverged from the Yamnaya. Our results also suggest distinct migrations bringing West Eurasian ancestry into South Asia before and after but not at the time of Yamnaya culture. We find no evidence of steppe ancestry in Bronze Age Anatolia from when Indo-European languages are attested there. Thus, in contrast to Europe, Early Bronze Age Yamnaya-related migrations had limited direct genetic impact in Asia.
273 citations
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University of Copenhagen1, Russian Academy of Sciences2, University of Lisbon3, University of Bern4, Swiss Institute of Bioinformatics5, Technical University of Denmark6, University of Chicago7, Chinese Academy of Sciences8, Leiden University9, Arctic and Antarctic Research Institute10, University of Cambridge11, University of Greenland12, American Museum of Natural History13, National Institutes of Health14, University of Helsinki15, University of Illinois at Urbana–Champaign16, University of Gothenburg17, University of Turku18, Wellcome Trust Sanger Institute19, University of California, Berkeley20, Southern Methodist University21
TL;DR: Analysis of 34 newly recovered ancient genomes from northeastern Siberia reveal at least three major migration events in the late Pleistocene population history of the region, including an initial peopling by a previously unknown Palaeolithic population of ‘Ancient North Siberians’ and a Holocene migration of other East Asian-related peoples, which generated the mosaic genetic make-up of contemporary peoples.
Abstract: Northeastern Siberia has been inhabited by humans for more than 40,000 years but its deep population history remains poorly understood. Here we investigate the late Pleistocene population history of northeastern Siberia through analyses of 34 newly recovered ancient genomes that date to between 31,000 and 600 years ago. We document complex population dynamics during this period, including at least three major migration events: an initial peopling by a previously unknown Palaeolithic population of ‘Ancient North Siberians’ who are distantly related to early West Eurasian hunter-gatherers; the arrival of East Asian-related peoples, which gave rise to ‘Ancient Palaeo-Siberians’ who are closely related to contemporary communities from far-northeastern Siberia (such as the Koryaks), as well as Native Americans; and a Holocene migration of other East Asian-related peoples, who we name ‘Neo-Siberians’, and from whom many contemporary Siberians are descended. Each of these population expansions largely replaced the earlier inhabitants, and ultimately generated the mosaic genetic make-up of contemporary peoples who inhabit a vast area across northern Eurasia and the Americas. Analyses of 34 ancient genomes from northeastern Siberia, dating to between 31,000 and 600 years ago, reveal at least three major migration events in the late Pleistocene population history of the region.
211 citations
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TL;DR: In this paper, the authors explain how the Corded Ware Culture in Europe was formed in terms of local adaptations and interactions between migrant Yamnaya people from the Pontic-Caspian steppe and indigenous North European Neolithic cultures.
Abstract: Recent genetic, isotopic and linguistic research has dramatically changed our understanding of how the Corded Ware Culture in Europe was formed. Here the authors explain it in terms of local adaptations and interactions between migrant Yamnaya people from the Pontic-Caspian steppe and indigenous North European Neolithic cultures. The original herding economy of the Yamnaya migrants gradually gave way to new practices of crop cultivation, which led to the adoption of new words for those crops. The result of this hybridisation process was the formation of a new material culture, the Corded Ware Culture, and of a new dialect, Proto-Germanic. Despite a degree of hostility between expanding Corded Ware groups and indigenous Neolithic groups, stable isotope data suggest that exogamy provided a mechanism facilitating their integration. This article should be read in conjunction with that by Heyd (2017, in this issue).
140 citations
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19 Jul 2013TL;DR: This new etymological dictionary offers a wealth of material collected from old and new Germanic sources, ranging from Gothic to Elfdalian, from Old English to the Swiss dialects, and incorporates several important advances in Proto-Germanic phonology, morphology and derivation.
Abstract: The Germanic languages, which include English, German, Dutch and Scandinavian, belong to the best-studied languages in the world, but the picture of their parent language, Proto-Germanic, continues to evolve. This new etymological dictionary offers a wealth of material collected from old and new Germanic sources, ranging from Gothic to Elfdalian, from Old English to the Swiss dialects, and incorporates several important advances in Proto-Germanic phonology, morphology and derivation. With its approximately 2,800 headwords and at least as many derivations, it covers the larger part of the Proto-Germanic vocabulary, and attempts to trace it back to its Proto-Indo-European foundations. The result is a landmark etymological study indispensable to Indo-Europeanists and Germanicists, as well as to the non-specialist.
134 citations
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TL;DR: In this article, the authors identify the Western Eurasian steppes, especially the lower Volga-Don region, as the homeland of modern domestic horses and map the population changes accompanying domestication from 273 ancient horse genomes.
Abstract: Domestication of horses fundamentally transformed long-range mobility and warfare1. However, modern domesticated breeds do not descend from the earliest domestic horse lineage associated with archaeological evidence of bridling, milking and corralling2–4 at Botai, Central Asia around 3500 bc3. Other longstanding candidate regions for horse domestication, such as Iberia5 and Anatolia6, have also recently been challenged. Thus, the genetic, geographic and temporal origins of modern domestic horses have remained unknown. Here we pinpoint the Western Eurasian steppes, especially the lower Volga-Don region, as the homeland of modern domestic horses. Furthermore, we map the population changes accompanying domestication from 273 ancient horse genomes. This reveals that modern domestic horses ultimately replaced almost all other local populations as they expanded rapidly across Eurasia from about 2000 bc, synchronously with equestrian material culture, including Sintashta spoke-wheeled chariots. We find that equestrianism involved strong selection for critical locomotor and behavioural adaptations at the GSDMC and ZFPM1 genes. Our results reject the commonly held association7 between horseback riding and the massive expansion of Yamnaya steppe pastoralists into Europe around 3000 bc8,9 driving the spread of Indo-European languages10. This contrasts with the scenario in Asia where Indo-Iranian languages, chariots and horses spread together, following the early second millennium bc Sintashta culture11,12. Analysis of 273 ancient horse genomes reveals that modern domestic horses originated in the Western Eurasian steppes, especially the lower Volga-Don region.
83 citations
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TL;DR: The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models to enable researchers and students alike to reproduce the analyses and learn by doing.
Abstract: The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this
1,679 citations
01 Jan 2016
TL;DR: In this article, a construction grammar approach to argument structure is used to deal with argument structure in a good book with a cup of tea in the afternoon, but instead they cope with some harmful virus inside their computer.
Abstract: Thank you for downloading constructions a construction grammar approach to argument structure. As you may know, people have search numerous times for their favorite readings like this constructions a construction grammar approach to argument structure, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some harmful virus inside their computer.
979 citations
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TL;DR: Animal Bones in ArchaeologyBook of Notes and Drawings for Beginners.
Abstract: Animal Bones in Archaeology Book of Notes and Drawings for Beginners. By Michael L. Ryder. (Mammal Society Handbooks.) Pp. xxiv + 65. (Blackwell (Scientific): Oxford and Edinburgh. Published for the Mammal Society, 1969.) 17s.
732 citations
Broad Institute1, Harvard University2, University of Tübingen3, Max Planck Society4, University of Mainz5, University of Washington6, University of California, Berkeley7, Massachusetts Institute of Technology8, Stockholm University9, University of Adelaide10, The Heritage Foundation11, National Museum of Natural History12, Sultan Qaboos University13, University of Edinburgh14, University of Costa Rica15, University of Antioquia16, Rambam Health Care Campus17, University of Pécs18, Al Akhawayn University19, Catholic University of the Sacred Heart20, University of Oxford21, Belgorod State University22, University of Toronto23, University of Buenos Aires24, University of Bern25, Russian Academy of Sciences26, Paul Sabatier University27, North-Eastern Federal University28, University of Chicago29, University of Arizona30, Stony Brook University31, University of Bergen32, Illumina33, Sofia Medical University34, Bashkir State University35, University of Cambridge36, Vilnius University37, Estonian Biocentre38, University of Strasbourg39, Amgen40, University College London41, Gladstone Institutes42, University of Tartu43, University of Oulu44, Muhimbili University of Health and Allied Sciences45, University of Palermo46, University of Tarapacá47, University of Chile48, Academy of Sciences of Uzbekistan49, Armenian National Academy of Sciences50, University of North Texas51, University of Santiago de Compostela52, University of Kharkiv53, Higher University of San Andrés54, Novosibirsk State University55, Leidos56, Lebanese American University57, University of Split58, University of Pennsylvania59, Banaras Hindu University60, Centre for Cellular and Molecular Biology61, Estonian Academy of Sciences62, Pompeu Fabra University63, Howard Hughes Medical Institute64
TL;DR: The authors showed that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunters-gatherer related ancestry.
Abstract: We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had ∼44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.
442 citations
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Harvard University1, Radcliffe Institute for Advanced Study2, Broad Institute3, University of California, Berkeley4, Howard Hughes Medical Institute5, Massachusetts Institute of Technology6, Sapienza University of Rome7, University of Padua8, Queen's University Belfast9, Russian Academy of Sciences10, Al-Farabi University11, University of Pennsylvania12, University College Dublin13, University of Vienna14, Pennsylvania State University15, Max Planck Society16, Centre for Cellular and Molecular Biology17, Birbal Sahni Institute of Palaeobotany18, Emory University19, Centre national de la recherche scientifique20, Kyrgyz National University21, Altai State University22, Academy of Sciences of the Czech Republic23, University of Oxford24, South Ural State University25, Kemerovo State University26, University College London27, Northwest University (China)28, University of Pittsburgh29, Samara State University30, Chelyabinsk State University31, University of Bologna32, Academy of Sciences of Uzbekistan33, University of Winnipeg34, Simon Fraser University35, National Museum of Natural History36, Tomsk State University37, Naturhistorisches Museum38, Národní muzeum39, Hazara University40, Deccan College Post-Graduate and Research Institute41, Pompeu Fabra University42, Hartwick College43, University of California, Santa Barbara44, Washington University in St. Louis45
TL;DR: It is shown that Steppe ancestry then integrated further south in the first half of the second millennium BCE, contributing up to 30% of the ancestry of modern groups in South Asia, supporting the idea that the archaeologically documented dispersal of domesticates was accompanied by the spread of people from multiple centers of domestication.
Abstract: By sequencing 523 ancient humans, we show that the primary source of ancestry in modern South Asians is a prehistoric genetic gradient between people related to early hunter-gatherers of Iran and Southeast Asia. After the Indus Valley Civilization's decline, its people mixed with individuals in the southeast to form one of the two main ancestral populations of South Asia, whose direct descendants live in southern India. Simultaneously, they mixed with descendants of Steppe pastoralists who, starting around 4000 years ago, spread via Central Asia to form the other main ancestral population. The Steppe ancestry in South Asia has the same profile as that in Bronze Age Eastern Europe, tracking a movement of people that affected both regions and that likely spread the distinctive features shared between Indo-Iranian and Balto-Slavic languages.
354 citations