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Prehistoric human migration between Sundaland and South Asia was driven by sea-level rise

  • Hie Lim Kim*
  • , Tanghua Li
  • , Namrata Kalsi
  • , Hung Tran The Nguyen
  • , Timothy A. Shaw
  • , Khai C. Ang
  • , Keith C. Cheng
  • , Aakrosh Ratan
  • , W. Richard Peltier
  • , Dhrubajyoti Samanta
  • , Mahesh Pratapneni
  • , Stephan C. Schuster (Co-last Author)
  • , Benjamin P. Horton (Co-last Author)
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

21 Downloads (CityUHK Scholars)

Abstract

Rapid sea-level rise between the Last Glacial Maximum (LGM) and the mid-Holocene transformed the Southeast Asian coastal landscape, but the impact on human demography remains unclear. Here, we create a paleogeographic map, focusing on sea-level changes during the period spanning the LGM to the present-day and infer the human population history in Southeast and South Asia using 763 high-coverage whole-genome sequencing datasets from 59 ethnic groups. We show that sea-level rise, in particular meltwater pulses 1 A (MWP1A, ~14,500–14,000 years ago) and 1B (MWP1B, ~11,500–11,000 years ago), reduced land area by over 50% since the LGM, resulting in segregation of local human populations. Following periods of rapid sea-level rises, population pressure drove the migration of Malaysian Negritos into South Asia. Integrated paleogeographic and population genomic analysis demonstrates the earliest documented instance of forced human migration driven by sea-level rise. © 2023, The Author(s).
Original languageEnglish
Article number150
JournalCommunications Biology
Volume6
Online published4 Feb 2023
DOIs
Publication statusPublished - 2023
Externally publishedYes

Funding

We thank Pavel Adamek, Elena Gusareva, Xianfeng Wang, Sharon Longford, Cassie E. Heinle, Sam Spence, Amit Ghosh, and Regin Tiong, for their helpful comments on writing the manuscript. H.L.K. was supported by The Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RG100/20). The computational work for this article was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg). B.P.H., T.L., T.A.S., D.S. were funded by the Ministry of Education Academic Research Fund MOE2019-T3-1-004 and MOE-T2EP50120-0007, the National Research Foundation Singapore, and the Singapore Ministry of Education, under the Research Centres of Excellence initiative. The GIA modelling is conducted in part using the research computing facilities and/or advisory services offered by Information Technology Services, the University of Hong Kong. This work is Earth Observatory of Singapore contribution number 439.

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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