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Landscape rules predict optimal superhighways for the first peopling of Sahul


Archaeological data and demographic modelling suggest that the peopling of Sahul required substantial populations, occurred rapidly within a few thousand years and encompassed environments ranging from hyper-arid deserts to temperate uplands and tropical rainforests. How this migration occurred and how humans responded to the physical environments they encountered have, however, remained largely speculative. By constructing a high-resolution digital elevation model for Sahul and coupling it with fine-scale viewshed analysis of landscape prominence, least-cost pedestrian travel modelling and high-performance computing, we create over 125 billion potential migratory pathways, whereby the most parsimonious routes traversed emerge. Our analysis revealed several major pathways—superhighways—transecting the continent, that we evaluated using archaeological data. These results suggest that the earliest Australian ancestors adopted a set of fundamental rules shaped by physiological capacity, attraction to visually prominent landscape features and freshwater distribution to maximize survival, even without previous experience of the landscapes they encountered.

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Fig. 1: Data layers used to create optimal pathways.
Fig. 2: Visual-prominence aggregate viewshed for the entire Sahul landmass.
Fig. 3: Model-averaged pathway probabilities.

Data availability

All thresholded binary masks created from all FETE runs, the model-averaged composite grid, lakes and archaeological sites are made publicly available in standard geospatial data formats as part of our Supplementary Data. Due to large file size, we provide the two digital elevation models and aggregate viewshed in standard geospatial data formats via GitHub:

Code availability

Due to how the development of FETE was funded, it is not currently possible to make the source code available to the public. As an alternative to public release of the code, the full methodology of the baseline version of FETE is described in White and Barber21 and we describe modifications made to support our study here. Researchers who are interested in replicating the functionality of FETE can do so by using an open-source or commercial GIS software package in combination with basic scripting in a high-level programming language such as Python and following the methodology described herein. We provide all code used for analyses via GitHub:


  1. Laland, K. N. & O’Brien, M. J. Niche construction theory and archaeology. J. Archaeol. Method Theory 17, 303–322 (2010).

    Article  Google Scholar 

  2. Dunne, J. A. et al. The roles and impacts of human hunter-gatherers in North Pacific marine food webs. Sci. Rep. 6, 21179 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Crabtree, S. A., Bird, D. W. & Bird, R. B. Subsistence transitions and the simplification of ecological networks. Nat. Hum. Behav. 47, 165–177 (2019).

  4. Crabtree, S. A., Vaughn, L. J. S. & Crabtree, N. T. Reconstructing ancestral Pueblo food webs in the southwestern United States. J. Archaeol. Sci. 81, 116–127 (2017).

    Article  Google Scholar 

  5. Romanowska, I., Gamble, C., Bullock, S. & Sturt, F. Dispersal and the Movius line: testing the effect of dispersal on population density through simulation. Quat. Int. 431, 53–63 (2017).

    Article  Google Scholar 

  6. Grothmann, T. & Patt, A. Adaptive capacity and human cognition: the process of individual adaptation to climate change. Glob. Environ. Change 15, 199–213 (2005).

    Article  Google Scholar 

  7. Potts, R. Variability selection in hominid evolution. Evol. Anthropol. 7, 81–96 (1998).

    Article  Google Scholar 

  8. Thomsen, C. J. Ledetraad Til Nordisk Oldkyndighed (Kjöbenhavn, S.L. Møllers bogtr., 1836).

  9. Montelius, O. Der Orient und Europa (Königliche Akademie der schönen Wissenschaften, Geschichte und Altertumskunde, 1899).

  10. Hershkovitz, I. et al. The earliest modern humans outside Africa. Science 359, 456–459 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Braje, T. J., Dillehay, T. D., Erlandson, J. M., Klein, R. G. & Rick, T. C. Finding the first Americans. Science 358, 592–594 (2017).

    Article  CAS  PubMed  Google Scholar 

  12. Skoglund, P. et al. Genomic insights into the peopling of the Southwest Pacific. Nature 538, 510–513 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Tobler, R. et al. Aboriginal mitogenomes reveal 50,000 years of regionalism in Australia. Nature 544, 180–184 (2017).

    Article  CAS  PubMed  Google Scholar 

  14. Nielsen, R. et al. Tracing the peopling of the world through genomics. Nature 541, 302–310 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Crema, E. R., Habu, J., Kobayashi, K. & Madella, M. Summed probability distribution of 14C dates suggests regional divergences in the population dynamics of the Jomon Period in eastern Japan. PLoS ONE 11, e0154809 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Antón, S. C., Leonard, W. R. & Robertson, M. L. An ecomorphological model of the initial hominid dispersal from Africa. J. Hum. Evol. 43, 773–785 (2002).

    Article  PubMed  Google Scholar 

  17. Breeze, P. S. et al. Palaeohydrological corridors for hominin dispersals in the Middle East 250–70,000 years ago. Quat. Sci. Rev. 144, 155–185 (2016).

    Article  Google Scholar 

  18. Hughes, J. K., Haywood, A., Mithen, S. J., Sellwood, B. W. & Valdes, P. J. Investigating early hominin dispersal patterns: developing a framework for climate data integration. J. Hum. Evol. 53, 465–474 (2007).

    Article  PubMed  Google Scholar 

  19. Vahdati, A. R., Weissmann, J. D., Timmermann, A., Ponce de León, M. S. & Zollikofer, C. P. E. Drivers of Late Pleistocene human survival and dispersal: an agent-based modeling and machine learning approach. Quat. Sci. Rev. 221, 105867 (2019).

    Article  Google Scholar 

  20. Bradshaw, C. J. A. et al. Stochastic models support rapid peopling of Late Pleistocene Sahul. Nat. Commun. (20201).

  21. White, D. A. & Barber, S. B. Geospatial modeling of pedestrian transportation networks: a case study from precolumbian Oaxaca, Mexico. J. Archaeol. Sci. 39, 2684–2696 (2012).

    Article  Google Scholar 

  22. Binford, L. R. Constructing Frames of Reference: An Analytical Method for Archaeological Theory Building Using Ethnographic and Environmental Data (Univ. California Press, 2001).

  23. Kealy, S., Louys, J. & O’Connor, S. Least-cost pathway models indicate northern human dispersal from Sunda to Sahul. J. Hum. Evol. 125, 59–70 (2018).

    Article  PubMed  Google Scholar 

  24. Kealy, S., Louys, J. & O’Connor, S. Islands under the sea: a review of early modern human dispersal routes and migration hypotheses through Wallacea. J. Island Coast. Archaeol. 11, 364–384 (2016).

    Article  Google Scholar 

  25. Bird, M. I. et al. Palaeogeography and voyage modeling indicates early human colonization of Australia was likely from Timor-Roti. Quat. Sci. Rev. 191, 431–439 (2018).

    Article  Google Scholar 

  26. Kealy, S., Louys, J. & O’Connor, S. Reconstructing palaeogeography and inter-island visibility in the Wallacean Archipelago during the likely period of Sahul colonization 65-45 000 years ago. Archaeol. Prospect 24, 259–272 (2017).

    Article  Google Scholar 

  27. Norman, K. et al. An early colonisation pathway into northwest Australia 70-60,000 years ago. Quat. Sci. Rev. 180, 229–239 (2018).

    Article  Google Scholar 

  28. Bird, M. I. et al. Early human settlement of Sahul was not an accident. Sci. Rep. 9, 8220 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  29. O’Connell, J. F. & Allen, J. The restaurant at the end of the universe: modelling the colonisation of Sahul. Aust. Archaeol. 74, 5–31 (2012).

    Article  Google Scholar 

  30. Birdsell, J. B. Some population problems involving Pleistocene man. Cold Spring Harbor Symp. Quant. Biol. 22, 47–69 (1957).

  31. Bowdler, S. in Sunda and Sahul: Prehistoric Studies in Southeast Asia Melanesia and Australia (eds. Allen, al.) 205–246 (Academic Press, 1977).

  32. Horton, D. R. Water and woodland: the peopling of Australia. Aust. Inst. Aborig. Stud. Newsl. 16, 21–27 (1981).

    Google Scholar 

  33. Tindale, N. B. in Ecological Biogeography of Australia (ed. Keast, A.) 1761–1797 (Dr W Junk Publishers, 1981).

  34. Veth, P. Islands in the interior: a model for the colonization of Australia’s arid zone. Archaeol. Ocean. 24, 81–92 (1989).

    Article  Google Scholar 

  35. Veth, P. Islands in the Interior: The Dynamics of Prehistoric Adaptations Within the Arid Zone of Australia (International Monographs in Prehistory, 1993).

  36. Hiscock, P. & Wallis, L. A. in Desert Peoples (eds. Veth, P. et al.) 34–57 (Blackwell, 2008).

  37. Veth, P., O’Connor, S. & Wallis, L. A. Perspectives on ecological approaches in Australian archaeology. Aust. Archaeol. 50, 54–66 (2000).

    Article  Google Scholar 

  38. Hallam, S. J. The relevance of Old World archaeology to the first entry of man into new worlds: colonization seen from the Antipodes. Quat. Res. 8, 128–148 (1977).

    Article  Google Scholar 

  39. Lourandos, H. & Ross, A. The great ‘intensification debate’: its history and place In Australian archaeology. Aust. Archaeol. 39, 54–63 (1994).

    Article  Google Scholar 

  40. O’Connell, J. F. & Allen, J. The process, biotic impact, and global implications of the human colonization of Sahul about 47,000 years ago. J. Archaeol. Sci. 56, 73–84 (2015).

    Article  Google Scholar 

  41. Bird, M. I., O’Grady, D. & Ulm, S. Humans, water, and the colonization of Australia. Proc. Natl Acad. Sci. USA 113, 11477–11482 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Brown, C. T., Liebovitch, L. S. & Glendon, R. Lévy flights in Dobe Ju/’hoansi foraging patterns. Hum. Ecol. 35, 129–138 (2007).

    Article  Google Scholar 

  43. Hamilton, M. J., Milne, B. T., Walker, R. S. & Brown, J. H. Nonlinear scaling of space use in human hunter-gatherers. Proc. Natl Acad. Sci. USA 104, 4765–4769 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hamilton, M. J., Davidson, A. D., Sibly, R. M. & Brown, J. H. Universal scaling of production rates across mammalian lineages. Proc. R. Soc. B 278, 560–566 (2011).

    Article  PubMed  Google Scholar 

  45. Lock, G. & Pouncett, J. Walking the Ridgeway revisited: the methodological and theoretical implications of scale dependency for the derivation of slope and the calculation of least-cost pathways. In Proc. 37th International Conference (eds. Frischer, B. et al.) 192–203 (Archaeopress, 2010).

  46. Thomas, Z. A. et al. Tipping elements and amplified polar warming during the Last Interglacial. Quat. Sci. Rev. 233, 106222 (2020).

    Article  Google Scholar 

  47. Xu, C., Kohler, T. A., Lenton, T. M., Svenning, J.-C. & Scheffer, M. Future of the human climate niche. Proc. Natl Acad. Sci. USA 117, 11350–11355 (2020).

  48. Bradshaw, C. J. A. et al. Minimum founding populations for the first peopling of Sahul. Nat. Ecol. Evol. 3, 1057–1063 (2019).

    Article  PubMed  Google Scholar 

  49. Bowler, J. M. et al. New ages for human occupation and climatic change at Lake Mungo, Australia. Nature 421, 837–840 (2003).

    Article  CAS  PubMed  Google Scholar 

  50. Fitzsimmons, K. E., Stern, N. & Murray-Wallace, C. V. Depositional history and archaeology of the central Lake Mungo lunette, Willandra Lakes, southeast Australia. J. Archaeol. Sci. 41, 349–364 (2014).

    Article  Google Scholar 

  51. Kemp, J., Pietsch, T., Gontz, A. & Olley, J. Lacustrine–fluvial interactions in Australia’s Riverine Plains. Quat. Sci. Rev. 166, 352–362 (2017).

    Article  Google Scholar 

  52. Mueller, N. et al. Water observations from space: mapping surface water from 25 years of Landsat imagery across Australia. Remote Sens. Environ. 174, 341–352 (2016).

    Article  Google Scholar 

  53. Tindale, N. B. in Biogeography and Ecology in Australia (eds. Keast, A. et al.) 36–51 (Springer, 1959).

  54. Bowler, J. M., Jones, R., Allen, H. & Thorne, A. G. Pleistocene human remains from Australia: a living site and human cremation from Lake Mungo, western New South Wales. World Archaeol. 2, 39–60 (1970).

    Article  CAS  PubMed  Google Scholar 

  55. Jones, R. The geographical background to the arrival of man in Australia and Tasmania. Archaeol. Phys. Anthropol. Ocean 3, 186–215 (1968).

    Google Scholar 

  56. Reynolds, H. The land, the explorers and the aborigines. Hist. Stud. 19, 213–226 (1980).

    Article  Google Scholar 

  57. Bellavia, G. Extracting ‘natural pathways’ from a digital elevation model. In Proc. CAA 2001 (eds. Burenhult, G. & Arvidsson, J.) 5–12 (Archaeopress, 2002).

  58. Clendon, M. Reassessing Australia’s linguistic prehistory. Curr. Anthropol. 47, 39–61 (2006).

    Article  Google Scholar 

  59. McConvell, P. The linguistic prehistory of Australia: opportunities for dialogue with archaeology. Aust. Archaeol. 31, 3–27 (1990).

    Article  Google Scholar 

  60. Redd, A. J. & Stoneking, M. Peopling of Sahul: mtDNA variation in aboriginal Australian and Papua New Guinean populations. Am. J. Hum. Genet. 65, 808–828 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. van Holst Pellekaan, S. Genetic evidence for the colonization of Australia. Quat. Int. 285, 44–56 (2013).

    Article  Google Scholar 

  62. Pedro, N. et al. Papuan mitochondrial genomes and the settlement of Sahul. J. Hum. Genet. 65, 875–887 (2020).

  63. McBryde, I. in Australians to 1788 (eds. Mulvaney, D. J. & White, J. P.) 252–273 (Academy of the Societal Sciences in Australia, 1987).

  64. McAdam, L. & Davidson, I. in The Archaeology of Portable Art: Southeast Asian, Pacific, and Australian Perspectives (eds. Langley, M. et al.) 220–240 (Routledge, 2018).

  65. Smith, M. A. & Veth, P. M. Radiocarbon dates for baler shell in the Great Sandy Desert. Aust. Archaeol. 58, 37–38 (2004).

    Article  Google Scholar 

  66. Robertson, S. Significance of baler shell (Melo) at Olympic Dam, South Australia. J. Anthropol. Soc. South Aust. 36, 1–11 (2012).

    Google Scholar 

  67. Maloney, J. et al. Refining search areas for submerged archaeological resources using subbottom data and applied geomorphology. in Ocean Sciences Meeting 2020 (2020).

  68. Flegontov, P. et al. Palaeo-Eskimo genetic ancestry and the peopling of Chukotka and North America. Nature 570, 236–240 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Vialou, D., Benabdelhadi, M., Feathers, J., Fontugne, M. & Vialou, A. V. Peopling South America’s centre: the late Pleistocene site of Santa Elina. Antiquity 91, 865–884 (2017).

    Article  Google Scholar 

  70. Hoguin, R., Franco, N. V. & Flegenheimer, N. Humans, technology, and environment in the early peopling of South America. PaleoAmerica 5, 307–308 (2019).

    Article  Google Scholar 

  71. Klein, H. S. The first Americans: the current debate. J. Interdiscip. Hist. 46, 543–561 (2016).

    Article  Google Scholar 

  72. Binford, L. R. The archaeology of place. J. Anthropol. Archaeol. 1, 5–31 (1982).

    Article  Google Scholar 

  73. Benjamin, J. et al. Aboriginal artefacts on the continental shelf reveal ancient drowned cultural landscapes in northwest Australia. PLoS ONE 15, e0233912 (2020).

  74. King, R. et al. Controlled-source electromagnetic methods to investigate the submerged cultural landscapes of the Pacific continental shelf. in Ocean Sciences Meeting 2020 (2020).

  75. Gustas, R. & Supernant, K. Least cost path analysis of early maritime movement on the Pacific Northwest Coast. J. Archaeol. Sci. 78, 40–56 (2017).

    Article  Google Scholar 

  76. Whiteway, T. G. Australian Bathymetry and Topography Grid (Geoscience Australia, 2009).

  77. Beaman, R. J. 3DGBR: A High-Resolution Depth Model for the Great Barrier Reef and Coral Sea (RRRC, 2010).

  78. Beaman, R. J. High-Resolution Depth Model for Northern Australia—100m (Geoscience Australia, 2018).

  79. GEBCO Grid (GEBCO, 2019);

  80. Daniell, J. J. Development of a bathymetric grid for the Gulf of Papua and adjacent areas: a note describing its development. J. Geophys. Res. Earth Surf. (2008).

  81. Tickle, P. Digital Elevation Models User Guide: 1second DSM, DEM & DEM-S; 3second DSM, DEM & DEM-S (Geoscience Australia, 2010).

  82. Jarvis, A., Guevara, E., Reuter, H. I. & Nelson, A. D. Hole-filled SRTM for the globe v.4 (CGIAR Consortium for Spatial Information, 2008).

  83. Dungan, K. A., White, D., Déderix, S., Mills, B. J. & Safi, K. A total viewshed approach to local visibility in the Chaco World. Antiquity 92, 905–921 (2018).

    Article  Google Scholar 

  84. Bliege Bird, R. et al. Fire mosaics and habitat choice in nomadic foragers. Proc. Natl Acad. Sci. USA 117, 12904–12914 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Pandolf, K. B., Givoni, B. & Goldman, R. F. Predicting energy expenditure with loads while standing or walking very slowly. J. Appl. Physiol. 43, 577–581 (1977).

    Article  CAS  PubMed  Google Scholar 

  86. Looney, D. P. et al. Metabolic costs of military load carriage over complex terrain. Mil. Med. 183, e357–e362 (2018).

    Article  PubMed  Google Scholar 

  87. Soule, R. G. & Goldman, R. F. Terrain coefficients for energy cost prediction. J. Appl. Physiol. 32, 706–708 (1972).

    Article  CAS  PubMed  Google Scholar 

  88. Santee, W., Blanchard, L., Speckman, K., Gonzalez, J. & Wallace, R. Load Carriage Model Development and Testing with Field Data (USARIEM, 2003).

  89. Wood, B. M. & Wood, Z. J. Energetically optimal travel across terrain: visualizations and a new metric of geographic distance with anthropological applications. in Proc. SPIE 6060 Visualization and Data Analysis 2006 (eds. Erbacher, R. F. et al.) 60600F-1–60600F-7 (2006).

  90. Tobler, W. Three Presentations on Geographical Analysis and Modeling (National Center for Geographic Information and Analysis, 1993).

  91. Mifflin, M. D. et al. A new predictive equation for resting energy expenditure in healthy individuals. Am. J. Clin. Nutr. 51, 241–247 (1990).

    Article  CAS  PubMed  Google Scholar 

  92. Frankenfield, D., Roth-Yousey, L. & Compher, C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J. Am. Diet. Assoc. 105, 775–789 (2005).

    Article  PubMed  Google Scholar 

  93. Williams, A. N., Ulm, S., Smith, M. & Reid, J. AustArch: a database of 14C and non-14C ages from archaeological sites in Australia—composition, compilation and review. Internet Archaeol. (2014).

  94. Rodríguez-Rey, M. et al. Criteria for assessing the quality of Middle Pleistocene to Holocene vertebrate fossil ages. Quat. Geochronol. 30, 69–79 (2015).

    Article  Google Scholar 

  95. Bird, M. I. et al. The efficiency of charcoal decontamination for radiocarbon dating by three pre-treatments—ABOX, ABA and hypy. Quat. Geochronol. 22, 25–32 (2014).

    Article  Google Scholar 

  96. Alex, B. et al. Radiocarbon chronology of Manot Cave, Israel and Upper Paleolithic dispersals. Sci. Adv. 3, e1701450 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  97. David, B. et al. 45,610–52,160 years of site and landscape occupation at Nawarla Gabarnmang, Arnhem Land plateau (northern Australia). Quat. Sci. Rev. 215, 64–85 (2019).

    Article  Google Scholar 

  98. Wood, R. et al. Towards an accurate and precise chronology for the colonization of Australia: the example of Riwi, Kimberley, Western Australia. PLoS ONE 11, e0160123 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Kiskowski, M. A., Hancock, J. F. & Kenworthy, A. K. On the use of Ripley’s K-function and its derivatives to analyze domain size. Biophys. J. 97, 1095–1103 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Kolmogorov, A. Sulla determinazione empirica di una legge di distribuzione. Giornale dell’Istituto Italiano degli Attuari 4, 83–91 (1933).

    Google Scholar 

  101. Smirnov, N. Table for estimating the goodness of fit of empirical distributions. Ann. Math. Stat. 19, 279–281 (1948).

    Article  Google Scholar 

  102. Besag, J. Efficiency of pseudolikelihood estimation for simple Gaussian fields. Biometrika 64, 616–618 (1977).

    Article  Google Scholar 

  103. Gallant, J., Wilson, N., Dowling, T., Read, A. & Inskeep, C. SRTM-derived 1 Second Digital Elevation Models Version 1.0 (Geoscience Australia, 2011).

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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the US Department of Energy or the United States Government. This research was done by the Australian Research Council Centre of Excellence for Australian Biodiversity and Heritage (CE170100015) and the ASU-SFI Center for Biosocial Complex Systems. M.I.B. is the recipient of an Australian Research Council Laureate Fellowship (FL140100044). We thank the Santa Fe Institute for support in beginning this research. For assistance in developing the basis of the paper, we thank K. Norman, F. Petchey, M. Price, S. Slater, C. McGuire and R. Wood. We thank R. Roberts for comments on the paper. Approved for public release: SAND2021-1499 J.

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Authors and Affiliations



S.A.C., S.U., M.I.B. and C.J.A.B. obtained funding from the Australian Research Council Centre of Excellence for Australian Biodiversity and Heritage and the ASU-SFI Center for Biosocial Complex Systems. D.A.W. and S.A.C. developed the FETE models. D.A.W., S.A.C. and F.S. did statistical evaluations. R.J.B. compiled seamless terrestrial and bathymetric digital elevation model data. S.A.C., D.A.W., S.U., A.N.W, C.J.A.B., F.S. and M.I.B. wrote the main text with specialist contributions from other authors. All authors provided comments and revisions.

Corresponding author

Correspondence to Stefani A. Crabtree.

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The authors declare no competing interests.

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Peer review information Nature Human Behaviour thanks Claudine Gravel-Miguel, Emma Slayton, Colin Wren and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Data layers used to create all-of-Sahul dataset.

The Sahul digital elevation model is an amalgamation of existing regional- and global-scale digital elevation models as shown here.

Extended Data Fig. 2 Bathymetry of Sahul at >50,000 years.

Base layers Natural Earth 1:10 M Land Polygons and SRTM-derived 1 Second Digital Elevation Models Version 1.0103. All data are available under Creative Commons Attribution 4.0 International Licence (

Extended Data Fig. 3 Visual prominence of Sahul at >50,000 years.

Base layers Natural Earth 1:10 M Land Polygons and SRTM-derived 1 Second Digital Elevation Models Version 1.0103. All data are available under Creative Commons Attribution 4.0 International Licence (

Extended Data Fig. 4 Bathymetry of Sahul at >50,000 years, plus Strahler Stream Order 9 streams extended to the coastline.

Base layers Natural Earth 1:10 M Land Polygons and SRTM-derived 1 Second Digital Elevation Models Version 1.0103. All data are available under Creative Commons Attribution 4.0 International Licence (

Extended Data Fig. 5 Superhighways of Sahul at >50,000 years with no archaeological sites.

Superhighways of Sahul at >50,000 years with no archaeological sites or labels included for figure reproduction purposes.

Extended Data Fig. 6 Superhighways of Sahul at >50,000 years with archaeological sites of >35,000 years, no labels.

Superhighways of Sahul at >50,000 years with archaeological sites of >35,000 years, no labels included for figure reproduction purposes.

Extended Data Fig. 7 Superhighways of Sahul at >50,000 years with archaeological sites of >35,000 years, with labels.

Superhighways of Sahul at >50,000 years with archaeological sites of >35,000 years, labels included for clarity.

Extended Data Fig. 8 Named archaeological sites from reference archaeological dataset.

Taken with Supplementary Table 8, readers can assess the age of sites corresponding to paths across Sahul.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5 and Supplementary Tables 1–9.

Reporting Summary

Supplementary Table

Supplemental Tables 1–9 in a combined workbook with multiple tabs.

Supplementary Data

This file contains five folders or code and data: (1) Supplemental Network Raw Rasters. Raw output for each of our scenarios in the form of binary raster masks for each model at all cutoffs. These data are the foundation input for determining distances between sites and networks. (2) Shapefile containing the sites presented in Supplementary Table 1. (3) Raw raster version of the path network map presented in Fig. 3. (4) Shapefiles containing best-available-approximation polygons for ancient lakes in the study region. (5) Binary raster mask for the landmass of Sahul used in this analysis.

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Crabtree, S.A., White, D.A., Bradshaw, C.J.A. et al. Landscape rules predict optimal superhighways for the first peopling of Sahul. Nat Hum Behav 5, 1303–1313 (2021).

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