Ecological Niche and Least-Cost Path Analyses to Estimate Optimal Migration Routes of Initial Upper Palaeolithic Populations to Eurasia

Part of the Replacement of Neanderthals by Modern Humans Series book series (RNMH)


This paper presents a computer-based method to estimate optimal migration routes of early human population groups by a combination of ecological niche analysis and least-cost path analysis. In the proposed method, niche probability is predicted by MaxEnt, an ecological niche model based on the maximum entropy theory. Location of known archaeological sites and environmental factors derived from palaeoterrain and palaeoclimate models, are input to the model to calculate the niche probability at each spatial pixel and weights of the environmental factors. The inverse of probability score is then used as an index of relative dispersal rate to accumulate the travel cost from a given origin. Based on this cumulative cost surface, least-cost paths from the origin to given destinations are visualised. This method was applied to the Initial Upper Palaeolithic population group (probably of modern humans) in Eurasia. The model identified three migration routes from the Levant to (1) Central Europe via Anatolia and Eastern Europe, (2) the Russian steppe via Caucasus Mountains, and (3) the Altai region via the southern coastal Iran and Afghanistan.


Ecological niche modelling Least-cost paths Environmental factors Initial Upper Palaeolithic Early modern human dispersal to Eurasia 



This research was financially supported by the MEXT KAKENHI Scientific Research Grant-in-Aid for Innovative Areas No. 1201 ‘Replacement of Neanderthals by Modern Humans: Testing Evolutionary Models of Learning’. The earlier version of this paper was presented at the 68th annual conference of the Anthropological Society of Nippon, held in Hamamatsu, Japan, in November 2014, and the Second International Conference of the Replacement of Neanderthals by Modern Humans, held at Date City, Hokkaido, Japan, in December 2014 (Kondo 2014). We would like to thank Takayuki Ako, Reiichiro Ishii, Hiroyuki Kamei, Hiroto Nakata, Atsushi Noguchi, Stephen Obrochta, and Philip Verhagen for their comments on the ideas presented in this paper.

The MODIS data product used in Fig. 2 was retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota,


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Research Institute for Humanity and NatureKita-ku, KyotoJapan
  2. 2.Waseda Institute for Advanced StudyWaseda UniversityTokyoJapan
  3. 3.The University MuseumThe University of TokyoTokyoJapan
  4. 4.Atmosphere and Ocean Research InstituteThe University of TokyoChibaJapan
  5. 5.Japan Agency for Marine-Earth Science and TechnologyYokosukaJapan
  6. 6.Nagoya University MuseumNagoya UniversityNagoyaJapan
  7. 7.Center for Ainu and Indigenous StudiesHokkaido UniversitySapporoJapan
  8. 8.National Institute of Polar ResearchTokyoJapan
  9. 9.Center for Spatial Information ScienceThe University of TokyoChibaJapan

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