Prof Peter Andras P.Andras@napier.ac.uk
Dean of School of Computing Engineering and the Built Environment
Where do successful populations originate from?
Andras, Peter; Stanton, Adam
Authors
Adam Stanton
Abstract
In order to understand the dynamics of emergence and spreading of socio-technical innovations and population moves it is important to determine the place of origin of these populations. Here we focus on the role of geographical factors, such as land fertility and mountains in the context of human population evolution and distribution dynamics. We use a constrained diffusion-based computational model, computer simulations and the analysis of geographical and land-quality data. Our analysis shows that successful human populations, i.e. those which become dominant in their socio – geographical environment, originate from lands of many valleys with relatively low land fertility, which are close to areas of high land fertility. Many of the homelands predicted by our analysis match the assumed homelands of known successful populations (e.g. Bantus, Turkic, Maya). We also predict other likely homelands as well, where further archaeological, linguistic or genetic exploration may confirm the place of origin for populations with no currently identified urheimat. Our work is significant because it advances the understanding of human population dynamics by guiding the identification of the origin locations of successful populations.
Citation
Andras, P., & Stanton, A. (2021). Where do successful populations originate from?. Journal of Theoretical Biology, 524, Article 110734. https://doi.org/10.1016/j.jtbi.2021.110734
| Journal Article Type | Article |
|---|---|
| Acceptance Date | Apr 22, 2021 |
| Online Publication Date | May 1, 2021 |
| Publication Date | 2021-09 |
| Deposit Date | Nov 22, 2021 |
| Journal | Journal of Theoretical Biology |
| Print ISSN | 0022-5193 |
| Publisher | Elsevier |
| Peer Reviewed | Peer Reviewed |
| Volume | 524 |
| Article Number | 110734 |
| DOI | https://doi.org/10.1016/j.jtbi.2021.110734 |
| Keywords | Computational modelling, Socio-technical evolution, Socio-biological simulation, Human geography, Geography of speciation |
| Public URL | http://researchrepository.napier.ac.uk/Output/2808851 |
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