Where do successful populations originate from?
Saved in:
| Title: | Where do successful populations originate from? |
|---|---|
| Authors: | Andras, Peter1 (AUTHOR) p.andras@keele.ac.uk, Stanton, Adam1 (AUTHOR) |
| Source: | Journal of Theoretical Biology. Sep2021, Vol. 524, pN.PAG-N.PAG. 1p. |
| Subjects: | Population dynamics, Human evolution, Computer simulation, Human geography |
| Abstract: | • Successful populations originate from rugged areas close to high-fertility lands. • We use simulations and geographical data to show this relationship objectively. • Our analysis predicts places where successful populations may have originated from. 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Theoretical Biology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 150696463 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Where do successful populations originate from? – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Andras%2C+Peter%22">Andras, Peter</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> p.andras@keele.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Stanton%2C+Adam%22">Stanton, Adam</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Theoretical+Biology%22">Journal of Theoretical Biology</searchLink>. Sep2021, Vol. 524, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Population+dynamics%22">Population dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Human+evolution%22">Human evolution</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Human+geography%22">Human geography</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: • Successful populations originate from rugged areas close to high-fertility lands. • We use simulations and geographical data to show this relationship objectively. • Our analysis predicts places where successful populations may have originated from. 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Theoretical Biology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=150696463 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.jtbi.2021.110734 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Population dynamics Type: general – SubjectFull: Human evolution Type: general – SubjectFull: Computer simulation Type: general – SubjectFull: Human geography Type: general Titles: – TitleFull: Where do successful populations originate from? Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Andras, Peter – PersonEntity: Name: NameFull: Stanton, Adam IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 09 Text: Sep2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 00225193 Numbering: – Type: volume Value: 524 Titles: – TitleFull: Journal of Theoretical Biology Type: main |
| ResultId | 1 |
