Footprints to singularity: A global population model explains late 20th century slow-down and predicts peak within ten years.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 02 02 2021
accepted: 05 05 2021
entrez: 20 5 2021
pubmed: 21 5 2021
medline: 7 10 2021
Statut: epublish

Résumé

Projections of future global human population are traditionally made using birth/death trend extrapolations, but these methods ignore limits. Expressing humanity as a K-selected species whose numbers are limited by the global carrying capacity produces a different outlook. Population data for the second millennium up to the year 1970 was fit to a hyper-exponential growth equation, where the rate constant for growth itself grows exponentially due to growth of life-saving technology. The discrepancies between the projected growth and the actual population data since 1970 are accounted for by a decrease in the global carrying capacity due to ecosystem degradation. A system dynamics model that best fits recent population numbers suggests that the global biocapacity may already have been reduced to one-half of its historical value and global carrying capacity may be at its 1965 level and falling. Simulations suggest that population may soon peak or may have already peaked. Population projections depend strongly on the unknown fragility or robustness of the Earth's essential ecosystem services that affect agricultural production. Numbers for the 2020 global census were not available for this study.

Identifiants

pubmed: 34014929
doi: 10.1371/journal.pone.0247214
pii: PONE-D-21-03679
pmc: PMC8136733
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0247214

Déclaration de conflit d'intérêts

The author has declared that no competing interests exist. Salary was provided by RPI, NIH and Grantham Foundation. The donors, Grantham Foundation and NIH, do not have any competing interest in this work.

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Auteurs

Christopher Bystroff (C)

Dept of Biological Sciences, Dept of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, United Sates of America.

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Classifications MeSH