Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

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

View ORCID ProfileChristopher Bystroff
doi: https://doi.org/10.1101/2021.02.04.429734
Christopher Bystroff
1Dept of Biological Sciences, Dept of Computer Science, Rensselaer Polytechnic Institute, Troy NY 12180
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Christopher Bystroff
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

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.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted February 05, 2021.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Footprints to Singularity: A global population model explains late 20th century slow-down and predicts peak within ten years
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Footprints to Singularity: A global population model explains late 20th century slow-down and predicts peak within ten years
Christopher Bystroff
bioRxiv 2021.02.04.429734; doi: https://doi.org/10.1101/2021.02.04.429734
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Footprints to Singularity: A global population model explains late 20th century slow-down and predicts peak within ten years
Christopher Bystroff
bioRxiv 2021.02.04.429734; doi: https://doi.org/10.1101/2021.02.04.429734

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Ecology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4667)
  • Biochemistry (10332)
  • Bioengineering (7653)
  • Bioinformatics (26277)
  • Biophysics (13497)
  • Cancer Biology (10663)
  • Cell Biology (15389)
  • Clinical Trials (138)
  • Developmental Biology (8480)
  • Ecology (12800)
  • Epidemiology (2067)
  • Evolutionary Biology (16817)
  • Genetics (11378)
  • Genomics (15451)
  • Immunology (10591)
  • Microbiology (25141)
  • Molecular Biology (10187)
  • Neuroscience (54317)
  • Paleontology (399)
  • Pathology (1663)
  • Pharmacology and Toxicology (2889)
  • Physiology (4331)
  • Plant Biology (9223)
  • Scientific Communication and Education (1585)
  • Synthetic Biology (2551)
  • Systems Biology (6769)
  • Zoology (1459)