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

Computational capability of ecological dynamics

View ORCID ProfileMasayuki Ushio, Kazufumi Watanabe, Yasuhiro Fukuda, Yuji Tokudome, View ORCID ProfileKohei Nakajima
doi: https://doi.org/10.1101/2021.09.15.460556
Masayuki Ushio
1Hakubi Center, Kyoto University, Kyoto 606-8501, Japan / Center for Ecological Research, Kyoto University, Otsu 520-2113, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Masayuki Ushio
  • For correspondence: ong8181@gmail.com k_nakajima@mech.t.u-tokyo.ac.jp
Kazufumi Watanabe
2B.Creation Inc., Ashiya, Hyogo 659-0068, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yasuhiro Fukuda
3Graduate School of Agricultural Science, Tohoku University, Osaki, Miyagi 989-6711, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yuji Tokudome
4Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kohei Nakajima
4Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kohei Nakajima
  • For correspondence: ong8181@gmail.com k_nakajima@mech.t.u-tokyo.ac.jp
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Ecological dynamics is driven by an ecological network consisting of complex interactions. Information processing capability of artificial networks has been exploited as a computational resource, yet whether an ecological network possesses a computational capability and how we can exploit it remain unclear. Here, we show that ecological dynamics can be exploited as a computational resource. We call this approach “Ecological Reservoir Computing” (ERC) and developed two types of ERC. In silico ERC reconstructs ecological dynamics from empirical time series and uses simulated system responses as reservoir states, which predicts near future of chaotic dynamics and emulates nonlinear dynamics. The real-time ERC uses population dynamics of a unicellular organism, Tetrahymena thermophila. Medium temperature is an input signal and changes in population abundance are reservoir states. Intriguingly, the real-time ERC has necessary conditions for reservoir computing and is able to make near future predictions of model and empirical time series.

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. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted September 17, 2021.
Download PDF

Supplementary Material

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.
Computational capability of ecological dynamics
(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
Computational capability of ecological dynamics
Masayuki Ushio, Kazufumi Watanabe, Yasuhiro Fukuda, Yuji Tokudome, Kohei Nakajima
bioRxiv 2021.09.15.460556; doi: https://doi.org/10.1101/2021.09.15.460556
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Computational capability of ecological dynamics
Masayuki Ushio, Kazufumi Watanabe, Yasuhiro Fukuda, Yuji Tokudome, Kohei Nakajima
bioRxiv 2021.09.15.460556; doi: https://doi.org/10.1101/2021.09.15.460556

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 (3579)
  • Biochemistry (7526)
  • Bioengineering (5486)
  • Bioinformatics (20703)
  • Biophysics (10261)
  • Cancer Biology (7939)
  • Cell Biology (11585)
  • Clinical Trials (138)
  • Developmental Biology (6574)
  • Ecology (10145)
  • Epidemiology (2065)
  • Evolutionary Biology (13556)
  • Genetics (9502)
  • Genomics (12796)
  • Immunology (7888)
  • Microbiology (19460)
  • Molecular Biology (7618)
  • Neuroscience (41917)
  • Paleontology (307)
  • Pathology (1253)
  • Pharmacology and Toxicology (2182)
  • Physiology (3253)
  • Plant Biology (7011)
  • Scientific Communication and Education (1291)
  • Synthetic Biology (1942)
  • Systems Biology (5410)
  • Zoology (1108)