Fluid Stigmergy: Investigating the self-organizing principles of animal collectives across scales
Clicks: 7
ID: 325154
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.6
/100
7 views
2 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #36 of 114 articles by views in integrative and comparative biology
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract Collective behavior is a ubiquitous phenomenon observed in a diverse array of species across scales, from single-celled microorganisms to large vertebrates like fish and birds. In aquatic and aerial environments, collective movements are inherently mechanical: as organisms move, they displace the surrounding medium, creating dynamic flow fields that provide opportunities for passive energy recycling and active fluid-mediated communication. We demonstrate how animals across scales assemble in fluid environments of different Reynolds number (Re) regimes. In addition, we highlight how emerging methodologies from artificial intelligence to biomimetic robotics enable new measurements of collective behavior in dynamic fluid environments. Finally, we propose a comparative framework that explores fluid-mediated collective behavior as a critical link between functional morphology and behavioral ecology.
| Reference Key |
openalex_W7203643664
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Hungtang Ko, Yangfan Zhang |
| Journal | integrative and comparative biology |
| Year | 2026 |
| DOI |
10.1093/icb/icag154
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.