| Title |
Density-dependent network structuring within and across wild animal systems
|
|---|---|
| Published in |
bioRxiv, July 2024
|
| DOI | 10.1101/2024.06.28.601262 |
| Authors |
Gregory F Albery, Daniel J Becker, Josh A Firth, Delphine De Moor, Sanjana Ravindran, Matthew Silk, Amy R Sweeny, Eric Vander Wal, Quinn Webber, Bryony Allen, Simon A Babayan, Sahas Barve, Mike Begon, Richard J Birtles, Theadora A Block, Barbara A Block, Janette E Bradley, Sarah Budischak, Christina Buesching, Sarah J Burthe, Aaron B Carlisle, Jennifer E Caselle, Ciro Cattuto, Alexis S Chaine, Taylor K Chapple, Barbara J Cheney, Timothy Clutton-Brock, Melissa Collier, David J Curnick, Richard J Delahay, Damien R Farine, Andy Fenton, Francesco Ferretti, Laura Feyrer, Helen Fielding, Vivienne Foroughirad, Celine Frere, Michael G Gardner, Eli Geffen, Stephanie S Godfrey, Andrea L Graham, Phil S Hammond, Maik Henrich, Marco Heurich, Paul Hopwood, Amiyaal Ilany, Joseph A Jackson, Nicola Jackson, David MP Jacoby, Ann-Marie Jacoby, Miloš Ježek, Lucinda Kirkpatrick, Alisa Klamm, James A Klarevas-Irby, Sarah Knowles, Lee Koren, Ewa Krzyszczyk, Jillian M Kusch, Xavier Lambin, Jeffrey E Lane, Herwig Leirs, Stephan T Leu, Bruce E Lyon, David W MacDonald, Anastasia E Madsen, Janet Mann, Marta Manser, Joachim Mariën, Apia Massawe, Robbie A McDonald, Kevin Morelle, Johann Mourier, Chris Newman, Kenneth Nussear, Brendah Nyaguthii, Mina Ogino, Laura Ozella, Craig Packer, Yannis P Papastamatiou, Steve Paterson, Eric Payne, Amy B Pedersen, Josephine M Pemberton, Noa Pinter-Wollman, Serge Planes, Aura Raulo, Rolando Rodríguez-Muñoz, Lauren Rudd, Christopher Sabuni, Pratha Sah, Robert J Schallert, Ben C Sheldon, Daizaburo Shizuka, Andrew Sih, David L Sinn, Vincent Sluydts, Orr Spiegel, Sandra Telfer, Courtney A Thomason, David M Tickler, Tom Tregenza, Kimberley VanderWaal, Sam Walmsley, Eric L Walters, Klara M Wanelik, Hal Whitehead, Elodie Wielgus, Jared Wilson-Aggarwal, Caroline Wohlfeil, Shweta Bansal |
| Abstract |
High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 16 | 40% |
| United States | 10 | 25% |
| Australia | 3 | 8% |
| Germany | 2 | 5% |
| France | 1 | 3% |
| New Zealand | 1 | 3% |
| Italy | 1 | 3% |
| Greece | 1 | 3% |
| Unknown | 5 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 53% |
| Scientists | 18 | 45% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |