Albery Gregory F, Becker Daniel J, Firth Josh A, De Moor Delphine, Ravindran Sanjana, Silk Matthew, Sweeny Amy R, Vander Wal Eric, Webber Quinn, Allen Bryony, Babayan Simon A, Barve Sahas, Begon Mike, Birtles Richard J, Block Theadora A, Block Barbara A, Bradley Janette E, Budischak Sarah, Buesching Christina, Burthe Sarah J, Carlisle Aaron B, Caselle Jennifer E, Cattuto Ciro, Chaine Alexis S, Chapple Taylor K, Cheney Barbara J, Clutton-Brock Timothy, Collier Melissa, Curnick David J, Delahay Richard J, Farine Damien R, Fenton Andy, Ferretti Francesco, Feyrer Laura, Fielding Helen, Foroughirad Vivienne, Frere Celine, Gardner Michael G, Geffen Eli, Godfrey Stephanie S, Graham Andrea L, Hammond Phil S, Henrich Maik, Heurich Marco, Hopwood Paul, Ilany Amiyaal, Jackson Joseph A, Jackson Nicola, Jacoby David M P, Jacoby Ann-Marie, Ježek Miloš, Kirkpatrick Lucinda, Klamm Alisa, Klarevas-Irby James A, Knowles Sarah, Koren Lee, Krzyszczyk Ewa, Kusch Jillian M, Lambin Xavier, Lane Jeffrey E, Leirs Herwig, Leu Stephan T, Lyon Bruce E, Macdonald David W, Madsen Anastasia E, Mann Janet, Manser Marta, Mariën Joachim, Massawe Apia, McDonald Robbie A, Morelle Kevin, Mourier Johann, Newman Chris, Nussear Kenneth, Nyaguthii Brendah, Ogino Mina, Ozella Laura, Packer Craig, Papastamatiou Yannis P, Paterson Steve, Payne Eric, Pedersen Amy B, Pemberton Josephine M, Pinter-Wollman Noa, Planes Serge, Raulo Aura, Rodríguez-Muñoz Rolando, Rudd Lauren, Sabuni Christopher, Sah Pratha, Schallert Robert J, Sheldon Ben C, Shizuka Daizaburo, Sih Andrew, Sinn David L, Sluydts Vincent, Spiegel Orr, Telfer Sandra, Thomason Courtney A, Tickler David M, Tregenza Tom, VanderWaal Kimberley, Walmsley Sam, Walters Eric L, Wanelik Klara M, Whitehead Hal, Wielgus Elodie, Wilson-Aggarwal Jared, Wohlfeil Caroline, Bansal Shweta
School of Natural Sciences, Trinity College Dublin, Dublin, Ireland.
Department of Biology, Georgetown University, Washington, DC, USA.
Nat Ecol Evol. 2025 Sep 4. doi: 10.1038/s41559-025-02843-z.
Theory predicts that high population density leads to more strongly connected spatial and social networks, but how local density drives individuals' positions within their networks is unclear. This gap reduces our ability to understand and predict density-dependent processes. Here we show that density drives greater network connectedness at the scale of individuals within wild animal populations. Across 36 datasets of spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals and insects, 80% of systems exhibit strong positive relationships between local density and network centrality. However, >80% of relationships are nonlinear and 75% are shallower at higher values, indicating saturating trends that probably emerge as a result of demographic and behavioural processes that counteract density's effects. These are stronger and less saturating in spatial compared with social networks, as individuals become disproportionately spatially connected rather than socially connected at higher densities. Consequently, ecological processes that depend on spatial connections are probably more density dependent than those involving social interactions. These findings suggest fundamental scaling rules governing animal social dynamics, which could help to predict network structures in novel systems.
理论预测，高种群密度会导致空间和社会网络的连接性更强，但局部密度如何驱动个体在其网络中的位置尚不清楚。这一差距降低了我们理解和预测密度依赖性过程的能力。在此，我们表明，密度在野生动物种群个体层面上推动了更强的网络连接性。在涵盖30种鱼类、爬行动物、鸟类、哺乳动物和昆虫的58000多个个体动物的36个空间和社会行为数据集中，80%的系统显示出局部密度与网络中心性之间存在强正相关关系。然而，超过80%的关系是非线性的，且75%的关系在较高值时较浅，这表明可能由于抵消密度影响的人口统计学和行为过程而出现饱和趋势。与社会网络相比，这些趋势在空间网络中更强且饱和程度更低，因为在较高密度下，个体在空间上的连接不成比例地高于社会连接。因此，依赖空间连接的生态过程可能比涉及社会互动的过程更依赖密度。这些发现揭示了支配动物社会动态的基本尺度规则，这有助于预测新系统中的网络结构。
