Density-dependent network structuring within and across wild animal systems

Résumé fourni par la source

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 density's effects, thereby producing saturating trends [11-15]. Density's 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.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.