Multiple spatial behaviours govern social network positions in a wild ungulate. (14th February 2021)

• Record Type: Journal Article
• Authors: Albery, Gregory F.; Morris, Alison; Morris, Sean; Pemberton, Josephine M.; Clutton‐Brock, Tim H.; Nussey, Daniel H.; Firth, Josh A.
• Editors: Sih, Andrew
• Is Part Of: Ecology letters. Volume 24:Number 4(2021)
• Page Start: 676
• Page End: 686
• Publication Date: 2021-02-14
• Subjects: Ecology -- Periodicals; 577
• DOI: 10.1111/ele.13684
• Languages: English
• ISSNs: 1461-023X

Abstract

Abstract: The structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals' observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43‐year dataset detailing a wild red deer population to investigate how individuals' spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi‐matrix animal models, we demonstrate that social network positions are shaped by two‐dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual‐level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality. Abstract : How does an animal's spatial behaviour determine their place in their social network? We show using a wild population of red deer that individuals' social network positions are driven by a combination of spatial activity levels, local population density, space sharing and landscape locations. These effects were large, especially when compared to the effects of other individual traits, revealing the importance of controlling for a range of spatial behaviours when investigating social network structure.