4.8 Article

Multiple spatial behaviours govern social network positions in a wild ungulate

期刊

ECOLOGY LETTERS
卷 24, 期 4, 页码 676-686

出版社

WILEY
DOI: 10.1111/ele.13684

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资金

  1. UK NERC
  2. BBSRC
  3. Royal Society
  4. ERC
  5. NSF [1414296]
  6. Bruce McEwen Career Development Fellowship from the Animal Models for the Social Dimensions of Health and Aging Research Network [NIH/NIH R24 AG065172]
  7. Merton College
  8. BBSRC [BB/S009752/1]
  9. NERC [NE/S010335/1]
  10. BBSRC [BB/S009752/1] Funding Source: UKRI
  11. NERC [NE/R001456/1, NE/S010335/1] Funding Source: UKRI
  12. Natural Environment Research Council [NE/R001456/1] Funding Source: researchfish

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The study, using a 43-year dataset, shows that the structure of wild animal social systems is influenced by multiple factors such as spatial behavior and population density. These results emphasize the importance of considering multiple spatial components when investigating the causes and consequences of sociality.
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.

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