Department of Biology, Georgetown University, Washington, DC, USA.
Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
Ecol Lett. 2021 Apr;24(4):676-686. doi: 10.1111/ele.13684. Epub 2021 Feb 14.
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.
野生动物社会系统的结构取决于内在和外在驱动因素的复杂组合。种群结构和空间行为是个体观察到的社会行为的关键决定因素，但由于数据稀缺和分析复杂性，很难同时量化这些空间成分和多个其他驱动因素。我们使用了一个 43 年的数据集来详细研究野生红鹿种群，以调查个体的空间行为如何驱动社会网络定位，同时评估其他潜在的影响因素。使用综合嵌套拉普拉斯近似 (INLA) 多矩阵动物模型，我们证明社会网络位置受二维景观位置、成对空间共享、个体范围大小以及种群密度的时空变化的影响，同时还受到个体水平表型特征的一些较小但可检测到的影响。这些结果表明该社会具有强烈的、多方面的时空结构，强调在研究社会性的原因和后果时，考虑多个空间成分的重要性。
