Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks.
Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks.
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DOI：
10.1073/pnas.1713568115
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发表时间：
2018-02-13
影响因子：
11.1
通讯作者：
Robinson GE
中科院分区：
文献类型：
--
作者：
Gernat T;Rao VD;Middendorf M;Dankowicz H;Goldenfeld N;Robinson GE
人类通信网络中的交互模式的特征在于不连续性和不可预测的时间（突发性）。通过这种网络模拟的传播动态比预期的要慢。作者开发了一种自动记录个体蜜蜂社会互动的技术，使人们能够在非人类社会中研究这两种现象。具体来说，通过分析超过120万蜜蜂的社会互动，我们证明，突发性不是人类特有的互动模式。我们还表明，蜜蜂社交网络上的传播动态比预期的要快，证实了早期的理论预测，即突发性和快速传播可以同时发生。我们希望这些发现将为未来的大规模社会组织、疾病传播和信息传播模型提供信息。社交网络是信息和疾病传播的媒介。传播的动力取决于网络中连续接触之间的时间分布，以及其他因素。重尾（突发）时间分布是人类通信网络的特征，包括面对面的接触和通过移动的电话、电子邮件和互联网社区的电子通信。突发性被认为是这些网络相对于随机参考网络传播缓慢的可能原因。然而，目前尚不清楚突发性是否是人类特有的通信模式的附带现象。此外，理论预测，快速，突发通信网络也应该存在。在这里，我们提出了一种高通量技术，用于自动监测个体蜜蜂的社会互动，并分析由五个蜂群中超过120万次互动组成的丰富而详细的数据集。我们发现，蜜蜂，像人类一样，也在爆发中相互作用，但传播速度明显快于随机参考网络，即使在实验人口扰动后仍然如此。因此，虽然突发性可能是社交互动的固有属性，但它并不总是抑制真实世界通信网络中的传播。我们预计，这些结果将为未来的大规模社会组织和信息以及疾病传播模型提供信息，并可能影响受威胁蜜蜂种群的健康管理。
Interaction patterns in human communication networks are characterized by intermittency and unpredictable timing (burstiness). Simulated spreading dynamics through such networks are slower than expected. A technology for automated recording of social interactions of individual honeybees, developed by the authors, enables one to study these two phenomena in a nonhuman society. Specifically, by analyzing more than 1.2 million bee social interactions, we demonstrate that burstiness is not a human-specific interaction pattern. We furthermore show that spreading dynamics on bee social networks are faster than expected, confirming earlier theoretical predictions that burstiness and fast spreading can co-occur. We expect that these findings will inform future models of large-scale social organization, spread of disease, and information transmission. Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities. Burstiness has been cited as a possible cause for slow spreading in these networks relative to a randomized reference network. However, it is not known whether burstiness is an epiphenomenon of human-specific patterns of communication. Moreover, theory predicts that fast, bursty communication networks should also exist. Here, we present a high-throughput technology for automated monitoring of social interactions of individual honeybees and the analysis of a rich and detailed dataset consisting of more than 1.2 million interactions in five honeybee colonies. We find that bees, like humans, also interact in bursts but that spreading is significantly faster than in a randomized reference network and remains so even after an experimental demographic perturbation. Thus, while burstiness may be an intrinsic property of social interactions, it does not always inhibit spreading in real-world communication networks. We anticipate that these results will inform future models of large-scale social organization and information and disease transmission, and may impact health management of threatened honeybee populations.
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DOI：
10.1016/s0950-5601(56)80129-9
发表时间：
1956-01-01
期刊：
British Journal of Animal Behaviour
影响因子：
--
作者：
Free, J. B.
通讯作者：
Free, J. B.
影响因子：
158.5
作者：
Christakis, Nicholas A.;Fowler, James H.
通讯作者：
Fowler, James H.
影响因子：
2.5
作者：
ALLEN, M. DELLA
通讯作者：
ALLEN, M. DELLA
大小和密度与图层面指数的相互作用
影响因子：
3.1
作者：
Anderson, BS;Butts, C;Carley, K
通讯作者：
Carley, K
影响因子：
2.5
作者：
Castles, Madelaine;Heinsohn, Robert;Carter, Alecia J.
通讯作者：
Carter, Alecia J.