Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning
Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning
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使用自动运动跟踪和监督机器学习解码种子收割机蚂蚁的警报信号传播
DOI：
10.1098/rspb.2021.2176
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Fewell, Jennifer H.
中科院分区：
文献类型：
--
作者：
Guo, Xiaohui;Lin, Michael R.;Azizi, Asma;Saldyt, Lucas P.;Kang, Yun;Pavlic, Theodore P.;Fewell, Jennifer H.
Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological approach to track alarm spread within a group of harvester ants,Pogonomyrmex californicus. We initially alarmed three ants and tracked subsequent signal transmission through the colony. Because there was no actual standing threat, the false alarm allowed us to assess amplification and adaptive damping of the collective alarm response. We trained a random forest regression model to quantify alarm behaviour of individual workers from multiple movement features. Our approach translates subjective categorical alarm scores into a reliable, continuous variable. We combined these assessments with automatically tracked proximity data to construct an alarm propagation network. This method enables analyses of spatio-temporal patterns in alarm signal propagation in a group of ants and provides an opportunity to integrate individual and collective alarm response. Using this system, alarm propagation can be manipulated and assessed to ask and answer a wide range of questions related to information and misinformation flow in social networks.
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DOI：
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发表时间：
1984
期刊：
影响因子：
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作者：
H. R. Hermann
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