Charoonratana L, Thiwatwaranikul T, Paisanpan P, Suksombat S, Smith M F
School of Physics, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
NANOTEC-SUT Center of Excellence on Advanced Functional Nanomaterials, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
Mov Ecol. 2023 Oct 16;11(1):64. doi: 10.1186/s40462-023-00426-w.
The movement of individual weaver ants, of Oecophylla smargandina, was previously tracked within an unfamiliar arena. We develop an empirical model, based on Brownian motion with a linear drag and constant driving force, to explain the observed distribution of ants over position and velocity. Parameters are fixed according to the isotropic, homogeneous distribution observed near the middle of the arena. Then, with no adjustable parameters, the model accounts for all features of the measured population distribution. The tendency of ants to remain near arena edges is largely explained as a statistical property of bounded stochastic motion though evidence for active wall-following behavior appears in individual ant trajectories. Members of this ant species are capable of impressive feats of collective action and long-range navigation. But we argue that they use a simplistic algorithm, captured semi-quantitatively by the model provided, to navigate within the confined region.
此前，人们在一个陌生的场地内追踪了单个黄猄蚁（Oecophylla smargandina）的活动。我们基于带有线性阻力和恒定驱动力的布朗运动开发了一个经验模型，以解释观察到的蚂蚁在位置和速度上的分布情况。根据在场地中部附近观察到的各向同性、均匀分布来确定参数。然后，在没有可调参数的情况下，该模型解释了测量到的种群分布的所有特征。蚂蚁倾向于停留在场地边缘，这在很大程度上被解释为有界随机运动的一种统计特性，尽管在单个蚂蚁的轨迹中出现了主动沿壁行为的证据。这种蚂蚁物种的成员能够完成令人印象深刻的集体行动和远距离导航壮举。但我们认为，它们在受限区域内导航时使用的是一种简单的算法，该模型已对其进行了半定量描述。
