Stochastic dynamics of social patch foraging decisions
Stochastic dynamics of social patch foraging decisions
复制标题
社会斑块觅食决策的随机动力学
DOI：
10.1103/physrevresearch.4.033128
复制
发表时间：
2022
影响因子：
4.2
通讯作者：
Kilpatrick, Zachary P.
中科院分区：
文献类型：
--
作者：
Bidari, Subekshya;El Hady, Ahmed;Davidson, Jacob D.;Kilpatrick, Zachary P.
动物通常成群觅食。社会觅食可以帮助动物避免被捕食，减少它们对食物资源丰富性的不确定性。尽管如此，理论机械模型的补丁觅食压倒性地集中在单个觅食的行为。在这项研究中，我们开发了一个机械模型，占的行为，个人觅食在一起，离开食物补丁后的证据积累过程。每个个体对斑块质量的信念由一个随机累积变量表示，该随机累积变量与另一个个体的信念耦合以表示信息的传递。我们认为一个有凝聚力的群体，并考虑间歇性脉动耦合（只沟通决定离开）和连续扩散耦合（沟通整个审议过程）模型的信息共享。采用脉冲耦合的群体可以获得更高的觅食效率，这取决于更强烈的耦合参数相比，那些使用扩散耦合。相反，使用扩散耦合的群体对信念权重和偏离标准的变化和异质性更鲁棒。效率是衡量的奖励率函数，该函数平衡的能量积累的时间，在一个补丁，计算通过解决一个有序的第一次通过时间的问题，每个人的补丁离开。使用合成的出发时间数据，我们可以区分两种通信模式，并确定模型参数。我们的模型建立了一个社会补丁觅食框架，以确定审慎的决策策略和形式的社会沟通，并允许模型拟合觅食动物群体的现场数据。
Animals typically forage in groups. Social foraging can help animals avoid predation and decrease their uncertainty about the richness of food resources. Despite this, theoretical mechanistic models of patch foraging have overwhelmingly focused on the behavior of single foragers. In this study, we develop a mechanistic model that accounts for the behavior of individuals foraging together and departing food patches following an evidence accumulation process. Each individual's belief about patch quality is represented by a stochastically accumulating variable, which is coupled to another's belief to represent the transfer of information. We consider a cohesive group, and model information sharing by considering both intermittent pulsatile coupling (only communicate decision to leave) and continuous diffusive coupling (communicate throughout the deliberation process). Groups employing pulsatile coupling can obtain higher foraging efficiency, which depends more strongly on the coupling parameter compared to those using diffusive coupling. Conversely, groups using diffusive coupling are more robust to changes and heterogeneities in belief weighting and departure criteria. Efficiency is measured by a reward rate function that balances the amount of energy accumulated against the time spent in a patch, computed by solving an ordered first passage time problem for the patch departures of each individual. Using synthetic departure time data, we can distinguish between the two modes of communication and identify the model parameters. Our model establishes a social patch foraging framework to identify deliberative decision strategies and forms of social communication, and to allow model fitting to field data from foraging animal groups.
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DOI：
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发表时间：
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期刊：
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影响因子：
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作者：
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DOI：
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发表时间：
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期刊：
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影响因子：
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