Honey bees make decisions regarding foraging and nest-site selection in groups ranging from hundreds to thousands of individuals. To effectively make these decisions, bees need to communicate within a spatially distributed group. However, the spatiotemporal dynamics of honey bee communication have been mostly overlooked in models of collective decisions, focusing primarily on mean field models of opinion dynamics. We analyze how the spatial properties of the nest or hive, and the movement of individuals with different belief states (uncommitted or committed) therein affect the rate of information transmission using spatially-extended models of collective decision-making within a hive. Honeybees waggle-dance to recruit conspecifics with an intensity that is a threshold nonlinear function of the waggler concentration. Our models range from treating the hive as a chain of discrete patches to a continuous line (long narrow hive). The combination of population-thresholded recruitment and compartmentalized populations generates tradeoffs between rapid information propagation with strong population dispersal and recruitment failures resulting from excessive population diffusion and also creates an effective colony-level signal-detection mechanism whereby recruitment to low quality objectives is blocked.

蜜蜂以数百至数千只的群体来做出有关觅食和筑巢地点选择的决定。为了有效地做出这些决定，蜜蜂需要在空间分布的群体内进行交流。然而，蜜蜂交流的时空动态在集体决策模型中大多被忽视，主要关注观点动态的平均场模型。我们使用蜂巢内集体决策的空间扩展模型来分析巢或蜂巢的空间特性以及其中具有不同信念状态（未承诺或承诺）的个体的移动如何影响信息传输率。蜜蜂通过摇摆舞来招募同类，其强度是摇摆器浓度的阈值非线性函数。我们的模型范围从将蜂巢视为一系列离散斑块到连续线（狭长蜂巢）。群体阈值招募和区隔群体的结合在快速信息传播与强烈群体分散和过度群体扩散导致的招募失败之间产生权衡，并且还创建了有效的群体水平信号检测机制，从而阻止了低质量目标的招募。