Jeschke Manon, Stahlsmeier Maximilian, Egelhaaf Martin, Bertrand Olivier J N
Neurobiology, Bielefeld University, Universitätstr. 25, 33615 Bielefeld, NRW, Germany.
J Exp Biol. 2025 Aug 1;228(15). doi: 10.1242/jeb.250514. Epub 2025 Jul 25.
Bumblebees are excellent navigators that travel long distances while following paths to known locations. They forage not only in open terrain but also in cluttered environments where obstacles force them to deviate from direct paths. This study investigated the underexplored aspect of how bees become experienced foragers and optimize flight behaviour in cluttered terrains. We recorded flight trajectories of novice bees with no prior experience in navigating cluttered laboratory environments and monitored their behavioural performance as they gained experience on subsequent foraging trips through numerous obstacles. By controlling for experience levels, we analysed how flight characteristics evolve with increasing expertise. Successful navigation in cluttered terrain requires avoiding collisions with obstacles. This is only possible if these can be detected through visual features such as the retinal displacement of contrast edges. Obstacles which are harder to detect and to avoid by the bees may affect their flight performance. By introducing transparent objects into our dense environment, we challenged collision avoidance and learning mechanisms, analysing the impact on flight optimization under different environmental conditions. Our findings reveal that experienced bees fly similar paths through clutter and quickly adapt their flights regardless of their training environment. However, the specific paths followed are influenced by environmental conditions. Transparent objects primarily affect naive bees' flight patterns while having minimal impact on flight optimization, suggesting that the efficient flights of experienced bees result not solely from reflexive collision avoidance but from learning and previous experience in cluttered environments.
大黄蜂是出色的导航者，它们在沿着路径前往已知地点的过程中能够飞行很长的距离。它们不仅在开阔地形觅食，还会在杂乱的环境中觅食，在这种环境中，障碍物迫使它们偏离直接路径。本研究调查了一个尚未充分探索的方面，即蜜蜂如何成为经验丰富的觅食者以及如何在杂乱地形中优化飞行行为。我们记录了在杂乱的实验室环境中没有先前导航经验的新手蜜蜂的飞行轨迹，并监测了它们在随后穿越众多障碍物的觅食行程中积累经验时的行为表现。通过控制经验水平，我们分析了飞行特征如何随着专业知识的增加而演变。在杂乱地形中成功导航需要避免与障碍物碰撞。只有通过视觉特征（如对比边缘的视网膜位移）检测到障碍物，才有可能做到这一点。蜜蜂难以检测和避免的障碍物可能会影响它们的飞行性能。通过在我们的密集环境中引入透明物体，我们对避撞和学习机制提出了挑战，分析了不同环境条件下对飞行优化的影响。我们的研究结果表明，经验丰富的蜜蜂在杂乱环境中飞行的路径相似，并且无论其训练环境如何，都能迅速调整飞行。然而，所遵循的具体路径受环境条件影响。透明物体主要影响未经验的蜜蜂的飞行模式，而对飞行优化的影响最小，这表明经验丰富的蜜蜂的高效飞行不仅仅源于反射性的避撞，还源于在杂乱环境中的学习和先前经验。
