Johnston Stuart T, Painter Kevin J
School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, 3010, Australia.
Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio (DIST), Politecnico di Torino, 39, 10125, Turin, Italy.
Mov Ecol. 2024 Feb 19;12(1):17. doi: 10.1186/s40462-024-00458-w.
Many baleen whales are renowned for their acoustic communication. Under pristine conditions, this communication can plausibly occur across hundreds of kilometres. Frequent vocalisations may allow a dispersed migrating group to maintain contact, and therefore benefit from improved navigation via the "wisdom of the crowd". Human activities have considerably inflated ocean noise levels. Here we develop a data-driven mathematical model to investigate how ambient noise levels may inhibit whale migration. Mathematical models allow us to simultaneously simulate collective whale migration behaviour, auditory cue detection, and noise propagation. Rising ambient noise levels are hypothesised to influence navigation through three mechanisms: (i) diminished communication space; (ii) reduced ability to hear external sound cues and; (iii) triggering noise avoidance behaviour. Comparing pristine and current soundscapes, we observe navigation impairment that ranges from mild (increased journey time) to extreme (failed navigation). Notably, the three mechanisms induce qualitatively different impacts on migration behaviour. We demonstrate the model's potential predictive power, exploring the extent to which migration may be altered under future shipping and construction scenarios.
许多须鲸以其声学通讯而闻名。在原始条件下，这种通讯可以在数百公里的范围内合理地发生。频繁的发声可能使分散的迁徙群体保持联系，从而通过“群体智慧”受益于更好的导航。人类活动极大地提高了海洋噪音水平。在此，我们开发了一个数据驱动的数学模型，以研究环境噪音水平如何抑制鲸鱼迁徙。数学模型使我们能够同时模拟鲸鱼的集体迁徙行为、听觉线索检测和噪音传播。环境噪音水平的上升被假设通过三种机制影响导航：（i）通讯空间减小；（ii）听到外部声音线索的能力降低；以及（iii）触发噪音回避行为。比较原始和当前的声景，我们观察到导航障碍的范围从轻微（行程时间增加）到极端（导航失败）。值得注意的是，这三种机制对迁徙行为产生了质的不同影响。我们展示了该模型的潜在预测能力，探索了在未来航运和建设场景下迁徙可能被改变的程度。
