Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, 57 rue Cuvier, 75005, Paris, France.
Neuro-PSI, UMR 9197, Université Paris-Sud, CNRS, Université Paris-Saclay, 91405, Orsay, France.
Sci Rep. 2018 Sep 26;8(1):14387. doi: 10.1038/s41598-018-31798-4.
Recent studies revealed that information on ecological patterns and processes can be investigated using sounds emanating from animal communities. In freshwater environments, animal communities are strongly shaped by key ecological factors such as lateral connectivity and temperature. We predict that those ecological factors are linked to acoustic communities formed by the collection of sounds emitted underwater. To test this prediction, we deployed a passive acoustic monitoring during 15 days in six floodplain channels of the European river Rhône. The six channels differed in their temperature and level of lateral connectivity to the main river. In parallel, we assessed the macroinvertebrate communities of these six channels using classical net sampling methods. A total of 128 sound types and 142 animal taxa were inventoried revealing an important underwater diversity. This diversity, instead of being randomly distributed among the six floodplain channels, was site-specific. Generalized mixed-effects models demonstrated a strong effect of both temperature and lateral connectivity on acoustic community composition. These results, congruent with macroinvertebrate community composition, suggest that acoustic communities reflect the interactions between animal communities and their environment. Overall our study strongly supports the perspectives offered by acoustic monitoring to describe and understand ecological patterns in freshwater environments.
最近的研究表明，可以利用动物群落发出的声音来研究生态模式和过程。在淡水环境中，动物群落受到侧向连通性和温度等关键生态因素的强烈影响。我们预测这些生态因素与由水下发出的声音组成的声群落有关。为了验证这一预测，我们在欧洲罗纳河的六个洪泛区河道中进行了为期 15 天的被动声学监测。这六个河道在温度和与主河道的侧向连通性方面存在差异。同时，我们使用传统的网采样方法评估了这六个河道的大型无脊椎动物群落。总共记录了 128 种声音类型和 142 种动物类群，揭示了水下生物多样性的重要性。这种多样性并非随机分布在六个洪泛区河道中，而是具有特定的位置特征。广义混合效应模型表明，温度和侧向连通性对声群落组成都有很强的影响。这些结果与大型无脊椎动物群落组成一致，表明声群落反映了动物群落及其环境之间的相互作用。总的来说，我们的研究强烈支持了声学监测在描述和理解淡水环境生态模式方面提供的观点。
