基于被动声学数据的franciscana海豚时空群定义。

IF 1.4 Q3 ACOUSTICS
João Pedro M Mura, Giovanne A Ferreira, Alexandre N Zerbini, Artur Andriolo
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引用次数: 0

摘要

利用被动声学监测和基于层次密度的空间聚类应用,结合噪声聚类,对白鱀豚回声定位声列进行了时空聚类。这种无监督的、客观的方法确定了生物学上相关的点击训练集群,为物种的社会组织提供了罕见的见解。观察到的结构显示出一致的簇内凝聚力和簇间分离,支持该方法的有效性。我们的研究结果表明,聚类声学检测可以作为描述社会群体的强大框架,并可以集成到未来的密度估计协议中,增强对这种神秘和脆弱物种的生态理解和保护潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatiotemporal group definition of franciscana dolphins from passive acoustic data.

We applied passive acoustic monitoring and Hierarchical Density-Based Spatial Clustering of Applications with Noise clustering to define spatiotemporally cohesive groupings of franciscana dolphin (Pontoporia blainvillei) echolocation click trains. This unsupervised, objective method identified biologically relevant click train clusters, offering rare insights into the species' social organization. The observed structure revealed consistent intra-cluster cohesion and inter-cluster separation, supporting the effectiveness of the approach. Our findings demonstrate that clustering acoustic detections can serve as a robust framework for delineating social groups and can be integrated into future density estimation protocols, enhancing the ecological understanding and conservation potential for this cryptic and vulnerable species.

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