Papale Elena B, Azzolin Marta A, Cascão Irma, Gannier Alexandre, Lammers Marc O, Martin Vidal M, Oswald Julie N, Perez-Gil Monica, Prieto Rui, Silva Mónica A, Torri Marco, Giacoma Cristina
Institute for the Study of Anthropic Impacts and Sustainability in the Marine Environment (CNR-IAS), unit of Capo Granitola, National Research Council, Via del Mare 3, 91021, Campobello di Mazara, TP, Italy.
Life Sciences and Systems Biology Department, University of Torino, Via Accademia Albertina 13, 10123, Torino, Italy.
BMC Zool. 2021 Jul 29;6(1):22. doi: 10.1186/s40850-021-00085-7.
Prioritizing groupings of organisms or 'units' below the species level is a critical issue for conservation purposes. Several techniques encompassing different time-frames, from genetics to ecological markers, have been considered to evaluate existing biological diversity at a sufficient temporal resolution to define conservation units. Given that acoustic signals are expressions of phenotypic diversity, their analysis may provide crucial information on current differentiation patterns within species. Here, we tested whether differences previously delineated within dolphin species based on i) geographic isolation, ii) genetics regardless isolation, and iii) habitat, regardless isolation and genetics, can be detected through acoustic monitoring. Recordings collected from 104 acoustic encounters of Stenella coeruleoalba, Delphinus delphis and Tursiops truncatus in the Azores, Canary Islands, the Alboran Sea and the Western Mediterranean basin between 1996 and 2012 were analyzed. The acoustic structure of communication signals was evaluated by analyzing parameters of whistles in relation to the known genetic and habitat-driven population structure.
Recordings from the Atlantic and Mediterranean were accurately assigned to their respective basins of origin through Discriminant Function Analysis, with a minimum 83.8% and a maximum 93.8% classification rate. A parallel pattern between divergence in acoustic features and in the genetic and ecological traits within the basins was highlighted through Random Forest analysis. Although it is not yet possible to establish a causal link between each driver and acoustic differences between basins, we showed that signal variation reflects fine-scale diversity and may be used as a proxy for recognizing discrete units.
We recommend that acoustic analysis be included in assessments of delphinid population structure, together with genetics and ecological tracer analysis. This cost-efficient non-invasive method can be applied to uncover distinctiveness and local adaptation in other wide-ranging marine species.
为了保护目的，对物种以下的生物群落或“单元”进行优先排序是一个关键问题。人们已经考虑了几种涵盖不同时间框架的技术，从遗传学到生态标记，以便以足够的时间分辨率评估现有的生物多样性，从而定义保护单元。鉴于声学信号是表型多样性的表现形式，对其进行分析可能会提供有关物种内当前分化模式的关键信息。在这里，我们测试了先前根据以下因素在海豚物种中划分出的差异：i）地理隔离，ii）不考虑隔离因素的遗传学，以及iii）不考虑隔离和遗传学因素的栖息地，是否可以通过声学监测检测到。对1996年至2012年间在亚速尔群岛、加那利群岛、阿尔沃兰海和西地中海盆地对条纹原海豚、真海豚和宽吻海豚的104次声学相遇记录进行了分析。通过分析与已知的遗传和栖息地驱动的种群结构相关的哨声参数，评估了通信信号的声学结构。
通过判别函数分析，来自大西洋和地中海的记录被准确地分配到它们各自的起源海域，分类率最低为83.8%，最高为93.8%。通过随机森林分析突出了各海域内声学特征差异与遗传和生态特征差异之间的平行模式。虽然目前还无法在每个驱动因素与各海域之间的声学差异之间建立因果联系，但我们表明信号变化反映了精细尺度的多样性，并且可以用作识别离散单元的代理。
我们建议在对海豚种群结构的评估中纳入声学分析，同时结合遗传学和生态示踪分析。这种具有成本效益且非侵入性的方法可用于揭示其他广泛分布的海洋物种的独特性和局部适应性。
