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. 2022 May 26;12(1):6980.
doi: 10.1038/s41598-022-10920-7.

Determinants of variability in signature whistles of the Mediterranean common bottlenose dolphin

Gabriella La Manna  1   2 , Nikolina Rako-Gospić  3 , Daniela Silvia Pace  4 , Silvia Bonizzoni  5 , Lucia Di Iorio  6   7 , Lauren Polimeno  8   9 , Francesco Perretti  8 , Fabio Ronchetti  8 , Giancarlo Giacomini  4 , Gianni Pavan  10 , Giulia Pedrazzi  4 , Helena Labach  11 , Giulia Ceccherelli  12   8
Affiliations

Determinants of variability in signature whistles of the Mediterranean common bottlenose dolphin

Gabriella La Manna et al. Sci Rep. .

Abstract

One of the most studied aspects of animal communication is the acoustic repertoire difference between populations of the same species. While numerous studies have investigated the variability of bottlenose dolphin whistles between populations, very few studies have focused on the signature whistles alone and the factors underlying differentiation of signature whistles are still poorly understood. Here we describe the signature whistles produced by six distinct geographical units of the common bottlenose dolphin (Tursiops truncatus) in the Mediterranean Sea and identify the main determinants of their variability. Particularly, the influence of the region (proxy of genetic distance), the geographic site, and the environmental (sea bottom-related) and demographical (population-related) conditions on the acoustic structure of signature whistles was evaluated. The study provides the first evidence that the genetic structure, which distinguishes the eastern and western Mediterranean bottlenose dolphin populations has no strong influence on the acoustic structure of their signature whistles, and that the geographical isolation between populations only partially affected whistle variability. The environmental conditions of the areas where the whistles developed and the demographic characteristics of the belonging populations strongly influenced signature whistles, in accordance with the "acoustic adaptation hypothesis" and the theory of signature whistle determination mediated by learning.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Multidimensional scaling plots showing the similarity of SWs grouped by site, region, population demography and sea bottom. PC (Port Cros); Al (Alghero); FI (Ostia-Fiumicino); LA (Lampedusa); GC (Gulf of Corinth); CL (Cres and Losjni).
Figure 2
Figure 2
PCA biplot displays the information on correlation among variables. The directions of the arrows show the relative loadings of the parameters on PC1 and PC2.
Figure 3
Figure 3
Effect of ‘region’ on (a) min and start frequencies (PC2) and (b) frequency range, duration and number of inflection points (PC3).
Figure 4
Figure 4
Effect of ‘site’ on (a) min and start frequencies (PC2) and (b) frequency range, duration and number of inflection points (PC3).
Figure 5
Figure 5
Effect of ‘sea bottom’ on (a) min and start frequencies (PC2) and (b) frequency range, duration and number of inflection points (PC3).
Figure 6
Figure 6
Effect of ‘population demography’ on (a) max and end frequencies (PC1), (b) min and start frequencies (PC2) and (c) frequency range, duration and number of inflection points (PC3).
Figure 7
Figure 7
Map of the six study sites in the Mediterranean Sea. PC (Port Cros); Al (Alghero); FI (Ostia-Fiumicino); LA (Lampedusa); GC (Gulf of Corinth); CL (Cres and Losjni). The original map was downloaded from the free source https://d-maps.com/ and modified by Preview in Mac Os.
Figure 8
Figure 8
Example of SW-IDs. The number represents the stereotyped contours (referred as SW in the text) of the SW-ID.
See this image and copyright information in PMC

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