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

Finite mixtures in capture-recapture surveys for modeling residency patterns in marine wildlife populations

This work aims to show how prior knowledge about the structure of a heterogeneous animal population can be leveraged to improve the abundance estimation from capture-recapture survey data. We combine the Open Jolly-Seber model with finite mixtures and propose a parsimonious specification tailored to the residency patterns of the common bottlenose dolphin. We employ a Bayesian framework for our inference, discussing the appropriate choice of priors to mitigate label-switching and nonidentifiability issues, commonly associated with finite mixture models. We conduct a series of simulation experiments to illustrate the competitive advantage of our proposal over less specific alternatives. The proposed approach is applied to data collected on the common bottlenose dolphin population inhabiting the Tiber River estuary (Mediterranean Sea). Our results provide novel insights into this population's size and structure, shedding light on some of the ecological processes governing its dynamics.

First acoustic evidence of signature whistle production by spinner dolphins (Stenella longirostris)

A dolphin's signature whistle (SW) is a distinctive acoustic signal, issued in a bout pattern of unique frequency modulation contours; it allows individuals belonging to a given group to recognize each other and, consequently, to maintain contact and cohesion. The current study is the first scientific evidence that spinner dolphins (Stenella longirostris) produce SWs. Acoustic data were recorded at a shallow rest bay called "Biboca", in Fernando de Noronha Archipelago, Brazil. In total, 1902 whistles were analyzed; 40% (753/1,902) of them were classified as stereotyped whistles (STW). Based on the SIGID method, 63% (472/753) of all STWs were identified as SWs; subsequently, they were categorized into one of 18 SW types. SWs accounted for 25% (472/1,902) of the acoustic repertoire. External observers have shown near perfect agreement to classify whistles into the adopted SW categorization. Most acoustic and temporal variables measured for SWs showed mean values similar to those recorded in other studies with spinner dolphins, whose authors did not differentiate SWs from non-SWs. Principal component analysis has explained 78% of total SW variance, and it emphasized the relevance of shape/contour and frequency variables to SW variance. This scientific discovery helps improving bioacoustics knowledge about the investigated species. Future studies to be conducted in Fernando de Noronha Archipelago should focus on continuous investigations about SW development and use by S. longirostris, expanding individuals' identifications (Photo ID and SW Noronha Catalog), assessing long-term whistle stability and emission rates, and making mother-offspring comparisons with sex-based differences.