Many bioacoustic studies have been able to identify individual mammals from variations in the fundamental frequency (F₀) of their vocalizations. Other characteristics of vocalization which encode individuality, such as amplitude, are less frequently used because of problems with background noise and recording fidelity over distance. In this paper, we investigate whether the inclusion of amplitude variables improves the accuracy of individual howl identification in captive Eastern grey wolves (Canis lupus lycaon). We also explore whether the use of a bespoke code to extract the howl features, combined with histogram-derived principal component analysis (PCA) values, can improve current individual wolf howl identification accuracies. From a total of 89 solo howls from six captive individuals, where distances between wolf and observer were short, we achieved 95.5% (+9.0% improvement) individual identification accuracy of captive wolves using discriminant function analysis (DFA) to classify simple scalar variables of F₀ and normalized amplitudes. Moreover, this accuracy was increased by 100% when using histogram-derived PCA values of F₀ and amplitudes of the first harmonic. We suggest that individual identification accuracy can be improved by including amplitude changes for species where F₀ has only been included so far. Using DFA on PCA values of both F₀ and amplitude could optimize vocal identification in a range of mammal bioacoustic studies.

Vocal divergence within species often corresponds to morphological, environmental, and genetic differences between populations. Wolf howls are long-range signals that encode individual, group, and subspecies differences, yet the factors that may drive this variation are poorly understood. Furthermore, the taxonomic division within the Canis genus remains contended and additional data are required to clarify the position of the Himalayan, North African, and Indian wolves within Canis lupus. We recorded 451 howls from the 3 most basal wolf lineages—Himalayan C. lupus chanco—Himalayan haplotype, North African C. lupus lupaster, and Indian C. lupus pallipes wolves—and present a howl acoustic description within each clade. With an additional 619 howls from 7 Holarctic subspecies, we used a random forest classifier and principal component analysis on 9 acoustic parameters to assess whether Himalayan, North African, and Indian wolf howls exhibit acoustic differences compared to each other and Holarctic wolf howls. Generally, both the North African and Indian wolf howls exhibited high mean fundamental frequency (F0) and short duration compared to the Holarctic clade. In contrast, the Himalayan wolf howls typically had lower mean F0, unmodulated frequencies, and short howls compared to Holarctic wolf howls. The Himalayan and North African wolves had the most acoustically distinct howls and differed significantly from each other and to the Holarctic wolves. Along with the influence of body size and environmental differences, these results suggest that genetic divergence and/or geographic distance may play an important role in understanding howl variation across subspecies.