Genetic distance from wolves affects family dogs' reactions towards howls.

Domestication dramatically changes behaviour, including communication, as seen in the case of dogs (Canis familiaris) and wolves (Canis lupus). We tested the hypothesis that domestication may affect an ancient, shared communication form of canids, the howling which seems to have higher individual variation in dogs: the perception and usage of howls may be affected by the genetic relatedness of the breeds to their last common ancestor with wolves ('root distance') and by other individual features like age, sex, and reproductive status. We exposed 68 purebred dogs to wolf howl playbacks and recorded their responses. We identified an interaction between root distance and age on the dogs' vocal and behavioural responses: older dogs from more ancient breeds responded longer with howls and showed more stress behaviours. Our results suggest that domestication impacts vocal behaviour significantly: disintegrating howling, a central, species-specific communication form of canids and gradually eradicating it from dogs' repertoire.

Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring.

BACKGROUND: Density estimation is a key issue in wildlife management but is particularly challenging and labour-intensive for elusive species. Recently developed approaches based on remotely collected data and capture-recapture models, though representing a valid alternative to more traditional methods, have found little application to species with limited morphological variation. We implemented a camera trap capture-recapture study to survey wolf packs in a 560-km2 area of Central Italy. Individual recognition of focal animals (alpha) in the packs was possible by relying on morphological and behavioural traits and was validated by non-invasive genotyping and inter-observer agreement tests. Two types (Bayesian and likelihood-based) of spatially explicit capture-recapture (SCR) models were fitted on wolf pack capture histories, thus obtaining an estimation of pack density in the area. RESULTS: In two sessions of camera trapping surveys (2014 and 2015), we detected a maximum of 12 wolf packs. A Bayesian model implementing a half-normal detection function without a trap-specific response provided the most robust result, corresponding to a density of 1.21 ± 0.27 packs/100 km2 in 2015. Average pack size varied from 3.40 (summer 2014, excluding pups and lone-transient wolves) to 4.17 (late winter-spring 2015, excluding lone-transient wolves). CONCLUSIONS: We applied for the first time a camera-based SCR approach in wolves, providing the first robust estimate of wolf pack density for an area of Italy. We showed that this method is applicable to wolves under the following conditions: i) the existence of sufficient phenotypic/behavioural variation and the recognition of focal individuals (i.e. alpha, verified by non-invasive genotyping); ii) the investigated area is sufficiently large to include a minimum number of packs (ideally 10); iii) a pilot study is carried out to pursue an adequate sampling design and to train operators on individual wolf recognition. We believe that replicating this approach in other areas can allow for an assessment of density variation across the wolf range and would provide a reliable reference parameter for ecological studies.

Howl variation across Himalayan, North African, Indian, and Holarctic wolf clades: tracing divergence in the world's oldest wolf lineages using acoustics.

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.

Visualizing sound: counting wolves by using a spectral view of the chorus howling.

INTRODUCTION: Monitoring large carnivores is a central issue in conservation biology. The wolf (Canis lupus) is the most studied large carnivore in the world. After a massive decline and several local extinctions, mostly due to direct persecutions, wolves are now recolonizing many areas of their historical natural range. One of the main monitoring techniques is the howling survey, which is based on the wolves' tendency to use vocalisations to mark territory ownership in response to howls of unknown individuals. In most cases wolf howling sessions are useful for the localisation of the pack, but they provide only an aural estimation of the chorus size. We tested and present a new bioacoustic approach to estimate chorus size by recording wolves' replies and visualising choruses through spectrograms and spectral envelopes. To test the methodology, we compared: a) the values detected by visual inspections with the true chorus size to test for accuracy; b) the bioacoustic estimations of a sample of free-ranging wolves' replies developed by different operators to test for precision of the method; c) the aural field estimation of chorus size of a sample of free-ranging wolves' replies with the sonogram analysis of the same recordings to test for difference between methods. RESULTS: Visual inspection of the chorus by spectrogram and spectrum proved to be useful in determining the number of concurrent voices in a wolf chorus. Estimations of chorus size were highly correlated with the number of wolves counted in a pack, and 92 % of 29 known chorus sizes were recognized by means of bioacoustic analysis. On the basis of spectrographic evidence, it was also possible to identify up to seven concurrent vocalisations in a chorus of nine wolves. Spectral analysis of 37 free ranging wolves' replies showed a high correlation between the chorus size estimations of the different operators (92.8 %), but a low correlation with the aural estimation (59.2 %). CONCLUSIONS: Wolf howling monitoring technique could be improved by recording wolves' replies and by using bioacoustic tools such as spectrograms and spectral envelopes to determine the size of the wolf chorus. Compared with other monitoring techniques (i.e., genetic analysis), bioacoustic analysis requires widely available informatic tools (i.e., sound recording set of devices and sound analysis software) and a low budget. Information obtained by means of chorus analysis can also be combined with that provided by other techniques. Moreover, howls can be recorded and stored in audio file format with a good resolution (i.e. in "Wave" format), thus representing a useful tool for future listening and investigations, which can be countlessly employed without risks of time deterioration.

Predicting the Spatial Distribution of Wolf (Canis lupus) Breeding Areas in a Mountainous Region of Central Italy.

Wolves (Canis lupus) in Italy represent a relict west European population. They are classified as vulnerable by IUCN, though have increased in number and expanded their range in recent decades. Here we use 17 years of monitoring data (from 1993 to 2010) collected in a mountainous region of central Italy (Arezzo, Tuscany) in an ecological niche-based model (MaxEnt) to characterize breeding sites (i.e. the areas where pups were raised) within home ranges, as detected from play-back responses. From a suite of variables related to topography, habitat and human disturbance we found that elevation and distance to protected areas were most important in explaining the locality of wolf responses. Rendezvous sites (family play-back response sites) typically occurred between 800 and 1200 m a.s.l., inside protected areas, and were usually located along mountain chains distant from human settlements and roads. In these areas human disturbance is low and the densities of ungulates are typically high. Over recent years, rendezvous sites have occurred closer to urban areas as the wolf population has continued to expand, despite the consequent human disturbance. This suggests that undisturbed landscapes may be reaching their carrying capacity for wolves. This, in turn, may lead to the potential for increased human-wolf interactions in future. Applying our model, both within and beyond the species' current range, we identify sites both within the current range and also further afield, that the species could occupy in future. Our work underlines the importance of the present protected areas network in facilitating the recolonisation by wolves. Our projections of suitability of sites for future establishment as the population continues to expand could inform planning to minimize future wolf-human conflicts.

Roaring high and low: composition and possible functions of the Iberian stag's vocal repertoire.

We provide a detailed description of the rutting vocalisations of free-ranging male Iberian deer (Cervus elaphus hispanicus, Hilzheimer 1909), a geographically isolated and morphologically differentiated subspecies of red deer Cervus elaphus. We combine spectrographic examinations, spectral analyses and automated classifications to identify different call types, and compare the composition of the vocal repertoire with that of other red deer subspecies. Iberian stags give bouts of roars (and more rarely, short series of barks) that are typically composed of two different types of calls. Long Common Roars are mostly given at the beginning or at the end of the bout, and are characterised by a high fundamental frequency (F0) resulting in poorly defined formant frequencies but a relatively high amplitude. In contrast, Short Common Roars are typically given in the middle or at the end of the bout, and are characterised by a lower F0 resulting in relatively well defined vocal tract resonances, but low amplitude. While we did not identify entirely Harsh Roars (as described in the Scottish red deer subspecies (Cervus elaphus scoticus)), a small percentage of Long Common Roars contained segments of deterministic chaos. We suggest that the evolution of two clearly distinct types of Common Roars may reflect divergent selection pressures favouring either vocal efficiency in high pitched roars or the communication of body size in low-pitched, high spectral density roars highlighting vocal tract resonances. The clear divergence of the Iberian red deer vocal repertoire from those of other documented European red deer populations reinforces the status of this geographical variant as a distinct subspecies.