We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Acoustic Battles for the Harem: How the Calls of Siberian Wapiti Reveal Their Status and Individuality


Researchers at HSE University, Lomonosov Moscow State University, and the A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences have studied the distinctive vocalisations of Siberian wapiti (Cervus canadensis sibiricus) stags during the peak of the mating season, when males produce rutting calls (bugles) to attract females (hinds) and deter rivals. The scientists have discovered how the acoustic parameters of these rutting calls reflect the stag's status—whether he currently holds a harem or is still attempting to acquire one—as well as his individual characteristics. The study has been published in Journal of Zoology.

Rutting calls are a vital component of intra-species interactions in Siberian wapiti, enabling stags to attract female hinds (sometimes entire groups) and intimidate rival males. These calls are integral to the mating season. In the wild, competition for keeping a harem (a group of females) is intense, prompting male ungulates to develop sophisticated strategies that combine physical displays and vocal demonstrations of strength. Acoustic displays are highly effective because they carry over long distances and remain reliable even in low-visibility conditions, such as at night, when deer engage in most of their interactions. Rutting calls enable females to assess a male's status and quality from a distance, while also signalling to rivals whether it is worth challenging him in a fight.

Siberian wapiti
© Ilya Volodin and Elena Volodina

The study findings suggest that rutting calls act as a kind of 'passport,' reflecting the stag's harem-holding status. Compared to peripheral stags that remain outside a harem, harem holders produce shorter rutting calls with a higher minimum fundamental frequency.

The fundamental frequency of sound is a parameter that is subjectively perceived as the pitch of a voice and includes various measurements, such as the minimum, maximum, initial, and final fundamental frequencies. Moreover, even in a single stag, a change in status leads to alterations in the parameters of his rutting calls: when he acquires a harem, the initial and maximum fundamental frequencies of his calls decrease, while the minimum fundamental frequency increases, and the calls become shorter.

Siberian wapiti
© Ilya Volodin and Elena Volodina

Although rutting calls can reflect a male's status and change as it evolves, their individual acoustic parameters typically remain consistent. It was previously believed that each stag has unique acoustic characteristics, a kind of vocal signature, allowing it to be distinguished from other stags. This presumed vocal individualisation is still used in nature reserves to monitor the number of stags by ear. In this method, a trained observer, stationed at a specific point, identifies the number of male deer nearby based on the differences in their voices.

According to Olga Sibiryakova, Associate Professor at the HSE Faculty of Biology and Biotechnology and co-author of the study, although individuality is encoded in rutting calls, it does not always manifest clearly enough: zoologists were able to correctly identify the individual stags in 53.2% of calls, which exceeds random chance but indicates that it is not always possible to identify a specific animal. It is noteworthy that discriminant analysis correctly classified 78.9% of bugles according to the stag's status.

'The vocalisations can convey information not only about the individual caller but also about his status, and status information is conveyed much more clearly in the sounds than individuality, which suggests that transmitting status information to others is of greater importance during the mating period,' the researcher notes.

The study findings can be applied to managing deer herds in natural environments, tracking these animals for conservation and hunting purposes, and developing non-invasive methods for studying ungulates. The use of non-invasive monitoring methods can facilitate the work of zoologists and ecologists by allowing them to track the status and behaviour of deer in various conditions without disrupting their natural habitat.

See also:

First Digital Adult Reading Test Available on RuStore

HSE University's Centre for Language and Brain has developed the first standardised tool for assessing Russian reading skills in adults—the LexiMetr-A test. The test is now available digitally on the RuStore platform. This application allows for a quick and effective diagnosis of reading disorders, including dyslexia, in people aged 18 and older.

Low-Carbon Exports Reduce CO2 Emissions

Researchers at the HSE Faculty of Economic Sciences and the Federal Research Centre of Coal and Coal Chemistry have found that exporting low-carbon goods contributes to a better environment in Russian regions and helps them reduce greenhouse gas emissions. The study results have been published in R-Economy.

Russian Scientists Assess Dangers of Internal Waves During Underwater Volcanic Eruptions

Mathematicians at HSE University in Nizhny Novgorod and the A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences studied internal waves generated in the ocean after the explosive eruption of an underwater volcano. The researchers calculated how the waves vary depending on ocean depth and the radius of the explosion source. It turns out that the strongest wave in the first group does not arrive immediately, but after a significant delay. This data can help predict the consequences of eruptions and enable advance preparation for potential threats. The article has been published in Natural Hazards. The research was carried out with support from the Russian Science Foundation (link in Russian).

Centre for Language and Brain Begins Cooperation with Academy of Sciences of Sakha Republic

HSE University's Centre for Language and Brain and the Academy of Sciences of the Republic of Sakha (Yakutia) have signed a partnership agreement, opening up new opportunities for research on the region's understudied languages and bilingualism. Thanks to modern methods, such as eye tracking and neuroimaging, scientists will be able to answer questions about how bilingualism works at the brain level.

How the Brain Responds to Prices: Scientists Discover Neural Marker for Price Perception

Russian scientists have discovered how the brain makes purchasing decisions. Using electroencephalography (EEG) and magnetoencephalography (MEG), researchers found that the brain responds almost instantly when a product's price deviates from expectations. This response engages brain regions involved in evaluating rewards and learning from past decisions. Thus, perceiving a product's value is not merely a conscious choice but also a function of automatic cognitive mechanisms. The results have been published in Frontiers in Human Neuroscience.

AI Predicts Behaviour of Quantum Systems

Scientists from HSE University, in collaboration with researchers from the University of Southern California, have developed an algorithm that rapidly and accurately predicts the behaviour of quantum systems, from quantum computers to solar panels. This methodology enabled the simulation of processes in the MoS₂ semiconductor and revealed that the movement of charged particles is influenced not only by the number of defects but also by their location. These defects can either slow down or accelerate charge transport, leading to effects that were previously difficult to account for with standard methods. The study has been published in Proceedings of the National Academy of Sciences (PNAS).

Electrical Brain Stimulation Helps Memorise New Words

A team of researchers at HSE University, in collaboration with scientists from Russian and foreign universities, has investigated the impact of electrical brain stimulation on learning new words. The experiment shows that direct current stimulation of language centres—Broca's and Wernicke's areas—can improve and speed up the memorisation of new words. The findings have been published in Neurobiology of Learning and Memory.

Artificial Intelligence Improves Risk Prediction of Complex Diseases

Neural network models developed at the HSE AI Research Centre have significantly improved the prediction of risks for obesity, type 1 diabetes, psoriasis, and other complex diseases. A joint study with Genotek Ltd showed that deep learning algorithms outperform traditional methods, particularly in cases involving complex gene interactions (epistasis). The findings have been published in Frontiers in Medicine.

Cerium Glows Yellow: Chemists Discover How to Control Luminescence of Rare Earth Elements

Researchers at HSE University and the Institute of Petrochemical Synthesis of the Russian Academy of Sciences have discovered a way to control both the colour and brightness of the glow emitted by rare earth elements. Their luminescence is generally predictable—for example, cerium typically emits light in the ultraviolet range. However, the scientists have demonstrated that this can be altered. They created a chemical environment in which a cerium ion began to emit a yellow glow. The findings could contribute to the development of new light sources, displays, and lasers. The study has been published in Optical Materials.

Genetic Prediction of Cancer Recurrence: Scientists Verify Reliability of Computer Models

In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.