If like me you tend to struggle with speaking a foreign language, then you’ve probably also experienced that ‘lost in translation’ feeling. During my PhD research studying Aegean wall lizards in Greece I learned various Greek phrases to get by, but the language baffled me all the same. Yes, I’ve said it many times before – it’s all Greek to me.
The origins of human language, and how it has diverged into a massive 6,500 different languages around the world, is an intriguing and complex question that remains largely unsolved, attracting a long history of debate and potential explanations, such as its importance in developing tools.
But we can also gain a lot of insight by studying the early evolution of vocal communication in other animals, particularly in those that are socially and behaviourally similar to us.
Animals in the Canidae family – wolves, domestic dogs, jackals and coyotes – are extremely sociable like us, often hunting and living in large packs and ranging over wide distances. Howling vocalisations help them to communicate over these great distances and are thought to play a role in important social interactions like maintaining group cohesion as well as in territorial advertising. Previous experiments using playbacks have shown that wolves better recognise the “voice” of familiar than unfamiliar individuals, (even if elements of their howls are artificially changed) and howling between individuals depends on how well the two get along.
New research published this week in Behavioural Processes has revealed that canids use different types of howls that are specific to their own species, and even subspecies, revealing new insights about the diversity and specialisation of their vocal communication.
The study, led by Dr Arik Kershenbaum at the University of Cambridge, is the largest of its kind so far. Initially, the researchers diligently gathered 6,000 recordings from captive and wild howling canids from all over the globe, ranging from India to Australia, to Europe and the United States. This included downloading recordings of domestic dog howls from YouTube. Maybe this beauty was part of the sample?
The 6,000 recordings were whittled down to 2,000 from a total of 13 species and subspecies of canids for the final study. These were fed into a machine learning computer algorithm, which eventually classified them into 21 discrete (distinguishable) types.
I particularly like this computer algorithm method because it avoids previously used human-based classification of howls. In particular, this new computer analysis is more likely to identify subtle similarities and differences between the vocalisations that human assessments could miss.
The study found that the vocalisations were usually very distinct among the 13 different species/subspecies, revealing typical vocal dialects or “vocal signatures” for each group.
But, some bore quite striking similarities, the consequences of which could be drastic. Specifically, similar vocalisations between different species could lead to interbreeding and the resulting hybrids could decrease genetic diversity, outcompete indigenous pure species, and even cause sterility. In one case, it could even threaten the survival of one species – the red wolf (Canis rufus).
Red wolves, which had been hunted almost to extinction in the U.S. by the middle of the 20th century, have been reintroduced into the wild but their success has been threatened by hybridisation with coyotes. This may be in part because the two species were found to use very similar vocalisations: modulated, whining howls. The researchers suggest that these new insights into howling behaviour could help keep the red wolf and coyote populations apart and so prevent the red wolf from disappearing altogether.
I think the next step is to develop ways of measuring how these vocal signals are transmitted to the actual ear of intended, natural receivers – that is, conspecifics – in natural environments, and their ensuing behavioural responses to them. This way we can understand how the howls have evolved to become tuned to effectively transmit to the ear of conspecifics in a given environment, as well as what type of information they are actually communicating.
For now, though, we are getting closer to realising the sheer complexity and specialisation of vocal communication in animals, which can have important consequences on species conservation.
Perhaps this type of research can also tell us something about how our own language skills and diverse dialects have arisen. We know that primitive humans started talking to each other at some point between 50,000 to 100,000 years ago, after which complex language quickly developed, with languages being universally connected by syntax.