Arik Kershenbaum’s research while affiliated with University of Cambridge and other places

Recent years have seen a dramatic rise in the use of passive acoustic monitoring (PAM) for biological and ecological applications, and a corresponding increase in the volume of data generated. However, data sets are often becoming so sizable that analysing them manually is increasingly burdensome and unrealistic. Fortunately, we have also seen a corresponding rise in computing power and the capability of machine learning algorithms, which offer the possibility of performing some of the analysis required for PAM automatically. Nonetheless, the field of automatic detection of acoustic events is still in its infancy in biology and ecology. In this review, we examine the trends in bioacoustic PAM applications , and their implications for the burgeoning amount of data that needs to be analysed. We explore the different methods of machine learning and other tools for scanning, analysing, and extracting acoustic events automatically from large volumes of recordings. We then provide a step-by-step practical guide for using automatic detection in bioacoustics. One of the biggest challenges for the greater use of automatic detection in bioacoustics is that there is often a gulf in expertise between the biological sciences and the field of machine learning and computer science. Therefore, this review first presents an overview of the requirements for automatic detection in bioacoustics, intended to familiarise those from a computer science background with the needs of the bioacoustics community, followed by an introduction to the key elements of machine learning and artificial intelligence that a biologist needs to understand to incorporate automatic detection into their research. We then provide a practical guide to building an automatic detection pipeline for bioacoustic data, and conclude with a discussion of possible future directions in this field.

Large predators are known to shape the behavior and ecology of sympatric predators via conflict and competition, with mesopredators thought to avoid large predators, while dogs suppress predator activity and act as guardians of human property. However, interspecific communication between predators has not been well‐explored and this assumption of avoidance may oversimplify the responses of the species involved. We explored the acoustic activity of three closely related sympatric canids: wolves Canis lupus, coyotes Canis latrans, and dogs Canis familiaris. These species have an unbalanced triangle of risk: coyotes, as mesopredators, are at risk from both apex‐predator wolves and human‐associated dogs, while wolves fear dogs, and dogs may fear wolves as apex predators or challenge them as intruders into human‐allied spaces. We predicted that risk perception would dictate vocal response with wolves and dogs silencing coyotes as well as dogs silencing wolves. Dogs, in their protective role of guarding human property, would respond to both. Eleven passive acoustic monitoring devices were deployed across 13 nights in central Wisconsin, and we measured the responses of each species to naturally occurring heterospecific vocalizations. Against our expectation, silencing did not occur. Instead, coyotes were not silenced by either species: when hearing wolves, coyotes responded at greater than chance rates and when hearing dogs, coyotes did not produce fewer calls than chance rates. Similarly, wolves responded at above chance rates to coyotes and at chance rates when hearing dogs. Only the dogs followed our prediction and responded at above chance rates in response to both coyotes and wolves. Thus, instead of silencing their competitors, canid vocalizations elicit responses from them suggesting the existence of a complex heterospecific communication network.

In the first part of this series, we delve into the foundational aspects of “Message in a Bottle (MIAB)” (henceforth referred to as MIAB). This study builds upon the legacy of the Voyager Golden Records, launched aboard Voyager 1 and 2 in 1977, which aimed to communicate with intelligent species beyond our world. These records not only offer a snapshot of Earth and human civilization but also represent our desire to establish contact with advanced alien civilizations. Given the absence of mutually understood signs, symbols, and semiotic conventions, MIAB, like its predecessor, uses scientific methods to design an innovative means of communication that encapsulates the story of humanity. Our goal is to share our collective knowledge, emotions, innovations, and aspirations in a way that provides a universal, yet contextually relevant, understanding of human society, the evolution of life on Earth, and our hopes and concerns for the future. Through this time and space traveling capsule, we also strive to inspire and unify current and future generations to celebrate and safeguard our shared human experience.

Does non-human communication, like language, involve meaning? This question guides our focus through an interdisciplinary review of the theories and terminology used to study meaning across disciplines and species. Until now, it has been difficult to apply the concept of meaning to communication in non-humans. This is partly because of the varied approaches to the study of meaning. Additionally, while there is a scholarly acknowledgement of potential meaning in non-human cognition, there is also scepticism when the topic of communication arises. We organise some of the key literature into a coherent framework that can bridge disciplines and species, to ensure that aspects of meaning are accurately and fairly compared. We clarify the growing view in the literature that, rather than requiring multiple definitions or being split into different types, meaning is a multifaceted yet still unified concept. In so doing, we propose that meaning is an umbrella term. Meaning cannot be summed up with a short definition or list of features, but involves multiple complexities that are outlined in our framework. Specifically, three global facets are needed to describe meaning: a Signal Meaning Facet, an Interactant Meaning Facet, and a Resultant Meaning Facet. Most importantly, we show that such analyses are possible to apply as much to non-humans as to humans. We also emphasise that meaning nuances differ among non-human species, making a dichotomous approach to meaning questionable. Instead, we show that a multifaceted approach to meaning establishes how meaning appears within highly diverse examples of non-human communication, in ways consistent with the phenomenon's presence in human non-verbal communication and language(s). Therefore, without further recourse to 'functional' approaches that circumvent the critical question of whether any non-human meaning exists, we show that the concept of meaning is suitable for evolutionary biologists, behavioural ecologists, and others to study, to establish exactly which species exhibit meaning in their communication and in what ways.

Communication is an essential asset enabling humankind to forge an advanced civilization. Using approximately 31,000 languages from the Stone Age to our present digital information society, humans have connected and collaborated to accomplish remarkable feats. As the newly dawned Space Age progresses, we are attempting to communicate with intelligent species beyond our world, on distant planets and in Earth’s far future. Absent mutually understood signs, symbols, and semiotic conventions, this study, the “Message in a Bottle”, uses scientific methods to assess and design a means of communication encapsulating the story of humanity, conveying our thoughts, emotions, ingenuity, and aspirations. The message will be structured to provide a universal yet contextual understanding of modern human society, evolution of life on Earth, and challenges for the future. In assembling this space and time capsule, we aim to energize and unite current generations to celebrate and preserve humanity.

Context: The ecology of cryptic animals is difficult to study without invasive tagging approaches or labour-intensive field surveys. Acoustic localisation provides an effective way to locate vocalising animals using acoustic recorders. Combining this with land cover classification gives new insight into wild animal behaviour using non-invasive tools. Aims: This study aims to demonstrate how acoustic localisation – combined with high-resolution land cover classification – permits the study of the ecology of vocalising animals in the wild. We illustrate this technique by investigating the effect of land cover and distances to anthropogenic features on coyote and wolf vocal behaviour. Methods: We collected recordings over 13 days in Wisconsin, USA, and triangulated vocalising animals’ locations using acoustic localisation. We then mapped these locations onto land cover using a high-resolution land cover map we produced for the area. Key results: Neither coyotes nor wolves vocalised more in one habitat type over another. Coyotes vocalised significantly closer to all human features than expected by chance, whereas wolves vocalised significantly further away. When vocalising closer to human features, coyotes selected forests but wolves showed no habitat preference. Conclusions: This novel combination of two sophisticated, autonomous sensing-driven tools permits us to examine animal land use and behavioural ecology using passive sensors, with the aim of drawing ecologically important conclusions. Implications: We envisage that this method can be used at larger scales to aid monitoring of vocally active animals across landscapes. Firstly, it permits us to characterise habitat use while vocalising, which is an essential behaviour for many species. Furthermore, if combined with additional knowledge of how a species’ habitat selection while vocalising relates to its general habitat use, this method could permit the derivation of future conclusions on prevailing landscape use. In summary, this study demonstrates the potential of integrating acoustic localisation with land cover classification in ecological research.

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.

Context: Synchronised acoustic recorders can be used as a non-invasive tool to detect and localise sounds of interest, including vocal wildlife and anthropogenic sounds. Due to the high cost of commercial synchronised recorders, acoustic localisation has typically been restricted to small or well funded surveys. Recently, low-cost acoustic recorders have been developed, but until now their efficacy has not been compared with higher specification recorders. Aims: The present study aimed to compare the efficacy of a newly developed low-cost recorder, the Conservation at Range through Audio Classification and Localisation (CARACAL), with an established, high-end recorder, the Wildlife Acoustics Song Meter (SM). Methods: Four recorders of each type were deployed in a paired set-up across five nights in Wisconsin, USA. The recordings allowed for manual identification of domestic dog (Canis familiaris), grey wolf (Canis lupus), coyote (Canis latrans) and barred owl (Strix varia) calls, and then the ability of each recorder type to detect and localise the vocalising animals was compared. Key results: The CARACALs were less sensitive, detecting only 47.5% of wolf, 55% of coyote, 65% of barred owl and 82.5% of dog vocalisations detected by the paired SMs. However, when the same vocalisations were detected on both recorders, localisation was comparable, with no significant difference in the precision or maximum detection ranges. Conclusions: Low-cost recording equipment can be used effectively for acoustic localisation of both wild and domestic animals. However, the lower sensitivity of the CARACALs means that a denser network of these recorders would be needed to achieve the same efficacy as the SMs. Deploying a greater number of cheaper recorders increases the labour time in the field and the quantity of data to process and store. Thus, there is a trade-off between cost and time to be considered. Implications: The ability to use low-cost recorders for acoustic localisation provides new avenues for tracking, managing and researching a wide range of wildlife species. Presently, CARACALs are more suited to monitoring species that have small home ranges and high amplitude vocalisations, and for when a large time investment for in situ equipment checks and data processing is feasible.