Arik Kershenbaum

Acoustic sequences in non-human animals: a tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well‐known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near‐future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial‐style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

Syntactic structure and geographical dialects in the songs of male rock hyraxes

Few mammalian species produce vocalizations that are as richly structured as bird songs, and this greatly restricts the capacity for information transfer. Syntactically complex mammalian vocalizations have been previously studied only in primates, cetaceans and bats. We provide evidence of complex syntactic vocalizations in a small social mammal: the rock hyrax (Procavia capensis: Hyracoidea). We adopted three algorithms, commonly used in genetic sequence analysis and information theory, to examine the order of syllables in hyrax calls. Syntactic dialects exist, and the syntax of hyrax calls is significantly different between different regions in Israel. Call syntax difference is positively correlated to geographical distance over short distances. No correlation is found over long distances, which may reflect limited dispersal movement. These findings indicate that rich syntactic structure is more common in the vocalizations of mammalian taxa than previously thought and suggest the possibility of vocal production learning in the hyrax.

Animal vocal sequences: not the Markov chains we thought they were.

Many animals produce vocal sequences that appear complex. Most researchers assume that these sequences are well characterized as Markov chains (i.e. that the probability of a particular vocal element can be calculated from the history of only a finite number of preceding elements). However, this assumption has never been explicitly tested. Furthermore, it is unclear how language could evolve in a single step from a Markovian origin, as is frequently assumed, as no intermediate forms have been found between animal communication and human language. Here, we assess whether animal taxa produce vocal sequences that are better described by Markov chains, or by non-Markovian dynamics such as the ‘renewal process’ (RP), characterized by a strong tendency to repeat elements. We examined vocal sequences of seven taxa: Bengalese finches Lonchura striata domestica, Carolina chickadees Poecile carolinensis, free-tailed bats Tadarida brasiliensis, rock hyraxes Procavia capensis, pilot whales Globicephala macrorhynchus, killer whales Orcinus orca and orangutans Pongo spp. The vocal systems of most of these species are more consistent with a non-Markovian RP than with the Markovian models traditionally assumed. Our data suggest that non-Markovian vocal sequences may be more common than Markov sequences, which must be taken into account when evaluating alternative hypotheses for the evolution of signalling complexity, and perhaps human language origins.

The Encoding of Individual Identity in Dolphin Signature Whistles: How Much Information Is Needed?

Bottlenose dolphins (Tursiops truncatus) produce many vocalisations, including whistles that are unique to the individual producing them. Such “signature whistles” play a role in individual recognition and maintaining group integrity. Previous work has shown that humans can successfully group the spectrographic representations of signature whistles according to the individual dolphins that produced them. However, attempts at using mathematical algorithms to perform a similar task have been less successful. A greater understanding of the encoding of identity information in signature whistles is important for assessing similarity of whistles and thus social influences on the development of these learned calls. We re-examined 400 signature whistles from 20 individual dolphins used in a previous study, and tested the performance of new mathematical algorithms. We compared the measure used in the original study (correlation matrix of evenly sampled frequency measurements) to one used in several previous studies (similarity matrix of time-warped whistles), and to a new algorithm based on the Parsons code, used in music retrieval databases. The Parsons code records the direction of frequency change at each time step, and is effective at capturing human perception of music. We analysed similarity matrices from each of these three techniques, as well as a random control, by unsupervised clustering using three separate techniques: k-means clustering, hierarchical clustering, and an adaptive resonance theory neural network. For each of the three clustering techniques, a seven-level Parsons algorithm provided better clustering than the correlation and dynamic time warping algorithms, and was closer to the near-perfect visual categorisations of human judges. Thus, the Parsons code captures much of the individual identity information present in signature whistles, and may prove useful in studies requiring quantification of whistle similarity.

Entropy rate as a measure of animal vocal complexity

Vocal complexity is an important concept for investigating the role and evolution of animal communication and sociality. However, no one definition of ‘complexity’ appears to be appropriate for all uses. Repertoire size has been used to quantify complexity in many bird and some mammalian studies, but is impractical in cases where vocalizations are highly diverse, and repertoire size is essentially non-limited at realistic sample sizes. Some researchers have used information-theoretic measures such as Shannon entropy, to describe vocal complexity, but these techniques are descriptive only, as they do not address hypotheses of the cognitive mechanisms behind vocal signal generation. In addition, it can be shown that simple measures of entropy, in particular, do not capture syntactic structure. In this work, I demonstrate the use of an alternative information-theoretic measure, the Markov entropy rate, which quantifies the diversity of transitions in a vocal sequence, and thus is capable of distinguishing sequences with syntactic structure from those generated by random, statistically independent processes. I use artificial sequences generated from different stochastic mechanisms, as well as real data from the vocalizations of the rock hyrax Procavia capensis, to show how different complexity metrics scale differently with sample size. I show that entropy rate provides a good measure of complexity for Markov processes and converges faster than repertoire size estimates, such as the Lempel–Ziv metric. The commonly used Shannon entropy performs poorly in quantifying complexity.

A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

BackgroundThe role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation.MethodsThis study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence) built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data). The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation’s Spatiotemporal Epidemiological Modeller (STEM).ResultsAlthough the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS) error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166–2 national subdivisions and with monthly time sampling.ConclusionsThe high spatial resolution possible with state-of-the-art numerical models can identify regions most likely to require intervention due to climate changes. Higher-resolution surveillance data can provide a better understanding of how climate fluctuations affect malaria incidence and improve predictions. An open-source modelling framework, such as STEM, can be a valuable tool for the scientific community and provide a collaborative platform for developing such models.

Unraveling Seasonality in Population Averages: An Examination of Seasonal Variation in Glucose Levels in Diabetes Patients Using a Large Population-based Data Set

It has been shown that the population average blood glucose level of diabetes patients shows seasonal variation, with higher levels in the winter than summer. However, seasonality in the population averages could be due to a tendency in the individual to seasonal variation, or alternatively due to occasional high winter readings (spiking), with different individuals showing this increase in different winters. A method was developed to rule out spiking as the dominant pattern underlying the seasonal variation in the population averages. Three years of data from three community-serving laboratories in Israel were retrieved. Diabetes patients (N = 3243) with a blood glucose result every winter and summer over the study period were selected. For each individual, the following were calculated: seasonal average glucose for all winters and summers over the period of study (2006–2009), winter-summer difference for each adjacent winter-summer pair, and average of these five differences, an index of the degree of spikiness in the pattern of the six seasonal levels, and number of times out of five that each winter-summer difference was positive. Seasonal population averages were examined. The distribution of the individuals differences between adjacent seasons (winter minus summer) was examined and compared between subgroups. Seasonal population averages were reexamined in groups divided according to the index of the degree of spikiness in the individuals glucose pattern over the series of seasons. Seasonal population averages showed higher winter than summer levels. The overall median winter-summer difference on the individual level was 8 mg/dL (0.4 mmol/L). In 16.9% (95% confidence interval [CI]: 15.6–18.2%) of the population, all five winter-summer differences were positive versus 3.6% (95% CI: 3.0–4.2%) where all five winter-summer differences were negative. Seasonal variation in the population averages was not attenuated in the group having the lowest spikiness index; comparison of the distributions of the winter-summer differences in the high-, medium-, and low-spikiness groups showed no significant difference (p = .213). Therefore, seasonality in the population average blood glucose in diabetes patients is not just the result of occasional high measurements in different individuals in different winters, but presumably reflects a general periodic tendency in individuals for winter glucose levels to be higher than summer levels. (Author correspondence: anneke@clalit.org.il)

Modelling evolutionarily stable strategies in oviposition site selection, with varying risks of predation and intraspecific competition

Many ovipositing mosquitoes, as well as other species, can detect biotic factors that affect fitness. However, a female mosquito seeking a high quality oviposition site (e.g. one with low risk of predation and competition to her progeny) must often balance the competing risk of increasing probability of mortality to herself while she continues to search, against increased probability of finding a high quality site. Such oviposition site selection may affect adult population size. We examined a female mosquito’s expected strategy of oviposition site selection under conditions of varying predator prevalence and adult mortality risk, by combining a detailed structured population model with a Markov chain implementation of the adult behavioural process. We used parameter values from the specific mosquito-predator system, Culiseta longiareolata-Notonecta maculata, although the overall results can be generalised to many mosquito species. Our model finds the evolutionarily stable strategy of oviposition site selection for different parameter combinations. Our model predicts that oviposition strategy does not vary smoothly with varying environmental risk of adult mortality, but that certain oviposition strategies become unstable at some parameter values. Mosquitoes will distribute their reproductive effort between breeding sites of varying predation risk only when adult mortality is low or larval competition high. Our model predicts that females will continue searching for predator-free pools, rather than oviposit in the first site encountered, regardless of the risk of mortality to the adult. The ecological basis for a reproductive strategy with alternative behaviours is important for understanding the effect of biotic factors on the population dynamics of mosquitoes, and for the development of biological control strategies, such as the dissemination of predator-cue chemicals.

Disentangling canid howls across multiple species and subspecies: Structure in a complex communication channel.

Wolves, coyotes, and other canids are members of a diverse genus of top predators of considerable conservation and management interest. Canid howls are long-range communication signals, used both for territorial defence and group cohesion. Previous studies have shown that howls can encode individual and group identity. However, no comprehensive study has investigated the nature of variation in canid howls across the wide range of species. We analysed a database of over 2000 howls recorded from 13 different canid species and subspecies. We applied a quantitative similarity measure to compare the modulation pattern in howls from different populations, and then applied an unsupervised clustering algorithm to group the howls into natural units of distinct howl types. We found that different species and subspecies showed markedly different use of howl types, indicating that howl modulation is not arbitrary, but can be used to distinguish one population from another. We give an example of the conservation importance of these findings by comparing the howls of the critically endangered red wolves to those of sympatric coyotes Canis latrans, with whom red wolves may hybridise, potentially compromising reintroduced red wolf populations. We believe that quantitative cross-species comparisons such as these can provide important understanding of the nature and use of communication in socially cooperative species, as well as support conservation and management of wolf populations.

An image processing based paradigm for the extraction of tonal sounds in cetacean communications

Dolphins and whales use tonal whistles for communication, and it is known that frequency modulation encodes contextual information. An automated mathematical algorithm could characterize the frequency modulation of tonal calls for use with clustering and classification. Most automatic cetacean whistle processing techniques are based on peak or edge detection or require analyst assistance in verifying detections. An alternative paradigm is introduced using techniques of image processing. Frequency information is extracted as ridges in whistle spectrograms. Spectral ridges are the fundamental structure of tonal vocalizations, and ridge detection is a well-established image processing technique, easily applied to vocalization spectrograms. This paradigm is implemented as freely available matlab scripts, coined IPRiT (image processing ridge tracker). Its fidelity in the reconstruction of synthesized whistles is compared to another published whistle detection software package, silbido. Both algorithms are also applied to real-world recordings of bottlenose dolphin (Tursiops trunactus) signature whistles and tested for the ability to identify whistles belonging to different individuals. IPRiT gave higher fidelity and lower false detection than silbido with synthesized whistles, and reconstructed dolphin identity groups from signature whistles, whereas silbido could not. IPRiT appears to be superior to silbido for the extraction of the precise frequency variation of the whistle.