The evolution of social play in songbirds, parrots and cockatoos - emotional or highly complex cognitive behaviour or both?

Social play has been described in many animals. However, much of this social behaviour among birds, particularly in adults, is still relatively unexplored in terms of the environmental, psychological, and social dynamics of play. This paper provides an overview of what we know about adult social play in birds and addresses areas in which subtleties and distinctions, such as in play initiation and social organisation and its relationship to expressions of play, are considered in detail. The paper considers emotional, social, innovative, and cognitive aspects of play, then the environmental conditions and affiliative bonds, suggesting a surprisingly complex framework of criteria awaiting further research. Adult social play has so far been studied in only a small number of avian species, exclusively in those with a particularly large brain relative to body size without necessarily addressing brain functions and lateralization. When lateralization of brain function is considered, it can further illuminate a possibly significant relevance of play behaviour to the evolution of cognition, to management of emotions, and the development of sociality.

callsync: An R package for alignment and analysis of multi-microphone animal recordings

To better understand how vocalisations are used during interactions of multiple individuals, studies are increasingly deploying on-board devices with a microphone on each animal. The resulting recordings are extremely challenging to analyse, since microphone clocks drift non-linearly and record the vocalisations of non-focal individuals as well as noise. Here we address this issue with callsync, an R package designed to align recordings, detect and assign vocalisations to the caller, trace the fundamental frequency, filter out noise and perform basic analysis on the resulting clips. We present a case study where the pipeline is used on a dataset of six captive cockatiels (Nymphicus hollandicus) wearing backpack microphones. Recordings initially had a drift of ~2 min, but were aligned to within ~2 s with our package. Using callsync, we detected and assigned 2101 calls across three multi-hour recording sessions. Two had loud beep markers in the background designed to help the manual alignment process. One contained no obvious markers, in order to demonstrate that markers were not necessary to obtain optimal alignment. We then used a function that traces the fundamental frequency and applied spectrographic cross correlation to show a possible analytical pipeline where vocal similarity is visually assessed. The callsync package can be used to go from raw recordings to a clean dataset of features. The package is designed to be modular and allows users to replace functions as they wish. We also discuss the challenges that might be faced in each step and how the available literature can provide alternatives for each step.

Multilevel Bayesian analysis of monk parakeet contact calls shows dialects between European cities

Geographic differences in vocalizations provide strong evidence for animal culture, with patterns likely arising from generations of social learning and transmission. Most studies on the evolution of avian vocal variation have predominantly focused on fixed repertoire, territorial song in passerine birds. The study of vocal communication in open-ended learners and in contexts where vocalizations serve other functions is therefore necessary for a more comprehensive understanding of vocal dialect evolution. Parrots are open-ended vocal production learners that use vocalizations for social contact and coordination. Geographic variation in parrot vocalizations typically take the form of either distinct regional variations known as dialects or graded variation based on geographic distance known as clinal variation. In this study, we recorded monk parakeets (Myiopsitta monachus) across multiple spatial scales (i.e., parks and cities) in their European invasive range. We then compared calls using a multilevel Bayesian model and sensitivity analysis, with this novel approach allowing us to explicitly compare vocalizations at multiple spatial scales. We found support for founder effects and/or cultural drift at the city level, consistent with passive cultural processes leading to large-scale dialect differences. We did not find a strong signal for dialect or clinal differences between parks within cities, suggesting that birds did not actively converge on a group level signal, as expected under the group membership hypothesis. We demonstrate the robustness of our findings and offer an explanation that unifies the results of prior monk parakeet vocalization studies.

Evidence for vocal signatures and voice-prints in a wild parrot

In humans, identity is partly encoded in a voice-print that is carried across multiple vocalizations. Other species also signal vocal identity in calls, such as shown in the contact call of parrots. However, it remains unclear to what extent other call types in parrots are individually distinct, and whether there is an analogous voice-print across calls. Here we test if an individual signature is present in other call types, how stable this signature is, and if parrots exhibit voice-prints across call types. We recorded 5599 vocalizations from 229 individually marked monk parakeets (Myiopsitta monachus) over a 2-year period in Barcelona, Spain. We examined five distinct call types, finding evidence for an individual signature in three. We further show that in the contact call, while birds are individually distinct, the calls are more variable than previously assumed, changing over short time scales (seconds to minutes). Finally, we provide evidence for voice-prints across multiple call types, with a discriminant function being able to predict caller identity across call types. This suggests that monk parakeets may be able to use vocal cues to recognize conspecifics, even across vocalization types and without necessarily needing active vocal signatures of identity.

Individual identity information persists in learned calls of introduced parrot populations

Animals can actively encode different types of identity information in learned communication signals, such as group membership or individual identity. The social environments in which animals interact may favor different types of information, but whether identity information conveyed in learned signals is robust or responsive to social disruption over short evolutionary timescales is not well understood. We inferred the type of identity information that was most salient in vocal signals by combining computational tools, including supervised machine learning, with a conceptual framework of "hierarchical mapping", or patterns of relative acoustic convergence across social scales. We used populations of a vocal learning species as a natural experiment to test whether the type of identity information emphasized in learned vocalizations changed in populations that experienced the social disruption of introduction into new parts of the world. We compared the social scales with the most salient identity information among native and introduced range monk parakeet (Myiopsitta monachus) calls recorded in Uruguay and the United States, respectively. We also evaluated whether the identity information emphasized in introduced range calls changed over time. To place our findings in an evolutionary context, we compared our results with another parrot species that exhibits well-established and distinctive regional vocal dialects that are consistent with signaling group identity. We found that both native and introduced range monk parakeet calls displayed the strongest convergence at the individual scale and minimal convergence within sites. We did not identify changes in the strength of acoustic convergence within sites over time in the introduced range calls. These results indicate that the individual identity information in learned vocalizations did not change over short evolutionary timescales in populations that experienced the social disruption of introduction. Our findings point to exciting new research directions about the robustness or responsiveness of communication systems over different evolutionary timescales.

Improving the workflow to crack Small, Unbalanced, Noisy, but Genuine (SUNG) datasets in bioacoustics: The case of bonobo calls

Despite the accumulation of data and studies, deciphering animal vocal communication remains challenging. In most cases, researchers must deal with the sparse recordings composing Small, Unbalanced, Noisy, but Genuine (SUNG) datasets. SUNG datasets are characterized by a limited number of recordings, most often noisy, and unbalanced in number between the individuals or categories of vocalizations. SUNG datasets therefore offer a valuable but inevitably distorted vision of communication systems. Adopting the best practices in their analysis is essential to effectively extract the available information and draw reliable conclusions. Here we show that the most recent advances in machine learning applied to a SUNG dataset succeed in unraveling the complex vocal repertoire of the bonobo, and we propose a workflow that can be effective with other animal species. We implement acoustic parameterization in three feature spaces and run a Supervised Uniform Manifold Approximation and Projection (S-UMAP) to evaluate how call types and individual signatures cluster in the bonobo acoustic space. We then implement three classification algorithms (Support Vector Machine, xgboost, neural networks) and their combination to explore the structure and variability of bonobo calls, as well as the robustness of the individual signature they encode. We underscore how classification performance is affected by the feature set and identify the most informative features. In addition, we highlight the need to address data leakage in the evaluation of classification performance to avoid misleading interpretations. Our results lead to identifying several practical approaches that are generalizable to any other animal communication system. To improve the reliability and replicability of vocal communication studies with SUNG datasets, we thus recommend: i) comparing several acoustic parameterizations; ii) visualizing the dataset with supervised UMAP to examine the species acoustic space; iii) adopting Support Vector Machines as the baseline classification approach; iv) explicitly evaluating data leakage and possibly implementing a mitigation strategy.

A survey of vocal mimicry in companion parrots

Parrots are one of the rare animal taxa with life-long vocal learning. Parrot vocal repertoires are difficult to study in the wild, but companion parrots offer a valuable data source. We surveyed the public about mimicry repertoires in companion parrots to determine whether vocal learning varied by (1) species, (2) sex, (3) age, and (4) social interaction with other parrots. Species differed significantly in mimicry ability, with grey parrots (Psittacus erithacus) having the largest mimicry repertoires. Analyses of all birds (n = 877) found no overarching effects of sex, age, or parrot-parrot social interactions on mimicry repertoires. Follow up analyses (n = 671), however, revealed a human bias to assume that talking parrots are male, and indicated that five of the 19 best-sampled species exhibited sex differences. Age-specific analyses of grey parrots (n = 187) indicated that repertoire size did not increase during adulthood. Most parrots were capable of improvisation (e.g. rearranging words) and used mimicry in appropriate human contexts. Results indicate that parrot vocal production learning varies among and within species, suggesting that the mechanisms and functions of learning also vary. Our data provide a rich foundation for future comparative research on avian vocalizations, and broaden our understanding of the underpinnings of communicative behavior and learning across all animals.

Fine-scale genetic structure reflects limited and coordinated dispersal in the colonial monk parakeet, Myiopsitta monachus

The genetic structure of animal populations has considerable behavioural, ecological and evolutionary implications and may arise from various demographic traits. Here, we use observational field data and molecular genetics to determine the genetic structure of an invasive population of monk parakeets, Myiopsitta monachus, at a range of spatial scales, and investigate the demographic processes that generate the observed structure. Monk parakeets construct large nests that can house several pairs occupying separate chambers; these nests are often aggregated within nesting trees. We determined patterns of relatedness within compound nests, within nesting trees and between trees. Spatial autocorrelation analyses of pairwise genetic relatedness revealed fine-scale genetic structure with relatives of both sexes spatially clustered within, but not beyond, nesting trees. In addition, males were more related to males sharing their compound nests than to other males occupying the same nesting tree. By contrast, males and females within compound nests were not significantly more closely related than elsewhere in the same tree, and we found no evidence for inbreeding. Adults showed high breeding site fidelity between years despite considerable disturbance of nest sites. Natal dispersal was female-biased, but dispersal distances were relatively short with some natal philopatry observed in both sexes. Sibling coalitions, typically of males, were observed amongst both philopatric and dispersing birds. Our results show significant clustering of kin within compound nests and nesting trees resulting from limited and coordinated natal dispersal, with subsequent breeding site fidelity. The resulting genetic structure has implications for social behaviour in this unusual parrot species.

Fine-scale genetic structure in the critically endangered red-fronted macaw in the absence of geographic and ecological barriers

Behavioural and socio-cultural traits are recognized in the restriction of gene flow in species with high cognitive capacity and complex societies. This isolation by social barriers has been generally overlooked in threatened species by assuming disrupted gene flow due to population fragmentation and decline. We examine the genetic structure and ecology of the global population of the Critically Endangered red-fronted macaw (Ara rubrogenys), an endemic species to the inter-Andean valleys of Bolivia. We found a fine-scale genetic structuring in four genetic clusters. Genetic diversity was higher in wild compared to captive-bred macaws, but similar to that of captive wild-caught macaws. We found no clear evidence of severe genetic erosion in the population in recent decades, but it was patent in historic times, overlapping with drastic human habitat transformation and macaw persecution over millennia. We found no evidence of geographical and ecological barriers, owing to the high dispersal ability, nesting and foraging habits between genetic clusters. The lack of genetic intermixing despite long-distance foraging and seasonal movements suggests recruitment in natal colonies and other social factors reinforcing philopatry-related genetic structure. Conservation efforts should be specifically focussed on major threats in each genetic cluster as independent conservation units, and also considered in ex-situ management.