Many morphs: Parsing gesture signals from the noise

Parsing signals from noise is a general problem for signallers and recipients, and for researchers studying communicative systems. Substantial efforts have been invested in comparing how other species encode information and meaning, and how signalling is structured. However, research depends on identifying and discriminating signals that represent meaningful units of analysis. Early approaches to defining signal repertoires applied top-down approaches, classifying cases into predefined signal types. Recently, more labour-intensive methods have taken a bottom-up approach describing detailed features of each signal and clustering cases based on patterns of similarity in multi-dimensional feature-space that were previously undetectable. Nevertheless, it remains essential to assess whether the resulting repertoires are composed of relevant units from the perspective of the species using them, and redefining repertoires when additional data become available. In this paper we provide a framework that takes data from the largest set of wild chimpanzee (Pan troglodytes) gestures currently available, splitting gesture types at a fine scale based on modifying features of gesture expression using latent class analysis (a model-based cluster detection algorithm for categorical variables), and then determining whether this splitting process reduces uncertainty about the goal or community of the gesture. Our method allows different features of interest to be incorporated into the splitting process, providing substantial future flexibility across, for example, species, populations, and levels of signal granularity. Doing so, we provide a powerful tool allowing researchers interested in gestural communication to establish repertoires of relevant units for subsequent analyses within and between systems of communication.

GesturalOrigins: A bottom-up framework for establishing systematic gesture data across ape species

Current methodologies present significant hurdles to understanding patterns in the gestural communication of individuals, populations, and species. To address this issue, we present a bottom-up data collection framework for the study of gesture: GesturalOrigins. By "bottom-up", we mean that we minimise a priori structural choices, allowing researchers to define larger concepts (such as 'gesture types', 'response latencies', or 'gesture sequences') flexibly once coding is complete. Data can easily be re-organised to provide replication of, and comparison with, a wide range of datasets in published and planned analyses. We present packages, templates, and instructions for the complete data collection and coding process. We illustrate the flexibility that our methodological tool offers with worked examples of (great ape) gestural communication, demonstrating differences in the duration of action phases across distinct gesture action types and showing how species variation in the latency to respond to gestural requests may be revealed or masked by methodological choices. While GesturalOrigins is built from an ape-centred perspective, the basic framework can be adapted across a range of species and potentially to other communication systems. By making our gesture coding methods transparent and open access, we hope to enable a more direct comparison of findings across research groups, improve collaborations, and advance the field to tackle some of the long-standing questions in comparative gesture research.

Flexibility in the social structure of male chimpanzees (Pan troglodytes schweinfurthii) in the Budongo Forest, Uganda

Individuals of social species experience competitive costs and social benefits of group living. Substantial flexibility in humans' social structure and the combination of different types of social structure with fission-fusion dynamics allow us to live in extremely large groups-overcoming some of the costs of group living while capitalizing on the benefits. Non-human species also show a range of social strategies to deal with this trade-off. Chimpanzees are an archetypical fission-fusion species, using dynamic changes in day-to-day association to moderate the costs of within-group competition. Using 4 years of association data from two neighbouring communities of East African chimpanzees (Pan troglodytes schweinfurthii), we describe an unexplored level of flexibility in chimpanzee social structure. We show that males from the larger Waibira community (N = 24-31) exhibited additional structural levels of semi-stable core-periphery society, while males from the smaller Sonso community (N = 10-13) did not. This novel core-periphery pattern adds to previous results describing alternative modular social structure in other large communities of chimpanzees. Our data support the hypothesis that chimpanzees can incorporate a range of strategies in addition to fission-fusion to overcome costs of social living, and that their social structures may be closer to that of modern humans than previously described.

A socio-ecological perspective on the gestural communication of great ape species, individuals, and social units

Over the last 30 years, most research on non-human primate gestural communication has been produced by psychologists, which has shaped the questions asked and the methods used. These researchers have drawn on concepts from philosophy, linguistics, anthropology, and ethology, but despite these broad influences the field has neglected to situate gestures into the socio-ecological context in which the diverse species, individuals, and social-units exist. In this review, we present current knowledge about great ape gestural communication in terms of repertoires, meanings, and development. We fold this into a conversation about variation in other types of ape social behaviour to identify areas for future research on variation in gestural communication. Given the large variation in socio-ecological factors across species and social-units (and the individuals within these groups), we may expect to find different preferences for specific gesture types; different needs for communicating specific meanings; and different rates of encountering specific contexts. New tools, such as machine-learning based automated movement tracking, may allow us to uncover potential variation in the speed and form of gesture actions or parts of gesture actions. New multi-group multi-generational datasets provide the opportunity to apply analyses, such as Bayesian modelling, which allows us to examine these rich behavioural landscapes. Together, by expanding our questions and our methods, researchers may finally be able to study great ape gestures from the perspective of the apes themselves and explore what this gestural communication system reveals about apes’ thinking and experience of their world.

Global COVID-19 lockdown highlights humans as both threats and custodians of the environment

The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence. However, negative effects of lockdown on conservation also emerged, as confinement resulted in some park officials being unable to perform conservation, restoration and enforcement tasks, resulting in local increases in illegal activities such as hunting. Overall, there is a complex mixture of positive and negative effects of the pandemic lockdown on nature, all of which have the potential to lead to cascading responses which in turn impact wildlife and nature conservation. While the net effect of the lockdown will need to be assessed over years as data becomes available and persistent effects emerge, immediate responses were detected across the world. Thus, initial qualitative and quantitative data arising from this serendipitous global quasi-experimental perturbation highlights the dual role that humans play in threatening and protecting species and ecosystems. Pathways to favorably tilt this delicate balance include reducing impacts and increasing conservation effectiveness.

BioTIME: A database of biodiversity time series for the Anthropocene

MOTIVATION

The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.

MAIN TYPES OF VARIABLES INCLUDED

The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.

SPATIAL LOCATION AND GRAIN

BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).

TIME PERIOD AND GRAIN

BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.

MAJOR TAXA AND LEVEL OF MEASUREMENT

BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

SOFTWARE FORMAT

.csv and .SQL.