Tolerant and intolerant macaques show different levels of structural complexity in their vocal communication

International audienceWe tested the social complexity hypothesis which posits that animals living in complex social environments should use complex communication systems. We focused on two components of vocal complexity: diversity (number of categories of calls) and flexibility (degree of gradation between categories of calls). We compared the acoustic structure of vocal signals in groups of macaques belonging to four species with varying levels of uncertainty (i.e. complexity) in social tolerance (the higher the degree of tolerance, the higher the degree of uncertainty): two intolerant species, Japanese and rhesus macaques, and two tolerant species, Tonkean and crested macaques. We recorded the vocalizations emitted by adult females in affiliative, agonistic and neutral contexts. We analysed several acoustic variables: call duration, entropy, time and frequency energy quantiles. The results showed that tolerant macaques displayed higher levels of vocal diversity and flexibility than intolerant macaques in situations with a greater number of options and consequences, i.e. in agonistic and affiliative contexts. We found no significant differences between tolerant and intolerant macaques in the neutral context where individuals are not directly involved in social interaction. This shows that species experiencing more uncertain social interactions displayed greater vocal diversity and flexibility, which supports the social complexity hypothesis

Robust ecological analysis of camera trap data labelled by a machine learning model

1. Ecological data are collected over vast geographic areas using digital sensors such as camera traps and bioacoustic recorders. Camera traps have become the standard method for surveying many terrestrial mammals and birds, but camera trap arrays often generate millions of images that are time‐consuming to label. This causes significant latency between data collection and subsequent inference, which impedes conservation at a time of ecological crisis. Machine learning algorithms have been developed to improve the speed of labelling camera trap data, but it is uncertain how the outputs of these models can be used in ecological analyses without secondary validation by a human. 2. Here, we present our approach to developing, testing and applying a machine learning model to camera trap data for the purpose of achieving fully automated ecological analyses. As a case‐study, we built a model to classify 26 Central African forest mammal and bird species (or groups). The model generalizes to new spatially and temporally independent data (n = 227 camera stations, n = 23,868 images), and outperforms humans in several respects (e.g. detecting ‘invisible’ animals). We demonstrate how ecologists can evaluate a machine learning model's precision and accuracy in an ecological context by comparing species richness, activity patterns (n = 4 species tested) and occupancy (n = 4 species tested) derived from machine learning labels with the same estimates derived from expert labels. 3. Results show that fully automated species labels can be equivalent to expert labels when calculating species richness, activity patterns (n = 4 species tested) and estimating occupancy (n = 3 of 4 species tested) in a large, completely out‐of‐sample test dataset. Simple thresholding using the Softmax values (i.e. excluding ‘uncertain’ labels) improved the model's performance when calculating activity patterns and estimating occupancy but did not improve estimates of species richness. 4. We conclude that, with adequate testing and evaluation in an ecological context, a machine learning model can generate labels for direct use in ecological analyses without the need for manual validation. We provide the user‐community with a multi‐platform, multi‐language graphical user interface that can be used to run our model offline.Additional co-authors: Cisquet Kiebou Opepa, Ross T. Pitman, Hugh S. Robinso

Real-time alerts from AI-enabled camera traps using the Iridium satellite network: a case-study in Gabon, Central Africa

Efforts to preserve, protect, and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real-time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real-time analysis where there is no reliable cellular or WiFi connectivity. Here, we present our design for a camera trap with integrated artificial intelligence that can send real-time information from anywhere in the world to end-users. We modified an off-the-shelf camera trap (Bushnell) and customised existing open-source hardware to rapidly create a 'smart' camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an 'alert' containing the image label and other metadata is then delivered to the end-user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed-canopy forest in Gabon, Central Africa. Results show the system can operate for a minimum of three months without intervention when capturing a median of 17.23 images per day. The median time-difference between image capture and receiving an alert was 7.35 minutes. We show that simple approaches such as excluding 'uncertain' labels and labelling consecutive series of images with the most frequent class (vote counting) can be used to improve accuracy and interpretation of alerts. We anticipate significant developments in this field over the next five years and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real-time use cases. Potential applications include, but are not limited to, wildlife tourism, real-time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

The importance of rat social behavior for translational research: An ethological approach

At present, the preclinical research interest in rodent social behavior is focused on its use as readout parameter in animal models for neuropsychiatric disorders (‘translational research’). However, there are some major limitations that hamper progress. Pivotal is the limited translational value of the animal models. This becomes apparent by the lack of reproducibility of research results and an overestimation of treatment effects. In this thesis I argue that this can be partly attributed to a currently common practice in behavioral neuroscience: i.e. a limited and too simplistic analysis of animal behavior which ignores behavioral complexity both in approach and analysis. To overcome this problem, I have adopted an ethological approach combined with automation of behavioral analysis to facilitate measurements of rat social behavior. To this end, I have developed a methodology allowing continuous monitoring of social interactions in an experimental setup, including species-specific characteristics. Next, this approach has been applied and tested on two established animal models of impaired social behavior: a chronic phencyclidine (PCP) model and the play deprivation model. Both models were chosen because of their known efficacy to reduce social behavior. An adjusted large home-cage enclosure permitting observations of group-housed rats was used in which rat behavior can be automatically followed and ultrasonic vocalizations can be recorded. First, I show that rat social behavior can be categorized in three distinct modes of inter-individual distances, ‘in contact’, ‘in proximity’ and ‘not in proximity’. A combination of the social modes with the velocity modes, ‘moving with low or high speed’ yields specific categories of behavior. These are susceptible to pharmacological treatments and environmental manipulations. Furthermore, the behavioral categories we defined with our automated analysis approach are consistent with the categories obtained with human scoring of these behaviors (hand scoring of the same experiments). Therefore, automated recognition of patterns in social behavior is a powerful tool for data analysis. Screening of rat exposed to PCP for 2 weeks revealed that the validity of chronic PCP administration as a model for diminished social behavior is limited to short term effects. Because, it only results in a temporarily reduction of social behavior. Moreover, the consummatory phase, i.e. the phase of active social interaction behavior, is not permanently affected, yet, the appetitive phase of social behavior seems permanently effected by chronic PCP, as reflected by a reduction in motivation to engage in social behavior. In the play deprivation model, play deprivation during the sensitive period leads to diminished adult social behavior, according to current literature. However, my behavioral analysis revealed a different effect of play deprivation on adult social behavior. Rather than diminishing sociability, play-deprived rats were actually more sensitive to social contact, i.e. effect of play deprivation merely on the appetitive phase. Also, play-deprived animals were more sensitive to a novel environment, when tested individually. Thus, the studies in this thesis show that an ethological approach in combination with automated methodology reveal differential effects of drug treatment or environmental manipulation on social behavior of rats

Social Vigilance of Friends and Foes in Western Lowland Gorillas (Gorilla gorilla gorilla)

In social species, such as many primate species, conspecifics can pose a threat and individuals that are socially vigilant can prevent harassment. Many previous studies have focused on the role of agonistic interactions on social vigilance. In a variety of primate species, individuals are more vigilant for aggressive or dominant group members. In contrast, only few studies have investigated whether affiliative relationships also affect social vigilance. These studies revealed that individuals with an affiliative relationship showed lower levels of vigilance towards each other. Here, we tested the differential effects of both dyadic agonism and affiliation on the level of social vigilance of group-living western lowland gorillas (Gorilla gorilla gorilla) at Apenheul Primate Park, The Netherlands. We made continuous focal observations of agonistic and affiliative interactions and we scored level of vigilance during neutral approaches of conspecifics. We found that dyads with many affiliative interactions showed lower levels of vigilance towards each other. The opposite pattern was found for agonistic experiences, but this effect was not statistically robust. In addition, the adult male and adolescent males received higher levels of social vigilance than individuals from other age-sex classes. Our results indicate that level of social vigilance was linked to affiliative and, to a lesser extent, agonistic relationships in western lowland gorillas. We suggest that future studies in both egalitarian and despotic species should investigate whether, next to aggression, affiliation also influences social vigilance

Azure-winged magpies’ decisions to share food are contingent on the presence or absence of food for the recipient

Helping others is a key feature of human behavior. However, recent studies render this feature not uniquely human, and describe discoveries of prosocial behavior in non-human primates, other social mammals, and most recently in some bird species. Nevertheless, the cognitive underpinnings of this prosociality; i.e., whether animals take others’ need for help into account, often remain obscured. In this study, we take a first step in investigating prosociality in azure-winged magpies by presenting them with the opportunity to share highly desired food with their conspecifics i) in a situation in which these conspecifics had no such food, ii) in a situation in which they too had access to that highly desired food, and iii) in an open, base-line, situation where all had equal access to the same food and could move around freely. We find that azure-winged magpies regularly share high-value food items, preferably with, but not restricted to, members of the opposite sex. Most notably, we find that these birds, and specifically the females, seem to differentiate between whether others have food or do not have food, and subsequently cater to that lack. Begging calls by those without food seem to function as cues that elicit the food-sharing, but the response to that begging is condition-dependent. Moreover, analyses on a restricted dataset that excluded those events in which there was begging showed exactly the same patterns, raising the possibility that the azure-winged magpies might truly notice when others have access to fewer resources (even in the absence of vocal cues). This sharing behavior could indicate a high level of social awareness and prosociality that should be further investigated. Further studies are needed to establish the order of intentionality at play in this system, and whether azure-winged magpies might be able to attribute desire states to their conspecifics

Long-tailed macaques (Macaca fascicularis) understand what conspecifics can see in a competitive situation

Visual perspective taking (VPT), an understanding of what others can see, is a prerequisite for theory of mind (ToM). While VPT in apes is proven, its presence in monkeys is much-debated. Several different paradigms have been developed to test its existence, but all face interpretational problems since results can be explained by simpler cognitive mechanisms than VPT. Therefore, we adjusted one method where two individuals compete for access to food, visible or invisible for the dominant competitor, to preclude cognitively simpler mechanisms. The subordinate long-tailed macaques tested, selected significantly more often the food item invisible than the item visible to the dominant. In most trials, subjects retrieved only one food item and preferred the invisible food item. Surprisingly, they occasionally adopted an alternative strategy to obtain both food items, by first choosing the visible, most at risk food item. Faster animals adopted this strategy proportionally more often than slower ones. Contrary to previous research, our results cannot be explained by simpler cognitive mechanisms, since behavioural reading was prevented by a one-way mirror between the competitor and the food, and accessibility was equal to both food items. This is the first unequivocal evidence of VPT in a monkey species, suggesting that this precursor to ToM is an evolutionarily conserved capacity present in monkeys, apes and humans

Early environment and the development of social behaviours in the Trinidadian guppy, Poecilia reticulata

One of the many advantages of group living is the swift transfer of information between group members. Social learning – learning from others – offers a quick and economical way to acquire information about the local environment and is considered adaptive under a wide range of circumstances. However, social information can be unreliable or quickly become outdated in rapidly changing environments. Thus flexibility in the utilization of social learning, depending on the associated costs and benefits, would be expected to be advantageous in most situations. Early environment plays a major role in shaping the morphological, physiological or behavioural phenotype of an animal, and conditions and experiences during early life can potentially prepare (or program) a developing individual for the environment it will encounter when adult. In this project we examined whether social behaviours such as grouping and social learning could be influenced by early life conditions and to what extent. For this purpose, we used two different strains of the guppy (domestic and wild-origin), Poecilia reticulata, a popular study system in behavioural and evolutionary ecology with well-described social behaviour. Overall, we found evidence for consistency and heritability in grouping behaviour, but although grouping tendencies were (to some extent) correlated with social learning propensities, we found no evidence for consistency and heritability in social learning. Furthermore, we saw that early environmental conditions and experiences play a major role in shaping the behavioural phenotype of an individual. We found that both cues about the value of social information and context cues like predation risk and population density in early life, can influence an individual’s reliance on social information later in life. Moreover, as males and females differ significantly in their strategies to maximise fitness and survival, these early life cues can affect the behaviour of the two sexes in different ways

Brain weight predicts yawn duration across domesticated dog breeds

Previous research shows that yawning enhances intracranial circulation and regulates brain temperature. Consistent with these functional outcomes, yawn duration correlates positively with interspecies variation in brain weight across mammals, with robust relationships documented at both the taxonomic rank of class and the more restricted scale of family (e.g., Felidae). This study provides the first investigation into whether differences in brain weight within a single species, domesticated dogs Canis lupus familiaris, can predict intraspecific variation in yawn duration. Measures of yawn duration were obtained from public videos available online and then paired with previously published brain and body weight data of different dog breeds. The final sample consisted of 272 yawns from 198 dogs across 23 breeds. Consistent with recent studies, we find robust correlations between yawn duration and brain weight across breeds. Moreover, these correlations remain significant after controlling for differences in body weight across breeds. These findings replicate and extend upon past work in this area and provide further support that yawns evolved to serve an important and large-scale neurophysiologic function