Daniela Hedwig

The African forest elephant ( Loxodonta cyclotis ) has recently been recognised as its own distinct species and classified as critically endangered. There is increased concern regarding how forest elephants will respond to their continuously deteriorating ecosystems due to climate change and habitat loss and fragmentation. Scoring an animal's body condition is non‐invasive, quick, and can serve as a proxy for monitoring its health and nutritional status. This study developed the first forest elephant‐specific body condition scoring (BCS) system and then investigated how sex, age, rank, and season were associated with adult male and female BCSs at the Dzanga Bai forest clearing, Dzanga‐Ndoki National Park (Central African Republic), using photographs taken during the early (December 2022–January 2023) and late (February–March 2023) dry season. The developed BCS system was based on systems used for Asian ( Elephas maximus ) and African savannah ( L. africana ) elephants and relied on reference photographs and an accompanying flow chart. Male forest elephants had significantly higher BCSs compared to their female counterparts, while no difference by age or rank was observed. Female forest elephants demonstrated a decline in BCS between the early and late dry season. Together, these results highlight different factors that may impact forest elephant condition, potentially reflecting the individual's overall health state.

The African forest elephant (Loxodonta cyclotis) plays a critical role in upholding the Congo Basin’s structure and function, a vital area that supports global carbon sequestration. However, between 1990 and 2021, the species’ numbers declined by 86%, mainly because of ivory hunting. Owing to their elusive nature in the region’s dense rainforests, their responses to human disturbances, such as gun hunting, are not well understood, though the limited studies that have been completed suggest that forest elephants may respond by altering their abundance, distribution and nocturnal activity. Using passive acoustic monitoring (PAM) in and around Nouabalé-Ndoki National Park, Republic of Congo, we assess how gun hunting impacts forest elephant occupancy and night-time vocal activity. Findings reveal that elephant occupancy drops from 0.54 to 0.52 following a gunfire event, a change sustained over 8 days. Additionally, increased gunshots led to a significant rise in the proportion of night-time vocal activity. These behavioural changes can affect forest elephant foraging and reproductive success and their interactions with vegetation, impacting forest growth and function. This study highlights the need for effective conservation strategies to protect the species and their habitats and demonstrates PAMs effectiveness in studying cryptic species in our world’s dense, highly biodiverse and life-sustaining tropical forests. This article is part of the theme issue ‘Acoustic monitoring for tropical ecology and conservation’.

Animal vocalizations encode rich biological information—such as age, sex, behavioural context and emotional state—making bioacoustic analysis a promising non‐invasive method for assessing welfare and population demography. However, traditional bioacoustic approaches, which rely on manually defined acoustic features, are time‐consuming, require specialized expertise and may introduce subjective bias. These constraints reduce the feasibility of analysing increasingly large datasets generated by passive acoustic monitoring (PAM). Transfer learning with Convolutional Neural Networks (CNNs) offers a scalable alternative by enabling automatic acoustic feature extraction without predefined criteria. Here, we applied four pre‐trained CNNs—two general purpose models (VGGish and YAMNet) and two avian bioacoustic models (Perch and BirdNET)—to African forest elephant ( Loxodonta cyclotis ) recordings. We used a dimensionality reduction algorithm (UMAP) to represent the extracted acoustic features in two dimensions and evaluated these representations across three key tasks: (1) call‐type classification (rumble, roar and trumpet), (2) rumble sub‐type identification and (3) behavioural and demographic analysis. A Random Forest classifier trained on these features achieved near‐perfect accuracy for rumbles, with Perch attaining the highest average accuracy (0.85) across all call types. Clustering the reduced features identified biologically meaningful rumble sub‐types—such as adult female calls linked to logistics—and provided clearer groupings than manual classification. Statistical analyses showed that factors including age and behavioural context significantly influenced call variation ( P < 0.001), with additional comparisons revealing clear differences among contexts (e.g. nursing, competition, separation), sexes and multiple age classes. Perch and BirdNET consistently outperformed general purpose models when dealing with complex or ambiguous calls. These findings demonstrate that transfer learning enables scalable, reproducible bioacoustic workflows capable of detecting biologically meaningful acoustic variation. Integrating this approach into PAM pipelines can enhance the non‐invasive assessment of population dynamics, behaviour and welfare in acoustically active species.

How populations adapt to their environment is a fundamental question in biology. Yet, we know surprisingly little about this process, especially for endangered species, such as nonhuman great apes. Chimpanzees, our closest living relatives, are particularly notable because they inhabit diverse habitats, from rainforest to woodland-savannah. Whether genetic adaptation facilitates such habitat diversity remains unknown, despite it having wide implications for evolutionary biology and conservation. By using newly sequenced exomes from 828 wild chimpanzees (388 postfiltering), we found evidence of fine-scale genetic adaptation to habitat, with signatures of positive selection in forest chimpanzees in the same genes underlying adaptation to malaria in humans. This work demonstrates the power of noninvasive samples to reveal genetic adaptations in endangered populations and highlights the importance of adaptive genetic diversity for chimpanzees.

Syntax, the combination of meaning-devoid phonemes into meaningful words, which in turn are combined in structurally and semantically complex sentences, is fundamental to the unlimited expressiveness of human languages. Studying the functions of call combinations in non-human species provides insights into the evolution of such syntactic capabilities. Here, we investigated the combination of high amplitude broadband calls with low frequency rumble vocalizations in a highly social species, the African forest elephantLoxodonta cyclotis. Rumbles play an integral role in coordinating social interactions by transmitting socially relevant information, including individual identity. By contrast, broadband calls, such as roars, are thought to function as signals of distress and urgency as they are typically produced in situations of high emotional intensity. Functional changes associated with the combination of these calls remain little understood. We found that call combinations were produced by all age-sex classes but were most prevalent in immature individuals. We found that rumbles used singularly occurred in all five investigated social contexts, whereas single broadband calls were restricted to two resource-related contexts. Call combinations also occurred in all five contexts, suggesting an increase in the functional use of broadband calls when combined with rumbles, analogous to the generativity brought about through syntax in human speech. Moreover, combining calls appeared to lead to functional shifts towards high-stake contexts. Call combinations were more likely in competition contexts compared to single rumbles, and more likely in separation contexts compared to single broadband calls. We suggest that call combination in forest elephants may aide to reduce message ambiguity in high-stake situation by simultaneously communicating distress and individual identity, which may be critical to secure access to resources, reduce the risk of injury and to reunite with or recruit the support of the family group.

The social complexity hypothesis (SCH) for communication states that the range and frequency of social interactions drive the evolution of complex communication systems. Surprisingly, few studies have empirically tested the SHC for vocal communication systems. Filling this gap is important because a co-evolutionary runaway process between social and vocal complexity may have shaped the most intricate communication system, human language. We here propose the African elephant Loxodonta spec. as an excellent study system to investigate the relationships between social and vocal complexity. We review how the distinct differences in social complexity between the two species of African elephants, the forest elephant L. cyclotis and the savanna elephant L. africana, relate to repertoire size and structure, as well as complex communication skills in the two species, such as call combination or intentional formant modulation including the trunk. Our findings suggest that Loxodonta may contradict the SCH, as well as other factors put forth to explain patterns of vocal complexity across species. We propose that life history traits, a factor that has gained little attention as a driver of vocal complexity, and the extensive parental care associated with a uniquely low and slow reproductive rate, may have led to the emergence of pronounced vocal complexity in the forest elephant despite their less complex social system compared to the savanna elephant. Conclusions must be drawn cautiously, however. A better understanding of vocal complexity in the genus Loxodonta will depend on continuing advancements in remote data collection technologies to overcome the challenges of observing forest elephants in their dense rainforest habitat, as well as the availability of directly comparable data and methods, quantifying both structural and contextual variability in the production of rumbles and other vocalizations in both species of African elephants.

Background: Videographic material of animals can contain inapparent signals, such as color changes or motion that hold information about physiological functions, such as heart and respiration rate, pulse wave velocity, and vocalization. Eulerian video magnification allows the enhancement of such signals to enable their detection. The purpose of this study is to demonstrate how signals relevant to experimental physiology can be extracted from non-contact videographic material of animals.Results: We applied Eulerian video magnification to detect physiological signals in a range of experimental models and in captive and free ranging wildlife. Neotenic Mexican axolotls were studied to demonstrate the extraction of heart rate signal of non-embryonic animals from dedicated videographic material. Heart rate could be acquired both in single and multiple animal setups of leucistic and normally colored animals under different physiological conditions (resting, exercised, or anesthetized) using a wide range of video qualities. Pulse wave velocity could also be measured in the low blood pressure system of the axolotl as well as in the high-pressure system of the human being. Heart rate extraction was also possible from videos of conscious, unconstrained zebrafish and from non-dedicated videographic material of sand lizard and giraffe. This technique also allowed for heart rate detection in embryonic chickens in ovo through the eggshell and in embryonic mice in utero and could be used as a gating signal to acquire two-phase volumetric micro-CT data of the beating embryonic chicken heart. Additionally, Eulerian video magnification was used to demonstrate how vocalization-induced vibrations can be detected in infrasound-producing Asian elephants.Conclusions: Eulerian video magnification provides a technique to extract inapparent temporal signals from videographic material of animals. This can be applied in experimental and comparative physiology where contact-based recordings (e.g., heart rate) cannot be acquired.

Quantitative assessments of the structure of vocalizations are a fundamental prerequisite to understand a species’ vocal communication system and, more broadly, the selective pressures shaping vocal repertoires. For example, to reduce ambiguity in signal interpretation in the absence of auxiliary visual cues, species in densely vegetated habitats should exhibit more discrete vocal signals than species in open habitats. To test this “ambiguity reduction hypothesis”, we conducted the first quantitative assessment of the rumble vocalizations of the forest elephant. Based on 686 forest elephant rumbles recorded with autonomous acoustic recording units at four sites across Central Africa, we used model-based cluster analyses paired with subsequent evaluation of cluster-discreteness and discriminant function analyses to quantify the structure of rumbles based on 23 source- and filter-related acoustic parameters. Model-based cluster analyses suggest that rumbles can be classified into five to eight types. Similar to previous findings in savannah elephants and contrary to the ambiguity reduction hypothesis, average silhouette coefficients below 0.34 indicated that these rumble types were highly intergraded. However, discriminant function analyses predicted rumble types with at least 75% accuracy whereby the location of the minimum fundamental frequency, middle slope and peak frequency contributed most to separation between types. In line with an increasing number of studies highlighting that a distinction between discrete and graded repertoires may have little biological significance, we propose that ambiguity reduction may take place through the evolution of perceptual and cognitive mechanisms, rather than acting on vocal production.

More than just numbers: We often frame negative human impacts on animal species in terms of numbers of individuals reduced or numbers of regions from which species are absent. However, human activities are likely affecting species in more complex ways than these figures can capture. Kühl et al. studied behavioral and cultural diversity in our closest relative, the chimpanzee. They found that human-mediated disturbance is reducing these complex traits. Human influence thus goes well beyond simple loss of populations or species, leading to behavioral change even where populations persist. Science , this issue p. 1453