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Stable isotope analysis is an increasingly used molecular tool to reconstruct the diet and ecology of elusive primates such as unhabituated chimpanzees. The consumption of C 4 plant feeding termites by chimpanzees may partly explain the relatively high carbon isotope values reported for some chimpanzee communities. However, the modest availability of termite isotope data as well as the diversity and cryptic ecology of termites potentially consumed by chimpanzees obscures our ability to assess the plausibility of these termites as a C 4 resource. Here we report the carbon and nitrogen isotope values from 79 Macrotermes termite samples from six savanna woodland chimpanzee research sites across equatorial Africa. Using mixing models, we estimated the proportion of Macrotermes C 4 plant consumption across savanna woodland sites. Additionally, we tested for isotopic differences between termite colonies in different vegetation types and between the social castes within the same colony in a subset of 47 samples from 12 mounds. We found that Macrotermes carbon isotope values were indistinguishable from those of C 3 plants. Only 5 to 15% of Macrotermes diets were comprised of C 4 plants across sites, suggesting that they cannot be considered a C 4 food resource substantially influencing the isotope signatures of consumers. In the Macrotermes subsample, vegetation type and caste were significantly correlated with termite carbon values, but not with nitrogen isotope values. Large Macrotermes soldiers, preferentially consumed by chimpanzees, had comparably low carbon isotope values relative to other termite castes. We conclude that Macrotermes consumption is unlikely to result in high carbon isotope values in either extant chimpanzees or fossil hominins.

Background Metabarcoding of vertebrate DNA found in invertebrates (iDNA) represents a potentially powerful tool for monitoring biodiversity. Preliminary evidence suggests fly iDNA biodiversity assessments compare favorably with established approaches such as camera trapping or line transects. Aims and Methods To assess whether fly‐derived iDNA is consistently useful for biodiversity monitoring across a diversity of ecosystems, we compared metabarcoding of the mitochondrial 16S gene of fly pool‐derived iDNA (range = 49–105 flies/site, N = 784 flies) with camera traps (range = 198–1,654 videos of mammals identified to the species level/site) at eight sites, representing different habitat types in five countries across tropical Africa. Results We detected a similar number of mammal species using fly‐derived iDNA (range = 8–15 species/site) and camera traps (range = 8–27 species/site). However, the two approaches detected mostly different species (range = 6%–43% of species detected/site were detected with both methods), with fly‐derived iDNA detecting on average smaller‐bodied species than camera traps. Despite addressing different phylogenetic components of local mammalian communities, both methods resulted in similar beta‐diversity estimates across sites and habitats. Conclusion These results support a growing body of evidence that fly‐derived iDNA is a cost‐ and time‐efficient tool that complements camera trapping in assessing mammalian biodiversity. Fly‐derived iDNA may facilitate biomonitoring in terrestrial ecosystems at broad spatial and temporal scales, in much the same way as water eDNA has improved biomonitoring across aquatic ecosystems. To assess whether fly‐derived iDNA is consistently useful for biodiversity monitoring across a diversity of ecosystems, we compared metabarcoding of the mitochondrial 16S gene of fly pool‐derived iDNA with camera traps at eight sites, representing different habitat types in five countries across tropical Africa. We detected a similar number of mammal species using fly‐derived iDNA and camera traps; however, the two approaches detected mostly different species suggesting these approaches are complementary.

Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (Pan troglodytes) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists with that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species. Citizen science has expanded rapidly in popularity, leading to a growing need to ensure data accuracy in citizen science research projects. We validated the accuracy of chimpanzee detection and individual identification data from the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees and other species across Equatorial Africa. When comparing data from citizen scientists with those of experts who coded the same videos, we found a high level of agreement in detecting and identifying chimpanzees, although citizen scientists assigned fewer IDs overall. The resulting citizen scientist data could be used to construct a robust social network with a similar structure and network positions to that constructed from expert data coded from the same camera trap videos.

As camera trapping grows in popularity and application, some analytical limitations persist including processing time and accuracy of data annotation. Typically images are recorded by camera traps although videos are becoming increasingly collected even though they require much more time for annotation. To overcome limitations with image annotation, camera trap studies are increasingly linked to community science (CS) platforms. Here, we extend previous work on CS image annotations to camera trap videos from a challenging environment; a dense tropical forest with low visibility and high occlusion due to thick canopy cover and bushy undergrowth at the camera level. Using the CS platform Chimp&See, established for classification of 599 956 video clips from tropical Africa, we assess annotation precision and accuracy by comparing classification of 13 531 1‐min video clips by a professional ecologist (PE) with output from 1744 registered, as well as unregistered, Chimp&See community scientists. We considered 29 classification categories, including 17 species and 12 higher‐level categories, in which phenotypically similar species were grouped. Overall, annotation precision was 95.4%, which increased to 98.2% when aggregating similar species groups together. Our findings demonstrate the competence of community scientists working with camera trap videos from even challenging environments and hold great promise for future studies on animal behaviour, species interaction dynamics and population monitoring. Résumé Alors que le piégeage photographique gagne en popularité et en application, certaines limites analytiques persistent, notamment le temps de traitement et la précision de l'annotation des données. Les images statiques sont le plus souvent enregistrées par les pièges photographiques, mais la collecte de vidéos est de plus en plus répandue, même si l'annotation des données prend beaucoup plus de temps. Pour surmonter les limitations liées à l’annotation des images, les études sur les pièges photographiques sont de plus en plus souvent associées aux plateformes de sciences communautaires (SC). Ici, nous étendons les travaux précédents sur les annotations d'images par la SC aux vidéos de pièges photographiques provenant d'un environnement difficile : une forêt tropicale dense avec une faible visibilité et une forte obstruction visuelle en raison de l'épaisse couverture de la canopée et des sous‐bois buissonneux au niveau de la caméra. En utilisant la plateforme de SC Chimp&See, établie pour la classification de 599 956 clips vidéo d'Afrique tropicale, nous évaluons la précision et l'exactitude des annotations en comparant la classification de 13 531 clips vidéo d'une durée d'une minute par un écologiste professionnel avec les résultats de 1 744 scientifiques communautaires enregistrés sur Chimp&See, en plus de ceux non‐enregistrés. Nous avons pris en compte 29 catégories de classification, comprenant 17 espèces et 12 catégories de niveau supérieur, dans lesquelles les espèces phénotypiquement similaires ont été regroupées. Dans l'ensemble, la précision des annotations était de 95,4 %, et de 98,2 % lorsque les groupes d'espèces similaires étaient regroupés. Nos résultats démontrent la compétence des scientifiques communautaires travaillant avec des vidéos issues de pièges photographiques, même dans des environnements difficiles, et sont très prometteurs pour les études futures sur le comportement des animaux, la dynamique des interactions entre les espèces et le suivi des populations. Even though they require more time for annotation compared to still images, camera trap videos provide valuable acoustic and visual information on species’ behaviour and can improve identification of individuals. Here we use Community Science (CS) to annotate camera trap videos from a challenging environment, a dense tropical forest with low visibility and high occlusion. Using the CS platform Chimp&See, we assess annotation precision and accuracy by comparing classification of 13 531 1‐min video clips by a professional ecologist with 1744 Chimp&See community scientists. Overall, annotation precision was between 95.4 and 98.1%. Our findings demonstrate the competence of community scientists with challenging videos and hold great promise for future studies on animal behaviour and population monitoring.

Metabarcoding of invertebrate‐derived DNA (iDNA) is an excellent tool for assessing terrestrial mammal diversity. A major constraint to wider adoption is the time and costs associated with sample processing. Here, we explored the effectiveness of bulk fly iDNA extraction, which increased the pooling of flies by an order of magnitude over currently used methods. One extraction method involved removing a single leg per fly from many flies, pooling these legs, and destructively extracting DNA from the pool (Nflies legs per pool = 105). The other involved non‐destructively extracting DNA from a large pool of entire flies (Nflies per pool = 105). We tested these methods on flies collected at eight sites, representing three different habitats across five countries in sub‐Saharan Africa (Nflies/site = 105; Nflies total = 840). We compared the mammal species detected using metabarcoding of these extracts with extracts generated using an approach that is currently widely used, the cost‐ and labor‐intensive destructive extraction of small pools of entire flies (Nflies per pool = 7; Nflies per site = 105 flies). The non‐destructive extraction from large pools of entire flies detected a greater number of mammals (Nspecies detections total = 58; x¯species/site $$ {\\overline{x}}_{\\mathrm{species}/\\mathrm{site}} $$  = 7.3; range = 1–12) than the destructive extraction from large pools of fly legs (Nspecies detections total = 15; x¯species/site $$ {\\overline{x}}_{\\mathrm{species}/\\mathrm{site}} $$  = 1.9; range = 0–3), while detecting a similar number of mammals as the destructive extraction from small pools of entire flies (Nspecies detections total = 67; x¯species/site $$ {\\overline{x}}_{\\mathrm{species}/\\mathrm{site}} $$  = 8.4; range = 5–15). Our findings indicate that the non‐destructive extraction of large pools of entire fly bodies has the potential to streamline and reduce costs of fly iDNA extraction. We hope this will promote the use of fly iDNA in terrestrial biomonitoring efforts. Metabarcoding of invertebrate‐derived DNA (iDNA) is an excellent tool for assessing terrestrial mammal diversity, but the time and costs associated with sample processing constrain its wider adoption. Our study indicates that the non‐destructive extraction of large pools of entire fly bodies has the potential to streamline and reduce the costs of fly iDNA extraction.

The metabarcoding of vertebrate DNA found in invertebrate‐derived DNA (iDNA) has proven a powerful tool for monitoring biodiversity. To date, iDNA has primarily been used to detect the presence/absence of particular taxa using metabarcoding, though recent efforts demonstrated the potential utility of these data for estimating relative animal abundance. Here, we test whether iDNA can also be used to reconstruct complete mammalian mitogenomes and therefore bring the field closer to population‐level analyses. Specifically, we used mitogenomic hybridization capture coupled with high‐throughput sequencing to analyze individual (N = 7) or pooled (N = 5) fly‐derived DNA extracts, and individual (N = 7) or pooled (N = 1) leech‐derived DNA extracts, which were known a priori to contain primate DNA. All sources of iDNA showed their ability to generate large amounts of mammalian mitogenomic information and deeper sequencing of libraries is predicted to allow for even more complete recovery of primate mitogenomes from most samples (90%). Sixty percent of these iDNA extracts allowed for the recovery of (near) complete mammalian mitochondrial genomes (hereafter mitogenomes) that proved useable for phylogenomic analyses. These findings contribute to paving the way for iDNA‐based population mitogenomic studies of terrestrial mammals. The metabarcoding of vertebrate DNA found in invertebrates (iDNA) has proven a powerful tool for monitoring biodiversity. To date, iDNA has primarily been used to detect the presence/absence of particular taxa using metabarcoding. Here, we show that iDNA extracts often allow for the recovery of complete mammalian mitochondrial genomes, which paves the way for iDNA‐based population mitogenomic studies of terrestrial mammals.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Chimpanzees possess a large number of behavioral and cultural traits among nonhuman species. The “disturbance hypothesis” predicts that human impact depletes resources and disrupts social learning processes necessary for behavioral and cultural transmission. We used a dataset of 144 chimpanzee communities, with information on 31 behaviors, to show that chimpanzees inhabiting areas with high human impact have a mean probability of occurrence reduced by 88%, across all behaviors, compared to low-impact areas. This behavioral diversity loss was evident irrespective of the grouping or categorization of behaviors. Therefore, human impact may not only be associated with the loss of populations and genetic diversity, but also affects how animals behave. Our results support the view that “culturally significant units” should be integrated into wildlife conservation.

Large brains and behavioural innovation are positively correlated, species-specific traits, associated with the behavioural flexibility animals need for adapting to seasonal and unpredictable habitats. Similar ecological challenges would have been important drivers throughout human evolution. However, studies examining the influence of environmental variability on within-species behavioural diversity are lacking despite the critical assumption that population diversification precedes genetic divergence and speciation. Here, using a dataset of 144 wild chimpanzee ( Pan troglodytes ) communities, we show that chimpanzees exhibit greater behavioural diversity in environments with more variability — in both recent and historical timescales. Notably, distance from Pleistocene forest refugia is associated with the presence of a larger number of behavioural traits, including both tool and non-tool use behaviours. Since more than half of the behaviours investigated are also likely to be cultural, we suggest that environmental variability was a critical evolutionary force promoting the behavioural, as well as cultural diversification of great apes. Environmental variability is one potential driver of behavioural and cultural diversity in humans and other animals. Here, the authors show that chimpanzee behavioural diversity is higher in habitats that are more seasonal and historically unstable, and in savannah woodland relative to forested sites.