Benjamin Debetencourt

We present Zamba, an open source Python package designed to streamline camera trap data processing through machine learning. Zamba supports inference and custom model training for species classification on videos and images, as well as depth estimation inference for videos.

Precise estimates of population dynamics and social grouping patterns are required for effective conservation of wild animal populations. It is difficult to obtain such information on non‐human great apes as they have slow reproductive rates. To gain a better understanding of demography in these populations, previous research has typically involved habituation\, a process that requires years. Here, we collected data continuously over year‐long periods to monitor an unhabituated population of critically endangered Western chimpanzees (Pan troglodytes verus) in the Moyen Bafing National Park, Guinea. We used two arrays of 100 camera traps that were placed opportunistically in two distinct 100 km² sites, named Bakoun and Koukoutamba. We identified 227 individuals in Bakoun and 207 in Koukoutamba through their unique facial features. Our camera trap data make clear that these individuals belong to six and seven closed groups, respectively. Six of those groups were near‐completely sampled with an average minimum size of 46.8 individuals (range: 37–58), and a mean adult sex ratio of 1.32 (range: 0.93–2.10). We described the demographic composition of these groups and use Bayesian social network analysis to understand population structure. The network analyses suggested that the social bonds within the two populations were structured by sex homophily, with male chimpanzees being more or equally likely to be observed together than other adult associations. Through estimation of minimum convex polygons, we described the minimum home range for those groups. Compared to other chimpanzee groups living in a similar environment (mosaic savanna‐forest), the Moyen Bafing region seems to host a high‐density of chimpanzees with small home ranges for their group size. Our research highlights the potential of camera traps for studying the demographic composition of chimpanzee populations with high resolution and obtaining crucial information on several groups in a time‐efficient and cost‐effective way.