Abstract:As with other species of great apes, chimpanzee numbers have declined over the past decades. Proper conservation of the remaining chimpanzees requires accurate and frequent data on their distribution and density. In Tanzania, 75% of the chimpanzees live at low densities on land outside national parks and little is known about their distribution, density, behavior or ecology. Given the sheer scale of chimpanzee distribution across western Tanzania (>20,000 km 2 ), we need new methods that are time and cost efficient while providing precise and accurate data across broad spatial scales. Scientists have recently demonstrated the usefulness of drones for detecting wildlife, including apes. Whilst direct observation of chimpanzees is unlikely given their elusiveness, we investigated the potential of drones to detect chimpanzee nests in the Issa valley, western Tanzania. Between 2015 and 2016, we tested and compared the capabilities of two fixed-wing drones. We surveyed twenty-two plots (50 × 500 m) in gallery forests and miombo woodlands to compare nest observations from the ground with those from the air. We performed mixed-effects logistic regression models to evaluate the impact of image resolution, seasonality, vegetation type, nest height and color on nest detectability. An average of 10% of the nests spotted from the ground were detected from the air. From the factors tested, only image resolution significantly influenced nest detectability in drone-acquired images. We discuss the potential, but also the limitations, of this technology for determining chimpanzee distribution and density and to provide guidance for future investigations on the use of drones for ape population surveys. Combining traditional and novel technological methods of surveying allows more accurate collection of data on animal distribution and habitat connectivity that has important implications for ape conservation in an increasingly anthropogenically-disturbed landscape.

Monitoring of animal populations is essential for conservation management. Various techniques are available to assess spatiotemporal patterns of species distribution and abundance. Nest surveys are often used for monitoring great apes. Quickly developing technologies, including unmanned aerial vehicles (UAVs) can be used to complement these ground-based surveys, especially for covering large areas rapidly. Aerial surveys have been used successfully to detect the nests of orang-utans. It is unknown if such an approach is practical for African apes, which usually build their nests at lower heights, where they might be obscured by forest canopy. In this 2-month study, UAV-derived aerial imagery was used for two distinct purposes: testing the detectability of chimpanzee nests and identifying fruiting trees used by chimpanzees in Loango National Park (Gabon). Chimpanzee nest data were collected through two approaches: we located nests on the ground and then tried to detect them in UAV photos and vice versa. Ground surveys were conducted using line transects, reconnaissance trails, and opportunistic sampling during which we detected 116 individual nests in 28 nest groups. In complementary UAV images we detected 48% of the individual nests (68% of nest groups) in open coastal forests and 8% of individual nests (33% of nest groups) in closed canopy inland forests. The key factor for nest detectability in UAV imagery was canopy openness. Data on fruiting trees were collected from five line transects. In 122 UAV images 14 species of trees (N = 433) were identified, alongside 37 tree species (N = 205) in complementary ground surveys. Relative abundance of common tree species correlated between ground and UAV surveys. We conclude that UAVs have great potential as a rapid assessment tool for detecting chimpanzee presence in forest with open canopy and assessing fruit tree availability. UAVs may have limited applicability for nest detection in closed canopy forest.