The orangutan is the world's largest arboreal mammal and images of the red ape moving through the tropical forest canopy symbolise its typical arboreal behaviour. Records of terrestrial behaviour are scarce and often associated with habitat disturbance. We conducted a large-scale species-level analysis of ground-based camera-trapping data to evaluate the extent to which Bornean orangutans Pongo pygmaeus come down from the trees to travel terrestrially and whether they are indeed forced to the ground primarily by anthropogenic forest disturbances. Although the degree of forest disturbance and canopy gap size influenced terrestriality, orangutans were recorded on the ground as frequently in heavily degraded habitats as in primary forests. Furthermore, all age-sex classes were recorded on the ground (flanged males more often). This suggests that terrestrial locomotion is part of the Bornean orangutan's natural behavioural repertoire to a much greater extent than previously thought and is only modified by habitat disturbance. The capacity of orangutans to come down from the trees may increase their ability to cope with at least smaller-scale forest fragmentation and to cross moderately open spaces in mosaic landscapes, although the extent of this versatility remains to be investigated.

Land-use changes can impact infectious disease transmission by increasing spatial overlap between people and wildlife disease reservoirs. In Malaysian Borneo, increases in human infections by the zoonotic malaria Plasmodium knowlesi are hypothesised to be due to increasing contact between people and macaques due to deforestation. To explore how macaque responses to environmental change impact disease risks, we analysed movement of a GPS-collared long-tailed macaque in a knowlesi-endemic area in Sabah, Malaysia, during a deforestation event. Land-cover maps were derived from satellite-based and aerial remote sensing data and models of macaque occurrence were developed to evaluate how macaque habitat use was influenced by land-use change. During deforestation, changes were observed in macaque troop home range size, movement speeds and use of different habitat types. Results of models were consistent with the hypothesis that macaque ranging behaviour is disturbed by deforestation events but begins to equilibrate after seeking and occupying a new habitat, potentially impacting human disease risks. Further research is required to explore how these changes in macaque movement affect knowlesi epidemiology on a wider spatial scale.

The development of GPS tags for tracking wildlife has revolutionised the study of home ranges, habitat use and behaviour. Concomitantly, there have been rapid developments in methods for estimating habitat use from GPS data. In combination, these changes can cause challenges in choosing the best methods for estimating home ranges. In primatology, this issue has received little attention, as there have been few GPS collar-based studies to date. However, as advancing technology is making collaring studies more feasible, there is a need for the analysis to advance alongside the technology. Here, using a high quality GPS collaring data set from 10 proboscis monkeys (Nasalis larvatus), we aimed to: 1) compare home range estimates from the most commonly used method in primatology, the grid-cell method, with three recent methods designed for large and/or temporally correlated GPS data sets; 2) evaluate how well these methods identify known physical barriers (e.g. rivers); and 3) test the robustness of the different methods to data containing either less frequent or random losses of GPS fixes. Biased random bridges had the best overall performance, combining a high level of agreement between the raw data and estimated utilisation distribution with a relatively low sensitivity to reduced fixed frequency or loss of data. It estimated the home range of proboscis monkeys to be 24–165 ha (mean 80.89 ha). The grid-cell method and approaches based on local convex hulls had some advantages including simplicity and excellent barrier identification, respectively, but lower overall performance. With the most suitable model, or combination of models, it is possible to understand more fully the patterns, causes, and potential consequences that disturbances could have on an animal, and accordingly be used to assist in the management and restoration of degraded landscapes.

Rapid reaction times to undesirable events are becoming increasingly important for the protection and conservation of habitats and species. This study demonstrates how Unmanned Aerial Vehicles, or drones, and satellite tracking of individual animals can be combined to identify important conservation issues (e.g. deforestation). When quickly disseminated, the information can lead to a rapid change in conservation policy. An adult male proboscis monkey, belonging to a one‐male social group, wasGPStracked for 6 months in Sabah, Malaysian Borneo during 2012. Riparian habitats featured heavily (25.4% of total time, 88.6% of all sleeping sites) in the group's home range. A fixed‐wing drone was used in 2015 to map the habitat in high‐resolution. These data revealed that 47.54 ha of forest had been cleared shortly before the drone flights.GPStagging data revealed the importance of this area for a one‐male proboscis monkey group. A total of 30.1% of the proboscis monkeys' home range area had been cleared, as well as 11.4% of sleeping sites. Furthermore, drone images revealed that the felling extended to the river's edge, disregarding water resources laws requiring riparian reserves of a minimum of 20 m. Following this discovery, a press release including drone imagery combined withGPSdata, was published linking habitat destruction to a species that is economically important for the tourism industry in Sabah. The day following dissemination of the data, the Sabah State Government ordered an immediate cessation on further land clearing at sensitive riparian reserves along the river. We propose that this combination of satellite and aerial data provides potential for an effective conservation tool for endangered, iconic and economically important species. This visually compelling data, feasible over large spatial scales, can directly inform policy change in a quick and timely manner.