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Conservation of rare ungulates requires reliable population size estimates and distribution maps for prioritizing investments and assessing the effectiveness of conservation measures. We used both camera trapping and a random encounter model approach, and faecal pellet group counts, to update the range and population size of the Bawean deer Axis kuhlii in the Bawean Island Nature Reserve and Wildlife Sanctuary, Indonesia. We studied 2-month periods to fulfil the assumption of population closure. Both methods provided similar population density estimates (higher in the dry season) of c. 227–416 individuals. The estimated range of the species is significantly narrower than previously reported. The main threats (habitat loss as a result of illegal logging, and disturbance by dogs and hunters) are ongoing. Based on these results we suggest that the species should retain its Critically Endangered status on the IUCN Red List.

BioOne Complete (complete.BioOne.org) is a full-text database of 200 subscribed and open-access titles in the biological, ecological, and environmental sciences published by nonprofit societies, associations, museums, institutions, and presses.

Biodiversity monitoring is crucial in tackling defaunation in the Anthropocene, particularly in tropical ecosystems. However, field surveys are often limited by habitat complexity, logistical constraints, financing and detectability. Hence, leveraging drones technology for species monitoring is required to overcome the caveats of conventional surveys. We investigated prospective methods for wildlife monitoring using drones in four ecosystems. We surveyed waterbird populations in Pulau Rambut, a community of ungulates in Baluran and endemic non-human primates in Gunung Halimun-Salak, Indonesia in 2021 using a DJI Matrice 300 RTK and DJI Mavic 2 Enterprise Dual with additional thermal sensors. We then, consecutively, implemented two survey methods at three sites to compare the efficacy of drones against traditional ground survey methods for each species. The results show that drone surveys provide advantages over ground surveys, including precise size estimation, less disturbance and broader area coverage. Moreover, heat signatures helped to detect species which were not easily spotted in the radiometric imagery, while the detailed radiometric imagery allowed for species identification. Our research also demonstrates that machine learning approaches show a relatively high performance in species detection. Our approaches prove promising for wildlife surveys using drones in different ecosystems in tropical forests.

The visual camouflage of many species living in the dense cover of the tropical rainforest become obstacles to conducting species monitoring. Unmanned aerial vehicles (drones) combined with thermal infrared imaging (TIR) can rapidly scan large areas from above and detect wildlife that has a body temperature that contrasts with its surrounding environment. This research tested the feasibility of DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to detect terrestrial and arboreal mammals in the five tree density classes in the remaining natural environment on the IPB University campus. This study demonstrated that large-size terrestrial mammal thermal signatures are visible in sparse vegetation at daytime and in the area under the canopy at night monitoring. In contrast, arboreal mammals were better detected in at early morning and night. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. The drones allow safe operation at low altitudes with low levels of disturbance to animals. Both terrestrial and arboreal mammals are well detected and easily identified when the drone is flying at an altitude < 50 m HAGL. Our preliminary results indicated that thermal surveys from drones are a promising method.

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Abstract. Rahman DE, Rinaldi D, Kuswanda W, Siregar R, Noor CF, Hakim F, Arief H, Putro HR. 2019. Determining the landscape priority and their threats for the Critically Endangered Pongo tapanuliensis population in Indonesia. Biodiversitas 20: 3584-3592. Understanding the habitat preference and spatial distribution for the management of medium-large primates is important for conserving and enhancing biodiversity in the most isolated and remote Batang Toru landscape, North Sumatra, Indonesia. Based on the first extensive orangutan survey dataset during 2000 and 2007, we aimed to provide microhabitat preference and distribution assessment for the new species of orangutan (Pongo tapanuliensis), a poorly known and threatened primate endemic in Indonesia. To inform future conservation measures, we develop a predictive habitat suitability map and use this map to show the current threat for Tapanuli orangutan in their habitat and as the basis of proposed of the landscape boundary in Batang Toru ecosystem. In order to identify some environmental factors affecting conservation, we analyzed the microhabitat preference of Tapanuli orangutan using maximum entropy modeling (MaxEnt). The modeled orangutan distribution map covers 1.458,06 km2 (58,52% of Batang Toru’s landscape) and reveals three distinct distribution areas. The four most important environmental predictors are the distance from the cultivation area, NDVI, mean precipitation, and distance from the secondary forest edge. The distribution of the orangutan overlap with land-use categories reveals that 42,98% of the distribution lies in protected areas, but that 15,54% lies in natural forest concessions and area for other purposes (APL). Large scale land-use masterplan is needed to provide strategies and control for future development in the possibility of land uses and management are allowed in the landscape including its conservation policies. Moreover, collaborative management strategies are needed to develop a sustainable management system. We confirmed the Batang Toru landscape as the sole of Indonesia’s biodiversity hotspots and a critical area to preserve the Tapanuli orangutan.