Artificial intelligence (AI) has become a significantly growing field in the environmental sector due to its ability to solve problems, make decisions, and recognize patterns. The significance of AI in wildlife acoustic monitoring is particularly important because of the vast amounts of data that are available in this field, which can be leveraged for computer vision and interpretation. Despite the increasing use of AI in wildlife ecology, its future in acoustic wildlife monitoring remains uncertain. To assess its potential and identify future needs, a scientific literature review was conducted on 54 works published between 2015 and March 2022. The results of the review showed a significant rise in the utilization of AI techniques in wildlife acoustic monitoring over this period, with birds (N = 26) gaining the most popularity, followed by mammals (N = 12). The most commonly used AI algorithm in this field was Convolutional Neural Network, which was found to be more accurate and beneficial than previous categorization methods in acoustic wildlife monitoring. This highlights the potential for AI to play a crucial role in advancing our understanding of wildlife populations and ecosystems. However, the results also show that there are still gaps in our understanding of the use of AI in wildlife acoustic monitoring. Further examination of previously used AI algorithms in bioacoustics research can help researchers better understand patterns and identify areas for improvement in autonomous wildlife monitoring. In conclusion, the use of AI in wildlife acoustic monitoring is a rapidly growing field with a lot of potential. While significant progress has been made in recent years, there is still much to be done to fully realize the potential of AI in this field. Further research is needed to better understand the limitations and opportunities of AI in wildlife acoustic monitoring, and to develop new algorithms that can improve the accuracy and usefulness of this technology.

Anthropogenic activities have driven many wildlife species towards extinction. Among these species, the geographic distributions of many are poorly documented, which can limit the effectiveness of conservation. The critically endangered Chinese pangolin (Manis pentadactyla) is experiencing population decline throughout its range due to land-use changes and illegal trade for food and traditional medicine. Using distribution records and maximum entropy modeling, we predicted the potential distribution of the Chinese pangolin across Nepal. Most suitable potential habitats of the Chinese pangolin occurred in forest areas of the mid-hill region in central and eastern Nepal, followed by cultivated land. Almost all potential suitable habitats of the Chinese pangolin occurred outside of protected areas, and most of them were encroached upon by cultivated land, human settlements, and infrastructure developments. The results from this study provide baseline information on the potential suitable habitats of the Chinese pangolin in Nepal, which helps to develop site- and species-specific management plans and to identify priority areas to minimize the current threats to the pangolin and enhance the stewardship of species conservation.

Wildlife attacks on livestock near human settlements are increasing due to the proximity of humans to protected areas. These attacks are often severe due to depredations of livestock adversely affecting the livelihoods of people. The nature of carnivore depredations on livestock can differ based on the carnivore species, animal husbandry practices, season, and deterrent technique. We surveyed people living near Bardia National Park (BNP), Nepal, to compare hoofed livestock depredations by leopards (Panthera pardus) and tigers (P. tigris) near (1 km) from this protected area. Overall, 1476 hoofed livestock were reportedly depredated by leopards, and 209 by tigers, during 2015–2019. The number of hoofed livestock killed by leopards each season was, at least, 86% higher than the number killed by tigers. More livestock were killed at BNP irrespective of carnivore deterrent techniques used. Due to severe effects created by livestock depredations near BNP, we recommend using more efficacious deterrent techniques when practical, in addition to improved livestock husbandry practices such as night penning.

Chinese pangolin populations are declining globally due to illegal wildlife trades in its range countries, especially China and Vietnam, where the largest markets for this species exist. Identifying the trade routes is crucial for developing conservation plans for the pangolin and understanding the attributes of the individuals involved in the illegal trade. We aimed to identify local trade routes and the socio-economic status of people involved in pangolin trades from the Gaurishankar Conservation Area [a Protected Area (PA)] and the Ramechhap district [a non-Protected Area (non-PA)] of Nepal. We found that pangolin traders were typically poor, illiterate, unemployed, male, and of working age (17–40 years old). Confiscation rates of pangolin parts were higher in non-PAs than Pas as the illegal trade routes seemed to differ between the PAs and non-PAs. From 2014 to 2018, the prices of pangolin scales in PAs and non-PAs increased by 50% and 67%, respectively. Our results highlight locals facilitating the trade of pangolins, therefore we recommend the need for other income generating sources such as ecotourism or providing incentives to promote local industries as well as to establish Community Based Anti-Poaching Units among range countries and trade route countries to control the trade of this globally threatened species.