Camera-trapping dataset of avian and mammalian diversity in Ma'anshan Nature Reserve and surrounding areas, Ganluo County, Sichuan Province (2021–2024)

Dataset Description  The dataset on avian and mammalian diversity in Ma'anshan Nature Reserve and surrounding areas of Ganluo County, Sichuan Province (2021–2024) was compiled by researchers including Han Li, Wei Dong, and others, with Xuelin Zhang as the corresponding author. This dataset is based on a systematic four-year infrared camera monitoring effort, covering an area of 282.06 km² within and around the reserve, with geographical coordinates ranging from 28°31′–29°01′N to 102°30′–102°54′E and an elevation span of 1,530–3,040 meters. The research team deployed 59 monitoring sites, accumulating a total of 17,586 camera working days and capturing 38,482 valid wildlife images, including 12,325 mammal records and 5,427 bird records.  Through careful sorting and identification of the imagery, the researchers documented 75 species of birds and mammals, belonging to 9 orders and 35 families. Among them, 24 species were mammals (4 orders, 14 families), and 51 were birds (5 orders, 21 families), including 5 species under China’s Class I national protection and 22 under Class II. The study recorded 5,911 independent detections for mammals and 1,578 for birds. Notably, the survey added two new mammal species—the red fox (Vulpes vulpes) and Père David's rock squirrel (Sciurotamias davidianus)—to the reserve’s records. However, detections of giant pandas (Ailuropoda melanoleuca) were significantly lower than in historical surveys, with only one valid observation recorded within the reserve.  The dataset provides detailed species inventories, spatiotemporal distribution data, and a compressed archive of representative species photos. The researchers employed standardized data processing methods, including the removal of blank shots, species identification, and independent detection counting, ensuring high data reliability. These findings serve as a critical foundation for future species distribution modeling, niche analysis, and conservation effectiveness assessments. The study also highlights the limitations of infrared camera technology in monitoring small mammals and arboreal species, recommending the integration of environmental DNA (eDNA) and other multi-source data approaches to enhance future monitoring efforts.