The Mountains of Southwest China is a global biodiversity hotspot. The Camera-trapping Network for the Mountains of Southwest China (SW China Network) has been established as one of the regional camera-trapping networks to measure biodiversity in China. This network was first initiated by Peking University in 2002, and now includes numerous partners from academic institutions, universities, conservation organizations, government agencies, and protected area administrations. The SW China Network spans across seven mountain ranges (i.e., Qinling, Minshan, Qionglai, Xiangling, Liangshan, Shaluli and Yunling Mountains) along the eastern edge of the Qinghai-Tibetan Plateau. Forty-one protected areas (e.g., nature reserves, community-managed protected areas, and timberlands, etc.) have joined the network, with each following a standardized survey protocol. Each protected area maintains its own camera-trapping database that is constructed using a common metadata structure. By December 2019, the SW China Network has generated approximately 3,025,900 camera-trapping images (excluding the empty images) at 5,738 survey stations, over 1,207,000 camera-days. An additional ~1,100,000 images are yet to be processed. We have recorded 63 wild mammal species (belonging to 7 orders and 21 families) and 182 wild bird species (belonging to 10 orders and 35 families), among which 18 are listed as Class-I, and 39 as Class-II National Key Protected Species. The network has four focal areas in the future: (1) construct an online data platform based on a common metadata structure, (2) provide training for reserve staff on camera data analysis to build local capacity for data management and analysis, (3) provide supports for regional biodiversity conservation and protected area management, and (4) conduct wildlife ecology research on the interspecific relationship, community assembly mechanisms, and ecological roles of large carnivores.

The Long-term Tiger-Leopard Observation Network (TLON) is a camera trap based program that was established in 2006 by Beijing Normal University. TLON covers an area of more than 15,000 km ² and is located in the temperate broadleaf and mixed forest in Northeast China. This area covers the Laoye Mountains, Zhangguangcai Mountains, and Wanda Mountains. The goals of TLON are to monitor the status of the Amur tiger (Panthera tigris altaica), Amur leopard (Panthera pardus orientalis), ungulate prey, and other sympatric mammal species. Additionally, a goal for TLON is to study animal’s response to different environmental factors and human activity. As of June 2019, TLON has more than 785,000 video recordings that include recordings for 28 wild mammal species and 32 wild birds species that span 1,736,000 days of camera trapping. TLON has helped advance several fields of scientific research which include: surveying of wildlife diversity, studying population status of animals, understanding the distribution and threats for tigers and leopards, interactions between sympatric carnivore species, and mammal habitat use. TLON has also helped with monitoring, evaluation, and the management of biodiversity in the Northeast Tiger and Leopard National Park.

The Camera-trapping Platform for Felid Species in China (Felid Monitoring Platform) was established in 2007 to evaluate the conservation status of the 12 native felid species in China and promote their conservation. The platform was initiated by the China Felid Conservation Alliance (CFCA), with collaborations from academic institutions, conservation organizations, government agencies, and protected area administrators. Monitoring using a grid-based or transect-based survey protocol has been conducted in 28 protected areas constituting nature reserves, scenic spots, civic protected areas, timberlands, unprotected areas, and other conservation areas spanning 10 provinces/autonomous regions. A camera trapping database is managed by CFCA and shared with protected area managers. By December 2019, the Felid Monitoring Platform has generated approximately 250,000 images with wildlife observations and 164,262 independent detections (not including additional data with ca. 50,000 unprocessed images) from 939 survey stations, with a sampling effort of 283,239 camera-days. To date, 91 wild mammal species (belonging to 7 orders and 24 families) and 102 wild bird species (belonging to 9 orders and 23 families) have been identified. Up to 25 species of those identified are listed as Class-I National Key Protected Species, and 55 species are listed as Class-II National Key Protected Species. Ten felid species were detected from 6,507 independent detections in 23 sites, including 3,196 (50.7%) detections of leopard (Panthera pardus) and 2,817 (44.7%) detections of leopard cat (Prionailurus bengalensis). In the future, the platform aims to improve CFCA staff capacity of camera data analysis, assess the conservation status for focal endangered felid species, and maintain volunteer working groups.

The Qinling Mountains, which are located in the midwestern part of China, are biogeographically important because they are home to China’s four national wildlife treasures, i.e., giant panda (Ailuropoda melanoleuca), golden takin (Budorcas bedfordi), golden monkey (Rhinopithecus roxellana) and crested ibis (Nipponia nippon). These species are also called the four flagship species in the Qinling forest ecosystem. Therefore, using infrared camera trapping to monitor the wildlife in the Qinling Mountains is very important since it can provide information of species and also scientific data on wildlife behaviour and activity pattern. The ecological research team from Tsinghua University conducted camera trappings between 2009 and 2020 in the Qinling Mountains for seven projects. These projects monitored wildlife diversity, primarily in four nature reserves, covering an area of 1,113 km ² (26.5 km × 42 km). There were a total of 267 camera-trapping sites. For the 152,160 camera working days, we were able to obtain totally 855,260 photos. From these photos we identified 27 mammal species and 63 bird species, and were able to address several research aspects including: wildlife behavior, identifying rare species, understanding habitat use and adaption, and understanding the human impacts on wildlife. Based on the gathered photos, we established the wildlife camera-trapping database of the middle Qinling Mountains, which has only been shared within the research group and collaborators. Based on our results from 10 years of monitoring, we propose the following suggestions for future research: (1) We need much longer time and we need to implement camera trapping in more habitat types to collect more digital images to be able to monitor the status of animal species rarely seen in front of cameras. For example, Mustela kathiah, Lutra lutra, and Catopuma temminckii were each captured only once in 10-year monitoring. (2) More deep data mining work is necessary in using this database to understand species-species relationships, species-habitat relationships, and population dynamics. (3) Continual research on the population dynamics of species with large populations (like Budorcas bedfordi and Sus scrofa) and carnivores species at the top of food chain (like Panthera pardus) is able to provide scientific support to the whole Qinling ecosystem. (4) Mining this photo database to monitor and research wildlife disease’s occurring as well as developing.

Infrared-triggered camera-trapping has been widely used for wildlife research. The development of this technology has helped facilitate contemporary biodiversity research and helped with conservation efforts in China. To promote the application of infrared-triggered camera-trapping in wildlife monitoring and research in China, the Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry added a wildlife camera-trapping database in Nature Reserves Biological Specimen Resources Sharing Sub-platform, that is publicly available at the website of http://www.papc.cn/. This paper briefly introduces the sub-platform by summarizing field areas being monitored, the monitoring program, how data is stored and analyzed, an introduction of achievements accomplished, and a summary of the next work plan. From 2010 to 2019, the sub-platform used infrared camera technology to investigate the diversity of mammals and birds in 13 different protected areas in China. This included 272,500 camera days 84,100 independent photographs, and the identification of 80 mammals species and 200 bird species. These recordings helped with animal behavior research, detection of rare species, understanding the effects of human disturbance and climate change, as well as with research in other fields. The next steps will be for the sub-platform to set up the sharing platform of camera-trapping database for nature protected areas, formulate unified and standardized plans for infrared camera survey design, monitor technology and data format, and work on gradually improving the infrared camera monitoring network for wildlife in China’s protected areas.

Located in Southwest China, the Longitudinal Range and Gorge Region is considered major biodiversity hotspots globally. This region is comprised of high mountains and deep valleys that run longitudinally, which creates both corridors for north-south ranging fauna as well as geographical isolators for latitudinal assemblages. This region is a stronghold for biodiversity conservation in China, supporting habitats for flagship species such as Bengal tiger (Panthera tigris titris), Yunnan snub-nosed monkey (Rhinopithecus bieti), Burmese snub-nosed monkey (R. strykeri), Gaoligong hoolock gibbon (Hoolock tianxing), western black crested gibbons (Nomascus concolor), and takin (Budorcas taxicolor). The camera-trapping monitoring platform for mammals and pheasants in the Longitudinal Range and Gorge Region of Southwest China was established in 2011. This program was initiated by the Kunming Institute of Zoology, Chinese Academy of Sciences. The monitoring areas include the Medog Region, the Gaoligong Mountains, Mangshi Phayre’s Langur Protected Area, Tongbiguan Provincial Nature Reserve, Biluo Snow Mountains, Baima Snow Mountains, Pudacuo National Park, Wuliang Mountains, Ailao Mountains, Huanglian Mountains National Nature Reserve, Mengyang Sub-region of Xishuangbanna National Nature Reserve, and Lancang County. The program has 35 sampling sites each with different protection designations including: national nature reserves, provincial nature reserves, national parks, and non-protected areas. By December 2019, the Program had generated approximately 269,900 independent records at 803 camera trap stations, with an extensive sampling effort of over 379,200 camera-days. We recorded 60 medium- and large-sized mammal species belonging to 7 orders and 20 families. Additionally, we recorded 15 pheasant species. Among these records 22 species are listed as Class-I, and 27 species as Class-II National Key Protected Species. Twenty-four species of the detected animals are categorized as globally threatened by IUCN, and 41 species are regionally threatened according to the Red list of China’s vertebrates. Moving forward, the Program plans to strengthen survey and monitoring efforts of threatened and flagship species. The Program plans to provide support for national park planning, regional biodiversity conservation, and exploration of anthropogenic impacts on communities of medium- and large-sized mammals and pheasants.

The Transboundary Animal Diversity Monitoring Platform of Southern Yunnan, China and Southeast Asia is jointly administered by the Animal Behaviour and Changing Environments Research Group of Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences and the Animal Diversity and Conservation Research Group of Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences. The platform was established in June 2012 with the aim of monitoring animal diversity in China’s Southern Yunnan and Southeast Asia. The monitoring objectives are to strengthen biodiversity inventory in Southern Yunnan and Southeast Asia, understand the distribution, population size, and protection status of key threatened animals, provide protection recommendations to policy makers, and develop conservation plans. To date, 22 monitoring sites containing 1,493 camera stations have been deployed. Until September 2019, we have obtained 718,995 photographs from 289 camera stations with 97,444 trapping days in nature reserves and sub-reserves in Southern Yunnan, i.e., Naban River (2012-2016), Mengla (2014-2019), Menglun (2015-2019), and Shangyong (2018-2019). In these photographs, we have identified 48 species of mammals and 80 species of birds. Species identification for Southeast Asia is still in progress. We have gained important achievements, reported the population ecology of wild boar (Sus scrofa) in Southwest China, found the spatiotemporal niche differentiation of northern pig-tailed macaque (Macaca leonina) and rhesus monkey (M. mulatta) in Naban River Watershed National Nature Reserve, revised the classification of muntjacs (Muntiacus), gorals (Naemorhedus) and the genus of Biswamoyopterus by using molecular biology techniques. In the future, we plan to cooperate with more protected areas in southern Yunnan, and extend our monitoring to other regions of Southeast Asia for more comprehensive biodiversity monitoring.

The Sanjiangyuan Community-based Camera-trapping Monitoring Platform relies on the help of local Tibetan herders with nature conservation efforts. This platform uses infrared-triggered camera trapping, which is important for research on Sanjiangyuan wildlife ecology, animal behavior, biodiversity monitoring, and evaluation of community management for conservation. The platform was established in October 2013 by Center for Nature and Society of Peking University and Shanshui Conservation Center. As of June 2019, the platform has 9 functional monitoring sites with 264 local rangers in Yushu Prefecture and Banma County in Guoluo Prefecture, covering an area of about 7,000 km ². We obtained 2,524,300 pictures resulting in 120,000 independent detections and documented 30 mammal and 37 bird species. This data has been used in surveying wildlife richness, accessing density and population dynamics of snow leopards (Panthera uncia), studying the inter-species relationship between snow leopards and co-occurring carnivores, and sharing management experience of community-based monitoring. The future directions for this platform will be to further summarize and publish the research results from the database, build a cloud-based database for better data sharing and public participation, establish an interactive management platform for national park administrators with the application of handhold terminals designed for national park rangers, and to identify species and snow leopard individuals via artificial intelligence.

The camera-trapping monitoring platform for the Qianjiangyuan National Park was established by the Qianjiangyuan National Park Administration in cooperation with the Institute of Botany, Chinese Academy of Sciences and Peking University. The monitoring platform covers the whole national park and several adjacent areas in the Jiangxi and Anhui provinces. The survey started May 2014 in Gutianshan, and July 2018 for the rest of the regions in the park. In November 2017 and March 2018 surveys began in the adjacent areas of the Jiangxi and Anhui provinces, respectively. As of May 2020, 718,515 pictures/videos of mammals and birds have been obtained resulting in 151,221 independent detections, with a survey effort of 331,834 camera-days from 1,033 stations in 343 1 km × 1 km grids. Among those detections, 658,644 pictures/videos were able to be identified to the species level, corresponding for 133,204 independent detections. The survey recorded 23 wild mammal species belonging to 7 orders and 15 families, and 75 wild bird species belonging to 9 orders and 27 families. We updated the baseline information for large- and medium-sized mammals in the park, and examined habitat selection and population dynamics for key species, which provided important information for park management. The monitoring platform will be expanded to cover more adjacent areas around the park to continually provide information to support park management and provide teaching materials for environmental education for the park.

The China mammal diversity observation network (China BON-Mammal) is a sub-network of the China Biodiversity Observation Network (China BON), organized by the Ministry of Ecology and Environment and led by the Nanjing Institute of Environmental Sciences. China BON-Mammal takes large and medium-sized terrestrial mammals as observation objects and sets a unified protocol and technical standards based on infrared camera trapping technology. From 2017 to 2019, 74 representative protected areas in 74 counties were selected as observation sample regions across 18 provinces of China to conduct infrared camera observations. By the end of 2019, more than 2 million photos were collected, 300,000 of which show wild animals. A total of 11 orders, 28 families, 132 species of mammals and 16 orders, 56 families, 408 species of birds were observed. Among these 45 species (33 mammal species and 12 bird species) were listed as Class-I National Key Protected Species. New records and rare species were also found. Here, we focus on the analysis of current achievements, existing problems, and next steps for the platform. In the future, China BON-Mammal will further improve data processing, analysis, and sharing to better promote biodiversity conservation.

Conserving biodiversity relies on the effective monitoring of species in a timely and credible way. Camera traps provide images and metadata for many mammal species and are now used widely enough that they can provide a viable method for biodiversity monitoring. Camera-trapping is rapidly deployable, allows standardization of protocols, and provides a voucher specimen (i.e. image) with relevant information about the species’ location, time and date of capture, and other capture details (camera model, etc.). This technique has resulted in millions of images being captured and stored for current and future examination of biodiversity. Camera-trapping has become particularly popular in China. Multiple institutions are running their own monitoring programs and collecting and storing wildlife images and associated metadata. There is an urgent need to standardize the metadata format in order to share data across institutions and with the larger conservation community. Global data sharing repositories, such as Wildlife Insights, exist but will need China’s data to effectively track global efforts for achieving sustainability. Three steps are needed for this to occur: common data standards, data sharing agreements and data embargo policies. We urge the Chinese conservation community to develop the policies and the mechanisms needed to share wildlife images within China and with the international community.

The Tuotuo River is a tributary to the Yangtze River, and ecologically important because it supports diverse habitat including many endemic species of the Qinghai-Tibet Plateau. The Tuotuo River basin is especially unique and includes many different and fragile habitats, but bird and mammal diversity remain unclear. From September 2017 to December 2018, 60 infrared cameras were placed evenly in a grid (60 1-km ² grids) across three sample plots, Bande Mountains, Daerzong Mountains and the mouth of Tongtian River. A total of 4,288 camera-days, and 2,353 independent photos were obtained. Based on these data, we identified a total of 38 species. We identified 16 species of mammals which could be divided into 5 orders, 10 families, 16 genera and 22 species of birds which could be divided into 8 orders, 15 families, 19 genera. Among 38 species, 26 are classified as falling under either first or second class animal protections in China or have important economic or research value. Four species that belong under Class-I National Key Protected Species include the snow leopard (Panthera uncia), white-lipped deer (Gervus albirostris), kiang (Equus kiang) and lammergeier (Gypaetus barbatus); 11 species are classified as Class-II National Key Protected Species and 11 species which are beneficial or have important economic value or research value. The saker falcon (Falco cherrug), a IUCN red list threatened and endangered species was detected, and two other vulnerable species and five species as near threatened were identified in images. The five most detected mammals in the Tuotuo River basin were blue sheep (Pseudois nayaur, RAI = 11.17), plateau pika (Ochotona curzoniae, RAI = 6.48), woolly hare (Lepus oiostolus, RAI = 4.99), Tibetan fox (Vulpes ferrilata, RAI = 3.36) and Tibetan gazelle (Procapra picticaudata, RAI = 2.87). The five most abundant avian species were red-billed chough (Pyrrhocorax pyrrhocorax, RAI = 3.08), black redstart (Phoenicurus ochruros, RAI = 1.26), rufous-necked snowfinch (Pyrgilauda ruficollis, RAI = 1.26), upland buzzard (Buteo hemilasius, RAI = 0.82) and white-rumped snowfinch (Pyrgilauda taczanowskii, RAI = 0.61). Meanwhile, livestock and human activities were also commonly recorded by infrared cameras (RAI = 8.72). The results provide an important basis for further investigating the biodiversity of the Tuotuo River basin of the Yangtze River and formulating conservation and management measures in the future.

In this study, we systematically determined the quantity, distribution, and population dynamics of wild bird and mammal species in the Gansu Anxi Extreme-arid Desert National Nature Reserve. We set 60 infrared cameras in three sample plots to monitor wild mammals and birds in the nature reserve. A total of 11,134 independent images were collected with a survey effort of 29,147 camera-days from August 2017 to September 2019. We identified 18 mammal species and 31 bird species, which include 5 and 11 species listed as Class I and Class II National Protected Wildlife in China, respectively. The analysis on the relative abundance of species showed that the five most abundant mammal species with highest RAIs (relative abundance index) in the reserve were Lepus tolai (RAI = 12.749), Pseudois nayaur (RAI = 4.690), Capra sibirica (RAI = 4.333), Equus hemionus (RAI = 3.163), Vulpes vulpes (RAI = 2.601). The bird species with highest RAIs were Alectoris chukar (RAI = 1.678), Columba rupestris (RAI = 1.142), Oenanthe deserti (RAI = 0.865), Phoenicurus ochruros (RAI = 0.374) and Oenanthe isabellina (RAI = 0.196). The results of the grid occupancy analysis for each species indicated that the most widely distributed mammals were Vulpes vulpes and Lepus tolai and the most widely distributed birds were Oenanthe deserti and Alectoris chukar. Compared to survey data collected over the last two decades, four newly recorded species (Cuon alpinus, Martes foina, Mustela sibirica, and Cervus albirostris) were found, and the observation of Panthera uncia was also the first in the reserve. Decreased human interference in the nature reserve is likely the main reason for the new species distributions and increase in the number of species within the reserve.

In this study, we monitored terrestrial birds and mammals based on the 60 camera trapping sites (each with 1 km × 1 km grid) from three monitoring plots in the Dinghushan National Nature Reserve and its surrounding forests (Lankeshan Provincial Nature Reserve and Xiaoxiang forest) in Guangdong Province. A total of 11,725 independent images were collected with up to 34,212 camera-days from January 2017 to December 2018. We recorded 75 species belonging to 13 orders, 32 families, and 63 genera. There were 12 mammal species and 63 bird species, among which Chinese pangolin (Manis pentadactyla) was listed as Class І National Key Protected and 9 species were listed as Class II National Key Protected Species in China. According to the relative abundance index (RAI), the top three mammal species with highest RAIs were Sus scrofa, Melogale moschata, and Muntiacus vaginalis. The top three avian species with highest RAI were Lophura nycthemera, Geokichla citrina, and Myophonus caeruleus. The top three mammal and bird species with highest RAI were mostly consistent among the monitoring plots. Silver pheasant had the highest RAI in Dinghushan. Prionailurus bengalensis was ranked third after Sus scrofa and Melogale moschata in Xiaoxiang forest. The top three avian species with the highest RAIs in Lankeshan were Garrulax canorus, Bambusicola thoracicus, and Leiothrix lutea. This study provides basic data for biodiversity monitoring and assessment in the Dinghushan National Nature Reserve and its surrounding forests.

In order to document the wildlife resources in the Guangdong Yunkaishan National Nature Reserve, 61 infrared cameras were used to monitor mammals and birds at 3 observation plots from January 2017 to September 2019. Based on the camera data, we found 9 mammal species belonging to 4 orders and 7 families, and 34 bird species belonging to 6 orders and 14 families. There were two species listed as Class II National Protected Wildlife in China: the red jungle fowl (Gallus gallus) and silver pheasant (Lophura nycthemera). Common green magpie (Cissa chinensis) was a new recorded species in Guangdong Province. The five most abundant mammal species with the highest relative abundance index (RAI) were Pallas’s squirrel (Callosciurus erythraeus), red muntjac (Muntiacus vaginalis), Chinese ferret-badger (Melogale moschata), wild boar (Sus scrofa) and palm civet (Paguma larvata), respectively. In addition, the three most abundant bird species with the highest RAI were blue whistling thrush (Myiophoneus caeruleus), scaly thrush (Zoothera dauma) and red billed leiothrix bird (Leiothrix lutea), respectively. The activity rhythm analysis of the three dominant mammals and three dominant bird species revealed that the Chinese ferret-badger was a diurnal animal, while the three birds (blue whistling thrush, scaly thrush and red billed leiothrix bird) and one mammal (Pallas’s squirrel) were nocturnal animals. The daily activity rhythm of the red muntjac showed two active peaks at 12:00-14:00 and 18:00-20:00. Our results provide important data on mammal and bird diversity in Guangdong Yunkaishan National Nature Reserve, which will be beneficial for wildlife protection and management in the reserve.