The Qinghai Lake area is the known highest place with Asian badger (Meles leucurus) distribution in the world. In order to test the hypothesis that human interference caused the nocturnal activity rhythm of badgers, we used infrared cameras in complementary of telemetry of radio collared two badgers to record activity rhythm of badgers at the entrances of their setts in the eastern shore of Qinghai Lake. We also estimated the population density and recorded the behaviors expressed by the badgers with infrared cameras and other conventional field investigations. The results showed: (1) through infrared camera records and sett density estimation, the average badger densities in this area were 1.2 ± 0.6 badgers/km² and being influenced by food abundance. (2) the most common behavior expressed by badgers at sett entrances was vigilance behavior when badger emerged from the setts, followed by the play behavior when badgers returned to setts. (3) badgers mainly emerged from the setts between 20:00-23:00 and returned to the sett between 4:00-7:00 in the following morning. Their activity peak focused between 23:00-4:00. Human activity had no influence on the nocturnal activity rhythm of badgers.

North Chinese leopard (Panthera pardus japonesis) is an endemic subspecies of the leopard in China. The basic ecological data of the leopard, such as the distribution, population and it’s dynamic, behavior, prey, is least known for lacking of a long-term study. The present paper reported a 7-year monitoring and survey on North Chinese leopard and it’s prey in Qingcheng Forest Farm of Jinzhong prefecture, Shanxi using camera traps. The monitoring recorded 14 individuals of leopard, with 11 adults (3 females and 8 males) and 3 cubs between May of 2007 and April of 2014. A residential female leopard bred 3 cubs in 2008 and 2009. The main prey of ungulates is wild boar (Sus scrofa) and roe deer (Capreolus pygargus). The relative abundance index (RAI) of wild boar and roe deer were 4.16 and 1.35 individuals/km², and absolute density were 3.48 and 3.61 individuals/km² , respectively.

Camera trapping has been used worldwide for wildlife monitoring, and a large number of pictures and video clips have been obtained. A new challenge for camera trapping practitioners is how to effectively store and manage the increasing number of pictures and video clips, and how to quickly generate and present metadata to other researchers, wildlife management organizations and to the public. As an open, interactive-web platform developed by Institute of Zoology, Chinese Academy of Sciences, CameraData (http://cameradata.ioz.ac.cn) is an online database for storing, analyzing and sharing wildlife photographic data from camera traps. CameraData aims to facilitate quick analysis and multiple uses of camera trap data, and also to provide professional services for wildlife conservation and management. The establishment of CameraData will benefit data sharing, collaboration and information services for wildlife monitoring in China and other parts of the world. This paper briefly introduces the key tools, main functions and tips for CameraData.

During the last two decades, infrared-triggered camera-trapping has been widely used in wildlife and biodiversity research and conservation. In the areas of wildlife ecology research, animal species inventory, biodiversity monitoring and protected area management in China, considerable outputs have been produced by scientific research and conservation applications based on camera-trapping. This technique has been successfully used to detect rare or elusive species, conduct biodiversity inventory, study animal behavior, estimate population parameters, and evaluate the effectiveness of protected area management. Along with the rapid development of modern ecological analysis and modeling tools, camera-trapping will play a more important role in wildlife research at various levels. Meanwhile, along with improvements in techniques, decreasing cost and increasing application interests, camera-trapping will be adopted by more researchers, wildlife managers and protected areas, and can be used for systematic wildlife monitoring using standard protocols. Efforts devoted to its future development and applications should focus on establishing systematically-designed monitoring networks and data-sharing protocols, and developing new analytical approaches and statistical models specifically based on camera-trapping data.

Khulan (Equus hemionus) are a first class, nationally protected animal in China. From April to November 2013, 28 infrared cameras were set up at 13 watering holes to study the activity rhythms of this species in the Mount Kalamaili Ungulate Nature Reserve, Xinjiang, China. The results showed that activity frequency was greatest in autumn (2,679 identification photos), then summer (1,990), and lowest in spring (294). Average aggregation of E. hemionus to watering holes was greater in daylight hours than at nights. Daily activity at watering holes peaked between 0:00-1:00, declined rapidly between 7:00-9:00, was lowest between 12:00-13:00 and 16:00-17:00 and rose rapidly between 21:00-22:00. Studying the activity of Equus hemionus around watering holes will provide a basis for effective protection and management of desert ungulates in northern Xinjiang. Additionally, it provides a baseline for the sympatric reintroduction of Equus przewalskii.

There are great knowledge gaps concerning the population dynamics and behavioral ecology of wild camels. This study focused on grouping behaviors of camels (Camelus ferus) through the use of continuous camera trapping at 11 water source sites and eight field surveys conducted in the Kumtag Desert to evaluate seasonal variation in grouping behavior. We recorded 430 individual wild camels in a total of 64 groups. The largest group contained 71 individuals, the smallest group 1. The average group size was 10.74 during the breeding season, and 2.94 during the non-breeding season. Our data on seasonal grouping of camels, including average and maximum group size, supported the idea that wild camels live in open fission fusion groups, which tend to concentrate during the winter rutting season. At these 11 water source sites, 281 groups were recorded over the course of one year. Though no difference in average group size was detected between seasons in the camera trap data, both camera trap and field survey data supported the hypothesis that maximum group size was larger in the breeding season than in the non-breeding season. Group size was larger on the northern slope of the Altun Mountains than at Xihu wetland. Topography of the water source sites, the camera angle view, and the monitoring duration of cameras could all lead to an underestimate of wild camel group size. Even considering the limitations of our study, camera traps provide a new method and insights compared with traditional field surveys, and they are more economical and practical as well.

Wildlife monitoring is one key indicator used for biodiversity assessment. Therefore, developing wildlife monitoring protocols is an important component of large-scale biodiversity monitoring program such as the Chinese Forest Biodiversity Monitoring Network (CForBio). Since 2011, the CForBio Network launched an initiative to investigate wildlife diversity using camera traps among forest dynamic plots in China. Because of this initiative, there is an urgent need to develop standardized camera trapping protocols. One important premise of camera-trapping protocols is that camera trap data can be used to conduct comparative research among different plots. Here, we propose camera-trapping protocols based on our own experience in using camera traps for wildlife surveys, and on the terrestrial vertebrate (camera trap) protocol implementation manual produced by the TEAM (Tropical Ecology Assessment & Monitoring) Network. We hope that these protocols can serve as the basis for a standardized tool used in wildlife diversity monitoring in forest ecosystems. We also provide recommendations for plot design, data management and long-term monitoring programs for wildlife diversity monitoring.

Abstract:

The Hunchun National Nature Reserve (HNNR) serves as core habitat for both Amur tiger (Panthera tigris altaica) and Amur leopard (Panthera pardus orientalis) in Northeast China. To investigate the relative abundance of wildlife and human disturbance within the reserve, we analyzed images from a monitoring network of 83 camera traps deployed between April and June of 2013 in HNNR. Among the 6,060 total trap nights, 18 species of mammals were detected from the images, including four Mustelids, three Felids, two species each from Canidae, Cervidae and Sciuridae, and one species each from Suidae, Ursidae, Moschidae, Erinaceidae and Leporidae, respectively. Cameras photographed 11 tigers and 13 leopards. Relative abundance index (RAI) of tigers (0.84) was higher than that of leopards (0.48). RAIs of ungulates, from high to low, were sika deer (Cervus nippon) (2.18), Siberian roe deer (Capreolus pygargus) (1.53) and wild boar (Sus scrofa) (0.92). RAI of human activities (40.64) and livestock grazing (2.76) were both significantly higher than animal species. The data also indicated that tigers and sika deer were mainly restricted to the core zone of HNNR and that their abundance was lower in the community-based natural resource management zone. In comparison, RAIs of Amur leopard were fairly similar among the three functional zones, Siberian roe deer tended to be more abundant in the northern section of HNNR but differences were not significant, and wild boar RAI was lower in the core zone. Frequent disturbance from human activities and livestock grazing throughout the core zone may be the most negative impact on wildlife in HNNR.

The development of camera traps has improved our ability to study Amur tigers (Panthera tigris altaica), Amur leopards (Panthera pardus orientalis) and their prey populations. This research introduces camera trap monitoring methods of Amur tigers, Amur leopards and their prey populations in Chunhua and Madida areas of the Hunchun Nature Reserve, Changbai Mountains, China. A selection of monitoring positions, methods of erecting, parameter settings, and data filtering techniques are presented. Additionally, unique identifiers of Amur tigers and Amur leopards based on body patterns, calculations of relative abundance indexes (RAI), and the establishment of RAI models between the predators and prey are presented. We discuss the applicability of unique identifiers with ipsilateral patterns, the differences between camera trap monitoring and traditional survey methods, and the error of camera trap monitoring. We conclude that predicting densities of Amur tigers and Amur leopards with camera traps and automatic-individual-identifiers still needs improvement. Camera trap densities of one pair per 25 km² can meet the needs for Amur tigers and leopards within Chunhua and Madida of the Hunchun Nature Reserve, but a separate monitoring project is needed for ungulates prey.

Infrared-triggered camera (camera trap) is a “non-invasive” method for detecting or recording wild animals, and is a useful tool for studying animal diversity, population ecology and animal behavior. The development of infrared camera traps facilitates contemporary biodiversity research and conservation efforts in China. In addition to researchers, most Chinese nature reserves are using camera traps to monitor animals. Based on publications from the past two decades, we summarized common issues related to research content, experimental design, and trends in infrared camera usage. We also discuss the drawbacks and limitations of infrared cameras in terms of disturbance to animals, image identification, and scope of application and security of the cameras in the field. Finally, we provide direction for the future establishment of monitoring protocols, data integration and sharing, and improving monitoring efficiency in using camera traps.

Between August 2009 and April 2013, in the Guanyingshan Nature Reserve, Shaanxi Province, we collected photo data on six ungulates (Budorcas taxicolor, Naemorhedus griseus, Elaphodus cephalophus, Capricornis milneedwardsii, Muntiacus reevesi and Moschus berezovskii) with 18 infrared cameras. Using the relative abundance index (RAI), we analyzed activity patterns and seasonal differences of these six species. The results show that: (1) their total RAI in the study area reaches 58.71%, the RAI of B. taxicolor was 28.02%, and it was 13.24% for N. griseus, 10.08% for E. cephalophus, 4.21% for C. milneedwardsii, 2.26% for M. reevesi, and 0.90% for M. berezovskii. (2) Monthly RAIs (MRAI) of six ungulates reflected seasonal activity patterns; B. taxicolor, N. griseus, E. cephalophus, C. milneedwardsii, M. reevesi exhibited similar activity patterns. These species were most active in summer, became inactive in autumn and winter, and then gradually increased activity in spring. M. berezovskii, on the other hand, was most active in winter and least active in summer. (3) The time-period relative abundance indices (TRAI) of the six ungulates reflect their daily activity patterns. B. taxicolor and N. griseus have similar daily activity patterns with an active peak at 06:00-20:00.The daily activity pattern of E. cephalophus, M. reevesi and M. berezovskii showed obvious crepuscular habits. C. milneedwardsii also has two peaks but at 02:00-06:00 and 20:00-22:00 implying nocturnal activities. (4) Comparative analyses of daily activity patterns among the four seasons showed that B. taxicolor displayed a different pattern in spring with an activity peak at 16:00-20:00. Compared with other seasons, N. gresius, E. cephalophus and C. milneedwardsii have different patterns in winter with either a delayed or advanced activity peak. In the case of M. reevesi, spring daily activity patterns showed two peaks at 00:00-10:00 and 18:00-20:00. Due to a paucity of captures, M. berezovskii showed different activity patterns in all four seasons. (5) Analysis of the nocturnality showed that C. milneedwardsii was obviously nocturnal with a nighttime relative abundance index (NRAI) of 65.81%. Our results help us to understand the activity patterns of these ungulates in Qinling, to monitor their population dynamics, and provide a theoretical basis and data support for the nature reserves to protect the ungulate animals more efficiently.

Sixty camera traps were set on 32 islands and one terrestrial plot in the Thousand Island Lake region from May 1, 2011 to March 31, 2014. In total, we recorded 23,639 photos that included nine species of large ground-dwelling mammals with a rate of independent photographs of 2.62%. The species-area relationship showed that species richness increased with island area (ha) with a slope, z value, of 0.27. On large islands (> 10 ha), the minimum trapping effort increased with island area. On small islands (< 10 ha), however, there was no clear pattern. The minimum trapping effort was not correlated with island isolation (d.f. = 20, F = 3.067, P = 0.095). Our results suggested that large ground-dwelling mammal populations have disappeared on smaller islands since the lake was formed. Based on these findings, we suggest that large MTE’s are required in islands with large areas when using camera traps in a fragmented landscape. On small islands, researchers should vary trapping efforts according to the island’s attributes, including species resources.