Spatial distribution drivers of Amur leopard density in northeast China
Introduction
The Amur leopard (Panthera pardus orientalis) is an elusive subspecies of leopard, which currently occurs in northeast China and the Russian Far East. It is the most rare felid subspecies in the world and has been listed as critically endangered on the IUCN red list since 1996 (Jackson and Nowell, 2008). The Amur leopard is also a first class protected subspecies in China (Wang, 1998). There were an estimated 50 individuals in Russia according to the winter tracking survey of 2013 (http://www.tx2.org.cn/picvideo/ShowArticle.asp?ArticleID=831) and 41 individuals estimated in Russia by camera trap surveys from 2003 to 2011 (Aramilev et al., 2012). Yang et al. (1998) estimated less than 10 Amur leopards in China; however, this estimate for the size of the Amur leopard population is derived from a snow track survey, conducted in China primarily for Amur tigers (Panthera tigris altaica). During recent years, while searching for snow tracks of Amur leopards, a large part of the Amur leopard range in China was also surveyed. There were 8–11 Amur leopards found during one survey on the southern slopes of Laoye Mountain in Jilin, China, taken during the winter 2011 to spring 2012 (Wu et al., 2013). An additional 5–7 leopards have been identified on the southern slopes of Laoyeling Mountain in Heilongjiang, China, during a winter survey in 2013 (http://www.tx2.org.cn/News/ShowArticle.asp?ArticleID=894). However, the snow track method may not estimate the number of individual leopards accurately.
All wildlife requires food and space for life activities (Morris, 2003). Habitat loss is a leading cause of population decline and extinction of endangered or threatened species (Halley and Iwasa, 2011). Food shortage is also a limiting factor of top predator populations, particularly large carnivores (Ullas Karanth and Chellam, 2009). Therefore, abundance, and the spatial distribution of prey population, may influence habitat selection and spatial distribution of predators (Aryal et al., 2014). Animals select habitat under the concomitant influences of habitat quality, resource availability, interspecific competition and interspecific interaction (Fretwell and Calver, 1969, Rosenzweig, 1981, Morris, 1988). Abundance and the associated spatial distribution of prey or food resources also play a crucial role in determining when and where predators forage (Santora et al., 2011, Karanth et al., 2004). Consequently, carnivore density or abundance may be correlated with preferred prey densities and may, in turn, affect the relative abundance of prey (Trites, 2002, Karanth et al., 2004, Hayward et al., 2007). Studies concerning the effects of prey abundance and spatial distribution on the use of space by carnivores provide insights into more effective ways to ensure the conservation of large carnivores (Karanth et al., 2004). Leopards usually live in remote areas, which are difficult to access, but they also occasionally visit the outskirts of urban areas adjacent to their ranges (Khorozyan and Abramov, 2007). Amur leopards prefer Korean pine forests at low elevations, well away from main roads, and avoid deciduous forests, meadows, shrubs and agricultural fields (Hebblewhite et al., 2011). Little is known regarding the effects of both prey species and population abundance on the spatial distribution of the Amur leopard population in northeast China, in the regions bordering the Russian Far East.
Reliable spatial distribution estimates of population density are crucial to population conservation and habitat management of elusive endangered species (Sollmann et al., 2013, Li and Wang, 2013, Zimmermann et al., 2013, Zhang et al., 2014). Camera trapping is an effective, non-invasive technique for wildlife surveys and is currently a popular tool for estimating population sizes of elusive, rare species (Karanth, 1995). Individual identification technology based on distinctive fur patterns makes identification of individual large mammals possible and accurate with camera trap photograph data (Hiby et al., 2009). To our knowledge, no studies have estimated the population size of Amur leopards using statistical estimators based on camera trap data in China. Therefore, we used the camera trap method to survey Amur leopards starting in the spring of 2012 in the southern Laoye Mountain in Jilin. Subsequently, the first evidence of a wild Amur leopard with two kittens was obtained in October 2013 by camera traps (Jiang and Qi, 2014).
In this study, we first estimated the density and spatial distribution of Amur leopard populations using spatially explicit capture–recapture (SECR) models with camera trap data (Royle et al., 2009). Then we assessed relationships between leopard density distribution and prey abundance, total prey biomass, or other habitat factors. We hypothesized that: (1) the population abundance and spatial distribution of prey species influence the spatial distribution of the Amur leopard population; (2) anthropogenic disturbances would decrease the spatial distribution of Amur leopard density; and (3) vegetation and elevation are the main habitat factors determining the spatial distribution of Amur leopard density.
Section snippets
Study area
The study area is located in the southern slopes of the Laoye Mountain of Jilin Province, northeast China, and borders Russia (E 130.609°–131.309°, N 43.231°–43.559°; Fig. 1). The study area is an important part of Amur leopard habitat in China. It is a mountainous area, with elevations ranging from 200 m–1200 m. The climate is temperate continental monsoonal with annual average temperature of 1.5 °C. Total annual precipitation is 450–600 mm, and occurs mainly from May to September. The dominant
Estimates of Amur leopard abundance, ungulate density and biomass
During about 15 months (totally 476 days) from 2013 to 2014, a total of 76 camera trap stations were set up at a density of one camera trap station per unit (i.e., 10 km2). We obtained a total of 76 photographic “captures” of Amur leopards in an area of 1214.53 km2. Ten individuals were unambiguously identified using the Extract Compare software from 68 of the photographic captures, whereas the remaining eight photographic captures were unidentifiable.
During February and March 2014, red deer and
Discussion
Individual recognition of the studied population is a precondition for the capture recapture method using camera traps (Foster and Harmsen, 2012). In this study, eight of the photographic captures were unidentifiable due to either high darkness of the leopard pictures or the high speed of the leopard when passing in front of the camera trap. Noss et al. (2003) assumed that when an individual captured by the camera trap cannot be identified, it could be attributed to one of the previously
Acknowledgments
We thank the support of the Fundamental Research Funds for the Central Universities of China (2572014EA06), the National Natural Science Foundation of China (NSFC 1272336) and the Study on Resource Survey Technology for Tiger and Amur Leopard Population (State Forestry Administration). We appreciate the support provided by Wangqing and Hunchun Forestry Bureaus of Jilin Province, China. We thank our colleagues; especially Jianmin Lang and Fuyou Wang, for helping with camera trapping and the
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