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The Amur leopard Panthera pardus orientalis is one of the most endangered cat subspecies in the world. The rare leopard is sympatric with Amur tiger Panthera tigris altaica and their prey in human dominated landscape. To conserve the felid species, it is important to understand the activity patterns of Amur leopards, including its interactions with Amur tigers, prey, and human activities. We used a data set from 163 camera traps to quantify the spatial-temporal overlap between Amur leopards, Amur tigers, prey species, and human disturbances (e.g., humans presence on foot, vehicles, domestic dogs, and cattle grazing) from January to December 2013 in the Hunchun Nature Reserve, NE China. Our results indicated that leopards were more active in daytime and twilight; the seasonal spatial-temporal overlaps between leopards and tigers were lower than that between leopards and their prey species. Human activities and cattle grazing could influence the spatial distribution and activity patterns of the leopards, and therefore, the conservation actions should focus on reduction of human disturbances to minimize the impacts to Amur leopard activity patterns.

Knowledge of abundance, or population size, is fundamental in wildlife conservation and management. Camera-trapping, in combination with capture-recapture methods, has been extensively applied to estimate abundance and density of individually identifiable animals due to the advantages of being non-invasive, effective to survey wide-ranging, elusive, or nocturnal species, operating in inhospitable environment, and taking low labor. We assessed the possibility of using coat patterns from images to identify an individual leopard cat (Prionailurus bengalensis), a Class II endangered species in South Korea. We analyzed leopard cat images taken from Digital Single-Lense Relfex camera (high resolution, 18Mpxl) and camera traps (low resolution, 3.1Mpxl) using HotSpotter, an image matching algorithm. HotSpotter accurately top-ranked an image of the same individual leopard cat with the reference leopard cat image 100% by matching facial and ventral parts. This confirms that facial and ventral fur patterns of the Amur leopard cat are good matching points to be used reliably to identify an individual. We anticipate that the study results will be useful to researchers interested in studying behavior or population parameter estimates of Amur leopard cats based on capture-recapture models.

Natural range loss limits the population growth of Asian big cats and may determine their survival. Over the past decade, we collected occurrence data of the critically endangered Amur leopard worldwide and developed a distribution model of the leopard’s historical range in northeastern China over the past decade. We were interested to explore how much current range area exists, learn what factors limit their spatial distribution, determine the population size and estimate the extent of potential habitat. Our results identify 48,252 km2 of current range and 21,173.7 km2 of suitable habitat patches and these patches may support 195.1 individuals. We found that prey presence drives leopard distribution, that leopard density exhibits a negative response to tiger occurrence and that the largest habitat patch connects with 5,200 km2of Russian current range. These insights provide a deeper understanding of the means by which endangered predators might be saved and survival prospects for the Amur leopard not only in China, but also through imperative conservation cooperation internationally.