Population monitoring of snow leopards using noninvasive collection of scat samples: a pilot study

The endangered snow leopard Panthera uncia occurs in rugged, high-altitude regions of Central Asia. However, information on the status of this felid is limited in many areas. We conducted a pilot study to optimize moecular markers for the analysis of snow leopard scat samples and to examine the feasibility of using noninvasive genetic methods for monitoring this felid. We designed snow leopard-specific primers for seven microsatellite loci that amplified shorter segments and avoided flanking sequences shared with repetitive elements. By redesigning primers we maximized genotyping success and minimized genotyping errors. In addition, we tested a Y chromosome-marker for sex identification and designed a panel of mitochondrial DNA primers for examining genetic diversity of snow leopards using scat samples. We collected scats believed to be from snow leopards in three separate geographic regions including north-western India, central China and southern Mongolia. We observed snow leopard scats in all three sites despite only brief 2-day surveys in each area. There was a high rate of species misidentification in the field with up to 54% of snow leopard scats misidentified as red fox. The high rate of field misidentification suggests sign surveys incorporating scat likely overestimate snow leopard abundance. The highest ratio of snow leopard scats was observed in Ladakh (India) and South Gobi (Mongolia), where four and five snow leopards were detected, respectively. Our findings describe a species-specific molecular panel for analysis of snow leopard scats, and highlight the efficacy of noninvasive genetic surveys for monitoring snow leopards. These methods enable large-scale noninvasive studies that will provide information critical for conservation of snow leopards.