A pinboard by
Muhammad Waqas khan

Student, Quaid-i-Azam University, Islamabad, Pakistan


Estimation of density and abundance of rare species after manageable time period is a key to understand population trends and is necessary for conservation actions. Non-invasive methods of data collection with recently developed Capture-Recapture (CR) techniques provide statistically valid densities estimate of cryptic species. Based on data collected from camera trapping, we used Spatially Explicit Capture-Recapture (SECR) approach to estimate density and abundance of snow leopard in Hopper-Hisper valleys of Central Karakoram National Park (CKNP), District Nagar, Gilgit-Baltistan, Pakistan. We placed 38 camera traps for 65 days over sampled area of 1856 km2 in March 2016. A total of 31 photo-captures of snow leopards were recorded over 2207 trap nights, with capture success of 1.4 captures/100 traps nights. Based on unique pelage patterns present on forehead, front limb, flanks of torso and dorsal surface of tail, we identified four snow leopard individuals. SECR model estimated density of 0.22 individuals / 100 km2. Total numbers of estimated snow leopard ranged from 4-6. Our study demonstrate that camera trapping in combination with Spatially Explicit Capture-Recapture (SECR) model is a promising tool of assessing densities of snow leopards across various regions where it occurs in very low densities.


Face Value: Towards Robust Estimates of Snow Leopard Densities.

Abstract: When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01) individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87). Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.

Pub.: 01 Sep '15, Pinned: 10 Jun '18