Himachal Pradesh to measure wildlife density

Numbers in the jungle: Himachal Pradesh to measure wildlife density

Hemlata Verma Posted online: Wed Oct 06 2010, 02:03 hrs


Shimla : The state government has started a new project to measure the density of wildlife in protected areas. Till now, the state wildlife department only had information about the habitats and general movements of wildlife species found in the state. The state will now conduct a proper scientific study across all protected forests to find out the density of wild animals. The surveyors will primarily use the well established method of camera traps for the purpose. In the initial round, focus will be on species that have been declared endangered, such as western tragopan, monal and snow leopard.
Specialised agencies in the sector, including the Wildlife Society of India, are being engaged in the project that will span across 25 listed protected areas (sanctuaries and national parks).

“In the first stage, the agencies are in the process of setting up camera traps for checking the density of western tragopan in their natural habitat in Tirthan, Sainj (Kullu )and Kugti (Chamba) sanctuaries,” said an official in the forest department.

For other birds like monal and chir and animals, including Himalayan thar, ghoral, serow (ungulate species locally known as emu), camera traps are being laid in Talra and Churdhar wildlife sanctuaries. The method will lead to compilation of per square kilometre density of the wild animals.

Just published in the Journal of Wildlife Management: SLN member article “Assessing Estimators of Snow Leopard Abundance”

The article Assessing Estimators of Snow Leopard Abundance was published in the Journal of Wildlife Management 72(8), pages 1826-1833. 2008. Congratulations to authors Kyle McCarthy, Todd Fuller, Ma Ming, Thomas McCarthy, Lisette Waits, and Kubanych Jumabaev.

The article in its entirety is available on the SLN Bibliography and may be found by visiting the link below:

http://www.snowleopardnetwork.org/bibliography/Assessing Estimators of Snow Leopard Abundance.pdf


The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture–recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June–December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km2. Photo capture–recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n=4/13), and 0.74 (n=5/6) individuals/100 km2 in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates (photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture–recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.