A new methodology developed by the Indian Statistical Institute, and WCS (Wildlife Conservation Society) may revolutionize how to count tigers and other big cats over large landscapes. The new method offers the opportunity for researchers to rigorously assess animal numbers at large geographical scales—a critical need for informing conservation interventions and wildlife management. Called “Bayesian Smoothing Model (BSM),” the methodology addresses a thorny problem faced by ecologists and conservationists: extrapolating accurate population counts in smaller areas, such as protected reserves, to wider regions where only weaker methods can be employed. Currently, scientists rely on information collected using rigorous but resource-intensive survey methods-such as camera trapping- to provide reliable results at smaller scales. However, they are compelled to use weak surrogate indices, such as track counts, while surveying large landscapes of 10,000 square kilometers or more. The current statistical method of integrating these two types of data, known as Index-Calibration, developed decades ago, which is known to generate misleading population estimates.
From Wildlife Conservation Society Photo Credit John Vlahakis