Earlier events :: 2013 :: STUDENT Poster

Estimating the Free-ranging Dog Population using Natural Marks in Two Distinct Localities of Bangalore (Work In Progress).

Presented by
Siddhant Nowlakha
Azim Premji University
Authors
Siddhant Nowlakha, Shahzeb Yamin. Azim Premji University, Bangalore. Email: Siddhant.N@Apu.Edu.In

Aim

Free-ranging dogs are insulated from food scarcity because of human subsidies and are generally buffered from intra-guild feedback mechanisms causing a very high growth of their population.

A large-scale dog control project can be adequately planned and assembled only when point estimate dog abundance is known. In our study, we have used, for the first time, natural marks to estimate dog population without any mark discrimination under Mark-Recapture framework.

Methods

We carried our study simultaneously on a 4 km transact each in Malleshwaram and BTM Layout in Bangalore between April 12 and 14, 2013. Every visible dog (except pets) was photographed along with its GPS location. The survey was repeated for 3 simultaneous days. Moreover we also mapped all the potential resource sites for dogs on our route such as butcheries and garbage dumps. Each dog was given a unique ID and overall sighting frequency of each individual was calculated.

Results

We recorded a total of 34 dogs in Malleshwaram and 85 dogs in BTM Layout. In a corresponding figure, Malleshwaram comprised six potential resource sites while BTM Layout had 17 such locations.. The sighting frequency sheet is presently under analysis with Program MARK. Hence the final population estimates will take another week.

Conservation

The final results are likely to produce a point estimate abundance of dogs in the surveyed region. The present estimation methods in use either attract high operational cost and time, or fall short in precision of results, esp. when applied on large scale.The methodology employed by us is the only approach to estimate free-ranging dog population in the most inexpensive and reliable manner on large geographic landscapes like a city and a forest region.