Analysing Patterns in Dog Behaviour

Chakraborty, Subham (2021) Analysing Patterns in Dog Behaviour. Masters thesis, Indian Institute of Science Education and Research Kolkata.

Text (MS Dissertation of Subham Chakraborty (16MS189)) 16MS189_Thesis_file.pdf - Submitted Version Restricted to Repository staff only Download (12MB)

Abstract

Dogs have been close companions of humans for thousands of years, ever since they first appeared some 9000 to 23000 years. They are spread across the world as pets or more commonly as strays. They are dependent on humans directly or indirectly for many aspects of their lives. They are well known as a model system and studied regularly in the fields of physiology, psychology, cognition, etc. The Indian free ranging dog happens to be one those urban-adapted canids which can live independent social lives without much direct intervention from humans. As such their behaviour and ecology has been studied for over a decade at the Dog Lab under Dr Anindita Bhadra. They are an ideal system to study human-animal interactions in an urban context and ultimately understand how dogs evolved from gray wolves in the first place,a question which is still unresolved. The Dog Lab has used various methods focused on groups or at the population level to understand and quantify behaviours of Indian free ranging dogs. In the course of its existence, a fairly comprehensive ethogram with 177 behaviours has been generated with both experimental and ad libitum data. Due to the current pandemic and the resulting restrictions on free movement, I could not focus my study on field observations. So after a period of ad libitum study and an initial training in field experiments, I focused my efforts on metadata analysis using 13 years worth of scan data generated through six experiments with largely two types of protocols - fovi cused long term observations on groups using fixed number of randomised scans in a given period of time interspersed with All Occurrence Sessions and random scans of dogs encountered in population level studies through opportunistic bouts of observation. I compiled the data collected in the experiments and simulated a synthetic dog day with scans spread out over 24 hours for each experiment as well as for combinations of experiments that had similar methodology for data

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