Free-ranging dogs quickly learn to recognize a rewarding person

Autor: Nandi, Srijaya, Chakraborty, Mousumi, Lahiri, Aesha, Gope, Hindolii, Bhaduri, Sujata Khan, Bhadra, Anindita
Rok vydání: 2024
Předmět:
Druh dokumentu: Working Paper
Popis: Individual human recognition is important for species that live in close proximity to humans. Numerous studies on domesticated species and urban-adapted birds have highlighted this ability. One such species which is heavily reliant on humans is the free-ranging dog. Very little knowledge exists on the amount of time taken by free-ranging dogs to learn and remember individual humans. Due to their territorial nature, they have a high probability of encountering the same people multiple times on the streets. Being able to distinguish individual humans might be helpful in making decisions regarding people from whom to beg for food or social reward. We investigated if free-ranging dogs are capable of identifying the person rewarding them and the amount of time required for them to learn it. We conducted field trials on randomly selected adult free-ranging dogs in West Bengal, India. On Day 1, a choice test was conducted. The experimenter chosen did not provide reward while the other experimenter provided a piece of boiled chicken followed by petting. The person giving reward on Day 1 served as the correct choice on four subsequent days of training. Day 6 was the test day when none of the experimenters had a reward. We analyzed the choice made by the dogs, the time taken to approach during the choice tests, and the socialization index, which was calculated based on the intensity of affiliative behaviour shown towards the experimenters. The dogs made correct choices at a significantly higher rate on the fifth and sixth days, as compared to Day 2, suggesting learning. This is the first study aiming to understand the time taken for individual human recognition in free-ranging dogs and can serve as the scaffold for future studies to understand the dog-human relationship in open environments, like urban ecosystems.
Databáze: arXiv