Using enclosed Y-mazes to assess chemosensory behavior in reptiles

Journal of Visualized Experiments
By: , and 

Links

Abstract

Reptiles utilize a variety of environmental cues to inform and drive animal behavior such as chemical scent trails produced by food or conspecifics. Decrypting the scent-trailing behavior of vertebrates, particularly invasive species, enables the discovery of cues that induce exploratory behavior and can aid in the development of valuable basic and applied biological tools. However, pinpointing behaviors dominantly driven by chemical cues versus other competing environmental cues can be challenging. Y-mazes are common tools used in animal behavior research that allow quantification of vertebrate chemosensory behavior across a range of taxa. By reducing external stimuli, Y-mazes remove confounding factors and present focal animals with a binary choice. In our Y-maze studies, a scenting animal is restricted to one arm of the maze to leave a scent trail and is removed once scent-laying parameters have been met. Then, depending on the trial type, either the focal animal is allowed into the maze, or a competing scent trail is created. The result is a record of the focal animal's choice and behavior while discriminating between the chemical cues presented. Here, two Y-maze apparatuses tailored to different invasive reptile species: Argentine black and white tegu lizards (Salvator merianae) and Burmese pythons (Python bivittatus) are described, outlining the operation and cleaning of these Y-mazes. Further, the variety of data produced, experimental drawbacks and solutions, and suggested data analysis frameworks have been summarized.
Publication type Article
Publication Subtype Journal Article
Title Using enclosed Y-mazes to assess chemosensory behavior in reptiles
Series title Journal of Visualized Experiments
DOI 10.3791/61858
Volume 170
Year Published 2021
Language English
Publisher Jove
Contributing office(s) Fort Collins Science Center
Description e61858, 19 p.
Online Only (Y/N) Y
Google Analytics Metrics Metrics page
Additional publication details