Transfer of physical understanding in a non-tool-using parrot
Van Horik, JO
Springer Verlag (Germany)
© The Author(s) 2016. This article is published with open access at Springerlink.com
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creative commons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made
Physical cognition has generally been assessed in tool-using species that possess a relatively large brain size, such as corvids and apes. Parrots, like corvids and apes, also have large relative brain sizes, yet although parrots rarely use tools in the wild, growing evidence suggests comparable performances on physical cognition tasks. It is, however, unclear whether success on such tasks is facilitated by previous experience and training procedures. We therefore investigated physical comprehension of object relationships in two non-tool-using species of captive neotropical parrots on a new means-end paradigm, the Trap-Gaps task, using unfamiliar materials and modified training procedures that precluded procedural cues. Red-shouldered macaws (Diopsittaca nobilis) and black-headed caiques (Pionites melanocephala) were presented with an initial task that required them to discriminate between pulling food trays through gaps while attending to the respective width of the gaps and size of the trays. Subjects were then presented with a novel, but functionally equivalent, transfer task. Six of eight birds solved the initial task through trial-and-error learning. Four of these six birds solved the transfer task, with one caique demonstrating spontaneous comprehension. These findings suggest that non-tool-using parrots may possess capacities for sophisticated physical cognition by generalising previously learned rules across novel problems.
Funding was provided by the Royal Society and Queen Mary University of London. We thank Esther Hermann for comments on earlier versions of the manuscript and Aidan Hulatt for coding videos for interobserver reliability scores.