Size is relative: use of relational concepts by wild hummingbirds

Autor: Theo Brown, T. Andrew Hurly, Susan D. Healy, Maria C. Tello-Ramos
Přispěvatelé: University of St Andrews. School of Biology, University of St Andrews. Centre for Biological Diversity, University of St Andrews. Institute of Behavioural and Neural Sciences, University of St Andrews. Centre for Social Learning & Cognitive Evolution
Rok vydání: 2022
Předmět:
Zdroj: Proceedings of the Royal Society B: Biological Sciences. 289
ISSN: 1471-2954
0962-8452
DOI: 10.1098/rspb.2021.2508
Popis: This work was supported by the Association for the Study of Animal Behaviour (S.D.H.), the University of Lethbridge and the Natural Sciences and Engineering Research Council of Canada (RGPIN 121496–2003; T.A.H.). Rufous hummingbirds (Selasphorus rufus) will readily learn the location and the colour of rewarded flowers within their territory. But if these birds could apply a relational concept such as ‘the larger flowers have more nectar’, they could forego learning the locations of hundreds of individual flowers. Here, we investigated whether wild male territorial rufous hummingbirds might use ‘larger than’ and ‘smaller than’ relational rules and apply them to flowers of different sizes. Subjects were trained to feed consistently from one of two flowers. Although the flowers differed only in size, the reward was always contained in the same-size flower. The birds were then tested on a choice of two empty flowers: one of the familiar size and the other a novel size. Hummingbirds applied relational rules by choosing the flower that was of the correct relational size rather than visiting the flower of the size rewarded during training. The choices made by the hummingbirds were not consistent with alternative mechanisms such as peak shift or associative learning. We suggest that while hummingbirds are very good at remembering the spatial locations of rewarding flowers, they would be able to use relative rules when foraging in new and changing environments. Publisher PDF
Databáze: OpenAIRE