Quantity discrimination in angelfish, Pterophyllum scalare: a novel approach with food as the discriminant

The ability to distinguish between different quantities of items is fundamental in many ecological contexts, and it has been shown in different animal species. This ability may also be context specific. Quantity estimation in fish has mainly been analysed in the context of social behaviour, whereas a majority of studies conducted with species other than fish tested it in the context of foraging. Surprisingly, little is known about the capacity of fish to discriminate between food quantities, possibly because of difficulties in testing individual fish in a novel, and thus aversive, test environment. Here, we present a novel approach that allowed us to test single angelfish, Pterophyllum scalare, while minimizing isolation-related stress. In binary choice tests, sets composed of similarly sized discrete food items differing in numerical size were presented and the spontaneous (untrained) choice of angelfish was investigated. In all contrasts tested in three experiments, angelfish preferred the numerically larger to the smaller food set. The performance of the fish was ratio dependent in the small but not in the large number range (more than four food items, contrasts that were investigated for the first time in fishes), and there was no significant difference in the magnitude of preference for the small versus the large values. However, overall results indicated that the response was ratio dependent, with an increase in accuracy as the numerical ratio between the contrasts increased. Furthermore, the same numerical ratios that were successfully discriminated with small quantities were also similarly discriminated with large quantities. Altogether, our results thus imply that angelfish utilize the approximate number system of quantity representation for the entire numerical range tested, and that their response is an attempt to maximize foraging success. (C) 2018 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.