Learning of Foraging Skills by Fish

Abstract

IntroductionInvestigations of the role of learning and memory in the foraging behaviour of fishes are at an exciting stage. Although less thoroughly studied than traditional laboratory favourites such as rats, pigeons or bees, fish species are no longer to be consigned to the 'poorly understood' category. It is now possible to place the capacities of fish in the context of learning and memory as a whole, as evidenced by previous reviews such as those by Hart (1986Hart ( , 1993, Hughes et al. (1992) and Kieffer & Colgan (1992). The present chapter attempts to integrate perspectives and findings from the fields of behavioural ecology and comparative psychology. This approach has been adopted for the following reasons:1. Comparative psychology has revealed broad regularities in the general principles of learning across invertebrate and vertebrate taxa (Logue 1988; Domjan 1998) and across spatial and temporal domains (Cheng & Spetch 2001). The general principles that apply to learning in bees, pigeons and rats are likely to apply to fishes also. Psychology can clarify the mechanisms that underlie observed behaviour, while behavioural ecology can evaluate the adaptive significance of behavioural capacities demonstrated by psychology. 2. In several cases, static first-generation models based on optimal foraging theory (OFT) that do not represent temporal changes in internal state fail to predict observed behaviour (Hart 1993). More recent studies using more flexible (e.g. dynamic-programming) models have been more successful because of their ability to represent changes in internal state (e.g. physiology and learning), interactions between intrinsic and extrinsic variables and continuous behavioural adjustment in response to these factors (Ehlinger 1989;Kieffer & Colgan 1991;Hart 1993;Dall et al. 1999). Although standard OFT models predict that animals should exhibit all-or-nothing choice, experiments usually reveal partial preferences. It is likely that future models will draw increasingly on psychological effects (e.g. discrimination, memory, cue competition, interference and attention) to explain such divergences from the predictions of simple or idealised models and to test models based on risk and information (Shettleworth 1988).

Less is more: density influences the development of behavioural life skills in trout

“…(i) Food searching In nature, food resources are often highly variable in time and space (Warburton 2003). To minimize energy costs and movement-associated predation risk while searching for food, animals need to find their way efficiently (Odling-Smee & Braithwaite 2003).…”

Memory retention of appetitive and aversive conditioning in the damselfish Stegastes fuscus

“…In unpredictable environments, learning is dispensable because there is no need to acquire information that cannot be used again. However, natural environments are somewhat predictable and, in such cases, the information acquired needs to be stored temporarily (Warburton, ). Stegastes fuscus is a territorial species that defends an area containing food and shelter from conspecifics and heterospecifics (Ferreira et al ., ; Osório et al ., ).…”

Masked Expression of Life-History Traits in a Highly Variable Environment

“…We obtained reservoir water-level data for 2003-2012 from the US Bureau of Reclamation (usbr 2013) for two reservoirs in the Republican River basin in southwest Nebraska that diff ered in the relative degree of annual waterefi ts of current reproductive investment (Forbes 1991;Bårdsen et al 2008). In fi shes, learning plays an important role in the development of numerous skills and behaviors (Kieff er and Colgan 1992;Laland et al 2003 and references therein), including foraging (Warburton 2003), antipredator behavior (Kelley and Magurran 2003;Kelley and Magurran 2006), and reproductive behavior (Witte and Nöbel 2011).…”