Spatial learning overshadows learning novel odors and sounds in both predatory and frugivorous bats
Marjorie May Dixon,
Gerald G Carter,
Michael J Ryan and
Rachel A Page
Behavioral Ecology, 2023, vol. 34, issue 3, 325-333
Abstract:
To forage efficiently, animals should selectively attend to and remember the cues of food that best predict future meals. One hypothesis is that animals with different foraging strategies should vary in their reliance on spatial versus feature cues. Specifically, animals that store food in dispersed caches or that feed on spatially stable food, such as fruits or flowers, should be relatively biased towards learning a meal’s location, whereas predators that hunt mobile prey should instead be relatively biased towards learning feature cues such as odor or sound. Several authors have predicted that nectar-feeding and fruit-feeding bats would rely relatively more on spatial cues, whereas closely related predatory bats would rely more on feature cues, yet no experiment has compared these two foraging strategies under the same conditions. To test this hypothesis, we compared learning in the frugivorous bat, Artibeus jamaicensis, and the predatory bat, Lophostoma silvicolum, which hunts katydids using acoustic cues. We trained bats to find food paired with a unique and novel odor, sound, and location. To assess which cues each bat had learned, we then dissociated these cues to create conflicting information. Rather than finding that the frugivore and predator clearly differ in their relative reliance on spatial versus feature cues, we found that both species used spatial cues over sounds or odors in subsequent foraging decisions. We interpret these results alongside past findings on how foraging animals use spatial cues versus feature cues, and explore why spatial cues may be fundamentally more rich, salient, or memorable.
Keywords: adaptive specializations; bat; belongingness; cue reliance; domain-specific learning; feature cues; modality; object cues; prepared learning; spatial cues (search for similar items in EconPapers)
Date: 2023
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