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environmental change
learning
optimal sampling
stimulus-response
contingencies
novelty
neophobia
set-shift
behavioral-responses
cane toads
predator recognition
habitat
selection
cognitive ecology
antipredator
habituation
animals
conservation
performance
Abstract:
Many animals respond well behaviorally to stimuli associated with human-induced rapid environmental change (HIREC), such as novel predators or food sources. Yet others make errors and succumb to evolutionary traps: approaching or even preferring low quality, dangerous or toxic options, avoiding beneficial stimuli, or wasting resources responding to stimuli with neutral payoffs. A common expectation is that learning should help animals adjust to HIREC; however, learning is not always expected or even favored in many scenarios that expose animals to ecological and evolutionary traps. We propose a conceptual framework that aims to explain variation in when learning can help animals avoid and escape traps caused by HIREC. We first clarify why learning to correct two main types of errors (avoiding beneficial options and approaching detrimental options) might be difficult (limited by constraints). We then identify and discuss several key behavioral mechanisms (adaptive sampling, generalization, habituation, reversal learning) that can be targeted to help animals learn to avoid traps. Finally, we discuss how individual differences in neophobia/neophilia and personality relate to learning in the context of HIREC traps, and offer some general guidance for disarming traps. Given how devastating traps can be for animal populations, any breakthrough in mitigating trap outcomes via learning could make the difference in developing effective solutions.
