Abstract
Wild animals encounter humans on a regular basis, but humans vary widely in their behaviour: whereas many people ignore wild animals, some people present a threat, while others encourage animals' presence through feeding. Humans thus send mixed messages to which animals must respond appropriately to be successful. Some species appear to circumvent this problem by discriminating among and/or socially learning about humans, but it is not clear whether such learning strategies are actually beneficial in most cases. Using an individual-based model, we consider how learning rate, individual recognition (IR) of humans, and social learning (SL) affect wild animals' ability to reach an optimal avoidance strategy when foraging in areas frequented by humans. We show that ‘true’ IR of humans could be costly. We also find that a fast learning rate, while useful when human populations are homogeneous or highly dangerous, can cause unwarranted avoidance in other scenarios if animals generalize. SL reduces this problem by allowing conspecifics to observe benign interactions with humans. SL and a fast learning rate also improve the viability of IR. These results provide an insight into how wild animals may be affected by, and how they may cope with, contrasting human behaviour.
Highlights
Humans present a threat to a wide range of animal species, and many populations of wild animals have decreased as a result of human activity [1]
As individual humans may act very differently from one another towards wild animals, they send ‘mixed messages’, to which animals must respond effectively in order to succeed in human-dominated environments
There are a few ways by which animals can do this, but their effectiveness depends on the relative number of dangerous humans present, the frequency of encounters, and how quickly animals can learn
Summary
Humans present a threat to a wide range of animal species, and many populations of wild animals have decreased as a result of human activity [1]. As food is a necessary resource and will often be time-consuming for animals to procure, there is little doubt that direct feeding provides an incentive for animals to approach humans more closely This potentially creates a new challenge for animals: will the human they encounter reward them with food, ignore them or try to harm them? Information about dangerous individual humans has been shown to spread through wild animal populations via social learning (SL), such that animals need not experience a direct encounter with a human to respond appropriately in the future [17]. We present an individual-based model of human–animal interactions where animals can either avoid encountering a human, or stay on their foraging ground and be subject to the human’s actions, whether dangerous, rewarding or neutral We use this model to assess the capacity for animals with different learning abilities to reach the optimal avoidance strategy within their lifetimes. 100 variable variable −1 usually initialized at 0.5; varies over time 0.1 (low) or 0.9 (high) 0 (no discrimination; full generalization) 1 (full discrimination; no generalization) 0 (no social learning) 1 (full social learning)
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