LAUSR

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.