How Should Prey Animals Respond to Uncertain Threats?

Joel Zylberberg,Michael Robert Deweese

doi:10.3389/fncom.2011.00020

Abstract

A prey animal surveying its environment must decide whether there is a dangerous predator present or not. If there is, it may flee. Flight has an associated cost, so the animal should not flee if there is no danger. However, the prey animal cannot know the state of its environment with certainty, and is thus bound to make some errors. We formulate a probabilistic automaton model of a prey animal's life and use it to compute the optimal escape decision strategy, subject to the animal's uncertainty. The uncertainty is a major factor in determining the decision strategy: only in the presence of uncertainty do economic factors (like mating opportunities lost due to flight) influence the decision. We performed computer simulations and found that in silico populations of animals subject to predation evolve to display the strategies predicted by our model, confirming our choice of objective function for our analytic calculations. To the best of our knowledge, this is the first theoretical study of escape decisions to incorporate the effects of uncertainty, and to demonstrate the correctness of the objective function used in the model.

Highlights

Prey animals frequently assess their surroundings to identify potential threats to their safety
3.1 The optimal decision strategy depends on the environment and varies with the animal’s uncertainty about the state of the environment The strategy that maximizes the expectation value of r, subject to the pi = fi(qi) constraints imposed by the ROC curves, is given by www.frontiersin.org
We argue that the results of our simulation support our chosen objective function. It has previously been conjectured (Cooper and Frederick, 2007) that, because the correct objective function is unknown, and prey animals have uncertain information about the environment, quantitative behavioral predictions are impossible. We have addressed both of these issues: the correct objective function, while hard to compute for real prey animals, is known, and we have explicitly incorporated the effects of imperfect information into our decision model

Summary

Introduction

Prey animals frequently assess their surroundings to identify potential threats to their safety. If an animal does not flee soon enough in the presence of a predator (type I error), it may be injured or killed If it flees when there is no legitimate threat (type II error), it wastes metabolic energy, and loses mating or foraging opportunities (Nelson et al, 2004; Creswell, 2008). The predominant assumption in the field appears to be that this uncertainty is not important, and that so long as the prey animal knows the most likely state of the environment (or the expected value of the state), they can still make economically optimal decisions.

Methods

Results

Conclusion