Foraging to balance conflicting demands: novel insights from grasshoppers under predation risk

Animal foraging may be influenced by multiple demands simultaneously(e g., nutrient gain and predator avoidance). Conventional approachesto understand the trade-offs between these demands require crammingthem in similar currencies, which is impractical in many fieldsituations. We introduce a new method, called multiobjectiveprogramming, as a framework to explore how animals balance conflictingdemands. Multiobjective programming allows one to explore theinfluence of foraging demands directly, without explicit assumptionsabout how they enter into fitness and without conversion tosome common currency. Using multiobjective programming, we showthat, as foraging demands change, animals may adaptively adjusttheir behavior, even if the constraints on feasible behaviorare unaffected (contrary to the predictions of the conventionalmodels). Hence, we may see a variable response in foraging thatis consistent with adaptive behavior. We used an empirical testwith herbivore grasshoppers and predator spiders to evaluatethe utility of multiobjective programming Our experiments showthat grasshoppers are able to optimally balance the foragingobjectives of energy intake and vigilance under changing levelsof predation risk. The multiobjective model is used both toevaluate the biological significance of the broad variationthat was observed in the grasshoppers' foraging behavior andto quantify explicitly the trade-off between energy intake andpredator avoidance.