Abstract

Foraging behavior of pollinators is shaped by, among other factors, the conflict between maximizing resource intake and minimizing predation risk; yet, empirical studies quantifying variation in both forces are rare, compared to those investigating each separately. Here, we discuss the importance of simultaneously assessing bottom-up and top-down forces in the study of plant-pollinator interactions, and propose a conceptual and testable graphical hypothesis for pollinator foraging behavior and plant fitness outcomes as a function of varying floral rewards and predation risk. In low predation risk scenarios, no noticeable changes in pollinator foraging behavior are expected, with reward levels affecting only the activity threshold. However, as predation risk increases we propose that there is a decrease in foraging behavior, with a steeper decline as plants are more rewarding and profitable. Lastly, in high predation risk scenarios, we expect foraging to approach zero, regardless of floral rewards. Thus, we propose that pollinator foraging behavior follows an inverse S-shape curve, with more pronounced changes in foraging activity at intermediate levels of predation risk, especially in high reward systems. We present empirical evidence that is consistent with this hypothesis. In terms of the consequences for plant fitness, we propose that specialized plant-pollinator systems should be more vulnerable to increased predation risk, with a steeper and faster decline in plant fitness, compared with generalist systems, in which pollinator redundancy can delay or buffer the effect of predators. Moreover, whereas we expect that specialist systems follows a similar inverse S-shape curve, in generalist systems we propose three different scenarios as a function not only of reward level but also compatibility, mating-system, and the interplay between growth form and floral display. The incorporation of trade-offs in pollinator behavior balancing the conflicting demands between feeding and predation risk has a promising future as a key feature enabling the development of more complex foraging models.

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