SAMPLING THE PREDATOR'S BUFFET: A MULTIPLE-PREY STUDY OF PREDATION ON LATE-PENNSYLVANIAN GASTROPODS FROM TEXAS

Predation may be the single most important process affecting natural selection because organisms must hazard predation on a daily basis. Arms races between predators and their prey are intriguing because they provide a direct link between predation and evolution; thus, many researchers have focused on morphological changes in single predator-prey systems. Most predators, however, are capable of handling multiple prey types. If one prey evolves an anti-predatory defense, it is more likely that the predator will prey-switch to easier prey, rather than evolving. Fluctuations in attack frequency on a given prey might vary with the presence or absence of different and more preferred prey in the system. For this reason, it is important to examine predation on communities of potential prey. In this study, we compare the following variables of each genus in five communities of bellerophontid and pleurotomariinid gastropods from Upper-Pennsylvanian shales in Texas: percent of predatory repair scars from the total population of repairs, percent biovolume of the total biovolume, and percent abundance. In addition, two genera of bellerophontid gastropods are examined further for potential defenses: shell thickness and body size.

Changes in potential defenses for bellerophontids did not track changes in repair frequency. Multiple regression analysis revealed no significant pattern between percent repair scars and percent biovolume for the community, but a significant relationship was found between percent abundance and percent of total repairs (r = 0.911, p-value < 0.001).

Although this result is counter-intuitive, it is predicted by optimal foraging theory: attack rate is a function of encounter rate. When a predator encounters a potential prey, it must decide whether to attack. This decision is based on the net energy gained per handling time required to take the prey. If the net energy gained per time is sufficient, the predator will always take that prey, even though a preferred prey may exist in the system. This is called the zero-one rule. It is tempting to associate increases in repair frequency with increased success rate of the predator, but this may not always be the case. If the predators in the system forage optimally, then the zero-one rule is in effect, and repair frequency is expected to reflect encounter rate.