In defense of the Type I functional response: The frequency and population-dynamic effects of feeding on multiple prey at a time

Abstract

Ecologists differ in the degree to which they consider the linear Type I functional response to be an unrealistic versus sufficient representation of predator feeding rates. Empiricists tend to consider it unsuitably non-mechanistic and theoreticians tend to consider it necessarily simple. Holling’s original rectilinear Type I is dismissed by satisfying neither desire, with most compromising on the smoothly saturating Type II response for which searching and handling are assumed to be mutually exclusive activities. We derive a ‘multiple-prey-at-a-time’ functional response reflecting predators that can continue to search when handling an arbitrary number of already-captured prey. The multi-prey model clarifies the empirical relevance of Holling’s two Type I forms and the conditions under which linearity can be a mechanistically-reasoned description of predator feeding rates, even when handling times are long. We find information-theoretic support for the linear Type I and multi-prey responses in 26% of 2,598 compiled empirical datasets, and find evidence that larger predator-prey body-mass ratios permit predators to search while handling greater numbers of prey. Incorporating the multi-prey response into the Rosenzweig-MacArthur population-dynamics model reveals that a non-exclusivity of searching and handling can lead to coexistence states and dynamics that are not anticipated by theory built on linear Type I or Type II responses. In particular, it can lead to bistable fixed-point and limit-cycle dynamics with long-term crawl-by transients between them under conditions where abundance ratios reflect top-heavy food webs and the functional response is effectively linear. We conclude that Type I responses should not be considered empirically unrealistic and that more bounded conclusions should be drawn in theory presuming the linear Type I to be appropriate.

Mark Novak
Mark Novak
Associate Professor
Kyle Coblentz
Kyle Coblentz
NSF Graduate Research Fellow