Reconsidering the importance of the past in predator-prey models: both numerical and functional responses depend on delayed prey densities.
We propose that delayed predator-prey models may provide superficially acceptable predictions for spurious reasons. Through experimentation and modelling, we offer a new approach: using a model experimental predator-prey system (the ciliates Didinium and Paramecium), we determine the influence of past-prey abundance at a fixed delay (approx. one generation) on both functional and numerical responses (i.e. the influence of present : past-prey abundance on ingestion and growth, respectively). We reveal a nonlinear influence of past-prey abundance on both responses, with the two responding differently. Including these responses in a model indicated that delay in the numerical response drives population oscillations, supporting the accepted (but untested) notion that reproduction, not feeding, is highly dependent on the past. We next indicate how delays impact short- and long-term population dynamics. Critically, we show that although superficially the standard (parsimonious) approach to modelling can reasonably fit independently obtained time-series data, it does so by relying on biologically unrealistic parameter values. By contrast, including our fully parametrized delayed density dependence provides a better fit, offering insights into underlying mechanisms. We therefore present a new approach to explore time-series data and a revised framework for further theoretical studies.
Laboratory of Protozoology, KLB07006, College of Life Science, South China Normal University, Guangzhou 510631, People's Republic of China.
Jiqiu
J
Li
Andy
A
Fenton
Lee
L
Kettley
Phillip
P
Roberts
David J S
DJ
Montagnes
D000818:Animals; D016798:Ciliophora / Q000502:physiology*; D008954:Models, Biological; D010247:Paramecium / Q000502:physiology*; D011156:Population Density; D011157:Population Dynamics; D011235:Predatory Behavior
Didiniium; Paramecium; functional response; numerical response; population dynamics