Functional response as a component of dynamic simulation models in biological control: the Catolaccus-boll weevil system

Abstract

A simulation model using Time Varying Distributed Delays was created on the HERMES (Hierarchical Environment for Research Modelling of Ecological Systems) of the USDA/ARS with the purpose of evaluating different forms of functional response components in dynamic simulations of biological control systems. The specific host-parasitoid life system used in the evaluation was the boll weevil- Catolaccus grandis system. Four forms of functional response equations were tested: Type I, Type II, a Type II modified to yield constant attack probabilities under constant host: parasitoid ratios, and a temperature-dependent Type II. Simulation runs showed that the parasitoid is potentially capable of considerable suppression of the host population. Predicted host numbers under Type I and II equations did not differ markedly, because realistic host numbers per parasitoid were often found in the linear portion of the Type II equation. The probability of attack using a Type I equation was always near 100% despite arbitrarily increasing the host population to create a wide range of host: parasitoid ratios. The Type II equation resulted in fluctuating attack probabilities which steadily declined as host: parasitoid ratio exceeded 100: 1. The modified Type II equation yielded attack probabilities starting at 52% and steadily declining to about 8% when host: parasitoid ratios neared 1000:1. We introduced a realistic, but hypothetical, relationship between functional response and temperature. Simulations using actual weather data from the Rio Grande Valley of Texas suggest that there is little difference between using Types I or II equations, but that the effect of temperature on attack rates is substantial in this system. Caution should be used when incorporating data from experiments into simulation models because experimental conditions are often unrealistically optimal. We discuss the possible importance of temperature and other diurnal or environmental events on functional response and the value of relevant data in this and other simulation models of biological control.