Evaluation of Parasite or Predator Responses

Abstract

The behaviour of searching parasites and predators in relation to varying populations of their hosts or prey is unlikely to be simple. Early theorists sought to describe the relationship by a single constant (Lotka 1925; Volterra 1931; Thompson 1930; Nicholson 1933; Nicholson & Bailey 1935). Solomon (1949) first suggested the terms functional and numerical for more complex responses of parasites and predators to their hosts and prey. These terms have since been used by several authors, not always as they were originally defined. They are suitable for describing the effects of the host or prey density on the behaviour and reproduction of the parasite or predator concerned, but not to describe the effects of the parasitism or predation on the host or prey population. The purpose of this paper is to review some of the uses of this terminology in the literature and to introduce a new and more precise system of classifying parasite or predator responses to host or prey density. It should be added, however, that it is almost an impossible task to find any system for classifying responses of this kind that caters for all cases, and there will certainly be instances in which the proposed system of terms is unsuitable. Solomon (1949) stated that '. . . to be density dependent, the enemy must respond to changes in the numbers of host (cf. Nicholson 1933; Varley 1947). The nature of this response is commonly twofold. First, there must be a FUNCTIONAL response to (say) an increase in the host density, because of the increased availability of victims: as host density rises, each enemy will attack more host individuals, or it will attack a fixed number more rapidly. A frequent, but not invariable result of this is an increase in the numbers of the enemy (a NUMERICAL influence) due to an increased rate of survival or reproduction, or of both; this may or may not be sufficient to produce an increase in the PROPORTION of enemies to the increasing hosts'. It is important to realize that a weak functional response may be insufficient to result in density-dependent mortality, for which there must be an increase in the proportion of hosts taken by each enemy as host density increases. Likewise, a numerical response in the enemy may not produce delayed density-dependency for which a proportionate increase in the numbers of enemy compared with those of the host or prey is necessary. Holling (1959a) elaborated these terms in his study of the predation of cocoons of Neodiprion sertifer (Geoff.) by small mammals in Canada. The functional response was defined in terms of changes in the number of prey consumed by each predator, and the numerical response as changes in the predator density at different prey densities. Holling divided the functional response into three basic types and expressed them graphically by plotting the numbers of prey taken per predator per unit time as the dependent variable against the prey density (Fig. la). Similarly, the numerical response was subdivided into three types (direct, none and inverse) and expressed as the numbers of predators per unit area against prey density (Fig. 2, A, B and C). Varley & Gradwell (1963a) used these terms in a different sense and implied that functional and numerical responses resulted in density-dependent and delayed density-dependent mortalities of the host or prey. A functional response was defined as occurring when '. . . local concentrations of prey are