ANALYSIS OF PROCESSES I N CONTROL OF INSECTS
49
sponse is based only on years when the budworm numbers were higher
than in the previous year; as far as it goes, it rises at a decreasing
rate, i.e. less than density-dependently. The curve of combined response is similar to Holling’s curve for BZurina in Fig. 1 8 ~ .
F. A NOTE ON TERMS
The terms functional and numerical response were originally intended
to apply to the responses of natural enemies to changes in the density
of their prey. In developing his analysis of predation, Holling (1961)
introduces an extension of the terminology, namely, functional response of predators to their own density. This is simply a new name for
the effects of competition and interference between predators, and
group stimulation, as measured by the effects upon their prey. (Holling
reviews a number of studies on this aspect of predation.) I regret only
that this may make the terms more cumbersome, since the user, to
make his meaning clear, would often have to write, e.g. ‘(numerical
response to prey density’’ or “functional response to predator density”.
I am more dubious about the distinction made by Holling (1959a,
1961) between “direct” numerical responses to prey density, in which
the numbers of predators increase as prey numbers rise, and “inverse”
responses, in which predator numbers decline as prey numbers increase.
His illustrations of direct responses show predator numbers rising, but
sometimes not at as great a proportionate rate as prey numbers. In the
latter cases we have an inverse density relationship; if it is at the same
time regarded as a direct numerical response, there may be some
confusion. Moreover, the need for the term “inverse numerical response”
to describe a decline in predator numbers in response to a rise in prey
numbers must be rather slight, since although predators often do decline at a time when prey density is rising, such a fall in predators must
very seldom be a response to the increase in prey.
VI. QUESTIONS BEARING O N A THEORY OF PARASITE-HOST
A . IS PARASITE FECUNDITY NOT A LIMITING FACTOR?
Nicholson (1933) and Nicholson and Bailey (1935) put forward a
model of parasite-host interaction in which one of the assumptions
was that the capacity of parasites to attack hosts is great enough to
match the numbers of hosts that they can find, so that it is the supply
of hosts and their ability to find them that limits the parasites’ increase,
not their own capacity to deal with hosts found. The model generates
oscillations of the host and parasite populations, the oscillations becoming increasingly violent and ending in extinction of the populations.
INTERACTION
49
sponse is based only on years when the budworm numbers were higher
than in the previous year; as far as it goes, it rises at a decreasing
rate, i.e. less than density-dependently. The curve of combined response is similar to Holling’s curve for BZurina in Fig. 1 8 ~ .
F. A NOTE ON TERMS
The terms functional and numerical response were originally intended
to apply to the responses of natural enemies to changes in the density
of their prey. In developing his analysis of predation, Holling (1961)
introduces an extension of the terminology, namely, functional response of predators to their own density. This is simply a new name for
the effects of competition and interference between predators, and
group stimulation, as measured by the effects upon their prey. (Holling
reviews a number of studies on this aspect of predation.) I regret only
that this may make the terms more cumbersome, since the user, to
make his meaning clear, would often have to write, e.g. ‘(numerical
response to prey density’’ or “functional response to predator density”.
I am more dubious about the distinction made by Holling (1959a,
1961) between “direct” numerical responses to prey density, in which
the numbers of predators increase as prey numbers rise, and “inverse”
responses, in which predator numbers decline as prey numbers increase.
His illustrations of direct responses show predator numbers rising, but
sometimes not at as great a proportionate rate as prey numbers. In the
latter cases we have an inverse density relationship; if it is at the same
time regarded as a direct numerical response, there may be some
confusion. Moreover, the need for the term “inverse numerical response”
to describe a decline in predator numbers in response to a rise in prey
numbers must be rather slight, since although predators often do decline at a time when prey density is rising, such a fall in predators must
very seldom be a response to the increase in prey.
VI. QUESTIONS BEARING O N A THEORY OF PARASITE-HOST
A . IS PARASITE FECUNDITY NOT A LIMITING FACTOR?
Nicholson (1933) and Nicholson and Bailey (1935) put forward a
model of parasite-host interaction in which one of the assumptions
was that the capacity of parasites to attack hosts is great enough to
match the numbers of hosts that they can find, so that it is the supply
of hosts and their ability to find them that limits the parasites’ increase,
not their own capacity to deal with hosts found. The model generates
oscillations of the host and parasite populations, the oscillations becoming increasingly violent and ending in extinction of the populations.
INTERACTION