The Roles of Density, Stage, and Patchiness in the Transmission of an Insect Virus

Abstract

Although the importance of insect viruses in the population dynamics of their hosts is widely acknowledged, ecologists are still relatively ignorant of the factors determining the rate of transmission of insect viruses in the field. I performed a series of field experiments in which I investigated the transmission dynamics of the nuclear poly— hedrosis virus (NPV) of Douglas—fir tussock moth, Orgyia pseudotsugata (Lepidoptera: Lymantriidae), in northern Idaho, USA. In these experiments, I reared healthy and infected healthy larvae that became infected as a measure of transmission. I explored the influences of density, stage structure, and spatial structure on transmission by manipulating the density and stage distribution of healthy and infected hosts, and the spatial distribution of infected hosts. The experiments indicate that transmission is strongly affected by the densities of both healthy and infected hosts, but the effect depends on the instar of each. Late instars are both more infectious and more likely to become infected than are early instars, so that the NPV is more likely to spread in populations of late—instar tussock moth larvae. I also found that transmission is affected by the spatial distribution of infected hosts, and this effect also depends on the instar of healthy hosts. That is, transmission to healthy early instars decreases with increasing patchiness of infected hosts, but transmission to healthy late instars is essentially unaffected by patchiness. I discuss how these results can be in— terpreted in terms of behavioral differences among instars, and relate the results to the mathematical theory of disease and the use of viruses in biological pest control.

Parasite transmission: reconciling theory and reality

“…By adding an explicit heterogeneity term to the standard transmission model, Dwyer et al (1997) showed that increasing the degree of heterogeneity among the host population leads to an increase in the degree of non-linearity in the transmission rate. Furthermore, Dwyer et al (1997) showed that the heterogeneity model fitted the observed transmission rates better than the simple homogeneous model, attributing the heterogeneity to inherent variations in susceptibility among the hosts, including differences in susceptibility between instars (Dwyer 1991). However, such heterogeneities may also arise through an environmental or spatial factor which results in some hosts being more at risk of contacting the parasites than others (Knell et al 1996(Knell et al , 1998a.…”

Patterns of covert infection by invertebrate pathogens: iridescent viruses of blackflies

“…Nothing is known about fue ability of fue novel (third) virus to cause patent infections in blackflies. The role of spatial heterogeneity in fue distribution of larvae was not addressed here but mar be an additional factor of imporlance in fue dynamics of fue host-pathogen interaction as reported in other insect virus systems (Dwyer 1991). The bioassay procedures used were highIy sensitive.…”

An empirical test of the role of small-scale transmission in large-scale disease dynamics

“…Evidence for effects of such large-scale mechanisms on the transmission of this or other baculoviruses, however, is almost entirely lacking (D' Amico and Elkinton, 1995;Dwyer, 1991). More-393 over, failed efforts to estimate the decay rate µ experimentally suggest that µ may be very low for this virus (Dwyer (1991), Online Appendices).…”

“…The total time in the m exposed classes is the sum of m such distributions, and a well-known theorem has shown that the sum follows a gamma distri-180 bution with mean, 1/δ, and variance, 1/(mδ 2 ) (Keeling and Rohani, 2008). For the tussock moth virus, the variance in the speed of kill is quite low (Dwyer (1991), also Online Appendices), so in practice we fixed m = 200, rather than estimating m from the observational data.…”

“…The approximation is highly accurate if transmission rates follow a gamma distribution, which has a fatter tail than a gamma distribution (G. Dwyer, unpublished). In general, we assume that transmission occurs among larvae in the fourth instar (= larval stage), the 192 instar that has the biggest impact on cumulative infection rates (Dwyer, 1991;Otvos et al, 1987).…”