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Host Dispersal and the Spatial Spread of Insect Pathogens
Author(s) -
Dwyer Greg,
Elkinton Joseph S.
Publication year - 1995
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1940933
Subject(s) - biological dispersal , biology , ballooning , ecology , epizootic , host (biology) , lymantria dispar , larva , spatial ecology , zoology , outbreak , population , virology , demography , physics , plasma , quantum mechanics , sociology , tokamak
Empirical studies of the spatial spread of insect pathogens have emphasized the importance of high dispersal rates, but typically rely strictly on observational data. In contrast, existing mathematical models on the spatial spread of infectious diseases have suggested that a highly infectious disease can spread rapidly even if the dispersal rate of its host is low; such models, however, are largely untested. To understand how host dispersal and disease infectiousness affect the spatial spread of infectious disease, we performed a field experiment in which we released a nuclear polyhedrosis virus (NPV) into two experimentally established, disease—free gypsy moth (Lymantria dispar) populations. We simultaneously and independently measured the long—distance dispersal of ballooning, first—instar, gypsy moth larvae, the stage in which dispersal is by far the greatest. Surprisingly, dispersal by ballooning was a good predictor of NPV spread only in the first few weeks of spread. Subsequently, the virus spread much farther and less directionally than did ballooning larvae. No infections appeared in control plots that started with only uninfected larvae, confirming that the virus we released caused the epizootic in our experimental populations. On the theory that additional spread was due to a combination of small—scale larval dispersal and a high rate of disease transmission, we compared our data to the predictions of a mathematical model for the spatial spread of insect pathogens that combines disease transmission and small—scale host dispersal. By using independent estimates of each of the model parameters, we used the model to make post hoc predictions of the rate of spread of the virus from an initial distribution dictated by larval ballooning. Although the model included both initial long—distance dispersal by larval ballooning and subsequent short—distance dispersal by larval crawling, it poorly matched the observed distribution of the virus. An alternative and as yet untested hypothesis is that the observed spread of the virus may be due to mechanical vectoring by a parasitoid fly, a mechanism for which there are as yet no available mathematical theory or relevant field data.