Spatial spread of microsporidia in forest insects

Parasitism is a common life history mode among organisms that has many diverse effects on the hosts. Parasites can affect the distribution and abundance of species, may enhance or prevent the invasion of species into new habitats, can affect the population dynamics and the behaviour of their hosts. Pathogens of insects, e.g. viruses, bacteria, fungi or microsporidia can cause mass mortality in beneficial or pest insects. Many of them have potential in biological pest control. Very little is known on the spatial spread of microsporidia in insects. Data on the influence of abiotic or biotic data are particularly lacking. In the proposed study, we will use the following model system to analyze the spatial spread of microsporidia. The gypsy moth (Lymantria dispar L.), a well known pest insect of oak forests, will serve as host for the microsporidian species, Nosema lymantriae. Previous studies showed how microsporidia are transmitted among gypsy moth larvae. A mathematical model that simulates the transmission of microsporidia at the small scale of one tree for one season is the basis for the spatial and temporal extension of the model. Abiotic factors, e.g. rain will be also integrated. In a first step, we will measure the short-term and short-distance spread of microsporidia. Factors such as the distance between trees, rain or larval densities will be tested. In a second step, we will create a higher population of gypsy moths in oak forests and we will release Nosema-infected larvae. We will monitor the spatial spread of the microsporidian species and use these data for the validation of the model. A further aspect of the proposed study will be the influence of Bacillus thuringiensis on the host-pathogen interactions. Preparations of B. thuringiensis are used for the control of insects. We will test, how the interactions of the gypsy moth and N. lymantriae will be influenced by B. thuringiensis and what the consequences of a field application are. We also will use the model to simulate these interactions.