WE PROPOSE DEVELOPING NEW COMPUTATIONAL TOOLS FOR TRACKING THE GEOGRAPHIC SPREAD OF PLANT PATHOGENS THROUGH AGRICULTURAL LANDSCAPES USING POPULATION GENETIC DATA. IN PARTICULAR, WE WILL DEVELOP STATE-OF-THE-ART PHYLOGEOGRAPHIC METHODS FOR RECONSTRUCTING THE SPREAD OF PATHOGENS BASED ON THE GENETIC RELATEDNESS OF PATHOGEN ISOLATES SAMPLED AT DIFFERENT GEOGRAPHIC LOCATIONS. OUR NEW METHODS WILL IMPROVE UPON EXISTING METHODS IN TWO MAJOR WAYS. FIRST, OUR APPROACH WILL BUILD ON SPATIAL NETWORK MODELS IN ORDER TO PROVIDE THE FLEXIBILITY NEEDED TO TRACK EPIDEMIC DYNAMICS ACROSS COMPLEX LANDSCAPES AND ACCOMMODATE SAMPLING ACROSS MULTIPLE LOCATIONS AND SCALES. SECOND, UNLIKE MOST EXISTING METHODS, OUR APPROACH WILL ALLOW FOR RECOMBINATION BETWEEN PATHOGEN LINEAGES, WHICH FREQUENTLY OCCURS IN MANY PLANT PATHOGENS AND LEADS TO THE EMERGENCE OF NEW STRAINS. OUR NEW PHYLOGEOGRAPHIC METHODS WILL BE IMPLEMENTED IN HIGH-PERFORMANCE, USER-FRIENDLY SOFTWARE FOR ANALYSIS AND WEB-BASED VISUALIZATION. TO BENCHMARK PERFORMANCE, WE WILL APPLY OUR METHODS TO STUDY THE SPATIAL DYNAMICS OF THREE CROP PATHOGENS OF MAJOR ECONOMIC IMPORTANCE: BARLEY YELLOW DWARF VIRUS, THE AFLATOXIN-PRODUCING MOLD ASPERGILLUS FLAVUS AND THE CUCURBIT DOWNY MILDEW PATHOGEN PSEUDOPERONOSPORA CUBENSIS. PHYLOGEOGRAPHIC ANALYSIS OF THESE PATHOGENS WILL PROVIDE NEW INSIGHTS INTO THEIR SPATIAL MOVEMENT, WHICH CAN BE DIRECTLY USED TO PREVENT FURTHER SPREAD. MORE GENERALLY, BY SYNTHESIZING ADVANCES IN SPATIAL EPIDEMIOLOGY AND POPULATION GENETICS, OUR SOFTWARE WILL ENABLE MORE TARGETED SURVEILLANCE AND CONTROL OF PLANT PATHOGENS BY IDENTIFYING MAJOR SOURCES OF INOCULUM AND REVEALING DOMINANT PATHWAYS OF SPREAD.