The geographic ranges of many tick species have expanded over the past several decades, and several new tickborne zoonoses have emerged. Two of these diseases are human monocytotropic ehrlichiosis (HME), caused by Ehrlichia chaffeensis; and human granulocytic anaplasmosis (HGA) caused by Anaplasma phagocytophilum. Maps of these and other emerging pathogens can play an important role in the assessment of regional public health. However, reliable data on the presence of vectors or pathogens is typically only available at isolated sample locations. The proposed research expands on a previous NIH-funded study in which information on serology of deer, climate, land cover, soils, and deer density were integrated into a regional geospatial database and used to map the distributions of E. chaffeensis and A. phagocytophilum. Our main objective is to apply concepts and methods from landscape ecology to improve our understanding of the environmental constraints on vector and pathogen spread, and to develop more effective methods for mapping pathogen distributions and disease risk. To accomplish this objective, we will (1) contrast the influences of various ecological variables on pathogen distributions across multiple spatial scales; (2) incorporate spatial indices of land cover heterogeneity as predictors of pathogen distributions; and (3) integrate ecological models with geostatistical methods to improve prediction accuracy and characterize spatial uncertainty. We expect that this work will result in an enhanced conceptual model of how the ranges of E. chaffeensis and A. phagocytophilum are constrained by multiple ecological factors operating at different spatial scales, along with more accurate maps of the geographic ranges of these pathogens. These maps will ultimately provide a framework for assessing infection risks in human populations. In addition, the methodologies that we develop will be useful for developing predictive maps of other vectors, pathogens, and diseases. [unreadable] [unreadable]