Invasive pathogens are becoming increasingly important in forested ecosystems, yet they are often difficult to study because of their rapid transmission. The rate and extent of pathogen spread are thought to be partially controlled by variation in host characteristics, such as when host size and location influence susceptibility. Few host-pathogen systems, however, have been used to test this prediction. We used Port Orford cedar (Chamaecyparis lawsoniana), a foundation tree species in riparian areas of California and Oregon (USA), and the invasive oomycete Phytophthora lateralis to assess pathogen impacts and the role of host characteristics on invasion. Across three streams that had been infected for 13–18 years by P. lateralis, we mapped 2241 trees and determined whether they had been infected using dendrochronology. The infection probability of trees was governed by host size (diameter at breast height [DBH]) and geomorphic position (e.g., active channel, stream bank, floodplain, etc.) similarly across streams. For instance, only 23% of trees <20 cm DBH were infected, while 69% of trees ≥20 cm DBH were infected. Presumably, because spores of P. lateralis are transported downstream in water, they are more likely to encounter well-developed root systems of larger trees. Also because of this water-transport of spores, differences in infection probability were found across the geomorphic positions: 59% of cedar in the active channel and the stream bank (combined) were infected, while 23% of trees found on higher geomorphic types were infected. Overall, 32% of cedar had been infected across the three streams. However, 63% of the total cedar basal area had been killed, because the greatest number of trees, and the largest trees, were found in the most susceptible positions. In the active channel and stream bank, 91% of the basal area was infected, while 46% was infected across higher geomorphic positions. The invasion of Port Orford cedar populations by P. lateralis causes profound impacts to population structure and the invasion outcome will be governed by the heterogeneity found in host size and location. Models of disease invasion will require an understanding of how heterogeneity influences spread dynamics to adequately predict the outcome for host populations.