Historically, U.S. forests have been invaded by a variety of nonindigenous insects and pathogens. Some of these pests have catastrophically impacted important species over a relatively short timeframe. To curtail future changes of this magnitude, agencies such as the U.S. Department of Agriculture Forest Service have devoted substantial resources to assessing the risks associated with recent or potential forest invaders. These assessments of risk typically include a mapping component; among other things, this presents a useful way to organize early-detection/rapid-response procedures. However, forest pest risk mapping is often limited to readily available and manageable data sets, which results in representations of risk that heavily favor climatic factors or estimates of host species distribution. Detailed examinations of human-mediated pathways of spread are often neglected in forest pest risk analyses owing to a lack of spatial data or uncertainty about a pest’s predictive model parameters. Humans are the most important facilitator of forest pest introduction and spread. With expanding global trade and interstate commerce, the number of potential forest invaders is likely to rise, making the analysis of human-mediated pathways particularly timely. In this synthesis, we present a number of spatial data sources, collected by Federal agencies and private companies for a range of purposes, which can be utilized to represent these human-mediated pathways. Although general in nature, queries can often be used to tailor these data sets to address specific pests. Perhaps, most importantly, the source data can usually be acquired for free or at negligible cost. Using the sudden oak death pathogen ( Phytophthora ramorum ) and other pests as examples, we illustrate how some of these data sources can be employed for mapping risks associated with human-mediated pathways. First, we demonstrate the use of foreign import cargo statistics— marine, airborne, and transborder—to assess the risk of introduction of new species at United States ports of entry. Second, we examine the utility of inland waterway cargo statistics, freight analysis networks, and other databases on domestic commodity traffic for mapping regional and local spread of forest pests. Third, we explain the diverse applications of business databases, not only to identify clusters of high-risk businesses, but also to rank these businesses using a suite of socioeconomic factors. Finally, we discuss the limited availability of up-to-date land use/landcover data, and present alternative data sources for representing highrisk areas of current urbanization as well as the forest-urban interface. Whereas many of these data sets are imperfect depictions of human-mediated pathways, integration of several can add significant depth to early-detection/rapid-response projects. To facilitate further applications, we discuss user considerations, future information needs, and potential sources of additional data regarding human-mediated pathways.