Spatial information about invasive species abundance is critical for estimating impact and understanding risk to ecosystems and economies. Unfortunately, at landscape and regional scales, most distribution datasets provide limited information about abundance. However, national and regional invasive plant occurrence datasets are increasingly available and spatially extensive. We aim to test whether the frequency of these point occurrences can be used as a proxy for abundance of invasive plants. We compiled both occurrence and abundance data for nine regionally important invasive plants in the northeast US using a combination of herbarium records, surveys of expert knowledge, and various invasive species spatial databases. We integrated all available abundance information based on infested area, percent cover, or qualitative descriptions into abundance rankings ranging from 0 (absent) to 4 (highly abundant). Within equal area grid cells of 800 m, we counted numbers of occurrence points and used an ordinal regression to test whether higher numbers of occurrence points were positively correlated with abundance rankings. We compiled a total 49,341 occurrence points in 18,533 cells, of which 12,183 points (25%) within 4,278 cells (32%) had associated abundance information. In six of nine study species we found slight but significant positive overall relationships between abundance rank and occurrence frequency at high abundance ranks. However, at low abundance rankings the relationship tended to be negative and the magnitude of the overall difference in occurrence frequency was too small to be relevant to management. My results suggest that currently available occurrence datasets are unlikely to serve as effective proxies for abundance, and models derived from invasive plant occurrence datasets should not be interpreted as indicative of plant abundance and associated impact. Increased efforts to collect and report invasive species abundance information, and/or higher densities of occurrence points in heavily infested areas are strongly needed for regional scale assessments of potential abundance and associated impact.