Abstract: Understanding demographic patterns across a landscape can be important to managing invasive species, preserving endangered species, and understanding species dynamics at larger scales than the single population. To describe and quantify spatial and temporal demographic heterogeneity of an invasive plant species, we collected data from a total of 40 populations of the perennial forb Centaurea stoebe (spotted knapweed) in two very different regions of New York state, USA, for three years. In both regions, C. stoebe grows along roadsides and in other areas where disturbances like mowing keep trees out. Demographic variables measured included size-dependent growth, survival, and seedset. From these data we constructed and parameterized separate IPMs (integral projection models), one for each population in each of the two annual intervals of the study. There were substantial differences among populations and between annual intervals in most demographic variables. Despite being an invasive species, the finite rate of population increase, λ, varied from >4 (‘jackpot’ populations) to < 1 (i.e., declining populations), with a long right tail. Unexpectedly, regional differences were less than within-region spatial variation in λ among populations. Values of λ were consistently most sensitive (elastic) to plant growth rates (sizet+1 as a function of sizet), so if full demographic data collection is not possible, we recommend prioritizing plant size. Deviations from the stable size distributions accounted for substantial differences between λ and observed Nt+1/Nt values within the same annual interval; we conclude that observed short-term changes in N may be poor predictors of the actual status of a population. In part due to differences in demographic variables between annual intervals in the same population, λ from one annual interval was not a good predictor of a population’s size at the end of the next annual interval. While C. stoebe, as a species of disturbed sites, may be unusually variable, these high levels of spatial and temporal heterogeneity are a cautionary example for extrapolating from a few populations to many. Management based on regional patterns, incorporating this variability, may therefore be preferable to managing individual populations.