There is increasing recognition that spatial scale(s), in terms of ecological processes, are critical to construct general ecological predictions. Ecological processes act at a variety of spatial and temporal scales and the variation of scale may lead to changes in ecological patterns. To understand a particular ecosystem, it is important to study the system at the appropriate scale(s), and to develop models that bridge the required scale(s). The aquatic golden apple snail(Pomacea canaliculata, Ampullariidae) was introduced from South America to mainland China around 1980s for commercial use. P. canaliculata has been listed as one of the 100 most invasive species by the Invasive Species Specialist Group of the International Union for Conservation of Nature. Given that the variation of traits in invasive species plays an important role in the establishment and spread of a population, it is necessary to examine trait variation at the spatial scale of the invasive species and to elucidate the possible underlying mechanisms. Using a nested sampling method, we collected individuals of P. canaliculata at different spatial scales in the Guangdong Province, southern China. We measured the phenotypic traits and conducted a variance component analysis. The variance in four phenotypic traits(body-mass, -height, -width and mouth width) was partitioned across five different nested spatial scales(in decreasing order of size: city, town, habitat, plot and individual). The results indicated that the four selected phenotypic traits had a similar variation pattern across spatial scales, with most of the variation occurring below the habitat level. The most phenotypic variation occurred at the individual and plot level, explaining nearly 80% of all the variation in phenotype. We found that the habitat level accounted for the remaining variation, with the exception of body-mass. At the larger scale, such as the town and city, there was no significant increase in trait variation. Consistent with the variance partitioning, the coefficient of trait variation decreased as scale increased. The lowest trait variation value occurred at the city scale, declining sharply from the town level, while the individual level showed the largest value. This result was confirmed when we analyzed the frequency distributions of phenotypic traits among different towns within the city scale. Towns within a city have similar trait-value frequency distributions, indicating that the overall trait distribution is conserved at the town-level, with no large variance occurring at the town-scale. We can speculate on the likely processes of scale where P. canaliculata phenotype traits changed. Our results suggest that processes acting at the regional scale e.g., the influence of climate played no significant role in trait variation. To effectively manage and predict biological invasions, attention should be focused on the genetic characteristics and the effect of local environmental factors. Finally, our study provided a general model for investigating trait variation across different ecological scales where samples are collected across nested spatial structures and analyzed using variance component analysis. In the future, incorporating the theory of eco-evolutionary dynamics to study trait variability in invasive species will enhance our ability to predict and manage the incursion.