Population abundance and trend estimates are crucial to science, management, and conservation. Shorebirds, which are abundant in many coastal habitats and play important roles in coastal ecosystems, are facing some of the most dramatic population declines of any group of birds globally. However, accurate and up-to-date population estimates are lacking for most shorebird species. We thus conducted large-scale, simultaneous, and community scientist-led surveys of the Atlantic Coast of southern South America, stretching from central Brazil to Tierra del Fuego, to gather counts of shorebirds stratified by habitat that we combined with remote sensing analyses and two-step hurdle models that accounted for presence and abundance. Our objectives were to estimate shorebird densities by habitat, identify high-concentration areas, understand the environmental factors affecting their distributions, and provide population estimates for both Nearctic and Neotropical species. We counted a total of 37,207 shorebirds of 17 species and, from those counts, estimated that nearly 1.1 million shorebirds use the region’s coastline. We found that the northern portion of the region was important for sandy beach specialists, while southern portions supported higher abundances of species that rely on intertidal mudflat and rocky habitats. We also found that shorebirds occurred in the highest densities in wetland habitats and that fewer shorebirds occupied areas that were further away from estuaries. Although not directly comparable, our results suggest the population sizes of the Nearctic species whose nonbreeding ranges are predominantly in southern South America may have declined substantially since previous estimates. At the same time, our study represents the first empirically derived population estimates for Neotropical breeding shorebird species and indicates that they are far more abundant than previously thought. Taken together, our results highlight the power of community scientists to carry out structured protocols at continental scales and generate critical data for a group of at-risk species.