A�������.Building and testing general principles is key to accelerate scientific progress. Here, we review the studies performed in Argentina in which ants were used as model organisms, in the context of ecological theories, hypotheses and concepts. Specifically, we focus on ant studies performed under the conceptual frameworks of ecological engineering, indirect interactions, seed dispersal, community assembly rules, biological invasions and integrated pest management. Those studies contributed to 1) supporting the concept of ecological engineers through the study of the physical changes in the environment caused by ants through the building and maintenance of their nests, and their consequences on other organisms such as soil biota, plants and herbivores; 2) questioning the convergence hypothesis, which proposes that independently assembled communities in similar, but geographically distant habitats converge in composition and functioning under similar environmental pressures; 3) showing that directed seed dispersal is an important process to increase plant performance in desert ecosystems; 4) understanding the type of control which prevails in communities (top-down or bo�om-up); 5) emphasizing the relevance of indirect interactions in the structure and functioning of ecosystems with examples of trophic cascades, indirect facilitation, exploitative competition and trait-mediated effects; 6) a be�er understanding of the causes of success or failure of biological invasions, via the study of the behavioral and demographic characteristics of invasive ant species in their native area, and the role of biotic resistance and mutualism facilitation; and 7) exploring the concept of integrated pest management via the study of the use of natural enemies, repellents and a�ractants, and the knowledge about the feeding and foraging behavior of pests. This body of work reinforces the key role of ants as model organisms to test ecological hypotheses and highlights the importance of using conceptual frameworks as guidance to be�er understand the complexity of natural systems.