1. Much recent research has focused on the use of species distribution models to explore the influence(s) of environment (predominantly climate) on species' distributions. A weakness of this approach is that it typically does not consider effects of biotic interactions, including competition, on species' distributions. 2. Here we identify and quantify the contribution of environmental factors relative to biotic factors (interspecific competition) to the distribution and abundance of three large, wide-ranging herbivores, the antilopine wallaroo (Macropus antilopinus), common wallaroo (Macropus robustus) and eastern grey kangaroo (Macropus giganteus), across an extensive zone of sympatry in tropical northern Australia. 3. To assess the importance of competition relative to habitat features, we constructed models of abundance for each species incorporating habitat only and habitat + the abundance of the other species, and compared their respective likelihoods using Akaike's information criterion. We further assessed the importance of variables predicting abundance across models for each species. 4. The best-supported models of antilopine wallaroo and eastern grey kangaroo abundance included both habitat and the abundance of the other species, providing evidence of interspecific competition. Contrastingly, models of common wallaroo abundance were largely influenced by climate and not the abundance of other species. The abundance of antilopine wallaroos was most influenced by water availability, eastern grey kangaroo abundance and the frequency of late season fires. The abundance of eastern grey kangaroos was most influenced by aspects of climate, antilopine wallaroo abundance and a measure of cattle abundance. 5. Our study demonstrates that where census and habitat data are available, it is possible to reveal species' interactions (and measure their relative strength and direction) between large, mobile and/or widely-distributed species for which competition is difficult to demonstrate experimentally. This allows discrimination of the influences of environmental factors and species interactions on species' distributions, and should therefore improve the predictive power of species distribution models.