Ecological niche models (ENMs) have become a practical and key mechanism for filling major gaps in spatial information for targeted conservation planning, particularly when only occurrence data are available. Nonetheless, accounting for abundance patterns in the internal structure of species’ ranges, and the role of biotic interactions in such models across broadscale, remains highly challenging. Our study gathered baseline information on abundance data of two Endangered Amazonian primates (Ateles chamek and Lagothrix lagotricha cana) to create geospatial abundance models using two spatial interpolation methods: Inverse distance weight (IDW) and Ordinary kriging (OK). The main goals were to: (i) test whether geospatial abundance models are correlated with habitat suitability derived from correlative ENMs; (ii) compare the strength of the abundance-suitability relationships between original and interpolated abundances; (iii) test whether interspecific competition between the two target taxa constrained abundance over broad spatial scales; and (iv) create ensemble models incorporating both habitat suitability and abundance to identify high-priority areas for conservation. We found a significant positive relationship between habitat suitability with observed and predicted abundances of woolly (L. l. cana) and spider (A. chamek) monkeys. Abundance-suitability correlations showed no significant differences when using original relative abundances compared to using interpolated abundances. We also found that the association between L. l. cana abundance and habitat suitability depended on the abundance of its putative competitor species, A. chamek. Our final models combining geospatial abundance information with ENMs were able to provide more realistic assessments of hotspots for conservation, especially when accounting for the important, but often neglected, role of interspecific competition in shaping species’ geographic ranges at broader scales. The framework developed here, including general trends in abundance patterns and suitability information, can be used as a surrogate to identify high-priority areas for conservation of poorly known species across their entire geographic ranges.