Abstract
Aim  Numerous geographical information system (GIS)‐based techniques for estimating a species’ potential geographical distribution now exist. While a species’ potential distribution is more extensive than its documented range, the lack of records from some suitable regions may simply derive from inadequate sampling there. Using occurrence records of both the study species and the more inclusive overall target group, I propose a progression of statistical models to evaluate apparent absences in species distributions.Location  Northern Venezuela.Methods  Employing data from the Smithsonian Venezuelan Project (a large set of standardized mammalian inventories undertaken across Venezuela), I tested distributional hypotheses for the sigmodontine rodent Oryzomys albigularis (Tomes, 1860). Those inventories collected O. albigularis in two of the five major montane regions of northern Venezuela (the Cordillera de Mérida/Macizo de El Tamá and Cordillera de la Costa Central). I used the Genetic Algorithm for Rule‐Set Prediction (GARP) to estimate the species’ potential distribution in northern Venezuela. Then, based on all collection localities from the Smithsonian Venezuelan Project, I determined the probability that the absence of O. albigularis from the three regions of potential presence where it was not documented (the Serranía de Perijá, Lara–Falcón highlands, and Cordillera de la Costa Oriental) could be the result of inadequate sampling.Results and main conclusions  All statistical models indicated that the sampling efforts of the Smithsonian Venezuelan Project were insufficient to demonstrate conclusively the absence of O. albigularis from any of the three regions lacking records. Indeed, a subsequent compilation of specimens from ten natural history museums confirmed its presence in the Serranía de Perijá and the Lara–Falcón highlands. Tests using empirical sampling effort and taking human modification of the landscape into account most closely fulfilled the assumptions required for the tests. By providing a framework for bringing additional quantitative rigour to studies of species distributions, these methods will probably prove of wide applicability to other systems.